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Journal articles on the topic 'Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)'

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Published: 4 June 2021
Last updated: 17 February 2022

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1

Swain, Priyadarshi Tapas Ranjan, and Sandhyarani Biswas. "Selection of Materials Using Multi Criteria Decision Making Method by Considering Physical and Mechanical Properties of Jute/Al2O3 Composites." Applied Mechanics and Materials 592-594 (July 2014): 729–33. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.729.

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Multi-Criteria Decision Making (MCDM) method plays a key role to find out the best option from all possible alternatives. From different application areas Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the Multi-Criteria Decision Making (MCDM) method to find out the correct result. TOPSIS is a real-world and valuable procedure for ranking and selection of a number of externally determined substitutes through distance measures. In this paper, application of techniques for order preference by similarity of an ideal solution (TOPSIS) method is applied for solving multiple criteria (objective) optimization problem in mechanical and physical properties of jute/Al2O3 fiber based hybrid composites. The best performance value of composite is designed from ideal solution and as well as the worst performance value of composite is designed for negative-ideal solution. The results have demonstrated the model to be both robust and efficient.
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Christine and Halim Agung. "IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM." Jurnal Terapan Teknologi Informasi 2, no. 2 (April 9, 2019): 171–80. http://dx.doi.org/10.21460/jutei.v2i2.106.

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Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care. Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution. The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage. The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system
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Christine and Halim Agung. "IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM." Jurnal Terapan Teknologi Informasi 2, no. 2 (April 9, 2019): 171–80. http://dx.doi.org/10.21460/jutei.2018.22.106.

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Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care. Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution. The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage. The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system
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Situmorang, Larisma, and Jijon Raphita Sagala. "Sistem Pendukung Keputusan Pemilihan Tentor Terbaik Dengan Metode Technique For Order Preference By Similarity To Ideal Solution (Topsis)." Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) 3, no. 3 (December 5, 2020): 209–14. http://dx.doi.org/10.32672/jnkti.v3i3.2418.

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Abstrak— Tentor adalah Sumber daya manusia yang merupakan bagian yang sangat terpenting bagi tumbuh kembangnya sebuah Bimbingan Belajar. Bimbingan Belajar yang berkembang dengan baik sangatlah dipengaruhi oleh kualitas sumber daya manusia, yang dalam hal ini adalah tentor yang bekerja di dalam sebuah Bimbingan Belajar tersebut. Oleh karena itu, dilakukan pemilihan tentor terbaik menggunakan Metode sistem Keputusan Pemilihan Tentor Terbaik di Bimbingan Manna adalah Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Sistem Pendukung Keputusan yang dibangun dapat membantu serta memudahkan pihak bimbingan belajar manna terutama ketua dalam mengambil sebuah keputusan pemilihan tentor terbaik yang dirancang dengan aplikasi berbasis website dan dengan database phpmyadmin. Form nilai matrik adalah form yang paling penting, karena didalam form ini dilakukan perhitungan dengan langkah-langkah perhitungan metode Topsis mulai dari awal, Nilai Matrik, Nilai Matrik Normalisasi, Nilai Bobot Normalisasi, Matrik Ideal Positif/Negatif, Jarak Solusi Ideal Positif/Negatif, Nilai Preferensi.
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Gupta, Arun, and Shailendra Kumar. "Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS)." International Journal of Production Management and Engineering 4, no. 2 (July 13, 2016): 43. http://dx.doi.org/10.4995/ijpme.2016.4102.

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<p>The flow-shop scheduling problem (FSP) has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM) method known as techniques for order preference by similarity to an ideal solution (TOPSIS) using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time). The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.</p>
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Kurniawan, Dwi Ely. "PEMILIHAN WISATA MENGGUNAKAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) DENGAN VISUALISASI LOKASI OBJEK." KLIK - KUMPULAN JURNAL ILMU KOMPUTER 5, no. 1 (February 28, 2018): 75. http://dx.doi.org/10.20527/klik.v5i1.132.

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<p><em>Batam is one of the existing city in Riau Islands Province, Indonesia. The amount of tourism potential and strategic location for tourists to come to Batam. But what is being searched is the difficulty of finding a tourist attraction based on certain parameters. To overcome these problems, it takes a technology that provides tourist recommendation map information. This research develops this application to give recommendation of tourism based on certain parameters as needed by using TOPSIS method in Batam City web based. The results of development, the application can run functionally (online), can store the tour data and criteria. It can also do the calculation of attractions based on TOPSIS decision. Users can fill the weight of some parameters of distance, time and cost. In order to provide ease in location visualization, the final result of decision calculation is able to provide tourist information in the form of object location of Google Maps API and a brief description of the tour.</em></p><p><em><strong>Keywords</strong>: location, tourist attraction, decision, TOPSIS</em></p><p><em>Batam merupakan salah satu Kota yang terdapat di Provinsi Kepulauan Riau, Indonesia. Banyaknya potensi pariwisata dan lokasi yang strategis membuat peluang wisatawan untuk datang ke Kota Batam. Namun kendala yang ditemukan adalah sulitnya menemukan objek wisata berdasarkan parameter tertentu. Untuk mengatasi masalah tersebut, maka dibutuhkan sebuah teknologi aplikasi yang menyajikan informasi peta rekomendasi wisata di Kota Batam berbasis web. Penelitian ini mengembangkan aplikasi ini untuk memberikan rekomendasi wisata berdasarkan parameter tertentu sesuai kebutuhan wisatawan dengan menggunakan metode TOPSIS. Hasil pengembangan aplikasi dapat berjalan secara online dapat mengelola data wisata dan data kriteria. Selain itu juga dapat melakukan perhitungan objek wisata berdasarkan keputusan TOPSIS. Pengguna dapat mengisi bobot dari beberapa parameter yaitu waktu, jarak dan biaya. Agar dapat memberikan kemudahan dalam visualisasi lokasi hasil akhir perhitungan keputusan, memberikan informasi wisata berupa lokasi objek dari Google Maps API dan deskripsi singkat wisata tersebut.</em></p><p><em><strong>Kata Kunci</strong>: lokasi, potensi wisata, keputusan, TOPSIS</em></p><p><em><br /></em></p>
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Tri susilo, Andri Anto, and Lukman Sunardi. "SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN POLISI PAMONG PRAJA (POL PP) DENGAN METODE TOPSIS (TECHNIQUE FOR ORDER OF PREFERENCE BY SIMILARITY TO IDEAL SOLUTION)." Jurnal Digital Teknologi Informasi 4, no. 2 (July 22, 2021): 52. http://dx.doi.org/10.32502/digital.v4i2.3543.

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Anggota Satuan Polisi Pamong Praja( Sat Pol PP) sebagai aparat Pemerintah Daerah yang diduduki oleh pegawai negeri sipil dan diberi tugas, tanggung jawab, dan wewenang sesuai dengan peraturan perundang-undangan dalam penegakan Peraturan Daerah dan Peraturan Kepala Daerah, penyelenggaraan ketertiban umum dan ketenteraman serta pelindungan masyarakat. Dalam proses penerimaan anggota Sat Pol PP melalui mekanisme tenaga kontrak terdapat beberapa kendala yang dihadapi yaitu belum adanya sistem yang dapat digunakan untuk mengolah data calon anggota Sat Pol PP dan harus mengkalkulasi hasil penilaian calon tenaga Sat Pol PP secara manual. Metode pendukung keputusan dalam penelitian ini adalah TOPSIS (TECHNIQUE FOR ORDER OF PREFERENCE BY SIMILARITY TO IDEAL SOLUTION). Hasil dari penelitian adalah Sistem Pendukung Keputusan Seleksi Penerimaan Tenaga Kontrak Polisi Pamong Praja (Pol PP) dengan Metode TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) Di Kota Lubuklinggau
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Okul, Deniz, Cevriye Gencer, and Emel Kizilkaya Aydogan. "A Method Based on SMAA-Topsis for Stochastic Multi-Criteria Decision Making and a Real-World Application." International Journal of Information Technology & Decision Making 13, no. 05 (September 2014): 957–78. http://dx.doi.org/10.1142/s0219622014500175.

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Stochastic multi-criteria acceptability analysis (SMAA-2) and the technique for order preference by similarity to ideal solution (TOPSIS) are methods for evaluating alternatives with multiple criteria. SMAA is a method that is used for solving multi-criteria decision-making problems with uncertain, inaccurate information, and does not require preference information from the decision makers. The TOPSIS method is based on the principle of determining a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution. This paper proposes a new method, SMAA-TOPSIS, by combining the SMAA and TOPSIS methods. The SMAA-TOPSIS method was executed for two problems: drug benefit-risk analysis and machine gun selection. This paper found that TOPSIS could be used with uncertain and arbitrarily distributed values for weights and criteria measurements by using a combination of SMAA and TOPSIS. Also, we obtained clearer and consistent SMAA outputs.
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Abbaspour, Asghar, Mahnaz Saremi, Ahmad Alibabaei, and Pedram S. Moghanlu. "Determining the optimal human reliability analysis (HRA) method in healthcare systems using Fuzzy ANP and Fuzzy TOPSIS." Journal of Patient Safety and Risk Management 25, no. 3 (January 23, 2020): 123–33. http://dx.doi.org/10.1177/2516043519900431.

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Purpose As one of the leading causes of deaths and injuries, medical errors constitute a veritable threat to patient safety. Despite this fact, no unique method has yet been established to identify and evaluate medical errors. This study was conducted to select an optimal human reliability analysis method compatible with healthcare systems from available methods. Design/methodology/approach: In order to select the optimal method for the identification and evaluation of medical errors, different criteria and sub-criteria were determined by reviewing the literature and based on experts’ opinions. Next, weights of criteria and sub-criteria were specified by using the fuzzy analytical network process (ANP). Finally, fuzzy technique for order preference by similarity to ideal solution method was used to prioritize the methods. Findings Six criteria and 21 sub-criteria for choosing the optimal method were determined. The utility, usability, and structure of a method had the highest influence with weights of 0.262, 0.191, and 0.187, respectively. Based on the results of fuzzy technique for order preference by similarity to ideal solution, the Human Error Assessment and Reduction Technique method with a closeness coefficient of 0.576 was selected as the optimal method for identifying medical errors. The Human Factors Analysis and Classification System and Systematic Human Error Reduction and Prediction Approach methods ranked second and third, respectively. Originality/value: To date, no studies have attempted to determine the optimal methods for identification and assessment of medical errors. This paper aimed to fill this gap by using fuzzy analytical network process and fuzzy technique for order preference by similarity to ideal solution techniques.
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Andi Dwi Pangestu. "SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN BERPRESTASI MENGGUNAKAN METODE AHP DAN TOPSIS : STUDI KASUS PT. TELKOM DIVISI ENTERPRISE SERVICE." Jurnal Indonesia Sosial Teknologi 1, no. 4 (November 21, 2020): 244–52. http://dx.doi.org/10.36418/jist.v1i4.36.

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Penentuan karyawan berprestasi pada PT. Telkom Divisi Enterprise Service dilakukan dengan cara memilih karyawan tiap bagian bidang kerja berdasarkan kriteria yang sudah ditentukan. Kriteria-kriteria yang digunakan adalah keterampilan, pengetahuan, keahlian, fleksibilitas, komunikasi, disiplin, tanggung jawab, loyalitas dan kredibilitas. Masalah yang dihadapi oleh perusahaan tersebut adalah bagaimana menentukan karyawan berprestasi dari sejumlah alternatif karyawan. Sistem ini merupakan Sistem Pendukung Keputusan (SPK) yang dibangun dengan menggunakan penggabungan metode Analitycal Hierarchi Process (AHP) dan Technique for Order Preference by Similarity to Ideal (TOPSIS) membantu penentuan karyawan berprestasi. AHP merupakan suatu metode pengambilan keputusan untuk menyelesaikan masalah penentuan pilihan yang sifatnya multiobjective dan metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) merupakan suatu bentuk metode pendukung keputusan yang didasarkan pada konsep bahwa alternatif yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif tetapi juga memiliki jarak terpanjang dari solusi ideal negatif. Pembobotan kriteria dilakukan dengan menggunakan AHP dan perankingannya dilakukan dengan menggunakan TOPSIS.
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Sururi, Nafis, Kusrini Kusrini, and Sudarmawan Sudarmawan. "Penentuan Wali Kelas Yang Ideal Menggunakan Metode TOPSIS." Creative Information Technology Journal 5, no. 2 (July 11, 2019): 85. http://dx.doi.org/10.24076/citec.2018v5i2.163.

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Pendidikan merupakan salah satu hal yang penting dalam suatu negara. Pendidikan bisa didapatkan pendidikan formal, informal maupun nonformal. Contoh pendidikan formal adalah sekolah dan pergururan tinggi, di dalam sekolahan terdapat wali kelas yang bertanggung jawab terhadap peserta didik di satu kelas atau ruang belajar di lingkungan sekolah. Dalam menentukan wali kelas yang ideal kepala sekolah dapat melihat karakteristik dan kemampuan yang dimiliki guru secara objektif. Multiple Criteria Decision Making (MCDM) merupakan salah satu metode yang paling banyak digunakan dalam pengambilan keputusan. Salah satu metode MCDM adalah Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Penelitian ini menggunakan metode TOPSIS yang dapat menganalisis keputusan multi-kriteria dimana metode tersebut dapat memilih alternatif terbaik dengan jarak terdekat dari alternatif ideal. Hasil yang diperoleh dari penelitian ini adalah Penentuan wali kelas dilakukan dengan cara mencari nilai preferensi setiap guru yang paling besar dari 3 kelas yang digunakan. Perhitungan yang dilakukan menggunakan bobot berbeda pada setiap kelas agar mendapatkan nilai prefensi sebagai acuan penentuan wali kelas yang ideal.Kata Kunci—Wali kelas, Ideal, TOPSISEducation is one of the important things in a country. Education can be obtained from formal, informal or non-formal education. Examples of formal education are schools and high schools, in schools there is a homeroom teacher who is responsible for students in one class or study room in a school environment. In determining the ideal homeroom, the principal can see the characteristics and abilities of the teacher objectively. Multiple Criteria Decision Making (MCDM) is one of the most widely used methods in decision making. One of the MCDM methods is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This study uses the TOPSIS method which can analyze multi-criteria decisions where the method can choose the best alternative with the closest distance from the ideal alternative. The results obtained from this study are Determination of the homeroom teacher is done by finding the preference value of each teacher, the largest of the 3 classes used. Calculations performed using different weights for each class in order to get the value of the prefix as a reference for determining the ideal homeroom teacher.Keywords—Homeroom teacher, Ideal, TOPSIS
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Susliansyah, S., Aditia Dwinanto, Heny Sumarno, Hendro Priyono, and Linda Maulida. "Decision Making on Student Academic Achievement Assessment Using the Topsis Method." IJISTECH (International Journal of Information System & Technology) 5, no. 1 (June 30, 2021): 60. http://dx.doi.org/10.30645/ijistech.v5i1.115.

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Student academic achievement is a very important matter for all school parties that are directly or indirectly related, especially for Depok Tourism Vocational School, student academic achievement is one of the benchmarks in the success of education. Currently, the process of determining student achievement from the academic side of the Depok Tourism Vocational School is still using a manual system, so it takes a long time to determine the assessment of student academic achievement, because there are quite a lot of student data recording. In addition, it is still less relevant because it has not used the right calculation method, resulting in inaccurate calculations. This research uses the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method, because this method is a simple concept and easy to understand and to help the optimal decision-making process to solve practical decision problems. The results of the research using the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method found that students with the name Akmal Adnanto got the first rank with the highest preference value of 0.760.
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Purnomo, Dian Eko Hari. "PEMILIHAN PEMASOK KAYU DENGAN MENGGUNAKAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS)." KAIZEN : Management Systems & Industrial Engineering Journal 2, no. 1 (May 31, 2019): 28. http://dx.doi.org/10.25273/kaizen.v2i1.5170.

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PT. JQK merupakan suatu perusahaan manufaktur yang memproduksi furnitur.. PT. XYZ mempunyai dua jenis yaitu pemasok kontrak dan pemasok tidak kontrak. Saat ini, di<em> </em>perusahaan dalam melakukan pemilihan pemasok tidak kontrak menjadi pemasok<em> </em>kontrak terkadang mengalami kesulitan. Kesulitan tersebut terjadi karena belum<em> </em>adanya kriteria yang secara rinci dapat dipergunakan untuk pemilihan pemasok. Sehingga pada penelitian ini akan berusahaan menemukan kriteria-kriteria yang berpengaruh dalam pemilihan pemasok. Pengolahan data pada penelitian ini menggunakan metode <em>Technique for Order Preference by Similarity to Ideal Solution </em>(TOPSIS). Kriteria yang dapat mempengeruhi pemilihan pemasok adalah jumlah total, jumlah total kualitas satu, jumlah total kualitas dua, jumlah total katu rusak, jumlah pengiriman maksimal, jumlah maksimal kualitas satu, jumlah maksimal kualitas dua, jumlah maksimal rusak, jumlah pengiriman minimal, jumlah minimal kualitas satu, jumlah minimal kualitas dua, jumlah minimal rusak, kerutinan, harga kualitas satu dan harga kualitas dua. Berdasarkan hasil pengolahan data nantinya akan diberikan beberapa usulan kepada perusahaan pihak perusahaan terkait dengan hasil perhitungan dan nilai untuk masing-masing pemasok.
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Wang, Qi Bing, and An Hua Peng. "Developing MCDM Approach Based on GRA and TOPSIS." Applied Mechanics and Materials 34-35 (October 2010): 1931–35. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1931.

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Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.
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Supiyan, Dede. "Perbandingan Metode SAW, WP Dan Topsis Dalam Penentuan Pembiayaan." Jurnal Ilmiah Informatika 4, no. 2 (December 21, 2019): 88–94. http://dx.doi.org/10.35316/jimi.v4i2.544.

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Decision support system is the composition of a computer-based information system that functions as a supporter of decision making in an organization or company. Decision making in determining the provision of financing is very important because with the right decision the provision of financing can run well. Decision making method is useful for determining the best alternative from a number of other alternatives based on certain criteria, including the simple additive weighting method, Weighted Product and Technique For Order Preference by Similarity to Ideal Solution. A comparison of the methods of this decision support system is carried out to determine which method provides the highest accuracy value of the financing data for the El-Raushan BMT cooperative. Based on comparison of the SAW Method, Weighted Product and TOPSIS methods show that the Weighted Product method is more accurate than the simple additive weighting method Technique For Order Preference by Similarity to Ideal Solution. Judging from the value of the accuracy of the three methods with the highest accuracy WP (Weighted Product) method with an accuracy value of 94%.
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Zhuang, Shufeng, Zhendong Yin, Zhilu Wu, and Xiaoguang Chen. "Dynamic Relay Satellite Scheduling Based on ABC-TOPSIS Algorithm." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3161069.

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Tracking and Data Relay Satellite System (TDRSS) is a space-based telemetry, tracking, and command system, which represents a research field of the international communication. The issue of the dynamic relay satellite scheduling, which focuses on assigning time resource to user tasks, has been an important concern in the TDRSS system. In this paper, the focus of study is on the dynamic relay satellite scheduling, whose detailed process consists of two steps: the initial relay satellite scheduling and the selection of dynamic scheduling schemes. To solve the dynamic scheduling problem, a new scheduling algorithm ABC-TOPSIS is proposed, which combines artificial bee colony (ABC) and technique for order preference by similarity to ideal solution (TOPSIS). The artificial bee colony algorithm is performed to solve the initial relay satellite scheduling. In addition, the technique for order preference by similarity to ideal solution is adopted for the selection of dynamic scheduling schemes. Plenty of simulation results are presented. The simulation results demonstrate that the proposed method provides better performance in solving the dynamic relay satellite scheduling problem in the TDRSS system.
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Doni, Rahmat, Faisal Amir, and Dicky Juliawan. "Sistem Pendukung Keputusan Kenaikan Jabatan Menggunakan Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)." Prosiding Seminar Nasional Riset Information Science (SENARIS) 1 (September 30, 2019): 69. http://dx.doi.org/10.30645/senaris.v1i0.9.

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Promotion is one way to Rumah Bermain Bilal to improve the performance of tutors in educating their students. The problem of leadership in decision-making still uses the choice of methods and assessment processes subjectively so that the process is not in accordance with the goals of the career path. Therefore, it is necessary to make a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method to help make decisions. In this study, using the criteria set by the company, namely planning, learning, evaluation, and training. The ranking results obtained from testing the calculations that the alternative Tutor F is the best tutor with the results of the calculation of 0.804 when compared to the other twelve alternatives. The TOPSIS method has a data accuracy rate of 85% from thirteen alternatives and can be used as a support for leadership decisions to make recommendations for increasing the career path of tutors.
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Xu, Wei, Zengchuan Dong, Li Ren, Jie Ren, Xike Guan, and Dunyu Zhong. "Using an improved interval technique for order preference by similarity to ideal solution to assess river ecosystem health." Journal of Hydroinformatics 21, no. 4 (June 6, 2019): 624–37. http://dx.doi.org/10.2166/hydro.2019.133.

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Abstract A river ecosystem health (REH) assessment system, based on indicators for morphological form, hydrology features, aquatic life, and habitat provision was established to characterize REH. The standard interval Technique for Order Preference by Similarity to Ideal Solution method (TOPSIS) does not fully consider dynamic changes in REH, so interval numbers and the mean were introduced into an improved version of TOPSIS to achieve a more objective analysis. The improved interval TOPSIS method was tested in the Zhangweinan River and a river ecosystem health integrated index (REHI) was calculated. The REHI decreased from 0.376 to 0.346 over the past 25 years and the REH ranged from general to poor for 1991 to 1995 and from poor to very poor for 1996 to 2000, 2001 to 2005, 2006 to 2010, and 2011 to 2015. The ecosystem health is poor because of dams and reservoirs in the upper reaches that prevent water flowing to the lower reaches, over-abstraction of water, and severe pollution. This method gives objective and accurate assessments of REH and can be used to support decision-making and evaluation in a range of fields.
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Tian, Jia Ping, Su Na Cao, Jia Xing Du, Ping Chen, and Huan Zhan. "Evaluation of Cyberwar’s Synthetical Ability Based on TOPSIS Method." Applied Mechanics and Materials 615 (August 2014): 286–89. http://dx.doi.org/10.4028/www.scientific.net/amm.615.286.

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A evaluation of cyberwar’s synthetical ability based on TOPSIS method is discussed in this article. The method is a technique for order preference by similarity to ideal solution which can avoid the difficulty in traditional evaluations that regard the multi-evaluation parameters as a single efficiency evaluating value. The article supply a new idea to the evaluation of cyberwar’s synthetical ability.
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liana, Lalhming, Amitabha Nath, Ch Udaya Bhaskara Rao, and Goutam Saha. "Multi Criteria Decision Making Approach and Clustering Technique for Dam Site Selection." Science & Technology Journal 8, no. 1 (January 1, 2020): 46–51. http://dx.doi.org/10.22232/stj.2020.08.01.05.

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Identification of dam sites is a strategic priority in water management scheme to preserve and conserve water. The selection of such sites relies on a number of biophysical as well as socio-economic factors. Clustering technique and several Multi Criteria Decision Making (MCDM) approach such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) provides valuable tools in the selection of suitable dam sites. This paper presents the application of TOPSIS and k-means clustering technique in the selection of dam site. We have used four criteria in selecting the dam site which were found to be influential criteria in such a problem through literature survey. Eight potential dam sites were selected in Tlawng watershed based on expert opinion and applied TOPSIS and k-means clustering methods to obtain the most ideal solution out of the eight potential dam sites. The computational time of TOPSIS in finding the ideal solution has been reduced when combined with k-means clustering method.
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Ahmad Taharim, Mohd Ariff, and Liew Kee Kor. "Application of fuzzy technique for order preference by similarity to the ideal solution in the selection of candidates." Social and Management Research Journal 9, no. 1 (June 1, 2012): 35. http://dx.doi.org/10.24191/smrj.v9i1.5211.

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Selecting the right candidate for the right cause is similar to identifying the most compromising solution of multi-criteria decision making (MCDM) problem. In real life the selection criteriamay involve vague and incomplete data which cannot be expressed in precise mathematical form or numerical values. Apparently fuzzy-based technique can be applied to describe and represent these data in fuzzy numbers. This paper presents a MCDM fuzzy TOPSIS based model designed to solve the selection problemfor allocation of government staff quarters. Result shows that the proposed model is suitable and appropriate. It was also found that the MCDM model which uses single decision maker rating process can also be applied to multiple decision makers. It is recommended that the application of fuzzy TOPSIS can be extended to other selection processes such as vendor selection, training evaluation or group marking of project works.
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Munawir, Munawir. "Analisis Penilaian Kinerja Terhadap Rasionalitas Dosen pada 114 Perguruan Tinggi Swasta (PTS) Wilayah Kopertis XIII Provinsi Aceh dengan Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 2, no. 1 (February 28, 2018): 20. http://dx.doi.org/10.35870/jtik.v2i1.45.

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This research aims to make a sort 104 University in Region XIII Kopertis Aceh Provincewith the method Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) against the ratio of lecturers and students. TOPSIS is one method that can beused to solve the problem of Fuzzy MADM. This research takes into account all thecriteria that support decision making in order to help speed up and facilitate thedecision-making process and do a minimal quantity of perangkingan especially thelecturer at a college. Based on research results, calculation of TOPSIS begins withforming a decision matrix is normalized, then continued with a decision matrixweighting normalization. The step is done to determine the ideal solution matrix ofpositive and negative solution is ideal. The last stages of the method is to calculate thevalue of the preference of each alternative (Vi) in order to get the final results, the mosthigh value Vi shows the best alternative. Based on the end result then sorted 25 Colleges(PTS) is Locality Kopertis XIII Aceh at its best.
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Wang, Jing, Bing Yan, Guohao Wang, and Liying Yu. "Rating TAs in fuzzy QFD by objective penalty function and fuzzy TOPSIS based on weighted Hamming distance." Journal of Intelligent & Fuzzy Systems 39, no. 3 (October 7, 2020): 3665–79. http://dx.doi.org/10.3233/jifs-191955.

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Quality function deployment (QFD) is an useful tool to solve Multi-criteria decision making, which can translate customer requirements (CRs) into the technical attributes (TAs) of a product and helps maintain a correct focus on true requirements and minimizes misinterpreting customer needs. In applying quality function deployment, rating technical attributes from input variables is a crucial step in fuzzy environments. In this paper, a new approach is developed, which rates technical attributes by objective penalty function and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) based on weighted Hamming distance under the case of uncertain preference characteristics of decision makers in fuzzy quality function deployment. A pair of nonlinear programming models with constraints and a relevant pair of nonlinear programming models with unconstraints called objective penalty function models are proposed to gain the fuzzy important numbers of technical attributes. Then, this paper compares the fuzzy numbers by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method based on weighted Hamming distance in consideration of the uncertain preference characteristics of decision makers. To end with, the developed method is examined with the numerical examples.
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Ismail, M. Panji. "SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENERIMAAN MAHASISWA BARU JALUR BEASISWA DENGAN METODE TOPSIS (TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION)." JIKO (Jurnal Informatika dan Komputer) 3, no. 1 (February 22, 2018): 1. http://dx.doi.org/10.26798/jiko.2018.v3i1.79.

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The scholarship path is one of the paths used by the University of Technology Yogyakarta (UTY) in accepting new students. The track consists of seven criteria: school accreditation, family condition, report card score, achievement, written test, interview test. In order to process the criteria, it is necessary to have a Decision Support System (DSS) capable of conducting the scholarship selection process quickly, accurately and objectively. DSS is a system that can perform a decision-making process based on the human mindset. SPK can tolerate any kind of data whether it is certain or uncertain. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a Multi-Criteria Decision Making (MCDM) category which is a decision-making technique of some alternative options, especially Multi Attribute Decision Making (MADC). TOPSIS aims to determine the ideal ideal solution and the ideal negative solution of the scholarship criteria. A positive ideal solution maximizes benefit criteria and minimizes cost criteria, whereas a negative ideal solution maximizes cost criteria and minimizes benefit criteria. The research methodology used is SDLC (System Development Life Cycle) and system implementation built using Delphi 7 programming language and data processing using DBMS SQL Server 2012.. The results of the system show that the system provides accurate and valid results in accordance with the data owned by prospective students so that full scholarship can be given in the right target.
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Xu, Ji Heng, Ling Li, Jian Yong Liu, Cheng Qun Fu, and Ji Lin Zheng. "Imprecise DEA Model Based on TOPSIS." Applied Mechanics and Materials 63-64 (June 2011): 723–27. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.723.

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In view of the defect that TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) can not deal with imprecise data properly in multiple criteria decision making. And the weights are often hard to reflect the fact because of subjective preference of decision makers. We proposed a hybrid model combines TOPSIS and imprecise DEA model to improve the disadvantages. Ideal DMU and anti-ideal DMU were built, and the corresponding positive ideal point and negative ideal point were established. Imprecise DEA was set up and an upper-lower limit method is utilized to formulate the imprecise efficiency scores of the two hypothetical DMUs. Based on the distances between DMU0 and the two hypothetical DMUs respectively, imprecise relative closeness was formulated to rank the superiority of all DMUs. The imprecise DEA model based on TOPSIS can avoid too subjective weights and make the evaluation more rational. A numerical example indicated the efficiency of the hybrid measure.
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Kohoiriah, Siti, Untoro Apsiswanto, and Tri Aristy Saputri. "PENERAPAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) DALAM SELEKSI PENERIMAAN MAHASISWA BARU." International Research on Big-Data and Computer Technology: I-Robot 4, no. 1 (April 30, 2020): 31–35. http://dx.doi.org/10.53514/ir.v4i1.170.

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Dalam proses seleksi penerimaan mahasiswa baru, tim penyeleksi memeriksa data mahasiswa baru satu persatu pada formulir yang telah dikumpulkan oleh mahasiswa, lalu penilaian tersebut dapat dilihat berdasarkan hasil tes yang telah dilalui oleh para calon mahasiswa baru sesuai dengan jalur masing – masing yang dipilih. Dari hasil tersebut berupa data, yang nantinya akan dipindahkan ke dalam buku besar sebagai rekapan hasil dari penilaian mahasiswa baru. Dalam proses tersebut terdapat suatu kendala yaitu membutuhkan waktu yang lama pada sistem penyusunan laporan penilaian sehingga dalam mengambil keputusan penerimaan mahasiswa baru dirasa kurang optimal. Maka dari itu peneliti menerapkan metode TOPSIS sebagai sistem penunjang keputusan untuk menyeleksi penerimaan mahasiswa baru sebagai alternatif yang baik serta dapat menentukan calon mahasiswa yang tergolong lulus atau tidaknya pada STMIK Dharma Wacana baik melalui jalur reguler maupun jalur beasiswa.
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Xu, Yu-Heng, Si-Yi Cheng, and Hu-Biao Zhang. "Radiator threat evaluation with missing data based on improved technique for order preference by similarity to ideal solution." Journal of Intelligent & Fuzzy Systems 40, no. 3 (March 2, 2021): 5433–42. http://dx.doi.org/10.3233/jifs-202245.

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To solve the problem of the missing data of radiator during the aerial war, and to address the problem that traditional algorithms rely on prior knowledge and specialized systems too much, an algorithm for radiator threat evaluation with missing data based on improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been proposed. The null estimation algorithm based on Induced Ordered Weighted Averaging (IOWA) is adopted to calculate the aggregate value for predicting missing data. The attribute reduction is realized by using the Rough Sets (RS) theory, and the attribute weights are reasonably allocated with the theory of Shapley. Threat degrees can be achieved through quantization and ranking of radiators by constructing a TOPSIS decision space. Experiment results show that this algorithm can solve the incompleteness of radiator threat evaluation, and the ranking result is in line with the actual situation. Moreover, the proposed algorithm is highly automated and does not rely on prior knowledge and expert systems.
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Biswas, Pranab, Surapati Pramanik, and Bibhas C. Giri. "NonLinear Programming Approach for Single-Valued Neutrosophic TOPSIS Method." New Mathematics and Natural Computation 15, no. 02 (June 20, 2019): 307–26. http://dx.doi.org/10.1142/s1793005719500169.

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We propose an approach for multi-attribute group decision-making (MAGDM) problems under neutrosophic information, where the preference values of alternatives over the attributes and the importance of attributes are expressed in terms of single-valued neutrosophic sets. Firstly, we develop a nonlinear programming approach based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine relative closeness intervals of alternatives. Secondly, we aggregate closeness intervals to find out the ranking order of all alternatives by computing their optimal membership degrees based on the ranking method of interval numbers. Finally, we provide an illustrative example to show the effectiveness of the proposed approach.
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Liang, Xiao Fei, and Yue Xu. "Reinforcement Planning Decision of Old Bridge Based on TOPSIS-AHP Method." Advanced Materials Research 919-921 (April 2014): 426–29. http://dx.doi.org/10.4028/www.scientific.net/amr.919-921.426.

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The application of technique for order preference by similarity to ideal solution(TOPSIS) and analytic hierarchy process(AHP) in reinforcement scheme optimization for bridge is investigated in order to select the optimal scheme from several primarily feasible ones. This paper calculates every index through AHP and applies the improved TOPSIS method to normalize and sort the evaluation index values. Integrating TOPSIS and AHP may Consider both the subjective intentions of policy makers, but also to a certain extent, to avoid arbitrariness.A real project demonstrates that this method is effective and feasible.
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Azmi, Meri. "SISTEM PENDUKUNG KEPUTUSAN UNTUK MEMILIH USAHA WARALABA MAKANAN MENGGUNAKAN METODE TOPSIS." Elektron : Jurnal Ilmiah 5, no. 2 (December 13, 2013): 61–68. http://dx.doi.org/10.30630/eji.5.2.55.

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Large number of franchises that will be selected as well as indicators of many criteria, it is necessary to build a decision support system that will help decide which franchise to choose. The model used in the decision support system is a Multiple Attribute Decision Making (MADM) and to perform calculations on the case MADM method in finding the best alternative based on the criteria specified use traditional methods TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to perform the calculations. TOPSIS method is chosen as the method is based on the concept that the best alternative was chosen not only has the shortest distance from the positive ideal solution, but also has the longest distance from the negative ideal solution.
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Méndez, Máximo, Mariano Frutos, Fabio Miguel, and Ricardo Aguasca-Colomo. "TOPSIS Decision on Approximate Pareto Fronts by Using Evolutionary Algorithms: Application to an Engineering Design Problem." Mathematics 8, no. 11 (November 20, 2020): 2072. http://dx.doi.org/10.3390/math8112072.

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A common technique used to solve multi-objective optimization problems consists of first generating the set of all Pareto-optimal solutions and then ranking and/or choosing the most interesting solution for a human decision maker (DM). Sometimes this technique is referred to as generate first–choose later. In this context, this paper proposes a two-stage methodology: a first stage using a multi-objective evolutionary algorithm (MOEA) to generate an approximate Pareto-optimal front of non-dominated solutions and a second stage, which uses the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) devoted to rank the potential solutions to be proposed to the DM. The novelty of this paper lies in the fact that it is not necessary to know the ideal and nadir solutions of the problem in the TOPSIS method in order to determine the ranking of solutions. To show the utility of the proposed methodology, several original experiments and comparisons between different recognized MOEAs were carried out on a welded beam engineering design benchmark problem. The problem was solved with two and three objectives and it is characterized by a lack of knowledge about ideal and nadir values.
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Khansa, Amalia, Fauziah Fauziah, and Aris Gunaryati. "Penerapan Metode Simple Additive Weighting (SAW) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) dalam Pemilihan Perangkat Pribadi." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 5, no. 2 (December 11, 2020): 195. http://dx.doi.org/10.35870/jtik.v5i2.179.

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Along with the rapid development of technology, many types of laptops and smartphones have sprung up. The many types on the market can make consumers confused in choosing products. The decision support system for choosing this personal device uses the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The basic concept of this method is to find the weighted sum of the performance ratings for each alternative for all attributes. In the results of manual and system calculations, the SAW and TOPSIS methods produce the same ranking. In the SAW method, the highest-ranking of laptops is obtained by Acer Swift 3 (SF314-56G) with a value of 0.977 and on smartphones, the highest score is obtained by the Samsung Galaxy M51 with a value of 1. In the TOPSIS method, the highest-ranking is obtained by a laptop with a value of 0.9507 and a smartphone with a value of 1.Keywords:Notebook; SAW; Decision Support System; Smartphone; TOPSIS.
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Sumiatun, Sumiatun, and Kuzairi Kuzairi. "ANALISIS OPTIMAL PENJUALAN PETIS MADURA MENGGUNAKAN METODE TOPSIS." Jurnal Matematika "MANTIK" 1, no. 1 (November 18, 2015): 17. http://dx.doi.org/10.15642/mantik.2015.1.1.17-21.

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Petis merupakan jenis makanan yang digemari orang banyak, selain dijadikan bahan untuk usaha yang ditekuni, petis juga bemanfaat untuk bahan pendamping makanan rigan seperti gorengan, uniknya petis Madura ini awet dan dijual sampai keluar Madura. Dalam penelitian ini metode yang digunakan adalah Technique For Order Preference By Similarity To Ideal Solution (TOPSIS). Metode TOPSIS adalah salah satu metode yang digunakan untuk menyelesaikan masalah Multi Attribute Decision Making (MADM). Metode TOPSIS didasarkan pada konsep dimana alternatif terpilih yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif, namun juga memiliki jarak terpanjang dari solusi ideal negatif. Metode TOPSIS memiliki beberapa kelebihan, diantaranya konsepnya yang sederhana dan mudah dipahami, komputasinya efisien, dan memiliki kemampuan untuk mengukur kinerja relatif dari alternatif-alternatif keputusan dalam bentuk matematis yang sederhana.
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Cho, Jaeho, Jaeyoul Chun, Inhan Kim, and Jungsik Choi. "QFD Based Benchmarking Logic Using TOPSIS and Suitability Index." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/851303.

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Users’ satisfaction on quality is a key that leads successful completion of the project in relation to decision-making issues in building design solutions. This study proposed QFD (quality function deployment) based benchmarking logic of market products for building envelope solutions. Benchmarking logic is composed of QFD-TOPSIS and QFD-SI. QFD-TOPSIS assessment model is able to evaluate users’ preferences on building envelope solutions that are distributed in the market and may allow quick achievement of knowledge. TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) provides performance improvement criteria that help defining users’ target performance criteria. SI (Suitability Index) allows analysis on suitability of the building envelope solution based on users’ required performance criteria. In Stage 1 of the case study, QFD-TOPSIS was used to benchmark the performance criteria of market envelope products. In Stage 2, a QFD-SI assessment was performed after setting user performance targets. The results of this study contribute to confirming the feasibility of QFD based benchmarking in the field of Building Envelope Performance Assessment (BEPA).
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Beg, Ismat, and Tabasam Rashid. "Modelling Uncertainties in Multi-Criteria Decision Making using Distance Measure and TOPSIS for Hesitant Fuzzy Sets." Journal of Artificial Intelligence and Soft Computing Research 7, no. 2 (April 1, 2017): 103–9. http://dx.doi.org/10.1515/jaiscr-2017-0007.

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Abstract A notion for distance between hesitant fuzzy data is given. Using this new distance notion, we propose the technique for order preference by similarity to ideal solution for hesitant fuzzy sets and a new approach in modelling uncertainties. An illustrative example is constructed to show the feasibility and practicality of the new method.
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Efendi, Dwi Marisa, Asep Afandi, Rustam Rustam, Sidik Rahmatullah, Sigit Mintoro, Supriyanto Supriyanto, and Reni Faselia. "Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode Technique For Order Of Preference By Similarity To Ideal Solution (Topsis)." Jurnal Ilmu Komputer dan Bisnis 12, no. 1 (May 1, 2021): 248–56. http://dx.doi.org/10.47927/jikb.v12i1.111.

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Karyawan merupakan suatu faktor yang sangat penting dalam keberlangsungan suatu organisasi. Karyawan yang berkualitas akan memudahkan suatu organisasi dalam mencapai tujuannya. Oleh karena itu, untuk memacu dan meningkatkan kinerja Karyawan agar lebih rajin dan semangat untuk bekerja lebih baik lagi, maka sebuah organisasi atau perusahan dapat memberikan penghargaan kepada para karyawan yang dianggap memiliki kinerja terbaik oleh perusahaan tersebut.Metode Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)dengan menggunakan aplikasi Borland Delphi 7, dan dengan menggunakan metode pengembangan sistem yaitu waterfall. Sehingga akan menghasilkan sebuah pengambilan keputusan calon karyawan terbaik secara terkomputerisasi dengan cara yang lebih efektif dan tidak menurut sudut pandang saja, atau kepada karyawan yang memiliki kedekatan hubungan tertentu dengan kepala kantor pos kuningan.Sistem perhitungan menggunakan metode topsis dalam menggunakan borland delphi 7 dengan sampel 10 data karyawan. Dan dengan menggunakan 6 kriteria yaitu pendidikan, absensi, masakerja, kedisiplinan,kerjasama dan pelayanan. Maka dari perhitungan tersebut didapat hasil ranking satu tertingi yaitu Tita Kurniati dengan hasil nilai 0,6916 dan mendapat hasil nilai error 0,034.
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Trisna, Novi, Sepsa Nur Rahman, and Annisak Izzaty Jamhur. "Sistem Pendukung Keputusan Penerima Beasiswa Dengan Metode Technique For Order Of Preference By Similarity To Ideal Solution (TOPSIS)." JURNAL INFORMATIKA 7, no. 3 (September 1, 2019): 126–32. http://dx.doi.org/10.36987/informatika.v7i3.1383.

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Rasyid, Abdul, and Septya Maharani. "Implementasi Technique For Order Preferences By Similary To Ideal Solution (Topsis) Pada Seleksi Asisten Laboratorium (Studi Kasus : Laboratorium RPL FMIPA Universitas Mulawarman)." Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer 11, no. 2 (September 12, 2016): 48. http://dx.doi.org/10.30872/jim.v11i2.214.

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Praktikum merupakan kegiatan akademik yang bertujuan untuk membantu Mahasiswa mengikuti praktikum yang disebut praktikan dalam memperdalam ilmu dengan mempraktekkan teori yang dituntun oleh asisten laboratorium. Pemilihan asisten laboratorium yang baru di program studi Ilmu Komputer harus sesuai dengan kemampuan calon asisten dengan praktikum matakuliah yang akan diajarkan, masalah dalam pemilihan calon asisten itu sendiri biasanya terjadi saat adminyaitu asisten kepala laboratorium dalam menilai setiap calon asisten apabila setiap calon memiliki kemampuan yang tidak jauh berbeda dengan calon asisten yang lain. Maka dari itu diperlukan suatu sistem yang dapat membantu admindalam menilai para calon asisten. Sistem Pendukung Keputusan (SPK) sebagai sistem komputer yang mengolah data menjadi informasi untuk mengambil dari masalah semi terstruktur yang spesifik sangatcocok dalam pengambilan keputusan. Salah satu metode yang dipakai didalam SPK ialah metode Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) dimana alternatif yang dipilih memiliki kedekatan dengan solusi ideal positif dan jauh dari solusi ideal negatif. Hasil yang dicapai dari penelitian ini menerapkan metode Technique For Order Preference by Similarity to Ideal Solutiondalam sistem pendukung keputusan yang dapat memberikan rekomendasi calon asisten kepada adminsebagai bahan pertimbangan untuk pengambilan keputusan secara tepat dan diharapkan dapat mempermudah proses keputusan yang terbaik.
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Wahyu Rifaldi, Khisan Ihza, Sentot Achmadi, and Joseph Dedy Irawan. "SISTEM INFORMASI BURSA KERJA DENGAN SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN TOPSIS (Technique For Order Preference By Similarity Of Ideal Solution)." JATI (Jurnal Mahasiswa Teknik Informatika) 5, no. 1 (February 28, 2021): 246–52. http://dx.doi.org/10.36040/jati.v5i1.3234.

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Masalah utama pada mahasiswa yang telah menyelesaikan pendidikan tinggi masih ada beberapa alumni yang belum mendapatkan pekerjaan di karenakan informasi yang didapatkan sedikit dan kurang informatif. Sehingga pusat karir Institut Teknologi Nasional Malang membantu alumni mahasiswa untuk mendapatkan informasi lowongan dengan cara memposting lowongan pekerjaan berupa gambar atau pranala di media sosial. Namun cara tersebut terbilang tidak efektif, dikarenakan mahasiswa harus mencari pekerjaan yang sesuai dengan bidangnya secara manual. Aplikasi yang akan dibangun pada penelitian ini yaitu sistem informasi bursa kerja dengan sistem pendukung keputusan menggunakan metode topsis berbasis website yang dapat dijadikan sarana penyebaran dan pengaksesan informasi lowongan pekerjaan. Metode topsis dapat digunakan untuk memberikan rekomendasi informasi lowongan kerja yang sesuai dengan kriteria dari alumni mahasiswa, sehingga dapat mempermudah proses pencarian informasi. Pengujian fungsional pada sistem ini dapat berjalan 100% dalam hal tampilan dan fungsi pada 3 web browser yaitu Chromium, Firefox, Microsoft Edge serta dari hasil pengujian aplikasi pada 25 pengguna didapatkan bahwa, 7 menyatakan sistem mudah untuk digunakan, 5 menyatakan desain aplikasi (user interface) sudah menarik atau sesuai dan 8 menyatakan fungsi pada sistem berjalan dengan baik dan sesuai.
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Zavadskas, Edmundas Kazimieras, Abbas Mardani, Zenonas Turskis, Ahmad Jusoh, and Khalil MD Nor. "Development of TOPSIS Method to Solve Complicated Decision-Making Problems — An Overview on Developments from 2000 to 2015." International Journal of Information Technology & Decision Making 15, no. 03 (May 2016): 645–82. http://dx.doi.org/10.1142/s0219622016300019.

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In recent years several previous scholars made attempts to develop, extend, propose and apply Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for solving problems in decision making issues. Indeed, there are questions, how TOPSIS can help for solving these problems? Or does TOPSIS solved decision making problems in the real world? Therefore, this study shows the recent developments of TOPSIS approach which are presented by previous scholars. To achieve this objective, there are 105 reviewed papers which developed, extended, proposed and presented TOPSIS approach for solving DM problems. The results of the study indicated that 49 scholars have extended or developed TOPSIS technique and 56 scholars have proposed or presented new modifications for problems solution related to TOPSIS technique from 2000 to 2015. In addition, results of this study indicated that, previous studies have modifications related to this technique in 2011 more than other years.
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Antuchevičiene, Jurgita. "EVALUATION OF ALTERNATIVES APPLYING TOPSIS METHOD IN A FUZZY ENVIRONMENT." Technological and Economic Development of Economy 11, no. 4 (December 31, 2005): 242–47. http://dx.doi.org/10.3846/13928619.2005.9637704.

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The paper analyses the problem of multiple attribute decision‐making (MADM) under fuzzy environment. In some cases the crisp value is inadequate to model real‐life situations. For this reason some fuzzy MADM methods have been developed. The extended TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) to fuzzy environment is presented in the current paper. Weights and ratings of each criterion are described in triangular fuzzy numbers. The relative closeness to the ideal solution of each alternative is calculated applying different approaches that were presented in different scientific papers. A computational experiment is presented to compare the results of a multiple attribute analysis that uses three modifications of fuzzy TOPSIS method in a particular situation.
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42

Dursun, Mehtap, and Osman Ogunclu. "Agile Supplier Evaluation Using Hierarchical TOPSIS Method." WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS 18 (April 19, 2021): 12–19. http://dx.doi.org/10.37394/23209.2021.18.3.

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Increased competitiveness of the market enforces companies to respond quickly and appropriately to sudden changes in the market in order to adapt to continuously updated conditions of business environment and keep their survivals. Agility concept rises at this level due to necessity of coping with unpredictable changes and uncertainty. Agility enables the firms responsiveness in a quick and an effective way to the set of interdependent changes required in design, production, marketing and organization of the companies. This study addresses agile supplier selection problem. Hierarchical fuzzy technique for order preference by similarity to ideal solution approach (TOPSIS) is proposed for agile supplier selection problem in an airline company.
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43

Murti, Alif Catur, and Noor Yulita Dwi Setyaningsih. "KOMBINASI SISTEM PENDUKUNG KEPUTUSAN DAN SISTEM INFORMASI GEOGRAFIS DALAM PENENTUAN LOKASI INDUSTRI DI KUDUS." Simetris : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 7, no. 1 (April 1, 2016): 263. http://dx.doi.org/10.24176/simet.v7i1.513.

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Industri merupakan bidang yang sangat vital dibidang pembangunan, disamping sebagai pendukung utama, industri juga sangat berperan dalam peningkatan perekonomian masyarakat Indonesia pada umumnya dan wilayah daerah pada khususnya. Konsep kombinasi SPK (Sistem Pendukung Keputusan) dan SIG (Sistem Informasi Geografis) dalam penentuan lokasi industri sangat sesuai. Metode SPK yang digunakan dalam penentuan lokasi industri yang layak adalah Technique For Order Preference by Similarity to Ideal Solution (TOPSIS), kemudian hasil pengolahan data yang didapat akan divisualisasikan menggunakan (SIG). Hasil dari metode ini menunjukkan bahwa lokasi desa Gondang Manis di Kecamatan Bae adalah lokasi yang tepat untuk dijadikan lokasi industri dengan nilai preferensi 0,575. Kata kunci: Industri, Perekonomian, SPK, TOPSIS, SIG, Pemetaan.
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44

Ye, Fei, and Qiang Lin. "Partner Selection in a Virtual Enterprise: A Group Multiattribute Decision Model with Weighted Possibilistic Mean Values." Mathematical Problems in Engineering 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/519629.

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This paper proposes an extended technique for order preference by similarity to ideal solution (TOPSIS) for partner selection in a virtual enterprise (VE). The imprecise and fuzzy information of the partner candidate and the risk preferences of decision makers are both considered in the group multiattribute decision-making model. The weighted possibilistic mean values are used to handle triangular fuzzy numbers in the fuzzy environment. A ranking procedure for partner candidates is developed to help decision makers with varying risk preferences select the most suitable partners. Numerical examples are presented to reflect the feasibility and efficiency of the proposed TOPSIS. Results show that the varying risk preferences of decision makers play a significant role in the partner selection process in VE under a fuzzy environment.
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45

Munawar, Zen. "PENERAPAN METODE ANALYTICAL HIERARCHY PROCESS DAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO ORDER SOLUTION DALAM SELEKSI PENERIMAAN MAHASISWA BARU JALUR BIDIK MISI." TEMATIK 4, no. 1 (June 30, 2017): 34–53. http://dx.doi.org/10.38204/tematik.v4i1.171.

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Metode Analytical Hierarchy Process (AHP) di gunakan untuk mengambil suatu keputusan dengan cara membandingkan secara berpasangan setiap kriteria yang di miliki oleh suatu permasalahan sehingga di dapat suatu bobot nilai dari kepentingan tiap kriteria – kriteria yang ada, dan Technique for Order Preference by Similarity to Order Solution (TOPSIS) di gunakan untuk mencari solusi yang paling ideal dan kebutuhan masalah yang ada, dalam hal ini dilakukan dalam menyeleksi penerimaan mahasiswa baru jalur bidik misi dengan cara di berikan bobot nilai sesuai dengan kebutuhan. Terdapat rumusan masalah yaitu bagaimana menentukan bobot nilai pada seleksi mahasiswa jalur bidik misi. Adapun Tujuannya mengembangkan sistem pendukung keputusan dalam seleksi mahasiswa jalur bidik misi. Sistem pendukung keputusan (SPK) dalam seleksi penerimaan mahasiswa ajalur bidikmisi dapat menyimpan data kriteria, data mahasiswa, data prioritas kriteria, dan menganalisis bobot nilai kriteria serta alternatif mahasiswa dengan menggunakan metode AHP dan TOPSIS, hasil dari analisis tersebut dapat digunakan untuk pelaporan penerimaan mahasiswa jalur bidikmisi. Metode AHP dan TOPSIS dapat menentukan alternatif mahasiswa terbaik hal ini terbukti dengan mahasiswa yang memiliki nilai tertinggi dari hasil perhitungan TOPSIS dan AHP yang di pilih. Sistem pendukung keputusan penerimaan calon mahasiswa bidikmisi menggunakan metode AHP dan TOPSIS dapat di kembangkan dengan membandingkan metode keduanya. Diharapkan ada yang melakuakan pengembangan lebih lanjut untuk masalah yang lain, bahkan yang lebih kompleks dengan jumlah kriteria dan alternatif yang lebih banyak
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46

Rahpeyma, Bentolhoda, and Mahnaz Zarei. "An Integrated QFD-TOPSIS Approach for Supplier Selection Under Fuzzy Environment." International Journal of Service Science, Management, Engineering, and Technology 9, no. 3 (July 2018): 62–81. http://dx.doi.org/10.4018/ijssmet.2018070105.

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This article describes how supplier selection is a multi-index problem which affects the efficiency of the whole supply chain in both manufacturing and service industries. Considering the importance of selecting effective suppliers, this article aims to integrate two well-known techniques, Quality Function Deployment (QFD) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in order to evaluate suppliers and rank them based on their merits. In order to handle the inherent uncertainty in the process of experts' judgments, fuzzy logic is involved in the methodology applied in this study. The validity of the utilized integrated approach is demonstrated through conducting a case study in the detergent manufacturing industry in Iran.
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47

Riandana, Yudistira Ergha, and Muhammad Hamka. "Sistem Pendukung Keputusan Penerima Pembiayaan Akad Multijasa Menggunakan Metode Analitycal Hierarchy Process Dan Technique For Order Preference By Similarity To Ideal Solution." Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) 21, no. 2 (November 17, 2020): 79. http://dx.doi.org/10.30595/techno.v21i2.7846.

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Lembaga Keuangan Syariah memiliki beberapa jenis syarat pembiayaan, salah satu jenis pembiayaan yang sesuai dengan kebutuhan sehari – hari yaitu Pembiayaan Multijasa. Pembiayaan tersebut mempunyai syarat yang disebut dengan akad yang berarti ikatan atau kewajiban. Akad Ijarah Multijasa merupakan akad pembiayaan pada bank atau koperasi syariah yang berfokus pada pembiayaan manfaat berdasarkan syariat islam. Banyaknya kriteria yang harus dipertimbangkan membuat pihak UJKS Senopati UMP membutuhkan waktu yang lebih lama dalam penyeleksian calon nasabah yang berhak menerima pinjaman, maka untuk mempermudah proses seleksi tersebut dibuatlah Sistem Pendukung Keputusan Penerima Pembiayaan Akad Ijarah Pembiayaan Multijasa menggunakan Metode Analitycal Hierarchy Process (AHP) dan Metode Technique For Order Preference By Similarity To Ideal Solution (TOPSIS). Metode AHP digunakan untuk menentukan bobot kriteria, sedangkan metode TOPSIS digunakan dalam menentukan rangking penerima pembiayaan multijasa di UJKS Senopati UMP. Berdasarkan pengolahan data yang dilakukan dapat diambil kesimpulan bahwa dengan menggunakan metode AHP, diketahui bahwa terdapat 7 prioritas kriteria dalam menentukan penerima pembiayaan multijasa yaitu yang pertama jumlah pembiayaan dengan nilai prioritas 34,4% , jangka waktu dengan nilai prioritas 23,3% , jaminan dengan nilai prioritas 17,8%, tujuan dengan nilai prioritas 9,6% , pekerjaan dengan nilai prioritas 6% , jumlah angsuran per bulan dengan nilai prioritas 5,7% , dan usia dengan nilai prioritas 4,2%. Sedangkan berdasarkan pengolahan menggunakan metode TOPSIS diketahui bahwa A8 (Alternatif 8 atau Nasabah 8) menempati peringkat pertama yang direkomendasikan untuk mendapat pembiaayan multijasa di UJKS Senopati UMP dengan nilai preferensi terbesar yaitu 0,680.
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48

Widjaja, Haris, and Ririn Ikana Desanti. "Decision Support System for Home Selection in South Tangerang City Using TOPSIS Method." IJNMT (International Journal of New Media Technology) 7, no. 2 (December 28, 2020): 76–81. http://dx.doi.org/10.31937/ijnmt.v7i2.1300.

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The desire to have a dream house makes people consider of the criteria of the house they will be lived. Many developers offer a variety of house alternatives ranging from price, location, design, building area and land area. Customers are pleased to choose their dream house as their desired. Based on that situation, this research is conduct to create a web-bases application for home selection that consider the useful criteria to help consumers choose a decent home by using the Technique for Order of Preference by Similarity To Ideal Solution (TOPSIS) method. The TOPSIS method has the concept that the best alternative has the shortest distance from a positive ideal solution and also has the farthest distance from a negative ideal solution. This TOPSIS method is applied to provide recommendations on the choice of home decisions in the South Tangerang area based on predetermined criteria. The results obtained in the TOPSIS calculation are the housing recommendations that are closest to the value of the calculation result.
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Duong, Truong Thi Thuy, and Nguyen Xuan Thao. "TOPSIS model based on entropy and similarity measure for market segment selection and evaluation." Asian Journal of Economics and Banking 5, no. 2 (June 22, 2021): 194–203. http://dx.doi.org/10.1108/ajeb-12-2020-0106.

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PurposeThe paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.Design/methodology/approachIntroducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.FindingsThe outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.Originality/valueThis paper put forward an effective multi-criteria decision-making dealing with uncertain information.
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50

Omosigho, S. E., and Dickson Omorogbe. "Supplier selection using different metric functions." Yugoslav Journal of Operations Research 25, no. 3 (2015): 413–23. http://dx.doi.org/10.2298/yjor130706028o.

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Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.
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