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Journal articles on the topic 'Information Gain Ratio'

Author: Grafiati

Published: 3 June 2025

Last updated: 20 July 2025

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1

Dimas, Ari Setyawan. "IMPLEMENTASI FUNGSI DISPERSION RATIO PADA PROSES SPLITING ATRIBUT ALGORITMA DECISION TREE." MADANI: Jurnal Ilmiah Multidisiplin 1, no. 2 (2023): 86–91. https://doi.org/10.5281/zenodo.7782439.

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Metode klasifikasi yang memiliki proses seleksi fitur adalah algoritma decision tree. Proses seleksi fitur pada algortima decision tree biasanya menggunakan fungsi Information Gain. Information gain  pada algoritma decision tree memiliki kelemahan jika ada dataset yang memiliki atribut key seperti Product-ID. Fungsi dispersion ratio pada algoritma decision tree dapat meningkatkan signifikansi proses seleksi fitur, sehingga dapat mengatasi kekurangan fungsi information gain. Proses splitting atribut pada decision tree menggunakan fungsi dispersion ratio dengan menggunakan dataset yang diam

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Ali, Euis Oktavianti, Maria Agustin, and Risna Sari. "IMPLEMENTASI ALGORITMA DECISION TREE DENGAN FITUR SELEKSI WEIGHT BY INFORMATION GAIN." MULTINETICS 9, no. 2 (2024): 118–26. http://dx.doi.org/10.32722/multinetics.v9i2.5715.

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Paper ini bertujuan adalah untuk menerapkan pemilihan bobot fitur dengan mempertimbangkan nilai Gain Ratio pada algoritma Decision Tree dalam mengklasifikasikan nilai akademik mahasiswa. Penentukan pemilihan fitur dari gain ratio berdasarkan informasi nilai split untuk mengurangi bias dalam fitur (atribut). Nilai Gain Ratio tertinggi akan menjadi akar percabangan pada pohon yang menjadi ciri penentu kelulusan mahasiswa. Kami menggunakan 82 data yang dibagi menjadi dua kelas yang disebut lulus dan tidak lulus. Dari data tersebut, diketahui bahwa atribut ip_smt 7 mendapatkan nilai gain ratio ter

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3

Suprapto, Suprapto. "Improvement Naive Bayes Menggunakan Forward Selection, Information Gain dan Gain Ratio untuk Penanganan Independensi Fitur." Jurnal Sosial Teknologi 5, no. 4 (2025): 925–34. https://doi.org/10.59188/jurnalsostech.v5i4.32084.

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Penelitian ini bertujuan untuk menganalisis peningkatan kinerja algoritma Naive Bayes (NB) dalam menangani independensi fitur menggunakan metode Forward Selection, Information Gain, dan Gain Ratio. Naive Bayes merupakan algoritma klasifikasi yang sering digunakan karena efisiensi komputasinya yang tinggi, namun sering mengalami penurunan performa ketika ada ketergantungan antar fitur. Penelitian ini menggunakan pendekatan eksperimental dengan menerapkan beberapa algoritma, yakni Naive Bayes, Forward Selection Naive Bayes (FSNB), Forward Selection Information Gain Naive Bayes (FSIGNB), dan Forw

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Kurniabudi, Kurniabudi, Abdul Harris, and Albertus Edward Mintaria. "Komparasi Information Gain, Gain Ratio, CFs-Bestfirst dan CFs-PSO Search Terhadap Performa Deteksi Anomali." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 1 (2021): 332. http://dx.doi.org/10.30865/mib.v5i1.2258.

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Large data dimensionality is one of the issues in anomaly detection. One approach used to overcome large data dimensions is feature selection. An effective feature selection technique will produce the most relevant features and can improve the classification algorithm to detect attacks. There have been many studies on feature selection techniques, each using different methods and strategies to find the best and relevant features. In this study, a comparison of Information Gain, Gain Ratio, CFs-BestFirst and CFs-PSO Search techniques was compared. The selection features of the four techniques w

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Mahalingam, P. R., and S. Vivek. "Predicting Financial Savings Decisions Using Sigmoid Function and Information Gain Ratio." Procedia Computer Science 93 (2016): 19–25. http://dx.doi.org/10.1016/j.procs.2016.07.176.

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Dyah, Ayu Kunthi Puspitasari, and Basti Farani Dinesh. "ANALISIS KINERJA PENGAJAR : PENGARUH KEPEMIMPINAN TRANSFORMASIONAL, IKLIM KERJA, DAN KEPUASAN KERJA." MADANI: Jurnal Ilmiah Multidisiplin 1, no. 2 (2023): 92–100. https://doi.org/10.5281/zenodo.7782501.

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Metode klasifikasi yang memiliki proses seleksi fitur adalah algoritma decision tree. Proses seleksi fitur pada algortima decision tree biasanya menggunakan fungsi Information Gain. Information gain  pada algoritma decision tree memiliki kelemahan jika ada dataset yang memiliki atribut key seperti Product-ID. Fungsi dispersion ratio pada algoritma decision tree dapat meningkatkan signifikansi proses seleksi fitur, sehingga dapat mengatasi kekurangan fungsi information gain. Proses splitting atribut pada decision tree menggunakan fungsi dispersion ratio dengan menggunakan dataset yang diam

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7

Prasetiyo, B., Alamsyah, M. A. Muslim, and N. Baroroh. "Evaluation of feature selection using information gain and gain ratio on bank marketing classification using naïve bayes." Journal of Physics: Conference Series 1918, no. 4 (2021): 042153. http://dx.doi.org/10.1088/1742-6596/1918/4/042153.

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Wang, Zhongzheng, Guangming Deng, and Jianqi Yu. "Group Feature Screening Based on Information Gain Ratio for Ultrahigh-Dimensional Data." Journal of Mathematics 2022 (December 2, 2022): 1–15. http://dx.doi.org/10.1155/2022/1600986.

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Most model-free feature screening approaches focus on the -individual predictor; therefore, they are not able to incorporate structured predictors like grouped variables. In this article, we propose a group screening procedure via the information gain ratio for a classification model, which is a direct extension of the original sure independence screening procedure and also model-free. The proposed method yields a better screening performance and classification accuracy. It is demonstrated that the proposed group screening method possesses the sure screening property and ranking consistency pr

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Azizah, Siti Roziana, Rudy Herteno, Andi Farmadi, Dwi Kartini, and Irwan Budiman. "Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 6 (2023): 1361–68. http://dx.doi.org/10.25126/jtiik.1067467.

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Penyakit jantung menjadi salah satu penyebab utama kematian bersama dengan penyakit lainnya. Dalam bidang teknologi, data mining dapat digunakan untuk mendiagnosa suatu penyakit yang bersumber dari data rekam medis pasien. Pada klasifikasi dataset medis, Naive Bayes merupakan salah satu metode terbaik yang digunakan. Tujuan dari penelitian ini adalah untuk mengetahui perbandingan hasil akurasi dari Naive Bayes menggunakan beberapa seleksi fitur yaitu Forward Selection, Backward Elimination, kombinasi union hasil seleksi fitur Forwad Selection dan Backward Elimination, Information Gain, Gain Ra

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Azizah, Siti Roziana, Rudy Herteno, Andi Farmadi, Dwi Kartini, and Irwan Budiman. "Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung." Jurnal Teknologi Informasi dan Ilmu Komputer 10, no. 6 (2023): 1361–68. https://doi.org/10.25126/jtiik.2023107467.

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Penyakit jantung menjadi salah satu penyebab utama kematian bersama dengan penyakit lainnya. Dalam bidang teknologi, data mining dapat digunakan untuk mendiagnosa suatu penyakit yang bersumber dari data rekam medis pasien. Pada klasifikasi dataset medis, Naive Bayes merupakan salah satu metode terbaik yang digunakan. Tujuan dari penelitian ini adalah untuk mengetahui perbandingan hasil akurasi dari Naive Bayes menggunakan beberapa seleksi fitur yaitu Forward Selection, Backward Elimination, kombinasi union hasil seleksi fitur Forwad Selection dan Backward Elimination, Information Gain, Gain Ra

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M. Yhogha Ismail Ibn Ibrahim and Sandi Badiwibowo Atim. "KLASIFIKASI LEVEL OBESITAS MENGGUNAKAN DECISION TREE C45 DALAM MENENTUKAN AKURASI PADA KRITERIA INFORMATION GAIN, GAIN RATIO, GINI INDEX." JIKI (Jurnal llmu Komputer & lnformatika) 5, no. 2 (2024): 169–78. https://doi.org/10.24127/jiki.v5i2.7191.

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Abstrak : Obesitas adalah penumpukan lemak ekstra yang disebabkan oleh ketidakcocokan jangka panjang antara asupan kalori dan pengeluaran energi. Menurut indeks RPJMN 2015-2019, 13,5 persen orang dewasa di Indonesia di atas usia 18 tahun kelebihan berat badan, 28,7 persen mengalami obesitas (BMI>25), bahkan 15,4 persen mengalami obesitas (BMI>27). 18,8% anak-anak berusia 5 hingga 12 tahun kelebihan berat badan, dan 10,8% dari mereka mengalami obesitas. Tindakan memilih, memeriksa, dan memodelkan sejumlah besar data untuk menemukan pola dan tren yang biasanya tidak diperhatikan. Algoritma

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Masripah, Siti, Dewi Ayu Nurwulandari, and Rizal Amegia Saputra. "Pencarian Criteria Splitting Terbaik Pada Algoritma C4.5 Untuk Mengukur Pemilihan Pembelajaran Pada Era Pendemi Covid-19." Jurnal Larik: Ladang Artikel Ilmu Komputer 2, no. 1 (2022): 1–7. http://dx.doi.org/10.31294/larik.v2i1.1292.

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Kondisi pandemi tahun 2022 masih berlangsung dan sudah memasuki tahun ke-2 sistem pembelajaran yang dilakukan masih belum 100% luring dan masih dilakukan secara daring. Sistem pembelajaran yang dilakukan secara daring tentunya membuat para orang tua, pendidik serta pelajar harus mengeluarkan biaya ekstra dan pemahaman yang ekstra karena tidak semua mampu mengatasi dua hal tersebut. Klasifikasi dalam menentukan pemilihan pembelajaran menjadi sangat penting, karena pembelajaran daring menuai pro dan kontra pada tengah masyarakat. Pada penelitian ini dataset didapat dari hasil survei terhadap ora

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13

Chen, Jingnian, Houkuan Huang, Fengzhan Tian, and Shengfeng Tian. "A selective Bayes Classifier for classifying incomplete data based on gain ratio." Knowledge-Based Systems 21, no. 7 (2008): 530–34. http://dx.doi.org/10.1016/j.knosys.2008.03.013.

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Putri, Nitami Lestari, Radityo Adi Nugroho, and Rudy Herteno. "Intrusion Detection System Berbasis Seleksi Fitur Dengan Kombinasi Filter Information Gain Ratio Dan Correlation." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 3 (2021): 457. http://dx.doi.org/10.25126/jtiik.0813154.

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<p><em>Intrusion Detection System</em> merupakan suatu sistem yang dikembangkan untuk memantau dan memfilter aktivitas jaringan dengan mengidentifikasi serangan. Karena jumlah data yang perlu diperiksa oleh IDS sangat besar dan banyaknya fitur-fitur asing yang dapat membuat proses analisis menjadi sulit untuk mendeteksi pola perilaku yang mencurigakan, maka IDS perlu mengurangi jumlah data yang akan diproses dengan cara mengurangi fitur yang dapat dilakukan dengan seleksi fitur. Pada penelitian ini mengkombinasikan dua metode perangkingan fitur yaitu <em>Information Gai

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15

Chauhan, Sneha, Sugata Gangopadhyay, and Aditi Kar Gangopadhyay. "Intrusion Detection System for IoT Using Logical Analysis of Data and Information Gain Ratio." Cryptography 6, no. 4 (2022): 62. http://dx.doi.org/10.3390/cryptography6040062.

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The rapidly increasing use of the internet has led to an increase in new devices and technologies; however, attack and security violations have grown exponentially as well. In order to detect and prevent attacks, an Intrusion Detection System (IDS) is proposed using Logical Analysis of Data (LAD). Logical Analysis of Data is a data analysis technique that classifies data as either normal or an attack based on patterns. A pattern generation approach is discussed using the concept of Boolean functions. The IDS model is trained and tested using the Bot-IoT dataset. The model achieves an accuracy

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Le, Sang Van. "Selection index for Duroc pigs based on average daily gain, feed conversion ratio, and intramuscular fat content." Ministry of Science and Technology, Vietnam 65, no. 1 (2023): 54–62. http://dx.doi.org/10.31276/vjste.65(1).54-62.

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This study was conducted to compare the genetic gain per sow per year of Duroc pigs in twelve scenarios. These scenarios were based on the number of traits used such as average daily gain (ADG), feed conversion ratio (FCR), intramuscular fat content (IMF) and were also based on the number of records of phenotype for these traits from the individual animal and its relatives. The values of all relevant genetic and economic parameters were selected from the literature and applied to the magnetotail (MT) index model to calculate the index selection accuracy and response per trait. Genetic gain per

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Müller, J. Gerhard. "Photon Detection as a Process of Information Gain." Entropy 22, no. 4 (2020): 392. http://dx.doi.org/10.3390/e22040392.

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Making use of the equivalence between information and entropy, we have shown in a recent paper that particles moving with a kinetic energy ε carry potential information i p o t ( ε , T ) = 1 ln ( 2 ) ε k B T relative to a heat reservoir of temperature T . In this paper we build on this result and consider in more detail the process of information gain in photon detection. Considering photons of energy E p h and a photo-ionization detector operated at a temperature T D , we evaluate the signal-to-noise ratio S N ( E p h , T D ) for different detector designs and detector operation conditions an

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Cohen, Shahar, Lior Rokach, and Oded Maimon. "Decision-tree instance-space decomposition with grouped gain-ratio." Information Sciences 177, no. 17 (2007): 3592–612. http://dx.doi.org/10.1016/j.ins.2007.01.016.

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Munthe, Ibnu Rasyid, and Volvo Sihombing. "Klasifikasi Algoritma Iterative Dichotomizer (ID3) untuk Tingkat kepuasan pada Sarana Laboratorium Komputer." Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP) 1, no. 2 (2018): 27–34. http://dx.doi.org/10.34012/jutikomp.v1i2.237.

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Hasil Penelitian ini dilakukan membangun model menggunakan Algoritma Iterative Dichotomizer(Id3). Dengan mengukur Gain Ratio, Information Gain, Gini Index dan Akurasi maka hasil diperoleh Gain tertinggi dari Gain Ratio, Information Gain dan Gini Index adalah variabel Minat berkunjung kembali dan Entropy variabel Laboratorium Komputer artinya mahasiswa mau berkunjung kembali dan mengunakan Laboratorium komputer merasakan puas pada variabel tersebut. Accuracy gain tertinggi adalah variabel minat berkunjung kembali, entropy variabel Fasilitas penunjang, dan Laboratorium Komputer artinya mahasiswa

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Ivandari, Ivandari, M. Adib Al Karomi, and Much Rifqi Maulana. "Improved C45 performance with gain ratio for credit approval dataset." JAICT 7, no. 2 (2022): 135. http://dx.doi.org/10.32497/jaict.v7i2.3978.

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<p class="AbstractL-MAG"><span>Abstract—</span> People's shopping behavior has undergone many changes after the COVID-19 pandemic. Many people have switched to using the marketplace to make buying and selling transactions. The payment process in the marketplace is relatively easy, especially when using a credit card. The increase in demand for credit must be addressed better by financial providers to minimize bad loans. The best thing in minimizing bad credit is to be more selective in choosing credit customers. Data mining is a field that can study old data to become new kno

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Daley, Daryl J., and David Vere-Jones. "Scoring probability forecasts for point processes: the entropy score and information gain." Journal of Applied Probability 41, A (2004): 297–312. http://dx.doi.org/10.1017/s0021900200112367.

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Theentropy scoreof an observed outcome that has been given a probability forecastpis defined to be –logp.Ifpis derived from a probability model and there is a background model for which the same outcome has probabilityπ, then the log ratio log(p/π) is theprobability gain, and its expected value theinformation gain, for that outcome. Such concepts are closely related to the likelihood of the model and its entropy rate. The relationships between these concepts are explored in the case that the outcomes in question are the occurrence or nonoccurrence of events in a stochastic point process. It is

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Al-Amidie, Muthana, Ahmed Al-Asadi, Amjad J. Humaidi, et al. "Robust Spectrum Sensing Detector Based on MIMO Cognitive Radios with Non-Perfect Channel Gain." Electronics 10, no. 5 (2021): 529. http://dx.doi.org/10.3390/electronics10050529.

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The spectrum has increasingly become occupied by various wireless technologies. For this reason, the spectrum has become a scarce resource. In prior work, the authors have addressed the spectrum sensing problem by using multi-input and multi-output (MIMO) in cognitive radio systems. We considered the detection and estimation framework for MIMO cognitive network where the noise covariance matrix is unknown with perfect channel state information. In this study, we propose a generalized likelihood ratio test (GLRT) for the spectrum sensing problem in cognitive radio where the noise covariance mat

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Daley, Daryl J., and David Vere-Jones. "Scoring probability forecasts for point processes: the entropy score and information gain." Journal of Applied Probability 41, A (2004): 297–312. http://dx.doi.org/10.1239/jap/1082552206.

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The entropy score of an observed outcome that has been given a probability forecast p is defined to be –log p. If p is derived from a probability model and there is a background model for which the same outcome has probability π, then the log ratio log(p/π) is the probability gain, and its expected value the information gain, for that outcome. Such concepts are closely related to the likelihood of the model and its entropy rate. The relationships between these concepts are explored in the case that the outcomes in question are the occurrence or nonoccurrence of events in a stochastic point pro

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Heymann, Fabian, Mário Lopes, Frederik Scheidt, et al. "DER adopter analysis using spatial autocorrelation and information gain ratio under different census‐data aggregation levels." IET Renewable Power Generation 14, no. 1 (2019): 63–70. http://dx.doi.org/10.1049/iet-rpg.2019.0322.

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Antoh, Soterio, Rudy Herteno, Irwan Budiman, Dwi Kartini, and Muhammad Itqan Mazdadi. "Prediksi Churn Pelanggan Telekomunikasi dengan Optimalisasi Seleksi Fitur dan Tuning Hyperparameter pada Algoritma Klasifikasi C4.5." Jurnal Sistem Informasi Bisnis 15, no. 1 (2025): 60–67. https://doi.org/10.14710/vol15iss1pp60-67.

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In the telecommunications industry, predicting customer churn is crucial for maintaining business sustainability. High churn rates can negatively impact profitability, necessitating effective retention strategies. This research aims to enhance the accuracy of telecommunications customer churn prediction by optimizing the C4.5 classification algorithm through feature selection and hyperparameter tuning. The methods used include Information Gain for feature selection and hyperparameter tuning with Random Search and Grid Search. This study utilizes the Telco Customer Churn dataset from Kaggle, sp

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Heinrich, Frank, Paul A. Kienzle, David P. Hoogerheide, and Mathias Lösche. "Information gain from isotopic contrast variation in neutron reflectometry on protein–membrane complex structures." Journal of Applied Crystallography 53, no. 3 (2020): 800–810. http://dx.doi.org/10.1107/s1600576720005634.

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A framework is applied to quantify information gain from neutron or X-ray reflectometry experiments [Treece, Kienzle, Hoogerheide, Majkrzak, Lösche & Heinrich (2019). J. Appl. Cryst. 52, 47–59], in an in-depth investigation into the design of scattering contrast in biological and soft-matter surface architectures. To focus the experimental design on regions of interest, the marginalization of the information gain with respect to a subset of model parameters describing the structure is implemented. Surface architectures of increasing complexity from a simple model system to a protein–lipid

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Masripah, Siti, and Lestari Yusuf. "PERBANDINGAN KRITERIA DECISION TREE PADA PENGETAHUAN MASYARAKAT PADA PEMILIHAN UMUM PRESIDEN INDONESIA." INTI Nusa Mandiri 18, no. 2 (2024): 183–91. http://dx.doi.org/10.33480/inti.v18i2.5065.

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In the Presidential election, gen z as a new voter, must know in advance who the presidential candidate will be in the 2024 election as well as the election process, because if voters do not know and do not understand, it will cause the wrong choice will result in their votes cannot be used even to abstain. What factors cause milennials and gen z generations to not know about elections can be determined using a decision tree. Therefore, in this study, a questionnaire was given to millennials and gen z generation to find out whether voters know the presidential candidate to be elected. The data

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Ning, Naiqiao, and Yong Tang. "Evaluation of an Information Flow Gain Algorithm for Microsensor Information Flow in Limber Motor Rehabilitation." Complexity 2021 (March 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/6638038.

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This paper conducts an evaluative study on the rehabilitation of limb motor function by using a microsensor information flow gain algorithm and investigates the surface electromyography (EMG) signals of the upper limb during rehabilitation training. The surface EMG signals contain a large amount of limb movement information. By analysing and processing the surface EMG signals, we can grasp the human muscle movement state and identify the human upper limb movement intention. The EMG signals were processed by the trap and filter combination denoising method and wavelet denoising method, respecti

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Dai, Jianhua, and Qing Xu. "Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification." Applied Soft Computing 13, no. 1 (2013): 211–21. http://dx.doi.org/10.1016/j.asoc.2012.07.029.

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Irfak, Muhammad, Istiadi, and Aviv Yuniar Rahman. "Support Vector Machine Application for Classification of Tempe Fermentation Maturity with Information Gain Selection Feature." Edutran Computer Science and Information Technology 1, no. 2 (2023): 1–9. http://dx.doi.org/10.59805/ecsit.v1i2.40.

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Tempe is one of the ingredients of traditional Indonesian cuisine. In making tempe, a soybean fermentation process is needed which is generally still carried out in an open environment so that the maturity time becomes slow and erratic. Therefore, in the tempe fermentation process, a detector is needed to find out optimal maturity in tempe. This detection effort makes it possible to use image processing by utilizing various feature extractions through the classification process. This research utilizes a variety of image features, namely texture features using the GLCM method and various color

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da Mota Santana, Jerusa, Marcos Pereira, Gisele Carvalho, Djanilson dos Santos, and Ana Oliveira. "Long-Chain Polyunsaturated Fatty Acid Concentrations and Association with Weight Gain in Pregnancy." Nutrients 14, no. 1 (2021): 128. http://dx.doi.org/10.3390/nu14010128.

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Lower concentrations of omega-3 (ω-3) and higher concentrations of omega-6 (ω-6) have been associated with excess weight in adults; however, the information on this relationship in pregnancy remains in its infancy. This study aimed to investigate the association between plasma levels of ω-3 and ω-6 long-chain polyunsaturated fatty acids (PUFAs) and weight gain during the gestational period. This is a prospective cohort study involving 185 pregnant women registered with the prenatal services of a municipality in the northeast of Brazil. The dosage of the serum concentration of fatty acids and t

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Arimori, Haruka, Norio Abiru, Shimpei Morimoto, et al. "Association between Lifestyle Factors and Weight Gain among University Students in Japan during COVID-19 Mild Lockdown: A Quantitative Study." Healthcare 11, no. 19 (2023): 2630. http://dx.doi.org/10.3390/healthcare11192630.

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We aimed to investigate the lifestyle factors influencing weight gain among university students in Japan during the mild lockdown imposed due to the novel coronavirus disease pandemic. In this cross-sectional study, we conducted a questionnaire survey of students who underwent health examinations at Nagasaki University in 2021. Students reporting a weight gain of ≥3 kg were included in the weight gain group; the remaining students were included in the non-weight-gain group. Fisher’s exact test and binary logistic regression were performed to determine the association between weight gain and ea

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Duke, Kyle, Daniela Cuenca, Steven Myers, and Jeanette Wallin. "Compound and Conditioned Likelihood Ratio Behavior within a Probabilistic Genotyping Context." Genes 13, no. 11 (2022): 2031. http://dx.doi.org/10.3390/genes13112031.

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In cases where multiple questioned individuals are separately supported as contributors to a mixed DNA profile, guidance documents recommend performing a comparison to see if there is support for their joint contribution. Anecdotal observations suggest the summed log of the individual likelihood ratios (LR), termed the simple LR product, should be roughly equivalent to or less than the log(LR) for the joint likelihood ratio, termed the compound LR. To assist casework analysts in evaluating statistical weights applied to a case at hand, this study assessed how consistently compound LRs conform

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Gottschalk, Allan. "Derivation of the Visual Contrast Response Function by Maximizing Information Rate." Neural Computation 14, no. 3 (2002): 527–42. http://dx.doi.org/10.1162/089976602317250889.

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A graph of neural output as a function of the logarithm of stimulus intensity often produces an S-shaped function, which is frequently modeled by the hyperbolic ratio equation. The response of neurons in early vision to stimuli of varying contrast is an important example of this. Here, the hyperbolic ratio equation with a response exponent of two is derived exactly by considering the balance between information rate and the neural costs of making that information available, where neural costs are a function of synaptic strength and spike rate. The maximal response and semisaturation constant o

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Rajesh, R., P. G. S. Velmurugan, S. J. Thiruvengadam, and P. S. Mallick. "Outage Performance of Bidirectional Full-Duplex Amplify-and-Forward Relay Network with Transmit Antenna Selection and Maximal Ratio Combining." Journal of Telecommunications and Information Technology 1 (March 28, 2018): 62–69. http://dx.doi.org/10.26636/jtit.2018.116417.

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In this paper, a bidirectional full-duplex amplify- and-forward (AF) relay network with multiple antennas at source nodes is proposed. Assuming that the channel state information is known at the source nodes, transmit antenna selection and maximal ratio combining (MRC) are employed when source nodes transmit information to the relay node and receive information from the relay node respectively, in order to improve the overall signal-to-interference plus noise ratio (SINR). Analytical expressions are derived for tight upper bound SINR at the relay node and source nodes upon reception. Further,

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Odesanya, Ituabhor. "Evaluation of Selection Combining, Equal Gain Combining and Maximum Ratio Techniques in Orthogonal Frequency Division Multiplexing System." International Journal of Advanced Networking and Applications 15, no. 04 (2023): 5996–6002. http://dx.doi.org/10.35444/ijana.2024.15401.

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Mobile communication systems employing orthogonal frequency division multiplexing technique are mainly the fourth and fifth generation. This technique serves as a multi-access scheme which supports information splitting in sub-channel frequencies during data transmission. This technique is sensitive to multipath fading and signal strength can be lost due to shadowing in different radio frequency propagation terrains during practical applications. One of the waysin mitigating this multipath fading problem is by utilizing antenna diversity combining techniques. In this paper, Simulink software i

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Pen, Mao Ling, and Ai Ming Huang. "A Multiattribute Measurement Algorithm for Packet Classification." Applied Mechanics and Materials 52-54 (March 2011): 168–73. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.168.

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Many network application technology need the algorithm for multi-dimensional packet classification, for example ,network security ,load balancing ,router policy, QoS etc. Considering the levels of multiattribute packet classified are excessive and traverse rule table times without number for matching classification rule, so efficiency is lower. A packet classification algorithm based on decision tree is put forward in the paper. As compared with some traditional packet classification matching algorithms, because three data are adopted including information gain, information gain ratio and Gini

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Feng, Junhong, Xishuan Niu, Jie Zhang, and Jian-Hong Wang. "Gene Selection and Classification of scRNA-seq Data Combining Information Gain Ratio and Genetic Algorithm with Dynamic Crossover." Wireless Communications and Mobile Computing 2022 (January 31, 2022): 1–16. http://dx.doi.org/10.1155/2022/9639304.

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Single-cell RNA sequencing (scRNA-seq) is emerging as a promising technology. There exist a huge number of genes in a scRNA-seq data. However, some genes are high quality genes, and some are noises and irrelevant genes because of unspecific technology reasons. These noises and irrelevant genes may have a strong influence on downstream data analyses, such as a cell classification, gene function analysis, and cancer biomarker detection. Therefore, it is very significant to obviate these irrelevant genes and choose high quality genes by gene selection methods. In this study, a novel gene selectio

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Kuz'kin, Venedikt M., Sergey A. Pereselkov, Yuri V. Matvienko, Vladimir I. Grachev, Sergey A. Tkachenko, and Nadezhda P. Stadnaya. "Holographic processing of hydroacoustic information using linear antennas." Radioelectronics. Nanosystems. Information Technologies. 15, no. 2 (2023): 169–78. http://dx.doi.org/10.17725/rensit.2023.15.169.

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The formation of an interferogram and a hologram of a moving underwater noise source using linear antennas is considered. The relationship between the spectral density of the hologram and the aperture and the angular dependence of the received field is derived. Antenna gain has been estimated. The issue of the limiting signal-to-noise ratio at which the holographic processing remains operational is discussed. An analytical expression is obtained that establishes a relationship between the signal/noise ratios at the output and input of the antenna. Conditions are formulated under which the inte

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Iswanto, Iswanto, Tulus Tulus, and Poltak Poltak. "COMPARISON OF FEATURE SELECTION TO PERFORMANCE IMPROVEMENT OF K-NEAREST NEIGHBOR ALGORITHM IN DATA CLASSIFICATION." Jurnal Teknik Informatika (Jutif) 3, no. 6 (2022): 1709–16. http://dx.doi.org/10.20884/1.jutif.2022.3.6.471.

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One of the most widely used data classification methods is the K-Nearest Neighbor (K-NN) algorithm. Classification of data in this method is carried out based on the calculation of the closest distance to the training data as much as the value of K from its neighbors. Then the new data class is determined using the most votes system from the number of K nearest neighbors. However, the performance of this method is still lower than other data classification methods. The cause is the use of the most voting system in determining new data classes and the influence of features less relevant to the

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Jeng, Shyr-Long, Rohit Roy, and Wei-Hua Chieng. "A Matrix Approach for Analyzing Signal Flow Graph." Information 11, no. 12 (2020): 562. http://dx.doi.org/10.3390/info11120562.

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Mason’s gain formula can grow factorially because of growth in the enumeration of paths in a directed graph. Each of the (n − 2)! permutation of the intermediate vertices includes a path between input and output nodes. This paper presents a novel method for analyzing the loop gain of a signal flow graph based on the transform matrix approach. This approach only requires matrix determinant operations to determine the transfer function with complexity O(n3) in the worst case, therefore rendering it more efficient than Mason’s gain formula. We derive the transfer function of the signal flow graph

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Gu, Jun Hua, Jie Song, Na Zhang, and Yan Liu Liu. "A Method of Web Information Automatic Extraction Based on XML." Applied Mechanics and Materials 20-23 (January 2010): 178–83. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.178.

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With the increasingly high-speed of the internet as well as the increase in the amount of data it contains, users are finding it more and more difficult to gain useful information from the web. How to extract accurate information from the Web efficiently has become an urgent problem. Web information extraction technology has emerged to solve this kind of problem. The method of Web information auto-extraction based on XML is designed through standardizing the HTML document using data translation algorism, forming an extracting rule base by learning the XPath expression of samples, and using ext

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Jamjoom, Mona. "The pertinent single-attribute-based classifier for small datasets classification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3227. http://dx.doi.org/10.11591/ijece.v10i3.pp3227-3234.

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Classifying a dataset using machine learning algorithms can be a big challenge when the target is a small dataset. The OneR classifier can be used for such cases due to its simplicity and efficiency. In this paper, we revealed the power of a single attribute by introducing the pertinent single-attribute-based-heterogeneity-ratio classifier (SAB-HR) that used a pertinent attribute to classify small datasets. The SAB-HR’s used feature selection method, which used the Heterogeneity-Ratio (H-Ratio) measure to identify the most homogeneous attribute among the other attributes in the set. Our empiri

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Mona, Jamjoom. "The pertinent single-attribute-based classifier for small datasets classification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3227–34. https://doi.org/10.11591/ijece.v10i3.pp3227-3234.

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Classifying a dataset using machine learning algorithms can be a big challenge when the target is a small dataset. The OneR classifier can be used for such cases due to its simplicity and efficiency. In this paper, we revealed the power of a single attribute by introducing the pertinent single-attributebased-heterogeneity-ratio classifier (SAB-HR) that used a pertinent attribute to classify small datasets. The SAB-HR’s used feature selection method, which used the Heterogeneity-Ratio (H-Ratio) measure to identify the most homogeneous attribute among the other attributes in the set. Our e

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Aslam, Irfan, Muhammad Noorul Amin, Amjad Mahmood, and Prayas Sharma. "New memory-based ratio estimator in survey sampling." Natural and Applied Sciences International Journal (NASIJ) 5, no. 1 (2024): 168–81. http://dx.doi.org/10.47264/idea.nasij/5.1.11.

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This study proposes a new estimator based on the Exponential Weighted Moving Average (EWMA) statistic by following the concept of Noor-ul-Amin (2021). The EWMA model consumed contemporary and empirical data to enhance the competence of the population mean estimation. The memory type estimate is proposed with a twofold utilisation of Auxiliary Information (AUI) in alignment with the sampling type, i.e., Simple Random Sampling (SRS). A detailed numerical study and analysis are conducted to estimate the projected efficiency. This study provides an efficient estimator for population mean in the oc

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Gunadi, I. Gede Aris, and Dewi Oktofa Rachmawati. "A Comparative Study on the Impact of Feature Selection and Dataset Resampling on the Performance of the K-Nearest Neighbors (KNN) Classification Algorithm." Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) 13, no. 2 (2024): 419–27. http://dx.doi.org/10.23887/janapati.v13i2.82174.

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This study aims to evaluate the impact of dataset balancing and feature selection on the performance of the K-Nearest Neighbors (KNN) classification algorithm. The primary objective is to determine the effect of different training data balance ratios on classification performance. Additionally, the study analyzes the contribution of feature selection methods and data balancing to the overall performance of the classification algorithm. Three datasets (Titanic, Wine Quality, and Heart Diseases) sourced from Kaggle, were utilized in this research. Following the preprocessing stage, the datasets

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Maillard, J. P. "Signal-to-Noise Ratio and Astronomical Fourier Transform Spectroscopy." Symposium - International Astronomical Union 132 (1988): 71–78. http://dx.doi.org/10.1017/s0074180900034793.

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The multiplex properties of the Fourier Transform Spectrometer (FTS) can be considered as disadvantageous with modern detectors and large telescopes, the dominant noise source being no longer in most applications the detector noise. Nevertheless, a FTS offers a gain in information and other instrumental features remain: flexibility in choosing resolving power up to very high values, large throughput, essential in high–resolution spectroscopy with large telescopes, metrologic accuracy, automatic substraction of parasitic background. The signal–to–noise ratio in spectra can also be improved: by

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Rustam, Z., Andrea Laksmirani Kristina, and Y. Satria. "Comparison between Fisher’s Ratio and Information Gain with SVM classifier for 3 levels of enthusiasm classification through face recognition." Journal of Physics: Conference Series 1752, no. 1 (2021): 012042. http://dx.doi.org/10.1088/1742-6596/1752/1/012042.

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Zhang, Jie, Junhong Feng, Xiani Yang, and Jianming Liu. "Gene selection and classification combining information gain ratio with fruit fly optimisation algorithm for single-cell RNA-seq data." International Journal of Computational Science and Engineering 24, no. 5 (2021): 495. http://dx.doi.org/10.1504/ijcse.2021.10041500.

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Zhang, Jie, Junhong Feng, Xiani Yang, and Jianming Liu. "Gene selection and classification combining information gain ratio with fruit fly optimisation algorithm for single-cell RNA-seq data." International Journal of Computational Science and Engineering 24, no. 5 (2021): 495. http://dx.doi.org/10.1504/ijcse.2021.118098.

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