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Journal articles on the topic 'J48 decision tree'

Author: Grafiati

Published: 4 June 2025

Last updated: 15 July 2025

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1

Lutfiyani, Rizka Safitri, and Niken Retnowati. "IMPLEMENTASI PENDETEKSIAN SPAM EMAIL MENGGUNAKAN METODE TEXT MINING DENGAN ALGORITMA NAÏVE BAYES DAN DECISION TREE J48." Jurnal Komputer dan Informatika 9, no. 2 (2021): 244–52. http://dx.doi.org/10.35508/jicon.v9i2.5304.

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Email cukup populer sebagai salah satu media komunikasi digital. Hal tersebut dikarenakan proses pengiriman pesan dengan email yang mudah. Sayangnya, kebanyakan pesan dalam email adalah email spam. Spam adalah pesan yang tidak diinginkan penerima pesan karena spam biasanya berisi pesan iklan maupun pesan penipuan. Ham adalah pesan yang diinginkan penerima pesan. Salah satu cara untuk menyortir pesan-pesan tersebut adalah dengan melakukan pengklasifikasian pesan email menjadi spam maupun ham. Naïve Bayes dan decision tree J48 ialah algoritma yang dapat digunakan untuk mengklasifikasikan pesan e

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Tundo, Tundo, Shoffan Saifullah, Mesra Betty Yel, Opi Irawansah, Zulfikar Yusya Mubarak, and Andi Saidah. "Prediction of palm oil production using hybrid decision tree based on fuzzy inference system Tsukamoto." Bulletin of Electrical Engineering and Informatics 13, no. 6 (2024): 4182–92. http://dx.doi.org/10.11591/eei.v13i6.7773.

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This research addresses the challenge of optimizing rule creation for palm oil production at PT Tapiana Nadenggan. It deals with the complexity of diverse agricultural variables, environmental factors, and the dynamic nature of palm oil production. The existing problem lies in the limitations of conventional decision tree models—J48, reduced error pruning (REP), and random—in capturing the nuanced relationships within the intricate palm oil production system. The study introduces hybrid decision tree models—specifically J48-REP, REP-Random, and Random-J48—to address this challenge via combinat

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Tundo, Tundo, and Shofwatul 'Uyun. "Perbandingan Decision Tree J48, REPTREE, dan Random Tree dalam Menentukan Prediksi Produksi Minyak Kelapa Sawit Menggunakan Fuzzy Tsukamoto." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 3 (2021): 473. http://dx.doi.org/10.25126/jtiik.2021833108.

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<h2 align="center"> </h2><p class="Default">Penelitian ini menerangkan analisis <em>decision tree</em> J48, REP<em>Tree</em> dan <em>Random Tree</em> dengan menggunakan metode <em>fuzzy </em>Tsukamoto dalam penentuan jumlah produksi minyak kelapa sawit di perusahaan PT Tapiana Nadenggan dengan tujuan untuk mengetahui <em>decision tree</em> mana yang hasilnya mendekati dari data sesungguhnya. Digunakannya <em>decision tree</em> J48, REP<em>Tree</em>, dan <em>Random Tree</em> yaitu u

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Tundo, Tundo, and Shofwatul 'Uyun. "Penerapan Decision Tree J48 dan Reptree dalam Menentukan Prediksi Produksi Minyak Kelapa Sawit menggunakan Metode Fuzzy Tsukamoto." Jurnal Teknologi Informasi dan Ilmu Komputer 7, no. 3 (2020): 483. http://dx.doi.org/10.25126/jtiik.2020731870.

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<p>Penelitian ini menerangkan penerapan <em>decision tree</em> J48 dan REPTree dengan menggunakan metode <em>fuzzy Tsukamoto</em> dengan objek yang digunakan adalah penentuan jumlah produksi minyak kelapa sawit di perusahaan PT Tapiana Nadenggan dengan tujuan untuk mengetahui <em>decision tree</em> mana yang hasilnya mendekati dari data sesungguhnya sehingga dapat digunakan untuk membantu memprediksi jumlah produksi minyak kelapa sawit di PT Tapiana Nadenggan ketika proses produksi belum diproses. Digunakannya <em>decision tree</em> J48 dan

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Ismanto, Heru, Azhari Azhari, Suharto Suharto, and Lincolin Arsyad. "Classification of the Mainstay Economic Region Using Decision Tree Method." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (2018): 1037. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1037-1044.

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The development of the region cannot be separated from the concept of economic growth and the determination of the mainstay region as a regional center that is expected to have a positive impact on economic growth to the surrounding regions. In fact, the determination of the mainstay region is a difficult thing to do. Some cases of the determination of the mainstay region are mostly on the basis of the prerogative rights of the policy makers without carefully seeing the achievements of the development of a region. The objective of this study is to develop a classification model of the mainstay

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Garg, Sharvan Kumar, Deepak Kumar Sinha, and Nidhi Bhatia. "Performance of Hoeffding Tree and C4.5 Algorithms to Envisage an Occurrence of Hepatitis–A Liver Disease." Journal of Computational and Theoretical Nanoscience 17, no. 6 (2020): 2423–29. http://dx.doi.org/10.1166/jctn.2020.8911.

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Premature forecasting of hepatitis is extremely imperative to save an individual years and take appropriate steps to control the ailment. Decision Tree algorithms have been effectively useful in a variety of fields particularly in medicinal discipline. This manuscript investigates the premature forecasting of hepatitis by means of a variety of decision tree algorithms. In this manuscript, we build up a Hepatitis prediction model that can aid medical experts in envisaging Hepatitis condition supported on the medicinal data of patients. At the outset, we have chosen 19 imperative medicinal attri

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Rahman, Aviv Yuniar. "Klasifikasi Citra Burung Lovebird Menggunakan Decision Tree dengan Empat Jenis Evaluasi." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 4 (2021): 688–96. http://dx.doi.org/10.29207/resti.v5i4.3210.

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Lovebird is a pet that many people in Indonesia have known. The diversity of species, coat color, and body shape gives it its charm. As well in this lovebird bird has its uniqueness of various rare colors. However, many ordinary people have difficulty distinguishing the types of lovebirds. This research is needed to improve previous study performance in classifying lovebird images using the Decision Tree J48 algorithm with 4 types of evaluation. In this case, also to reduce the stage of feature extraction to speed up the computational process. Based on available comparisons, the results obtain

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Tundo, Tundo, and Shofwatul 'Uyun. "Konsep Decision Tree Reptree untuk Melakukan Optimasi Rule dalam Fuzzy Inference System Tsukamoto." Jurnal Teknologi Informasi dan Ilmu Komputer 9, no. 3 (2022): 513. http://dx.doi.org/10.25126/jtiik.2022922601.

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<p class="Default">Penelitian ini menjelaskan tentang <em>decision tree</em> REPTree dalam membuat suatu <em>rule</em> yang terbentuk dari produksi minyak kelapa sawit di PT Tapiana Nadenggan, yang dipengaruhi oleh faktor banyaknya kelapa sawit, permintaan yang ada, serta persediaan yang tersedia. Konsep dari <em>decision tree</em> REPTree adalah konsep awal dari <em>decision tree</em> J48 yang kemudian mengalami pemangkasan kembali, sehingg <em>rule</em> yang yang terbentuk lebih minimal dan praktis. <em>Rule</em> y

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Maulana, Mohamad Firman, and Meriska Defriani. "Logistic Model Tree and Decision Tree J48 Algorithms for Predicting the Length of Study Period." PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic 8, no. 1 (2020): 39–48. http://dx.doi.org/10.33558/piksel.v8i1.2018.

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One point to be assessed in the accreditation process in an institution is the length of the student's study period. The Informatics department in XYZ college has been accredited by the national accreditation bureau for higher education (BAN-PT), but the accreditation has the potential to be improved. One thing that affects the accreditation value is many students did not graduate on time. Therefore, the current study used available student data, both academic and non-academic, using data mining. Two model classifications were used, i.e. Logistic Model Tree (LMT) and Decision Tree J48. The stu

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Asim Shahid, Muhammad, Muhammad Mansoor Alam, and Mazliham Mohd Su’ud. "A fact based analysis of decision trees for improving reliability in cloud computing." PLOS ONE 19, no. 12 (2024): e0311089. https://doi.org/10.1371/journal.pone.0311089.

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The popularity of cloud computing (CC) has increased significantly in recent years due to its cost-effectiveness and simplified resource allocation. Owing to the exponential rise of cloud computing in the past decade, many corporations and businesses have moved to the cloud to ensure accessibility, scalability, and transparency. The proposed research involves comparing the accuracy and fault prediction of five machine learning algorithms: AdaBoostM1, Bagging, Decision Tree (J48), Deep Learning (Dl4jMLP), and Naive Bayes Tree (NB Tree). The results from secondary data analysis indicate that the

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Kumar, Sunil, Saroj Ratnoo, and Jyoti Vashishtha. "HYPER HEURISTIC EVOLUTIONARY APPROACH FOR CONSTRUCTING DECISION TREE CLASSIFIERS." Journal of Information and Communication Technology 20, Number 2 (2021): 249–76. http://dx.doi.org/10.32890/jict2021.20.2.5.

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Decision tree models have earned a special status in predictive modeling since these are considered comprehensible for human analysis and insight. Classification and Regression Tree (CART) algorithm is one of the renowned decision tree induction algorithms to address the classification as well as regression problems. Finding optimal values for the hyper parameters of a decision tree construction algorithm is a challenging issue. While making an effective decision tree classifier with high accuracy and comprehensibility, we need to address the question of setting optimal values for its hyper pa

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Aung, Nway Oo, and Naing Thin. "Decision Tree Models for Medical Diagnosis." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 1697–99. https://doi.org/10.31142/ijtsrd23510.

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Data mining techniques are rapidly developed for many applications. In recent year, Data mining in healthcare is an emerging field research and development of intelligent medical diagnosis system. Classification is the major research topic in data mining. Decision trees are popular methods for classification. In this paper many decision tree classifiers are used for diagnosis of medical datasets. AD Tree, J48, NB Tree, Random Tree and Random Forest algorithms are used for analysis of medical dataset. Heart disease dataset, Diabetes dataset and Hepatitis disorder dataset are used to test the de

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Ikhsan, Ali Nur, Alif Nur Fadilah, and Alifah Dafa Iftinani. "Performance Comparison of Decision Tree J48, CART, and Naïve Bayes Algorithms for Predicting Chronic Kidney Disease." Indonesian Journal of Artificial Intelligence and Data Mining 7, no. 1 (2023): 64. http://dx.doi.org/10.24014/ijaidm.v7i1.26472.

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Chronic Kidney Disease could be a worldwide issue that proceeds to extend with high treatment costs. Accurate diagnosis is essential for managing this disease. There is a requirement for a technique to anticipate chronic kidney disease, with prevalent use being made of Decision Tree J48, Naive Bayes, and CART algorithms which offer benefits like swift computation, ease of use, and high precision. The researchers aimed to determine the comparison results of Decision Tree J48, CART, and Naive Bayes algorithms for predicting chronic kidney disease. From the research findings, it was concluded tha

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Pandian, A., K. Manikandan, V. Ramalingam, Payal Bhowmick, and Sree Vaishnavi. "Author Identification of Bengali Poems." International Journal of Engineering & Technology 7, no. 4.19 (2018): 17–21. http://dx.doi.org/10.14419/ijet.v7i4.19.21988.

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Author identification of Bengali poems is a project mainly focusing on identification of an author of a poem. We train the system using a dataset consisting of features extracted from poems by various authors. Features like count of characters, words, spaces, vowels and consonants of Bengali poems are considered. The training algorithm used is J48 decision tree. It has additional features of J48 like it accounts for missing values, prunes decision trees, and derives rules from the data, etc. All of this is helpful when we want to classify with larger datasets.Â

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Pandian, A., V. Ramalingam, K. Manikandan, Payal Bhowmick, and Shree Vaishnavi. "Comparison of Algorithms in Authorship Identification using Bengali Poems." International Journal of Engineering & Technology 7, no. 4.19 (2018): 22–25. http://dx.doi.org/10.14419/ijet.v7i4.19.21989.

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Author identification of Bengali poems is a paper mainly focusing on identification of an author of a poem. We train the system using a dataset consisting of features extracted from poems by various authors. Features like count of characters, words, spaces, vowels and consonants of Bengali poems are considered. Many training algorithms can be used to identify the authors. Some of the algorithms are J48, SVM, PCA, RDM, Random Forest Tree, Logic Regression, Naive Bayes etc. Every algorithm has its own advantages and disadvantages. The training algorithm used the most is J48 decision tree. It has

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J, Shankar Murthy. "Network Software Vulnerability Identifier using J48 decision tree algorithm." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (2021): 1889–92. http://dx.doi.org/10.22214/ijraset.2021.37685.

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Abstract: Software vulnerabilities are the primary causes of different security issues in the modern era. When vulnerability is exploited by malicious assaults, it substantially jeopardizes the system's security and may potentially result in catastrophic losses. As a result, automatic classification methods are useful for successfully managing software vulnerabilities, improving system security performance, and lowering the chance of the system being attacked and destroyed. In the software industry and in the field of cyber security, the ever-increasing number of publicly reported security fla

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Nadaf, Aftab, and Prof Sandip B. Shrote. "MACHINE LEARNING BASED DIABETES PREDICTION USING DECISION TREE J48." Industrial Engineering Journal 52, no. 12 (2023): 06–11. http://dx.doi.org/10.36893/iej.2023.v52i12.006-011.

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Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International Diabetes Federation 382 million people are living with diabetes across the entire world. By 2035, this will be doubled as 592 million. Diabetes is a disease caused due to the increase level of blood glucose. This high blood glucose produces the symptoms of frequent urination, increased thirst, and increased hunger. Diabetes is a one of the leading causes of blindness, kidney failure, amputations, heart failure and stroke. When we eat, our body turns food into sugars, or glucose.

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Dr.G.Manikanta, Dr G. Manikanta. "Decision Tree Analysis on J48 Algorithm for Data Mining." Journal of Science and Technology 7, no. 5 (2023): 200–205. http://dx.doi.org/10.46243/jst.2022.v7.i05.pp200-205.

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Li, Tun, and Gong Shen Liu. "Stock Price’s Prediction with Decision Tree." Applied Mechanics and Materials 48-49 (February 2011): 1116–21. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1116.

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Establishment of one process and some ameliorations of decision tree’s algorithm in order to predict the second day’s price change. The experiment builds a J48 tree, which is comfortable with continuous attributes, based on 10 years historical stock prices. After careful selection and preprocessing of financial data, high prediction accuracy is obtained. An introduction of dynamic-constructed tree reduces tree’s cost, and increases prediction’s quality on accuracy as well as average error distance.

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Rodríguez Mazahua, Nidia, Lisbeth Rodríguez Mazahua, Asdrúbal López Chau, and Giner Alor Hernández. "Comparative Analysis of Decision Tree Algorithms for Data Warehouse Fragmentation*." Revista Perspectiva Empresarial 7, no. 2-1 (2020): 31–43. http://dx.doi.org/10.16967/23898186.667.

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One of the main problems faced by Data Warehouse designers is fragmentation.Several studies have proposed data mining-based horizontal fragmentation methods.However, not exists a horizontal fragmentation technique that uses a decision tree. This paper presents the analysis of different decision tree algorithms to select the best one to implement the fragmentation method. Such analysis was performed under version 3.9.4 of Weka, considering four evaluation metrics (Precision, ROC Area, Recall and F-measure) for different selected data sets using the Star Schema Benchmark. The results showed that

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Gomathi, S., and V. Narayani. "Early prediction of systemic lupus erythematosus using hybrid K-Means J48 decision tree algorithm." International Journal of Engineering & Technology 7, no. 1.3 (2017): 28. http://dx.doi.org/10.14419/ijet.v7i1.3.8982.

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The objective of the paper is to propose an enhanced algorithm for the prediction of chronic, autoimmune disease called Systemic Lupus Erythematosus (SLE). The Hybrid K-means J48 Decision Tree algorithm (HKMJDT) has been proposed for the effective and early prediction of the SLE. The reason for combining both the clustering and classification algorithms is to obtain the best accuracy and to predict the disease in the early stage. The performance of algorithms such as Naïve Bayes, decision tree, random forest, J48 and Hoeffding tree has been combined with K-means clustering algorithm and compar

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B. Palad, Eddie Bouy, Mary Jane F. Burden, Christian Ray Dela Torre, and Rachelle Bea C. Uy. "Performance evaluation of decision tree classification algorithms using fraud datasets." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2518–25. http://dx.doi.org/10.11591/eei.v9i6.2630.

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Text mining is one way of extracting knowledge and finding out hidden relationships among data using artificial intelligence methods. Surely, taking advantage of different techniques has been highlighted in previous researches however, the lack of literature focusing on cybercrimes implies the lack of utilization of data mining in facilitating cybercrime investigations in the Philippines. This study therefore classifies computer fraud or online scam data coming from Police incident reports as well as narratives of scam victims as a continuation of a prior study. The dataset consists mainly of

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Eddie, Bouy B. Palad, Jane F. Burden Mary, Ray dela Torre Christian, and Bea C. Uy Rachelle. "Performance evaluation of decision tree classification algorithms using fraud datasets." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2518–25. https://doi.org/10.11591/eei.v9i6.2630.

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Text mining is one way of extracting knowledge and finding out hidden relationships among data using artificial intelligence methods. Surely, taking advantage of different techniques has been highlighted in previous researches however, the lack of literature focusing on cybercrimes implies the lack of utilization of data mining in facilitating cybercrime investigations in the Philippines. This study therefore classifies computer fraud or online scam data coming from Police incident reports as well as narratives of scam victims as a continuation of a prior study. The dataset consists mainly of

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Giasson, Elvio, Eliana Casco Sarmento, Eliseu Weber, Carlos Alberto Flores, and Heinrich Hasenack. "Decision trees for digital soil mapping on subtropical basaltic steeplands." Scientia Agricola 68, no. 2 (2011): 167–74. http://dx.doi.org/10.1590/s0103-90162011000200006.

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When soil surveys are not available for land use planning activities, digital soil mapping techniques can be of assistance. Soil surveyors can process spatial information faster, to assist in the execution of traditional soil survey or predict the occurrence of soil classes across landscapes. Decision tree techniques were evaluated as tools for predicting the ocurrence of soil classes in basaltic steeplands in South Brazil. Several combinations of types of decicion tree algorithms and number of elements on terminal nodes of trees were compared using soil maps with both original and simplified

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Mitschek, Marivic, and Rosanna Esquivel. "A Comparative Analysis of Decision Tree Classification Algorithms for Blended Learning Analytics in WEKA." Celt: A Journal of Culture, English Language Teaching & Literature 23, no. 2 (2023): 321–34. http://dx.doi.org/10.24167/celt.v22i2.4960.

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This study explores the application of decision tree classification algorithms for analyzing student performance data within a blended learning environment. The analysis, conducted using WEKA 3.8.6, focused on four attributes believed to influence student performance: course type, course level outcome (CLO), topic learning outcome (TLO), and level of assessment. A comparative analysis of J48, Random Forest, and SimpleCart algorithms revealed valuable insights. J48 demonstrated efficiency in model building, while Random Forest offered a balance between interpretability and accuracy. SimpleCart

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Mustakim, Nurul Ain, Maslina Abdul Aziz, and Shuzlina Abdul Rahman. "Predicting Consumer Behavior in E-Commerce Using Decision Tree: A Case Study in Malaysia." Information Management and Business Review 16, no. 3(I) (2024): 201–9. http://dx.doi.org/10.22610/imbr.v16i3(i).3965.

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Understanding and predicting consumer behavior will help e-commerce businesses improve customer satisfaction and devise better marketing strategies. This study is intended to explore the use of decision tree algorithms in predictions of consumer purchase behavior in the e-commerce platform in Malaysia. Comparing the performances of J48, Random Tree, and REPTree decision tree models using an online shopper dataset collected by surveying 560 Malaysians, on various aspects like accuracy, precision, recall, and F1 score. Results indicate that the highest accuracy has been achieved with the Random

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杜, 飞. "CDN Domain Name Detection Method Based on J48 Decision Tree." Computer Science and Application 11, no. 07 (2021): 1982–93. http://dx.doi.org/10.12677/csa.2021.117203.

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Mihǎescu, Marian Cristian, Paul Ştefan Popescu, and Dumitru Dan Burdescu. "J48 list ranker based on advanced classifier decision tree induction." International Journal of Computational Intelligence Studies 4, no. 3/4 (2015): 313. http://dx.doi.org/10.1504/ijcistudies.2015.072879.

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Jehad, Reham, and Suhad A.Yousif. "Fake News Classification Using Random Forest and Decision Tree (J48)." Al-Nahrain Journal of Science 23, no. 4 (2020): 49–55. http://dx.doi.org/10.22401/anjs.23.4.09.

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FakeNews is one of the most popular phenomena that have considerable effects on our social life, especially in the political domain. Nowadays, creating fake news becomes very easy because of users' widespread using the internet and social media. Therefore, the detection of elusiveness news is a crucial problem that needs to be considerable mainly because of its challenges like the limited amount of the benchmark datasets and the amount of the published news every second. This research proposed utilizing two different machine learning algorithms (random forest and decision tree (J48)) to detect

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Lima, Nilsa Duarte da Silva, Irenilza de Alencar Nääs, João Gilberto Mendes dos Reis, and Raquel Baracat Tosi Rodrigues da Silva. "Classifying the Level of Energy-Environmental Efficiency Rating of Brazilian Ethanol." Energies 13, no. 8 (2020): 2067. http://dx.doi.org/10.3390/en13082067.

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The present study aimed to assess and classify energy-environmental efficiency levels to reduce greenhouse gas emissions in the production, commercialization, and use of biofuels certified by the Brazilian National Biofuel Policy (RenovaBio). The parameters of the level of energy-environmental efficiency were standardized and categorized according to the Energy-Environmental Efficiency Rating (E-EER). The rating scale varied between lower efficiency (D) and high efficiency + (highest efficiency A+). The classification method with the J48 decision tree and naive Bayes algorithms was used to pre

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Taha Chicho, Bahzad, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, and Dilovan Assad Zebari. "Machine Learning Classifiers Based Classification For IRIS Recognition." Qubahan Academic Journal 1, no. 2 (2021): 106–18. http://dx.doi.org/10.48161/qaj.v1n2a48.

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Classification is the most widely applied machine learning problem today, with implementations in face recognition, flower classification, clustering, and other fields. The goal of this paper is to organize and identify a set of data objects. The study employs K-nearest neighbors, decision tree (j48), and random forest algorithms, and then compares their performance using the IRIS dataset. The results of the comparison analysis showed that the K-nearest neighbors outperformed the other classifiers. Also, the random forest classifier worked better than the decision tree (j48). Finally, the best

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Guedes, Eduardo dos Santos, Eudo Tabosa de Oliveira, Obedio de Sousa Albuquerque, Ailton Lopes de Sousa, and Gilberto de Melo Júnior. "Comparação de algoritmos de aprendizado de máquina baseados em árvores de decisão na previsão de nível de escrita do ensino básico: estudo de caso em escolas do município de Vitória do Xingu - Pará." Cuadernos de Educación y Desarrollo 16, no. 11 (2024): e6269. http://dx.doi.org/10.55905/cuadv16n11-036.

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A análise de dados educacionais utilizando ferramentas computacionais é de grande valia para os gestores tomadores de decisão de instituições de ensino. O objetivo deste trabalho é a coleta e o pré-processamento de dados educacionais do ensino básico fundamental no município de Vitória do Xingu, estado do Pará, Brasil, com a finalidade de aplicá-los em algoritmos de aprendizado de máquina baseado em Árvores de Decisão, visando à comparação e análise de desempenho entre diferentes modelos. Foram aplicados em cinco algoritmos Decision Stump, Hoeffding Tree, J48, Random Forest e Random Tree. A av

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G, Aruna Kranthi. "Data mining systems classification based on the mining methods." International Journal of Research and Applications 6, no. 24 (2019): 1406–9. https://doi.org/10.5281/zenodo.13347089.

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<strong>ABSTRACT</strong>The paper pertains to this data mining approaches and also the limitation with the data mining. Numerous classification methodscovered in the paper are based in our own tree. Our choice tree based classification J48, CART and also ID3 are discussed about the paper. The paper is helpful to speak contrasts the decision shrub predicated classification methods additionally to choose exactly the advantageous classification process based on demand.<strong>Keywords:</strong> Data mining, J48, classification algorithm. 

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Ramadhani, Rahmi, and Yeka Hendriyani. "Prediksi Prestasi Siswa Berbasis Data Mining Menggunakan Algoritma Decision Tree (Studi Kasus: SMKN 2 Padang)." Voteteknika (Vocational Teknik Elektronika dan Informatika) 9, no. 3 (2021): 11. http://dx.doi.org/10.24036/voteteknika.v9i3.112633.

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Pengujian ini bertujuan untuk memperkirakan prestasi siswa tergantung pada status sosial ekonomi orang tua, disiplin, dan motivasi siswa menggunakan teknik penambangan informasi dengan algoritma J48 yang dibantu oleh aplikasi WEKA. Penelitian ini menggunakan 8 atribut yang dipartisi dengan 1variabel terikat dan 7 variabel bebas. Pendekatan yangg digunakann adalahh kuantitatiff. Subyekk penelitiann inii adalahh siswaa kelass XI SMK Negeri 2 Padang yang berjumlahh 450 siswaa. Strategi pengumpulann informasi yangg digunakann adalahh dokumentasii dann polling. Berdasarkan pengujian yang dilakukan

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Kaunang, Fergie Joanda. "Penerapan Algoritma J48 Decision Tree Untuk Analisis Tingkat Kemiskinan di Indonesia." CogITo Smart Journal 4, no. 2 (2019): 348. http://dx.doi.org/10.31154/cogito.v4i2.141.348-357.

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Kemiskinan telah menjadi masalah sosial dan tantangan bagi masyarakat di seluruh dunia yang terus dicari penyelesaiannya. Berdasarkan identifikasi dari Badan Program Pembangunan PBB (UNDP) yang bekerjasama dengan Oxford Poverty and Human Development Initiative (OPHI), 1.3 miliar penduduk dunia teridentifikasi sebagai penduduk miskin pada bulan September tahun 2018. Di tingkat nasional, Indonesia, tingkat kemiskinan tertinggi terjadi pada tahun 1999 dengan persentase sebesar 23.43%. Berdasarkan data dari Badan Pusat Statistik Indonesia (BPS), penduduk miskin di Indonesia mencapai 25.95 juta ora

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Munmun, Farha Akhter, and Sumi Khatun. "A Hybrid Method: Hierarchical Agglomerative Clustering Algorithm with Classification Techniques for Effective Heart Disease Prediction." International Journal of Research and Innovation in Applied Science 07, no. 07 (2022): 56–60. http://dx.doi.org/10.51584/ijrias.2022.7704.

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Prediction of heart disease is challenging because countless data are collected for clinical data analysis, but all this information is not equally important for making the right decisions. We have proposed a hybrid method: Hierarchical Agglomerative Clustering algorithm combined with conventional classification techniques such as K-Nearest Neighbors (K-NN), Decision Tree (J48), and Naïve Bayes which aims to reduce the prediction time by clustering the patients having almost similar symptoms of heart failure. This approach minimizes the forecasting time based on clusters of patients instead of

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Fauzi, Ihsan, Hilmy Sukma Nurmakarim, Ramadhan Islami Pasha, and Chaerur Rozikin. "COMPARATIVE STUDY OF SPAM EMAIL CLASSFICATION DECISION TREE BETWEEN USING CART AND J48." JATI (Jurnal Mahasiswa Teknik Informatika) 9, no. 3 (2025): 4032–36. https://doi.org/10.36040/jati.v9i3.13533.

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Email merupakan salah satu bentuk komunikasi digital yang paling populer dan efisien di era modern. Namun, seiring dengan meningkatnya penggunaan email. Email spam merupakan pesan yang tidak diinginkan yang dikirimkan secara massal ke sejumlah besar penerima dengan tujuan mengiklankan produk atau layanan, menyebarkan malware. Spam mengganggu pengguna dan mengonsumsi sumber daya jaringan dan server. Solusi yang ditawarkan dalam mengatasi spam menggunakan decision tree. Decision tree merupakan teknik pembelajaran mesin klasifikasi data berdasarkan fitur-fitur tertentu. Dalam konteks penyaringan

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Blasi, A. H., and M. Alsuwaiket. "Analysis of Students' Misconducts in Higher Education using Decision Tree and ANN Algorithms." Engineering, Technology & Applied Science Research 10, no. 6 (2020): 6510–14. http://dx.doi.org/10.48084/etasr.3927.

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A major problem that the Higher Education Institutions (HEIs) face is the misconduct of students’ behavior. The objective of this study is to decrease these misconducts by identifying the factors which cause them on college campuses. CRISP-DM Methodology has been applied to manage the process of data mining and two data mining techniques: J48 Decision Tree (DT) and Artificial Neural Networks (ANNs) have been used to build classification models and to generate rules to classify and predict students' behavior and the location of misconduct in college campuses. They take into consideration seven

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Blasi, A. H., and M. A. Alsuwaiket. "Analysis of Students' Misconducts in Higher Education Institutions using Decision Tree and ANNs." Engineering, Technology & Applied Science Research 10, no. 6 (2020): 6510–14. https://doi.org/10.48084/etasr.3927.

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A major problem that the Higher Education Institutions (HEIs) face is the misconduct of students’ behavior. The objective of this study is to decrease these misconducts by identifying the factors which cause them on college campuses. CRISP-DM Methodology has been applied to manage the process of data mining and two data mining techniques: J48 Decision Tree (DT) and Artificial Neural Networks (ANNs) have been used to build classification models and to generate rules to classify and predict students' behavior and the location of misconduct in college campuses. They take into considerat

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Alaba, O. B., E. O. Taiwo, and O. A. Abass. "Data mining algorithm for development of a predictive model for mitigating loan risk in Nigerian banks." Journal of Applied Sciences and Environmental Management 25, no. 9 (2021): 1613–16. http://dx.doi.org/10.4314/jasem.v25i9.11.

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The focus of this paper is on the development of data mining algorithm for developing of predictive loan risk model for Nigerian banks. The model classifies and predicts the risk involved in granting loans to customers as either good or bad loan by collecting data based on J48 decision tree, BayesNet and Naïve Bayes algorithms for a period of ten (10) years (2010 2019) from using structured questionnaire. The formulation and simulation of the predictive model were carried out using Waikato Environment for Knowledge Analysis (WEKA) software. The performance of the three algorithms for predictin

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Budiman, Budiman, Reni Nursyanti, R. Yadi Rakhman Alamsyah, and Imannudin Akbar. "Data Mining Implementation Using Naïve Bayes Algorithm and Decision Tree J48 In Determining Concentration Selection." International Journal of Quantitative Research and Modeling 1, no. 3 (2020): 123–34. http://dx.doi.org/10.46336/ijqrm.v1i3.72.

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Computerization of society has substantially improved the ability to generate and collect data from a variety of sources. A large amount of data has flooded almost every aspect of people's lives. AMIK HASS Bandung has an Informatic Management Study Program consisting of three areas of concentration that can be selected by students in the fourth semester including Computerized Accounting, Computer Administration, and Multimedia. The determination of concentration selection should be precise based on past data, so the academic section must have a pattern or rule to predict concentration selectio

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Oladimeji, O., A. Oladimeji, and O. Oladimeji. "Detecting breast cancer through blood analysis using decision tree (J48) classification algorithm." Journal of Fundamental and Applied Sciences 13, no. 3 (2021): 1275–84. http://dx.doi.org/10.4314/jfas.v13i3.8.

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Breast cancer is the second major cause of death in the world. Breast cancer accounts for 16% of all cancer deaths worldwide. Most of the methods of detecting breast cancer very expensive and difficult such as mammography. The objective of this research paper is detecting breast cancer through blood analysis using J48 algorithm which will serve as alternative to these expensive methods. The J48 algorithm was used to classify 116 instances also,10-fold cross validation and holdout procedure were used coupled changing of random seed. Average accuracies of 84.65% and 89.99% were acquired fo

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Jayasingh, Suvendra Kumar, Jibendu Kumar Mantri, and P. Gahan. "Comparison between J48 Decision Tree, SVM and MLP in Weather Forecasting." International Journal of Computer Science and Engineering 3, no. 11 (2016): 42–47. http://dx.doi.org/10.14445/23488387/ijcse-v3i11p109.

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Kaunang, Fergie Joanda, Reymon Rotikan, and Gleadies Stella Tulung. "Pemodelan Sistem Prediksi Tanaman Pangan Menggunakan Algoritma Decision Tree." CogITo Smart Journal 4, no. 1 (2018): 213. http://dx.doi.org/10.31154/cogito.v4i1.115.213-218.

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Pertanian sebagai salah satu sektor industri menjadi bagian pekerjaan yang menunjang pemenuhan kebutuhan makanan pokok masyarakat seperti tanaman pangan. Cuaca yang berubah-ubah dan tidak menentu dapat mempengaruhi hasil panen terlebih khusus dari segi jumlah hasil produksi. Hal ini membuat cuaca menjadi salah satu faktor penentu hasil produksi dari tanaman pangan. Memprediksi hasil panen tanaman pangan dengan baik dapat membantu para pemangku kepentingan baik petani ataupun mereka yang bekerja dalam industri pengolahan hasil tanaman pangan. Dewasa ini, Data Mining dan Machine Learning adalah

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Setiawan, Johan, Dita Amalia, and Iwan Prasetiawan. "Data Mining Techniques for Predictive Classification of Anemia Disease Subtypes." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 8, no. 1 (2024): 10–17. http://dx.doi.org/10.29207/resti.v8i1.5445.

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Anemia, characterized by insufficient red blood cells or reduced hemoglobin, hinders oxygen transport in the body. Understanding the different types of anemia is vital to tailor effective prevention and treatment. This research explores the role of data mining in predicting and classifying anemia types, focusing on complete blood count (CBC) and demographic data. Data mining is the key to building models that help healthcare professionals diagnose and treat anemia. Employing the cross-industry standard process for data mining (CRISP-DM), with its six phases, facilitates this effort. Our study

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Palwisut, Paranya. "Risk Prediction Model of Road Accidents During Long Holiday in Thailand Using Ensemble Learning with Decision Tree Approach." Suan Sunandha Science and Technology Journal 10, no. 2 (2023): 213–21. http://dx.doi.org/10.53848/ssstj.v10i2.499.

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The rate of injury and death from traffic accidents during the New Year and Songkran Festival each year has high and are continuously on the increase. The researchers, therefore, has decided to study and develop a model for predicting the road accident risk during the holiday season with ensemble learning based on decision tree approach. The aim is to help reduce accidents and loss of life caused by road accidents. The dataset used in this research is traffic accidents resulting in injury and death data during the long holiday from 2008 to 2015 from hospitals across the country, accumulatively

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Mustakim, Nurul Ain, Zatul Himmah Abdul Karim, Muna Kameelah Sauid, Noorzalyla Mokhtar, Zuhairah Hassan, and Nur Hazwani Mohamad Roseli. "Gender-Based Analysis of Online Shopping Patterns on Shopee in Malaysia: A J48 Decision Tree Approach." Information Management and Business Review 16, no. 3(I)S (2024): 844–54. http://dx.doi.org/10.22610/imbr.v16i3(i)s.4116.

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The purpose of this study is to investigates the gender differences of Shopee platform for online shopping behavior by using the J48 decision tree algorithm to classify and predict shopping frequency among male and female consumers for Malaysia context. WEKA software was used in this study to analyze the datasets. From the experiments, the majority of Shopee user were female consumers. The findings shows that female consumer behavior is more complicated and more varied regarding purchasing behavior. The study's findings demonstrate the potential of gender specific insights to enhance e-commerc

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Pujianto, Utomo, and Putri Yuni Ristanti. "Perbandingan kinerja metode C4.5 dan Naive Bayes dalam klasifikasi artikel jurnal PGSD berdasarkan mata pelajaran." TEKNO 29, no. 1 (2019): 50. http://dx.doi.org/10.17977/um034v29i1p50-67.

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Pendidikan mempunyai standar sebagai acuan dalam proses pembelajaran. Dalam hal ini Pemerintah telah mengatur standar pendidikan di Indonesia, mengacu pada Peraturan Pemerintah Republik Indonesia Nomor 19 Tahun 2005 Pasal 6 ayat (1) yaitu kurikulum untuk jenis pendidikan umum, kejuruan, dan khusus pada jenjang pendidikan dasar dan menengah. Sesuai dengan Peraturan Pemerintah tersebut, ditetapkannya Peraturan Menteri Pendidikan Nasional Republik Indonesia Nomor 23 Tahun 2006 pasal 1 ayat (2), tentang Standar Kompetensi Lulusan yang diantaranya memuat SK-KMP (Standar Kompetensi Kelompok Mata Pel

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Rukmana, Indra, Arvin Rasheda, Faiz Fathulhuda, Muh Rizky Cahyadi, and Fitriyani Fitriyani. "Analisis Perbandingan Kinerja Algoritma Naïve Bayes, Decision Tree-J48 dan Lazy-IBK." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 3 (2021): 1038. http://dx.doi.org/10.30865/mib.v5i3.3055.

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This research is focused on knowing the performance of the classification algorithms, namely Naïve Bayes, Decision Tree-J48 and K-Nearest Neighbor. The speed and the percentage of accuracy in this study are the benchmarks for the performance of the algorithm. This study uses the Breast Cancer and Thoracic Surgery dataset, which is downloaded on the UCI Machine Learning Repository website. Using the help of Weka software Version 3.8.5 to find out the classification algorithm testing. The results show that the J-48 Decision Tree algorithm has the best accuracy, namely 75.6% in the cross-validati

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Bakar, Norazhar Abu, Imran Sutan Chairul, Sharin Ab Ghani, Mohd Shahril Ahmad Khiar, and Mohd Zamri Che Wanik. "Improvement of transformer dissolved gas analysis interpretation using j48 decision tree model." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 1 (2023): 48. http://dx.doi.org/10.11591/ijai.v12.i1.pp48-56.

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<span lang="EN-US">Dissolved gas analysis (DGA) is widely accepted as an effective method to detect incipient faults within power transformers. Gases such as hydrogen, methane, acetylene, ethylene and ethane are normally utilized to identify the transformer fault conditions. Several techniques have been developed to interpret DGA results such as the key gas method, Doernenburg, Rogers, IEC ratio-based methods, Duval Triangles, and the latest Duval Pentagon methods. However, each of these approaches depends on the experts' shared knowledge and experience rather than quantitative scientifi

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