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All Journal Jurnal Masyarakat Informatika Voteteknika (Vocational Teknik Elektronika dan Informatika) Syntax Jurnal Informatika POSITIF INFORMAL: Informatics Journal Format : Jurnal Imiah Teknik Informatika Faktor Exacta PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal ULTIMA InfoSys Jurnal Teknologi Jurnal TAMBORA CCIT (Creative Communication and Innovative Technology) Journal Building of Informatics, Technology and Science Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Mnemonic JISA (Jurnal Informatika dan Sains) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmu dan Teknologi Peternakan Terpadu (JITPU) CSRID
Herfandi Herfandi
Universitas Teknologi Sumbawa
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Immunology & microbiology Industrial & Manufacturing Engineering

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Application of Information Gain to Select Attributes in Improving Naïve Bayes Accuracy in Predicting Customer's Payment Capability Herfandi, Herfandi; Zaen, Mohammad Taufan Asri; Yuliadi, Yuliadi; Julkarnain, M.; Hamdani, Fahri
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1044

Abstract

The customer is the main factor in the running of PT. XYZ. A good understanding of customers is very important for predicting the capability of customers to pay. The implementation of credit collectibility is used to determine the quality of customer credit, one of which is the customer's capability to pay interest and principal on time. While manually, it is very difficult to accurately predict the capability of customer credit payments. Data mining techniques with the Naïve Bayes algorithm were chosen to classify customers to be able to find patterns, analyze and predict, because they have good performance, are efficient, and simple. The Naïve Bayes algorithm has a weakness in terms of sensitivity to many attributes, so the accuracy is low. Based on the problem stated, his study will apply the Information Gain method to select the most influential attribute on the label in order to increase the accuracy of the Naïve Bayes algorithm. This research produces a new dataset with seven attributes: TENOR, SALARY, DOWN PAYMENT, INSTALLMENT, APPROVAL, OTR CLASS, AGE with Labels: Status and Id: Id number based on the Information Gain method. The dataset comparison process with 995 data records showed an increase in accuracy, precision, and AUC using the new dataset compared to the old dataset, but in the t-Test test with an alpha value = 0.05 there is a difference but not significant. In the evaluation process, performance experienced a significant increase in the use of new datasets with the following percentages of performance improvement: accuracy = 8%, precision = 18.42%, recall = 17.65% and AUC= 0.057%. The results of this study obtained AUC of 0.876, accuracy of 87.88%, precision of 61.90%, and recall of 76.47%, and classified into good classification. 
Structural Correlation Patterns in Regional COVID-19 Surveillance Data and Implications for Epidemiological Monitoring Herfandi, Herfandi; Mofidul, Rafat bin; Khan, Ijaz ahmad
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026 (Ongoing)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.1.77361

Abstract

The Covid-19 pandemic has had a significant impact on the health sector in various regions, including Kabupaten Sumbawa. This study aims to analyze relationships among attributes in the Covid-19 dataset using the Correlation Matrix algorithm within the CRISP-DM methodology. The dataset was obtained from the official website of the Government of Kabupaten Sumbawa, comprising 10,573 records, of which 405 were cleaned after the data cleaning process. The analysis was conducted using RapidMiner 9.9 software. The findings indicate a very strong correlation between the attributes KONTAK ERAT-DISCARDE, SUSPEK-DISCARDE, and KONFIRMASI-MENINGGAL DUNIA with the increase in total Covid-19 cases. In addition, a significant negative correlation was observed between the attribute PP-MASIH KARANTINA and the number of deaths. Furthermore, an almost perfect correlation was found between PROBABLE-DISCARDE and PROBABLE-MENINGGAL. Based on these findings, it is recommended that the government prioritize monitoring cases before they are declared discarded and strengthen the quarantine system for travelers. This study provides a data-driven foundation for formulating evidence-based pandemic response policies.
Co-Authors Aditya Agus Wisanto Agung Susilo Yuda Irawan Ahmad Fauzul Kabir Ahmad Muchlis Ali Kafabillah Assegaf , Ridwan Anggi Fitria Ari Syahwatullah Arman Diansyah Baihaqi, Kiki Ahmad Deri Afriliyansa Eko Purwirawansyah Elga Ramdani Eri Sasmita Susanto Fahri Hamdani Fifit Alfiah Gilang Ginanta Haris Yusuf Bakhtiar I Made Widiarta Idham Amdin Julkarnain, M. Kamal Prihandani Kevin Noanda Aditya Rudy Yanto Khan, Ijaz ahmad Lokesworo M Julkarnain M. Julkarnain M. Julkarnain Moch Wahyu Firmansyah Mofidul, Rafat bin Mohammad Taufan Asri Zaen Muhammad Hanif muhammad rizky, muhammad Mujahidin Patti Peiloh Mulyanto, Yudi Nurul Maulida Solihat Randi Candra Kirana Reza Avrizal Reza Maulana Safira, Azzahrah Maulya Saruni Dwiasnati Suarantalla, Ryan Sukarna, Royan Habibie Sultan Naufal Abdillah Syarifuddin Syarifuddin Ulfatus Soleha Yuliadi Yuliadi Yuliadi Yuliadi Yulian Ansori