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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Techno.Com: Jurnal Teknologi Informasi Briliant: Jurnal Riset dan Konseptual Journal of Development Research JPM (Jurnal Pemberdayaan Masyarakat) JAST : Jurnal Aplikasi Sains dan Teknologi Jurnal Nasional Komputasi dan Teknologi Informasi bit-Tech Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Darmabakti : Junal Pengabdian dan Pemberdayaan Masyarakat Computer Science (CO-SCIENCE) Prosiding Seminar Nasional Pengabdian Masyarakat Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Journal of Information System and Application Development
Indana, Luthfi
Sistem Informasi, Fakultas Teknologi Informasi, Universitas Merdeka Malang
Aerospace Engineering Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Neuroscience Social Sciences Transportation Other

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Journal : computer science co-science

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Perancangan Sistem Informasi Surat Administrasi Penduduk Elektronik Menggunakan Metode Scrum Indana, Luthfi; Ilmananda, Asri Samsiar
Computer Science (CO-SCIENCE) Vol. 5 No. 2 (2025): Juli 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/co-science.v5i2.9511

Abstract

Letter management is a routine activity carried out at the Kerta Jaya Village office in Banyuasin. Currently, the administration of administrative documents in this village has been done manually, resulting in long queues. This study aims to develop an information system for managing electronic administrative documents for residents, such as domicile certificates, death certificates, and single-marriage certificates. This research is a research and development (R&D) study using the Scrum method. The Scrum method divides tasks into small parts (sprints). In each sprint, researchers focus on completing several features that can be used immediately. The Scrum method was used because it has a structured framework with sprints that produce functional incremental products. This method is suitable because it allows for rapid adaptation so that application development does not take too long. The result of this study is an information system for managing electronic administrative letters in Kerta Jaya Village, Banyuasin District. From the results of the application's usability aspect, the percentage obtained on 30 respondents was 79.16%, meaning this application is suitable for use by the community.
Performance of Distance Metrics in SMOTE for Binary Imbalanced Classification Fandi Yulian Pamuji; Luthfi Indana; Mohammad Dwi Irfan Affandi
Computer Science (CO-SCIENCE) Vol. 6 No. 2 (2026): July 2026 (On Process)
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/co-science.v6i2.12543

Abstract

Skewed class distribution continues to be one of the central obstacles in binary classification, since a learning model tends to lean toward the dominant class and consequently overlooks observations belonging to the under-represented class. The purpose of this research is to examine how the choice of distance measure inside SMOTE, specifically Euclidean, Manhattan, Chebyshev, and Hamming, affects predictive quality on imbalanced binary data. Ten publicly available binary datasets drawn from the KEEL repository, whose imbalance ratios span from 1.86 up to 15.80, were used in the experiment. Every dataset was preprocessed and partitioned into 80% for training and 20% for testing; oversampling with SMOTE was carried out on the training portion only, after which four learners, namely Naive Bayes, Decision Tree, Logistic Regression, and k-Nearest Neighbor, were assessed. Model quality was judged through the Matthews Correlation Coefficient (MCC) together with the G-Mean, as these two indicators describe imbalanced performance more faithfully than plain accuracy. The comparison revealed that pairing Euclidean-based SMOTE with Logistic Regression yielded the strongest average scores (MCC = 0.72; G-Mean = 0.79); Manhattan-based SMOTE reached its top MCC again with Logistic Regression (MCC = 0.68) and its top G-Mean with the Decision Tree (G-Mean = 0.79); Chebyshev-based SMOTE delivered the best overall combination together with the Decision Tree (MCC = 0.74; G-Mean = 0.84); and Hamming-based SMOTE performed best alongside Logistic Regression (MCC = 0.73; G-Mean = 0.81). Taken together, these outcomes suggest that the distance function chosen within SMOTE shapes the quality of the generated synthetic points and, in turn, the behavior of the trained classifier.
Co-Authors AA Sudharmawan, AA Aditya Hidayat Pratama Andanuwari, Reo Aldo Anggraini, Sinar Perbawani Abrina Anis Zubair, Anis Asri Samsiar Ilmananda Ayu Chandra Kartika Fitri Dewi, Shabrina Syntha Efendi, Kelvin Nur Fandi Yulian Pamuji Fitri Rahmawati Galih Sulaksono, Aditya Hamas Afif Aswari Hans Arkananta, Ivanderich Haris Satriyawan Haryono, Dhanang Andryansah Hidayatullah, Moch. Rizky Putra Karyudi, Mochammad Daffa Putra Laksana, Indra Dwi Madre Volenta Adil Marcella, Lorensiana Mohammad Dwi Irfan Affandi Nugroho, Ferdyanto Adhi Oktaviastuti, Blima Putra, Agung Surya Rahmatina Hidayati Rinanti, Rosyida Fajri Rofiqul Muslikh, Ahmad Ronald David Marcus Ryan Almayda, Dennis Sane, Bastion Faruq Sasongko, Redoti Zulfikar Soenarto Soenarto Viry Puspaning Ramadhan Wicaksono, Muhammad Dicho Nugroho Wijaya, Handika Setya wijaya, Handika Setya