Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal JSiI (Jurnal Sistem Informasi) Jurnal Pengabdian Sains dan Humaniora
Khairuddin
Universitas Putera Batam
Computer Science & IT Decision Sciences, Operations Research & Management Education Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Evaluasi Klasifikasi Hasil Catur Blitz pada Dataset Tidak Seimbang Skala Besar Menggunakan Cost-Sensitive Learning Khairuddin
Jurnal Sistem Informasi Vol. 13 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/xv0d9m54

Abstract

The rapid growth of online chess platforms has generated large-scale structured game data that can be utilized for data-driven analysis. In blitz mode games, match outcomes are categorized into win, lose, and draw; however, the distribution of these outcomes is inherently imbalanced, with draw representing a small minority of the dataset. This study aims to evaluate the effectiveness of cost-sensitive learning through balanced class weighting in improving classification performance on an imbalanced large-scale blitz chess dataset. A total of 100,000 rated blitz games were extracted from the Lichess open database and processed through preprocessing, feature extraction, and stratified data splitting. Three supervised learning algorithms - Support Vector Machine (SVM), Decision Tree, and Random Forest - were implemented. Model performance was evaluated using Macro F1-score as the primary metric, along with accuracy and 5-fold stratified cross-validation. The results indicate that without cost-sensitive learning, the recall for the minority class (draw) approaches zero despite achieving higher overall accuracy (0.54). In contrast, applying balanced class weighting significantly improves minority class detection, increasing recall for draw up to 0.73 with a Macro F1-score of approximately 0.40, although overall accuracy decreases to 0.45. This demonstrates the trade-off between global performance and minority class sensitivity. Feature importance analysis further reveals that move count is the most influential predictor of match outcomes. These findings confirm that imbalance-aware learning plays a critical role in large-scale chess outcome classification and highlight the importance of appropriate evaluation metrics in imbalanced datasets
Digital Anti-Cyberbullying Campaign through a Student Collaboration Project Nur Elfi Husda; Michael Jibrael Rorong; Muhammat Rasid Ridho; Nurhabsyina; Faine Fabiola; Khairuddin
Jurnal Pengabdian Sains dan Humaniora Vol. 5 No. 1 (2026): 2026 May Edition
Publisher : Fakultas Keguruan dan Ilmu Pendidikan-Universitas Timor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpsh.v5i1.10666

Abstract

The rapid growth of social media has intensified adolescents’ digital interactions while increasing the risk of cyberbullying, which negatively affects students’ psychological well-being. Low digital literacy and limited understanding of online ethics are key factors contributing to adolescents’ vulnerability to online harassment. This community service program aimed to enhance students’ awareness and understanding of ethical and responsible social media use through a collaborative digital campaign project. The program employed a Participatory Action Research (PAR) approach consisting of observation, problem formulation, intervention, and evaluation. The participants were students of SMA Negeri 28 Batam from various grade levels. The intervention was conducted through poster design and digital content creation competitions focusing on cyberbullying prevention. The results indicate increased student engagement, improved understanding of online ethics, and greater awareness of the dangers of hoaxes and cyberbullying. In addition, the program contributed to the development of students’ soft skills, including teamwork, creativity, and communication. This collaborative project demonstrates its potential as a participatory and sustainable digital literacy education model for cyberbullying prevention among students.
Co-Authors Faine Fabiola Husda, Nur Elfi Michael Jibrael Rorong Muhammat Rasid Ridho Nurhabsyina