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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
Kurnia Naradinata
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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Pengembangan Aplikasi Point of Sales Berbasis Web pada Bengkel Menggunakan Metode Agile Kurnia Naradinata; Afiani Agus Abdillah; Kahfi Ahmad Arpiandi
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 06 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Micro, Small and Medium Enterprises (MSMEs) in the automotive sector, such as repair shops, still heavily rely on manual transaction and stock recording, which is prone to data loss, calculation errors, and delayed reports. This study aims to design and implement a web-based Point of Sale (POS) application at G Speed Bintaro Workshop using the Agile method with the Scrum framework. The system implementation is built utilizing modern database technology and an appropriate development environment. The test results show that all features function according to specifications, including recording spare parts sales transactions and service services, automatic stock management, tracking customer vehicle medical history, and real-time operational reporting. This system is proven to mitigate vulnerabilities in transaction work document management, reduce queue buildup, and maintain strict inventory data synchronization. The application of a web-based POS application using the Agile method is an effective digitalization solution for automotive MSMEs.
Analisis Pengelompokan Pola Pelanggaran Kode Etik Profesi TI Berdasarkan Karakteristik Insiden Siber Menggunakan Algoritma K-Means Clustering Yusuf Arif Rahman; Kahfi Ahmad Arpiandi; Kurnia Naradinata; Fathur Nurrohman; Ghufron Malik Azizi; Rahmawati
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 06 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rising intensity of cyber incidents in Indonesia is not merely a technical issue but also reflects failures in applying the professional code of ethics in information technology (IT), such as the obligation to avoid harm, preserve data confidentiality, and exercise professional competence responsibly. This study aims to group cyber incidents by their characteristics and then interpret the resulting clusters as indications of IT professional code-of-ethics violations. The K-Means Clustering algorithm was applied to the Cybersecurity Incident Dataset (Habeeb, 2024) using the CRISP-DM framework. The numerical variables analysed include financial loss, number of affected users, resolution time, severity score, and attack sophistication. The optimal number of clusters was determined by combining the Elbow method and the Silhouette coefficient. The analysis produced three distinct clusters, namely high-impact and sophisticated incidents, medium operational incidents, and high-volume low-impact incidents, with a Silhouette value of 0.53 indicating an adequate clustering structure. Mapping each cluster onto ethical principles shows that high-volume incidents are most associated with weak awareness and basic controls, whereas high-impact incidents are most associated with negligence of professional responsibility on critical systems. These findings can serve as a basis for more targeted mitigation prioritisation and professional ethics enforcement.
Co-Authors Afiani Agus Abdillah Fathur Nurrohman Ghufron Malik Azizi Kahfi Ahmad Arpiandi Rahmawati Yusuf Arif Rahman