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Yulya Muharmi
Department of Computer Science, Universitas Lampung
Computer Science & IT

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Analysis of Product Purchase Patterns Using the Apriori Algorithm on FMCG Distributor Transaction Data in the Riau Region Yulya Muharmi; Nurul Azwanti; Dhella Amelia
Jurnal Pepadun Vol. 7 No. 1 (2026): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v7i3.324

Abstract

This study investigates purchasing patterns of fast-moving consumer goods (FMCG) in Riau Province, Indonesia, using the Apriori algorithm within the Market Basket Analysis framework. Transaction data from a distributor comprising 4,422 transactions and 243 unique products across Pekanbaru, Kampar, and Rokan Hulu were analyzed to generate frequent itemsets and association rules, evaluated using support, confidence, and lift metrics. The application of a consistent minimum support and confidence threshold ensures statistically robust rule extraction across regions with different transaction scales.The results reveal strong intra-brand associations within the snack category, with several rules exhibiting lift values above ten, indicating systematic bundling behavior rather than random co-occurrence. These findings suggest that retailers tend to stock complementary product variants simultaneously, reflecting structured purchasing patterns at the outlet level. Regional comparison highlights differences in rule density across districts, shaped by transaction volume and the proportional effect of the support threshold, demonstrating how dataset scale influences association complexity. Overall, the study demonstrates that the Apriori algorithm effectively uncovers meaningful purchasing structures in distributor-level transaction data. The findings provide actionable insights for inventory management, regional distribution planning, and targeted promotions, while contributing to the literature by examining FMCG purchasing behavior in a multi-region distribution context using empirical distributor data.
Information System for Guidance on Student Practical Work Reports in the Computer Science Department of the Web-Based Information Management Study Program Yulya Muharmi; Bambang Hermanto; Viona Almadea
Jurnal Pepadun Vol. 6 No. 3 (2025): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v6i3.301

Abstract

The supervision of practical work (KP) reports in the Computer Science Department has traditionally been carried out manually, which often leads to several issues such as difficulty aligning schedules between students and supervisors and challenges in tracking the history of report revisions. To address these limitations, a web-based internship report supervision information system was developed to support the guidance process in an online, structured, and well-documented manner.This research adopted the Waterfall model as the system development framework, while a descriptive qualitative approach was applied during the requirements analysis and implementation phases. The system includes key features such as consultation scheduling, report submission, revision tracking, and management of user profiles and announcements. System evaluation was conducted through black-box testing and a User Acceptance Test (UAT), yielding a score of 81%, which indicates that users were generally satisfied with the system’s performance.Overall, the presence of this system improves efficiency and transparency in the supervision process and strengthens communication and progress monitoring for both students and supervisors.
Co-Authors Bambang Hermanto Dhella Amelia Nurul Azwanti Viona Almadea