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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal ICT : Information and Communication Technologies Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Bharasumba Jurnal Multidispliner Jurnal Pengabdian Masyarakat Berkarya JICS : Journal Of International Community Service
Wirhan Fahrozi, Wirhan
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Determining Sales Based on Goods Data Classification Using the Web-Based C4.5 CRISP-DM Method Gunawan, Bayu; Fahrozi, Wirhan
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i2.278

Abstract

The increasing complexity of product distribution and sales activities at PT Mitra Bersama has created challenges in accurately classifying product performance, particularly due to manual data processing that is inefficient and prone to error. To address this issue, this study aims to develop an intelligent decision-support system capable of classifying best-selling and non-best-selling products using a data-driven approach. The CRISP-DM methodology was applied to guide the overall analytical process, consisting of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The C4.5 algorithm was used to perform the classification through entropy and information gain calculations to determine the most influential attributes. The results show that Type of Food has the highest information gain (0.0113340), followed by Initial Stock, Unit, Month, and Ending Stock, indicating that product characteristics and early inventory levels play a significant role in predicting sales performance. These findings were implemented into a web-based application to facilitate real-time classification and assist decision-makers in optimizing inventory planning, distribution strategies, and sales forecasting. This research contributes to improving organizational efficiency by providing a systematic, accurate, and accessible tool that supports better strategic decision-making in product sales management.
Data Mining for Drug Inventory Using Web-Based FP-Growth Method Puspita, Della; Fahrozi, Wirhan
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i2.263

Abstract

Pharmacy inventory management plays a critical role in ensuring product availability and preventing financial losses due to overstock or stock shortages. However, many pharmacies, including Global Medcare Pharmacy in Medan, still experience challenges in maintaining optimal inventory levels due to the absence of data-driven management systems. This study aims to develop and implement a website-based data mining application using the FP-Growth algorithm to identify frequent itemsets and uncover association patterns within pharmaceutical sales transactions. The FP-Growth algorithm was applied to 300 transaction records to generate frequent item combinations with a minimum support threshold of 3%. The results reveal strong associations among specific drugs, such as Amlodipine 10mg, Azithromycin 500mg, and Cetirizine 10mg, with confidence levels reaching up to 100%. These findings demonstrate that FP-Growth effectively identifies purchasing patterns that can guide pharmacies in forecasting demand, managing stock levels, and designing promotional bundles. The practical implication of this research is that integrating FP-Growth into pharmacy information systems can enhance decision-making accuracy, improve service quality, and increase operational efficiency. Nevertheless, the study is limited to a single-site dataset and static analysis; future research should employ larger datasets and hybrid predictive approaches for real-time implementation across multiple pharmacy networks.
Co-Authors adhar, Deni Deny, Deny Adhar fithry tahel, fithry Ginting, Erwin Gunawan, Bayu Harahap, Ahir Yugo Nugroho Harahap, Charles Bronson Heri Gunawan Hts, Dedek Indra Gunawan Ikorasaki, Frans Indra, Evta Indriani, Ulfah Lili Tanti, Lili Meizar, Abdul Muhardi Saputra Puspita, Della RUSTAM, MUHAMMAD TAUFIQ Safrizal Safrizal Syahputri, Nita Ultami, Eliza Yulistya Wahyuni, Linda