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All Journal Jurnal Mandiri IT
Aulia, Regifia Ningrum Nur
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Computer Science & IT Library & Information Science Mathematics

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Implementation of association method using fp-growth algorithm on sales transaction data at Koperasi Primer Pullahta Hankam Pusdatin KEMHAN RI Aulia, Regifia Ningrum Nur; Prabukusumo, M Azhar; Hidayati, Ajeng
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.446

Abstract

The conventional recording of sales transaction data frequently results in inaccuracies and presents significant obstacles to comprehensive data analysis. This study was conducted at Primkop Pullahta Hankam Pusdatin Kemhan RI with the aim of generating a product list based on item categories that are most frequently purchased together. These item combinations are expected to assist the cooperative in optimizing sales performance. The research employed a data mining technique known as association rule mining, which is designed to identify and predict customer purchasing behavior through analysis of transaction patterns. The dataset used comprised sales transaction records collected between September and November 2024. The FP-Growth algorithm was selected for its efficiency in identifying frequent itemsets without candidate generation. This algorithm utilized minimum support and confidence thresholds to generate association rules. The modeling process produced five association rules, each meeting the criteria of a minimum support of 20% and a minimum confidence of 80%, indicating strong co-occurrence among specific product combinations. Functional testing using the blackbox method demonstrated that all implemented features performed in accordance with specified functional requirements. The findings offer valuable insights for cooperative management by enabling data-driven decision-making in inventory planning, promotional bundling, and strategic sales targeting. These implications underscore the practical contribution of the research in enhancing operational efficiency and sales strategy within the cooperative sector.
Development of a laravel-based web information system for network device maintenance management using the rapid application development method Bimorogo, Sembada Denrineksa; Lediwara, Nadiza; Heikhmakhtiar, Aulia Khamas; Aulia, Regifia Ningrum Nur; Sunami, Yoga; Priyani, Kadek Jana; Azahra, Manda Fatimah
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.456

Abstract

Information and Communication Technology (ICT) infrastructure is essential for government operations, particularly in managing network devices. Within the ICT Hardware Infrastructure Subdivision (Subbidang Harinfra TIK) of the Data and Information Center at the Indonesian Ministry of Defense, documentation of maintenance activities remains fragmented, making monitoring, analysis, and historical data storage less effective. This study developed a web-based information system using the Laravel framework and the Rapid Application Development (RAD) approach to address these issues. The system automates documentation, monitoring, and reporting, ensuring more structured, transparent, and efficient processes. Black Box testing confirmed reliable functionality, data validation, and improved efficiency in maintenance activities. Unlike previous studies that focused on general asset or helpdesk systems, this research emphasizes ICT infrastructure maintenance in a defense environment, highlighting security and adaptability for sensitive data. The implementation enhances systematic documentation and operational transparency, with future improvements directed toward intelligent notifications and platform integration in line with Industry 4.0 trends.
Co-Authors Azahra, Manda Fatimah Bimorogo, Sembada Denrineksa Heikhmakhtiar, Aulia Khamas Hidayati, Ajeng Lediwara, Nadiza Prabukusumo, M Azhar Priyani, Kadek Jana Sunami, Yoga