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All Journal Journal of Intelligent Decision Support System (IDSS) Jurnal Mandiri IT
Prabukusumo, M Azhar
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Computer Science & IT Library & Information Science Mathematics

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Digitalization of guest record management through a web-based information system to support security and efficiency Mawadah, Helvina Salsabila; Prabukusumo, M Azhar; Saputra, Bagus Hendra
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 2 (2025): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i2.297

Abstract

Digitization of visitor registration improves efficiency and security in visit management in many institutions. This project seeks to create a web-based information system that replaces manual registration techniques to reduce the possibility of data loss and inaccuracy of registration, while increasing the efficiency and accuracy of guest information processing. The study used a software development methodology that leverages the Rapid Application Development (RAD) concept, which facilitates rapid and adaptive system development. The novelty of this system lies in its integration of automated blacklist detection and personalized notification workflows, features that are not commonly found in prior visitor registration systems. The system was designed and implemented specifically within an institutional environment but has the potential to be generalized and adapted for diverse organizational contexts, including government offices, corporate facilities, and educational institutions. The study results show that the web-based information system improves efficiency in visitor registration through automated verification, real-time monitoring, and notification integration, thereby facilitating safer and more organized guest management. This solution aims to enable institutions to improve their visitor reception processes, strengthen workplace security, and facilitate digital transformation in visit management.
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.
Co-Authors Aulia, Regifia Ningrum Nur Hidayati, Ajeng Mawadah, Helvina Salsabila Saputra, Bagus Hendra