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All Journal Jurnal Computech & Bisnis (e-Journal) JUITA : Jurnal Informatika Jurnal INFOTEL
Imam Riadi
Universitas Ahmad Dahlan, Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Library & Information Science

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Implementation of association rule using apriori algorithm and frequent pattern growth for inventory control Imam Riadi; Herman Herman; Fitriah Fitriah; Suprihatin Suprihatin; Alwas Muis; Muhajir Yunus
JURNAL INFOTEL Vol 15 No 4 (2023): November 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i4.980

Abstract

Business success is a business that is able to compete and grow keep abreast of developments in the business world. Especially in the retail sector, where competition is getting tighter. Business owners need to pay attention to the layout of goods and stock management to improve service and meet consumer needs because consumers often have difficulty in finding goods. On the other hand, shortages and excess stock often occur due to lack of goods management. Based on these problems, appropriate techniques are needed for the management of goods supply, one of which is to apply techniques found in the branch of science. Data mining is a technique of association rules. This study aims to find patterns of placement and purchase of goods in generating Association Rule using FP-Growth algorithm. The dataset in this study used data on sales of goods in clothing stores. The results of the study of 140 transactions there are 24 association rules consisting of 7 association rules with 2-itemsets and 17 association rules with 3-itemsets that most often appear in transactions. Based on the order of the highest support value, namely CKJ→STX^LK with a support value of 67%, while the highest confidence value, there are 3 association rules that get the same value, namely STX^CKJ→LK, STX^CAK→LK, STX^RI→LK with a value of 100%. Thus, the rules of association produced by the frequent itemset algorithm, FP-growth, can serve as decision support for the sales of goods in small and medium-sized retail businesses
Mobile Forensics in Human Trafficking Investigation Services Using Mobile Laboratory Muammar Muammar; Imam Riadi; Rusydi Umar
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 1, March 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i1.24060

Abstract

This research examines the application of a mobile digital forensic laboratory developed by the Digital Forensics Center (DFC) at UMP to handle digital evidence directly at crime scenes, specifically in human trafficking cases. Integrating the Association of Chief Police Officers' (ACPO) methods, this mobile lab facilitates the investigative process, from planning to evidence collection and analysis, without delaying transport to a central lab, thereby speeding response times and minimizing evidence degradation.  We employed Magnet Axiom and DF-Tools to analyze WhatsApp data. Each demonstrated varying performance in identifying key digital evidence such as text messages, media, and group chats. DF-Tools showed an advantage in identifying multimedia artifacts with a 69.48% data acquisition success rate, compared to Magnet Axiom at 68.57%. Additionally, police bolstered their efforts to uncover human trafficking networks by implementing Base Transceiver Station (BTS)-based location tracking techniques to pinpoint suspect and victim locations via phone data or identity numbers. The research findings demonstrate that mobile labs enable rapid on-site responses, offer flexibility in collecting and securing digital evidence, and enhance efficiency and effectiveness of digital forensic investigations.
Architectural and Fundamental Analysis of Blockchain: A Comparative Overview of Working Mechanisms, Tokenization, and Data Decentralization Dedy Sumarhadi; Sunardi Sunardi; Imam Riadi
JURNAL COMPUTECH & BISNIS Vol. 20 No. 1 (2026): Jurnal Computech & Bisnis (e-Journal)
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/jcb.v20i1.01

Abstract

Blockchain technology has evolved from a nascent peer-to-peer payment system into a paradigm-shifting digital trust infrastructure, fundamentally challenging conventional centralised models. However, a deep understanding of the fundamental technical aspects behind the popularity of crypto assets remains limited. This study aims to: (1) analyse the fundamental architecture of blockchain; (2) evaluate tokenisation mechanisms; and (3) conduct a comparative analysis of its characteristics against traditional database systems. The research employs a qualitative descriptive method utilising a Systematic Literature Review (SLR) approach to synthesise technical literature published between 2023 and 2025. The analysis focuses on consensus mechanisms, the architectural transition from monolithic to modular systems (Layer-2 scaling), and the measurement of decentralisation using the Nakamoto Coefficient. The results indicate that: (1) blockchain offers distinct advantages in data integrity (immutability) and censorship resistance through a distributed append-only ledger structure, standing in sharp contrast to the CRUD (Create, Read, Update, Delete) model of relational databases; and (2) recent innovations such as Zero-Knowledge Proofs and Optimistic Rollups serve as critical solutions to the "Blockchain Trilemma" (balancing scalability, security, and decentralization). This study concludes that blockchain is not an absolute replacement for conventional databases, but rather a specialised solution for ecosystems that require high transparency and "trustless" interactions without a central authority.
Co-Authors Alwas Muis Dedy Sumarhadi Fitriah Herman Herman Muammar Muammar Muhajir Yunus Rusydi Umar Sunardi Sunardi Suprihatin Suprihatin