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All Journal JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Rahman, Afida
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Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering

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E-commerce Transaction Fraud Detection Using the Naive Bayes Algorithm Dautd, Zahri Aksa; Aqmal S, M Fauzan; Sugiarta, Achmad; Rahman, Afida
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 1 (2025): February
Publisher : Lumina Infinity Academy Foundation

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This study utilizes the Naive Bayes algorithm to detect fraudulent transactions occurring on e-commerce platforms by analyzing several key attributes, including the transaction time, transaction amount, the user's geographic location, and the payment method used. This algorithm was chosen due to its advantage of simplicity in handling probabilistic-based classification, which facilitates the analysis of complex data. Based on the study's findings, the Naive Bayes model demonstrates a commendable ability with an accuracy rate of 80% in identifying transactions categorized as fraudulent activities. This research contributes valuable insights that can be applied to enhance the security and trust in online transaction systems.
Analysis of Cigarette Sales Transactions Using Apriori Algorithm at Madura Store Mahendra, Mochammad Augustiar; Sa'adah, Mamba'us; Puspitarini, Erri Wahyu; Rahman, Afida
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 2 (2025): June
Publisher : Lumina Infinity Academy Foundation

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Developments in the cigarette industry continue to increase and there are also challenges in classifying cigarette sales. In this case, the method of classifying cigarette sales using the Apriori algorithm can be one way that can be used. The purpose of this study is to identify significant cigarette sales and classify sales transactions based on sales patterns. The method to be used in this study has several stages. First, we collect cigarette sales data from several different cigarette shops. The data includes information such as transaction ID, items purchased, and sales amounts. Then, we pre-process the data to prepare the raw data for further analysis. The results of this study indicate that classifying cigarette sales using the Apriori algorithm is able to identify significant sales patterns and classify transactions with a more adequate level of accuracy. This research provides new insights in analyzing cigarette sales data and can help decision-making in the cigarette industry.
Evaluation of Reading Interest Based on Octalysis Gamification Fairuzabadi, Ahmad; Rahman, Afida
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
Publisher : Lumina Infinity Academy Foundation

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An abstract is often presented separate from the article, so it must be able to In the rapidly evolving information and technology era, literacy remains a crucial factor for a competitive and innovative society. Despite its significance, Indonesia faces a severe literacy challenge, evidenced by low reading interest and poor performance in international assessments like PISA. This issue is exacerbated by data from UNESCO and global literacy rankings, revealing that only a minimal fraction of the population engages in regular reading. With the advent of Industry 4.0, the ability to access and analyze information through reading has become increasingly vital. This study aims to address this challenge by leveraging gamification to enhance reading motivation and engagement. Specifically, it employs the Octalysis Framework by Yu-kai Chou to design a gamified system tailored to intrinsic user motivations. The research has three main objectives: identifying user profiles using Octalysis to understand individual reading motivations; designing and implementing gamification elements in the "Codex Horizon" app, including points, achievements, and community features; and evaluating the effectiveness of these elements in increasing reading engagement. The study seeks to provide insights into how gamification, grounded in Octalysis Framework, can be utilized to improve literacy in Indonesia, offering practical guidance for developers, educators, and policymakers.
Apriori Algorithm and Business Intelligence Methods for Bookstore’s Customer Preferences Analysis Ramadhan, Silmy Kafi; Septiani, Devi; Rahman, Afida; Handayani, Endah Tri Esti
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 3 (2025): October
Publisher : Lumina Infinity Academy Foundation

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This study explores the use of a priori algorithm in analyzing sales transaction data at Rony Jaya Bookstore. By combining data mining and business intelligence, the study successfully uncovered significant customer buying patterns, which were then used to support strategic decision-making. The results of the analysis showed that there was a close relationship between certain book categories, such as Fiction Books and Educational Books with a confidence level of 87.5%, as well as Non-Fiction Books and Educational Books with a confidence level of 88.89%. These findings provide valuable insights into developing marketing strategies, such as creating custom promotional packages and arranging product layouts in stores to make them more appealing to customers. This research also highlights the importance of ensuring data quality so that the resulting analysis is more accurate and relevant. Overall, the study offers a practical guide for Rony Jaya Bookstore and other businesses looking to leverage data mining and business intelligence technologies to improve efficiency and customer satisfaction.
Co-Authors Ahmad Fairuzabadi Aqmal S, M Fauzan Dautd, Zahri Aksa Handayani, Endah Tri Esti Mahendra, Mochammad Augustiar Puspitarini, Erri Wahyu Ramadhan, Silmy Kafi Sa'adah, Mamba'us Septiani, Devi Sugiarta, Achmad