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Analysis of Online Transportation Customer Satisfaction Using C4.5 Algorithm Irawan, Ryan Avrilio; Marpaung, Fhadillah Ain; Saputra, Idris Ivan; Widarti, Dinny Wahyu; Fairuzabadi, Ahmad
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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Abstract

In the era of increasing business competition, transportation companies are required to enhance the efficiency and effectiveness of their services. One method that can be employed to optimize fleet management is through Data Mining analysis. This study focuses on optimizing Ojek online transportation services using the C.4.5 Algorithm method. The aim of this research is to group customers and areas based on service demand patterns, thus improving fleet distribution and reducing waiting times. The data used in this study includes location, demand, and trip frequency information. The analysis results show that the C.4.5 algorithm method effectively groups the data, providing optimal fleet distribution and enhancing service performance. This research demonstrates that applying data mining through the C.4.5 algorithm method can be an effective strategy for improving management and operational efficiency in Ojek online transportation services, offering competitive advantages in service efficiency and customer satisfaction.
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.
Application of Apriori Algorithm to Find Flower Purchase Patterns Tusianto, Daffa Yauzan; Fairuzabadi, Ahmad; Sujito, Sujito
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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Abstract

This research aims to apply the Apriori algorithm in analyzing flower purchase patterns at a flower shop. Apriori algorithm is used to identify product combinations that are often purchased together, in the hope of finding purchasing patterns that can be utilized to improve marketing strategies and store operational efficiency. Transaction data from the shop is processed to extract frequent itemsets and generate association rules by setting the right threshold of support and confidence values. The results of this study show that flower combinations such as Tulip and Bougenville frequently co-occur in purchases, with significant support-confidence products. These findings provide insights into consumer purchasing behavior that can be used to recommend product bundling or product rearrangement in stores. This research contributes to the application of data mining in the retail sector, particularly in increasing sales and customer satisfaction in flower shops.