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JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2686228X     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal of Information System Research (JOSH)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 803 Documents
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Improving the POSPAY Mobile Interface Using User-Centered Approach with User Experience Questionnaire Evaluation Tasya Arnomel Mareta; Evi Yulianingsih; Ari Muzakir
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i6.9474

Abstract

Digital public service applications require interfaces that are clear, efficient, and consistent to support fast and accurate transactions. In the PT Pos Indonesia service environment, POSPAY users may experience difficulties in locating core services, understanding menu structures, and completing tasks efficiently due to navigation and interface consistency issues. This study aims to improve the POSPAY mobile interface using a user-centered approach and to evaluate user experience using the User Experience Questionnaire. The study involved 20 participants (staff and customers). Observation and semi-structured interviews were conducted to elicit user needs, which were translated into prioritized requirements and implemented in a high-fidelity clickable prototype developed with Figma. Participants completed standardized task scenarios before completing the questionnaire. The results show positive mean scores in five dimensions, with Perspicuity (1.70) and Efficiency (1.55) as the highest, followed by Attractiveness (1.45), Dependability (1.20), and Stimulation (1.05). Novelty (0.65) remained neutral, indicating that the proposed interface is perceived as functional but not strongly innovative. The main contribution of this study is a context-specific requirement set and traceable mapping between user needs and prototype features for POSPAY in a postal service setting, supported by quantitative user experience evidence to prioritize interface refinement and implementation decisions at PT Pos Indonesia.
Pemanfaatan Algoritma FP-Growth pada Teknik Data Mining untuk Mengidentifikasi Pola Stok Produk Elektronik Irawaty Irawaty
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i6.9517

Abstract

Managing the availability of electronic product stock is a crucial issue in the retail world due to the high variety of products and dynamic consumer purchasing patterns. Inaccuracy in determining the amount of stock can lead to excess inventory or product shortages, which impacts on decreasing operational efficiency. This study aims to apply the FP-Growth algorithm in the data mining process to determine the pattern of electronic product stock availability based on purchase transaction data. The dataset used in this study consists of 150 electronic product purchase transaction data. The main problem faced is the lack of optimal utilization of transaction data to determine the relationship between products that are frequently purchased together. As a solution, this study applies the Frequent Pattern Growth (FP-Growth) algorithm because of its ability to find association patterns without the need to generate candidate itemsets, making it more efficient in data processing. The research process begins with calculating the frequency of item occurrences, determining the minimum support value of 20% (30 transactions), forming an FP-Tree, and mining frequent itemsets and association rules. The results show that Mouse, Laptop, and Keyboard are the items with the highest frequency, respectively 80%, 73%, and 70% of the total transactions. The Mouse–Laptop–Keyboard purchasing pattern has a support value of 55% with a confidence level of 80%. While the Mouse → Keyboard rule yields the highest confidence level of 85%. Based on these results, it can be concluded that the FP-Growth algorithm is effective in identifying purchasing patterns for electronic products and can be used as a basis for decision-making in prioritizing stock availability more precisely and data-driven.
Pengelompokan Tanaman Perkebunan Berdasarkan Produktivitas dan Luas Lahan dengan K- Means Clustering Ethaniel Williano Adhi Putra; Yunus Widjaja
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i3.9518

Abstract

Plantation data in West Java was grouped based on land area and crop productivity using the K-Means method. This data was obtained from Open Data Jabar from 2022 to 2024 and analyzed using a quantitative approach. Three groups can be identified based on the clustering results: one group has high productivity but relatively limited land area, another has large land area but suboptimal productivity, and the last group has equally low productivity and land area. The results indicate that land area does not always correlate with productivity. This study emphasizes the importance of selecting relevant variables and using methods consistently to produce more accurate and understandable analyses.

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