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All Journal Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Putra, Gusty Nanda Kharisma
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Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences

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Optimalisasi Website Kelurahan Merjosari Menggunakan Metode Observasi Suwandono, Purbo; Wahyudi, M. Ilham Setyo; Ramadhani, Auzhar Rafli; Prasetyo, Rino Ayogi Adi; Putra, Gusty Nanda Kharisma
JURNAL APLIKASI DAN INOVASI IPTEKS "SOLIDITAS" (J-SOLID) Vol. 7 No. 2 (2024): Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS
Publisher : Badan Penerbitan Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/js.v7i2.6440

Abstract

Perkembangan teknologi informasi telah mendorong kelurahan untuk mengadopsi media digital sebagai sarana pelayanan publik yang lebih efisien. Kelurahan Merjosari, Kecamatan Lowokwaru, Kota Malang, telah memiliki website sebagai bagian dari upaya tersebut. Namun, website ini masih menghadapi berbagai kendala seperti informasi yang tidak up-to-date, tampilan yang kurang menarik, dan minimnya fitur interaktif. Penelitian ini bertujuan untuk mengidentifikasi masalah-masalah yang ada pada website Kelurahan Merjosari dan menawarkan solusi optimalisasi. Metode yang digunakan meliputi observasi lapangan, analisis kebutuhan, dan implementasi optimalisasi dengan menggunakan platform WordPress. Hasil yang dicapai menunjukkan bahwa pembaruan dan penambahan fitur baru pada website Kelurahan Merjosari telah meningkatkan kualitas informasi, tampilan, dan kemudahan akses bagi masyarakat. Optimalisasi ini berdampak pada peningkatan kepuasan masyarakat terhadap pelayanan kelurahan serta mendorong partisipasi aktif warga dalam program-program kelurahan.
Supply Chain Optimization in the Retail Industry by Integrating Apriori Algorithms and Time Series Forecasting in Business Intelligence Putra, Gusty Nanda Kharisma; Silviana, Silviana; Riyadi, Agung; Praseptiawan, Mugi
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 3 No. 1 (2026): Vol. 3 No. 1 (2026): February
Publisher : Lumina Infinity Academy Foundation

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Abstract

This study investigates the integration of the Apriori algorithm and time series forecasting within a Business Intelligence (BI) framework to optimize supply chain operations in the retail industry. The Apriori algorithm was utilized to identify significant purchasing patterns, enabling strategic decisions such as product bundling and cross-selling. Concurrently, time series forecasting, with an ARIMA model achieving a mean absolute percentage error (MAPE) of 8%, provided accurate demand predictions, supporting improved inventory management and resource allocation. The integration of these methods into a BI dashboard facilitated real-time monitoring and data-driven decisionmaking, leading to enhanced operational efficiency and reduced costs. While challenges such as data quality, computational resource demands, and user adaptability were observed, this research underscores the transformative potential of analytics in retail supply chain management. Future advancements in machine learning and IoT integration are recommended to further enhance system performance. Overall, this study demonstrates a pathway for retailers to achieve operational excellence and superior customer satisfaction through data-driven strategies.
Co-Authors Agung Riyadi Praseptiawan, Mugi Prasetyo, Rino Ayogi Adi Purbo Suwandono Ramadhani, Auzhar Rafli Silviana Silviana Wahyudi, M. Ilham Setyo