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All Journal Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan International Journal of Artificial Intelligence Research Technomedia Journal Jurnal Teknologi dan Informasi El-Mujtama: Jurnal Pengabdian Masyarakat
Asmara, Rengga
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Religion Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Interactive Dashboard Development for Student Performance Monitoring: Integrating Academic and Socio-Demographic Data Humaira, Fitrah Maharani; Yuwono, Wiratmoko; Asmara, Rengga; Widodo, Rusminto Tjatur; Susetyoko, Ronny; Adawiyah, Robi’Atul
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1590

Abstract

Strategic decision  making in institutional settings is often constrained by the fragmentation and heterogeneity of data across multiple sources. This study addresses this critical gap by developing and validating an interactive web-based dashboard designed to consolidate and transform heterogeneous institutional data from seven distinct sources into actionable insights. A complex feature engineering pipeline was necessitated, involving comprehensive data integration and structural consistency checks. Techniques like Text Normalization and Feature Mapping were applied to clean over a lot of inconsistent entries, alongside Feature Binning and Extraction to generate analytically robust metrics. The system was implemented using Python for data processing and ReactJS for the dynamic interface, and its viability was validated via structured User Acceptance Testing (UAT). The subsequent descriptive analysis provided key insights into student demographics, geographical reach, and enrollment compliance across academic levels. Crucially, the comprehensive UAT resulted in an outstanding overall acceptance score of very worthy. However, feedback analysis indicated a dominant user focus on visual aspects, with noted complaints regarding the suboptimal color scheme and contrast impacting user experience. The findings confirm that complex feature engineering is a viable and effective strategy for transforming fragmented institutional data into an immediately deployable strategic resource. This system offers a validated blueprint for data consolidation in higher education. Future work is accordingly  directed toward revising the color palette and contrast ratios to enhance visual clarity and user experience, alongside continuous optimization of data completeness to maintain the dashboard’s utility
Co-Authors ., Nailussa’ada Achmad Basuki Adawiyah, Robi’atul Ahsan, Ahmad Syauqi Al, Mohammad Jawahir Amalia, Luri Shafira Andhik Ampuh Yunanto Arna Fariza Azahro Choirunisa, Nadia Azizah, Agustiani Nur Basofi, Arif Fachrian, Zuhad Achmad Fatmawati, Risa Ferry Astika Saputra Hasnaa, Rosyiidah Humaira, Fitrah Maharani Ira Prasetyaningrum Istiqomah, Galuh Nurul M Udin Harun Al Rasyid, M Udin Harun Martono, Hero Yudo Nurhidayah - Panggalih, Bintang Ampuh Rizky Yuniar Hakkun Rusminto Tjatur Widodo Santoso, Dian Septiani Sekar Puranti, Zazabillah Susetyoko, Ronny Taufiq Hidayatullah Tita Karlita Wibowo, Prasetyo Wiratmoko Yuwono Yanuar Risah Prayogi Zufar, Farhan Izzudin Az