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All Journal Jurnal Riset Multidisiplin Edukasi Jurnal Sistem Informasi dan Ilmu Komputer
Dicopran Sisco
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Computer Science & IT Other

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HYBRID BI MODEL: KOLABORASI MACHINE LEARNING DAN VISUAL ANALYTICS UNTUK PENINGKATAN KETEPATAN PREDIKSI BISNIS Didi Sangaji; Dicopran Sisco; Tata Sutabri
Jurnal Riset Multidisiplin Edukasi Vol. 2 No. 10 (2025): Jurnal Riset Multidisiplin Edukasi (Edisi Oktober 2025)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/jurmie.v2i10.1087

Abstract

Big data complexity demands integration of accurate machine learning (ML) with interpretable visual analytics (VA). Traditional ML models face transparency challenges, while pure VA systems are limited in multidimensional pattern recognition. This study synthesizes 15 peer-reviewed articles (2021-2025) to evaluate ML-VA integration effectiveness in data-driven business decision-making. We identify five primary visualization designs (interactive dashboards, heatmaps, bubble charts, network graphs, counterfactual visualization), three feedback mechanisms (real-time, user refinement, interactive exploration), and human-in-the-loop (HITL) implementation for algorithm transparency. Results demonstrate Model M3 (SHAP/LIME+Network Graphics) achieves ROC-AUC 0.941, F1-Score 0.921, Accuracy 0.924, and Precision 0.931—exceeding traditional baseline by 16.7% on ROC-AUC. Critical improvements occur in model transparency (+170.5%), interpretability (+215.9%), and user engagement (+118.7%), without compromising predictive accuracy. Hybrid BI implementation yields significant business impact: process efficiency +35%, cost reduction -27%, analytical accuracy +44%, data processing capacity +85%. Structured HITL mechanism ensures meaningful human input, complete audit trails, and continuous model improvement. Evaluation framework encompasses confusion matrix, multi-metrics (accuracy, precision, recall, F1, specificity, ROC-AUC), and internal-external validity. The primary contribution is the proposed Hybrid BI Architecture that synergizes automatic ML capabilities with human domain knowledge, creating a responsible AI ecosystem with robust governance, full transparency, and measurable accountability for superior organizational decision-making in the digital transformation era.
Optimalisasi Metode Response Policy Zone (RPZ) Internet Sehat pada Jaringan FTTH Prabumulih Dicopran Sisco; Tata Sutabri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4172

Abstract

Abstract. One example of advanced information and communication technology is the internet. One can readily obtain the knowledge they require thanks to the internet. As a result, the internet is a crucial tool that needs to be used and understood to the fullest. The internet may be used for both beneficial and harmful purposes, which is why it is a double-edged sword with all of its risks. By filtering negative content using a list of 773 thousand negative content blocked on the trust + ™ Positive website by the Ministry of Communication and Information, the author hopes to create a positive internet network in the Prabumulih community and enable effective and efficient use of internet resources. The author can create a favorable online environment in Prabumulih City by utilizing the action research approach and the policy zone response method.
Co-Authors Didi Sangaji Tata Sutabri