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All Journal Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) International Journal of Advances in Data and Information Systems Journal of Applied Research In Computer Science and Information Systems
Abdul Rahman, Titik Khawa
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Integrating multi-criteria decision making and public sentiment analysis for sustainable urban green space planning S. Kuba, Muhammad Syafaat; Faisal, Muhammad; Nurnawaty, Nurnawaty; Abdul Rahman, Titik Khawa; Syamsuri, Andi Makbul; Hayat, Muhyiddin AM; Bakti, Rizki Yusliana
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.11168

Abstract

Sustainable planning of green open spaces (GOS) requires decision-making models that combine expert evaluation with public input. This study proposes a novel hybrid framework that integrates multi-criteria group decision making (MCGDM) with public sentiment analysis to support community-based and data-driven urban planning. The workflow consists of evaluating 25 community-proposed GOS locations using stepwise weight assessment ratio analysis (SWARA) for criteria weighting and MABAC-BORDA for multi-criteria ranking, resulting in 11 feasible alternatives. To incorporate community perspectives, a term frequency-inverse document frequency-support vector machine (TF-IDF–SVM) classifier was applied to 1500 public comments, where SVM achieved the highest accuracy (0.80–0.96). The integrated approach improves ranking stability, reduces decision ambiguity, and strengthens alignment between expert judgment and community sentiment. This study contributes a transparent, participatory decision-support model that unifies MCGDM and sentiment analysis to enhance the effectiveness of sustainable GOS planning.
Co-Authors Bakti, Rizki Yusliana lia kamelia Muhammad Faisal Muhyiddin A.M Hayat Ninuk Wiliani Nurnawaty, Nurnawaty Ramli, Suzaimah Reni Haerani S. Kuba, Muhammad Syafa'at Sutisna, Nandang Syamsuri, Andi Makbul