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All Journal CIVED (Journal of Civil Engineering and Vocational Education) JURNAL KARYA TEKNIK SIPIL IPTEK Journal of Proceedings Series Jurnal Transportasi Jurnal Konstruksia Jurnal Optimasi Sistem Industri Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil Journal of Advanced Civil and Environmental Engineering Jurnal Vokasi Indonesia Transparansi Jurnal Ilmiah Ilmu Administrasi Journal of Information Systems and Informatics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Bulletin of Network Engineer and Informatics (BUFNETS) Jurnal Testing dan Implementasi Sistem Informasi
Mochamad Agung Wibowo
Departemen Teknik Sipil, Fakultas Teknik, Universitas Diponegoro
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Transportation Other

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Artificial Intelligence and Machine Learning for SDG-Oriented Decision Making in Public Governance: A Bibliometric Analysis and Systematic Literature Review Lorensius Anang Setiyo Waluyo; Mochamad Agung Wibowo; Ridwan Sanjaya
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.4021

Abstract

This study maps the development of literature on artificial intelligence (AI) and machine learning (ML) in public decision-making oriented toward achieving the Sustainable Development Goals (SDGs). A bibliometric analysis was conducted on 380 Scopus-indexed documents published between 2017 and 2026, while a focused systematic literature review was performed on 17 studies selected through PRISMA-based screening. Data were cleaned using OpenRefine and analyzed with VOSviewer and Bibliometrix to identify keyword networks, thematic trends, author productivity, country collaboration, and scientific development structures. The findings show that AI and ML are central themes in SDG-oriented decision-making research, strongly connected to decision support systems, public policy, sustainability, climate change, environmental sustainability, smart cities, energy, health, and public governance. Publication growth accelerated markedly after 2023, with India and China as dominant contributors, although international collaboration remains limited. The review also reveals major challenges related to explainability, including black-box algorithms, data bias, low transparency, weak data governance, limited institutional capacity, and unclear legal and ethical accountability. This study argues that AI/ML for SDGs must move beyond accuracy and efficiency toward explainable, auditable, trustworthy, and socially accountable decision support systems globally.
Vehicle Routing Problem (VRP) Approaches for Waste Collection Optimization: A Systematic Literature Review Munengsih Bunga; Mochamad Agung Wibowo; Sutikno
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 1 (2026): Maret
Publisher : Universitas Wahid Hasyim

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Abstract

An effective route is necessary because waste transport is an important part of the urban waste management system. The most popular technique is the Vehicle Routing Problem (VRP) to maximize fleet movement while reducing risk, time, cost, and energy. To identify developments in VRP models in the context of waste transportation, this study used a Systematic Literature Review (SLR), conducted in accordance with PRISMA guidelines, to review 96 articles. The SLR results indicate that VRP models have evolved from basic models such as CVRP and VRPTW to more constraint-rich models such as MTVRP, ARP, risk-aware VRP, EVRP, and multi-objective VRP. Hybrid and metaheuristic algorithms such as ALNS, GA, ACO, and SA have become the most popular in solving this problem due to their ability to handle large problem sizes and high operational complexity. Route planning can now utilize real-time data thanks to the integration of IoT, WSN, and GIS technologies. Overall, these results indicate that VRP research in waste transport is moving towards smarter, more adaptive, and sustainable approaches. These results also enable the development of more contextual models and algorithms in the future.
Design and Evaluation of a Decision Support System for Classifying Tourism Site Crowding and Recommending Governance Responses in Bunaken National Park Aditya Kalua; Mochamad Agung Wibowo; Luther Alexander Latumakulita
Jurnal Testing dan Implementasi Sistem Informasi Vol. 4 No. 1 (2026): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v4i1.2232

Abstract

Effective governance of marine protected areas (MPAs) requires reliable mechanisms to translate multidimensional ecological and social data into coordinated institutional action. Despite widespread adoption of carrying capacity frameworks, a significant "implementation gap" persists between theoretical conservation thresholds and operational decision-making at the site level. This study addresses that gap by designing, implementing, and evaluating a Decision Support System (DSS) artifact tailored for Bunaken National Park (BNP), Indonesia. Grounded in Design Science Research (DSR) principles, the artifact employs a deterministic, rule-based classification engine that processes four normalized input dimensions visitor density, social carrying capacity, infrastructure load, and governance readiness to compute a Composite Crowding Index (CCI). The CCI is mapped through an explicit IF-THEN rule engine to four crowding categories (Low, Moderate, High, Extreme), each linked to a validated governance action package. A deterministic rule-based approach was chosen over probabilistic or machine-learning alternatives to ensure full decision traceability, which is a non-negotiable requirement for public-sector governance. System robustness was evaluated through structured scenario testing across 140 logic-coverage cases, assessed against four criteria: output consistency (100%), expert rule alignment (97.8%), decision traceability (100%), and processing efficiency (<1.15 seconds per scenario). The artifact successfully automates the mapping of site-level crowding status to discrete, auditable governance actions. The theoretical contribution lies in formalizing subjective management reasoning into a transparent, reproducible DSS that bridges sustainability science and institutional practice in high-pressure marine tourism environments.
Arah Kebijakan Pengelolaan Risiko Proyek Kerjasama Pemerintah dan Badan Usaha (KPBU): (Policy Guidelines for Risk Management in Public-Private Partnership (PPP) Projects) Endah Murtiana; Mustafa Nahdi; Naniek Widayati; Mochamad Agung Wibowo; Rizal Zainuddin Tamin; Najid
Transparansi : Jurnal Ilmiah Ilmu Administrasi Vol. 9 No. 1: Juni 2026
Publisher : Institut Ilmu Sosial dan Manajemen STIAMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/9dqysd69

Abstract

Proyek Kerjasama Pemerintah dan Badan Usaha (KPBU) menjadi penting dan relevan dalam rangka untuk mendorong peran serta swasta dalam pembangunan infrastruktur di Indonesia secara massive. Kemampuan pemerintah untuk menyelenggarakan pembangunan infrasturktur dalam rangka memenuhi kebutuhan masyarakat harus melibatkan peran serta dari Badan Usaha Swasta agar percepatan terjadi dengan kualitas infrastruktur yang memadai. Penelitian ini bertujuan untuk memetakan kebijakan proyek KPBU di Indonesia agar masyarakat mengetahui pentingnya peran swasta dalam pembangunan infrastuktur di Indonesia. Melalui telaah literatur terdahulu penelitian ini akan membandingkan proyek KPBU solisated dan unsolisated di Indonesia dengan negara lain, selanjutnya penelitian ini akan memberikan pengetahuan baru tentang pentingnya pengembangan KPBU di Indonesia. Abstract The Public-Private Partnership (PPP) project is important and relevant to encourage the participation of the private sector in infrastructure development in Indonesia on a massive scale. The government's ability to organize infrastructure development to meet the needs of the community must involve the participation of Private Business Entities so that acceleration occurs with adequate infrastructure quality. This study aims to map the KPBU project policy in Indonesia so that the public knows the importance of the private sector's role in infrastructure development in Indonesia. Through a review of previous literature, this study will compare solicited and unsolicited in PPP projects in Indonesia with other countries, then this study will provide new knowledge about the importance of PPP development in Indonesia.
Co-Authors Aditya Kalua Aditya Kalua Aditya Lapu Kalua Ahmad Hilmi Saifunuha Akhlis Munazilin Andini Nugrahardani Arif Haidar Nur Shidqi Arif Hidayat Bagus Hario Setiadji Broto Sunaryo Eko Marsudi Utomo Ferry Hermawan Frida Kistiani Frida Kristiani Geofanny Dominica Sihaloho Hari Budieny Iqbal Setyo Jatmiko Jati Utomo Dwi Hatmoko Kusnawi Kusnawi Lorensius Anang Setiyo Waluyo Luther Alexander Latumakulita Luther Latumakulita Moammar Zachari Moh Nur Sholeh Munengsih Bunga Mustafa Nahdi Najid Naniek Utami Handayani Naniek Widayati Rama Ijon Turnip Rani Pranita Rezza Mahendra Putra Ridwan Sanjaya Riqi Radian Khasani Rizal Zainuddin Tamin Rizki Fatmawati Rizky Parlika Sari, Endah Murtiana Satria Sentik Herman Merukh Sriyana Sriyana Sutikno Syafrudin Syafrudin Undayani Cita Sari Wisard Widsli Kalengkongan Yoannes Romando Sipayung Yoga A. Harsoyo