Integration of the Hybrid Decision Support System and Machine Learning Algorithm to Determine Government Assistance Recipients: A Case Study in the Indonesian Funding Program

  • Indra Rusyadi Adiwijaya Institut Teknologi Bandung
  • Sapto Wahyu Indratno Institut Teknologi Bandung https://orcid.org/0000-0003-0739-5757
  • Manahan Siallagan Institut Teknologi Bandung
  • Agus Widodo National Research and Innovation Agency Indonesia
  • Eka Gandara National Research and Innovation Agency Indonesia
Keywords: AHP, DSS, Feature Selection, Machine Learning, Logistic Regression, MCDM, SAW

Abstract

The Indonesian government provides incentives to facilitate community development through various funding programs to improve the economy and restore the national economy. However, there were many obstacles in determining the proper target beneficiaries. This study aims to assist decision-makers in determining targeted and accountable beneficiary candidates. In this study, a hybrid Analytical Hierarchy Process (AHP) method with Simple Additive Weighting (SAW) was used and integrated with machine learning modeling using Logistic Regression (LR). The AHP approach is used to determine the weight of each criterion, and the SAW method is used to sort out each available alternative with the help of an expert team's assessment. Instead, the LR method is used for the predictive analysis and classification of the resulting data.

Author Biographies

Indra Rusyadi Adiwijaya, Institut Teknologi Bandung

Indra Rusyadi is a Master's student in computational science at the Bandung Institute of Technology, Indonesia. He received his bachelor's degree in Computer Science from Bogor Agricultural Institute, Indonesia. He also works as an engineer in a government agency at the National Research and Innovation Agency. His areas of research interest include data science, innovation and technology management, Business Intelligence, Decision Management, Technology Transfer, Technology Commercialization, Strategic Decision Making

Sapto Wahyu Indratno, Institut Teknologi Bandung

Sapto Wahyu Indratno is an Associate Professor of Mathematics and Statistics at the Bandung Institute of Technology, Indonesia. He received his Ph.D. in Mathematics at Kansas State University, United States of America. He received his bachelor's degree in Mathematics at the Bandung Institute of Technology, Indonesia, and his M.Sc in Mathematics at the University of Twente, The Netherlands. His area of research interest is mathematics and statistics. He has published more than 30 articles in various national and international journals and conferences. He has more than 20 years of teaching and research experience.

Manahan Siallagan, Institut Teknologi Bandung

Manahan Siallagan is currently a lecturer at the School of Business and Management Institute of Technology. He graduated from Mathematic, InstitutTeknologi Bandung in 1998. He got master degree from electrical engineering, InstitutTeknologi Bandung in 2003. He continued his study at Tokyo Institute of Technology and got both of Master and Doctoral degree in computational intelligent and systems science in 2013. Joined the School of Business and Management (SBM) – ITB as a full-time tutor in 2007 and as a full time lecturer after he received a PhD from Tokyo Institute of Technology, Japan in 2014. His experience as a lecturer in private university since 2000, as a research assistant and full time tutor at decision making and strategic negotiation of research interest group since 2005. There are some in several international journals, such as Systems Research and Behavioral Science, Evolutionary and Institutional Economics Review, and Frontiers in Psychological and Behavioral Science. There are some books chapters in Springer edition. His research interest social simulation, decision science and negotiation, system thinking and agent based modeling.

Agus Widodo, National Research and Innovation Agency Indonesia

Agus Widodo is an associate engineer at a government agency. He received his doctorate from the University of Indonesia in Computer Science, an MSc from Newcastle University, UK, in Computer Science, and a bachelor's degree from Louisiana State University, USA, in Computer Science. His research interests include technology auditing, Big Data, Machine Learning, and Technology Forecasting. He also teaches at a private university in Indonesia. He has more than ten research articles published in various well-known journals and conferences.

Eka Gandara, National Research and Innovation Agency Indonesia

Eka Gandara is currently working at the National Research and Innovation Agency, coordinating the implementation of utilizing research and innovation in society. Obtained a master's degree from Sriwijaya University Palembang public policy and a bachelor's degree from the Agricultural Institute of Bogor, Indonesia, fisheries. He is active in developing rural communities through innovation activities. He is also interested in developing the rural economy and Small and Medium Enterprises (SMEs) and actively conducts surveillance programs for SMEs. His research interests include agriculture and fisheries, appropriate technology, decision-making, and negotiation science, technology dissemination, and technology commercialization.

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Published
2023-06-30
How to Cite
[1]
Adiwijaya, I., Indratno, S., Siallagan, M., Widodo, A. and Gandara, E. 2023. Integration of the Hybrid Decision Support System and Machine Learning Algorithm to Determine Government Assistance Recipients: A Case Study in the Indonesian Funding Program. MENDEL. 29, 1 (Jun. 2023), 15-24. DOI:https://doi.org/10.13164/mendel.2023.1.015.
Section
Research articles