Group Decision Support System to Determine Regional Development Priority Using the Item-Based Clustering Hybrid Method
Sri Setiyowati1, Sumiati2, Sutarti2, Andrianto Heri Wibowo3, Vidila Rosalina2 & Tb. Ai Munandar2 Show affiliations
- Univ. Mathla’ul Anwar, Indonesia
- Universitas Serang Raya, Indonesia
- Universitas Mathla’ul Anwar, Indonesia
Journal of Computer Science, Volume 15, Issue 4, pp. 511–518 · doi.org/10.3844/jcssp.2019.511.518
Abstract
Determination of regional development priorities is usually influenced by two factors, firstly the policy-making subjectivity (regional head) second to the results of the development data analysis. But both often do not go hand in hand because in fact subjectivity is more dominant than combining the two. The development of computational technology, especially in the area of decision support, provides space to solve various problems related to the decision making process. This study aims to develop a Group Decision Support System (GDSS) model for determining regional development priorities in the future. An alternative approach in the form of developing a GDSS model is carried out so that it can be used to determine regional development priorities that are able to combine analysis of data on development results and subjectivity of policy makers. It means, policy-enforcing subjectivity still exists but the results of development data analysis are also used. This model combines the GDSS concept, MVHAC cluster technique and Item-based Cluster Hybrid Method (ICHM) to accommodate joint decision making from each group decision maker. The results of the testing of the model developed against six regions in Banten Province show that there are three regions that must be prioritized in the future. Those are Pandeglang, Lebak and Kota Serang.
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Setiyowati, S., Sumiati, Sutarti, Wibowo, A. H., Rosalina, V. & Ai Munandar, T. (2019). Group Decision Support System to Determine Regional Development Priority Using the Item-Based Clustering Hybrid Method. Journal of Computer Science, 15(4), 511–518. https://doi.org/10.3844/jcssp.2019.511.518
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