Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity

Abstract

Indonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative.

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Clustering Car Sales by Brands in R Language: The Example of Türkiye

“…Öğelerin ait oldukları küme artık değişmeyene veya en büyük işlem yenileme sayısına ulaşılana kadar 2. ve 3. Adımlar tekrarlanmaktadır (Awangga, 2019).…”