The Clustering of Ranting Muhammadiyah Using the K-MODES Algorithm
DOI:
https://doi.org/10.56873/jitu.8.2.6066Keywords:
Clustering, Clusters, Elbow method, K-Modes, Sub-branch or Ranting MuhammadiyahAbstract
Research on Muhammadiyah often focuses on its preaching models, responses to various conditions, and strategies in proselytization or resource management, but there is limited exploration of the Muhammadiyah organization itself. Specifically, the condition of Pimpinan Ranting Muhammadiyah (The Leader of Muhammadiyah Sub-Branch or PRM) as the lowest organizational structure, is seldom addressed. Currently, the LPCR utilizes SICARA to categorize organizations based on scores reflecting routine activities, yet it does not map these organizations based on similar potential. Thus, there is a need for a method to group these organizations based on a condition mapping to facilitate targeted revitalization efforts. This study aims to cluster PRM based on the Branch and Sub-branch Information System (Sistem Informasi Cabang dan Ranting or SICARA) questionnaire responses. Given that the SICARA questionnaire data is categorical, the K-MODES method was chosen for clustering. The optimal number of clusters was determined using the elbow method. The resulting clusters, derived using the elbow method, there are eight clusters, each exhibiting distinct characteristics.
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