APPLICATION OF DATA MINING TO PREDICT VILLAGE STATUS BASED ON VILLAGE DEVELOPMENT INDEX IN KOTO MASJID VILLAGE
DOI:
https://doi.org/10.54973/abjcd.v6i1.613Keywords:
Village Development Index, data mining, classification, Decision Tree, Smart Village.Abstract
Data-based village development is a strategic approach to improving community welfare through more targeted planning. One of the key instruments in measuring village progress in Indonesia is the Village Development Index (Indeks Desa Membangun or IDM), which includes social, economic, and ecological dimensions. However, analytical utilization of IDM data remains low, especially in villages with limited resources and data literacy. This community service activity was conducted in Koto Masjid Village, Kampar Regency, with the aim of enhancing the capacity of village officials and youth organization (Karang Taruna) members to understand and process IDM data using classification methods in data mining. The implementation methods included theoretical training, hands-on workshops on classification algorithms (Decision Tree and Naive Bayes), data analysis simulations, and evaluation and mentoring sessions. The results showed an increase in participants' understanding from an average of 45% to 82% based on pre-test and post-test scores. In addition, the classification model developed by the participants achieved an accuracy rate of 87% in predicting village status. Final evaluations indicated that 95% of participants found the activity highly beneficial and expressed interest in learning more advanced data mining techniques. This activity not only transferred technical skills but also promoted a data-driven decision-making mindset at the village level. The implementation of classification methods based on IDM has proven to be an effective strategy in supporting the transformation towards independent and sustainable Smart Villages.
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