Abstract

This research examines the use of agricultural technology by millennial farmers in South Sulawesi Province by applying the Density-Based Spatial Clustering Algorithm with Noise (DBSCAN) to the agricultural census data of South Sulawesi Province Phase 1 in 2023. The secondary data used includes the number of millennial farmers aged 19-39 who use or do not use digital technology, divided by district/city and gender. The analysis process begins with preprocessing to prepare the data, followed by clustering using the DBSCAN algorithm, determining the optimal values for the Eps and minPts parameters, and evaluating the quality of the formed clusters using the silhouette coefficient and elbow method. The results of the study indicate that the combination of Eps value of 1.000 and minPts value of 7 produces optimal clustering with 2 clusters formed and 92 data points clustered, while 4 other data points are considered as noise. Evaluation using the silhouette coefficient and elbow method also indicates that the optimal data grouping is k=2.

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