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Shallots are one of the most strategic horticultural commodities in Indonesia, with high demand and varying production levels across regions. Differences in productivity between areas often create challenges in managing distribution and formulating national food policies. This study aims to analyze shallot production data in Indonesia by applying the K-Means Clustering algorithm using Python. The production data were collected from official agricultural statistics publications, followed by preprocessing, normalization, and determination of the optimal number of clusters using the Elbow method and Silhouette Score. The clustering results show the formation of several groups representing regions with high, medium, and low production levels. Visualization of the clustering results reveals the distribution patterns of shallot production, which can serve as a basis for supporting policy formulation in the development of shallot production centers in Indonesia. Thus, the application of K-Means Clustering with Python proves to be an effective approach to provide clearer insights into regional production variations and can be utilized as an analytical tool to support decision-making in the agricultural sector.

This study aims to analyze the optimization of the role of Dandim 1301/Sangihe in handling the eruption of Mount Ruang as part of the implementation of the Indonesian Army’s (TNI AD) main duties in the field of Military Operations Other Than War (OMSP). The research was conducted in Sitaro Regency, North Sulawesi, using a qualitative approach with purposive sampling techniques. The informants consisted of personnel from Kodim 1301/Sangihe, BPBD staff, and community leaders. Data was collected through interviews, observations, and documentary studies. The results show that the role of Dandim is crucial in coordinating and mobilizing disaster response, but there are still challenges such as limited personnel, logistics, equipment, and weak inter-institutional coordination. The study concludes that optimization can be achieved through the development of a disaster risk map, strengthening inter-institutional collaboration, utilizing technology (drones), and conducting routine disaster training and simulations. These measures are expected to improve the effectiveness and speed of response in facing volcanic eruptions.