Spare Part Selection for Storage in PLN Suku Cadang Warehouse Using Clustering Analysis
Keywords:
clustering, power plant, spare partsAbstract
PLN Suku Cadang (PLNSC) faces challenges in determining which spare parts should be stored in warehouses to support power plant operations. This study employs the k-Means clustering method to analyze historical data, in-cluding demand frequency, lead time, quantity, and cost. Using this method, spare parts are grouped into several clusters to identify storage priorities. The clustering results are further validated using specific criteria: high demand frequency, low lead time, high quantity, and low cost. This study demon-strates that the clustering method can help optimize inventory management, reduce downtime risks, and improve cost efficiency in storage.
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