Mapping of Product Sales Potential Based on Brands in The East Kalimantan Region using Hybrid Analytical Framework - Gaffar, Achmad F O, Mr; Mulyanto, Mulyanto, Mr; Putra, Arief BW, Mr; Sumadi, Muhammad Taufiq, Mr; Gaffar, Emmilya Umma Aziza (Knowledge Engineering and Data Science, 2025)
In geographically dispersed markets, operational costs should be reflected in sales planning to support accurate performance evaluation. However, such considerations are often neglected in practice. This study proposes a hybrid analytical framework to map brand-based product sales potential, with and without operational cost consideration, using historical sales data from PT Karya Inti Total Anugerah (PT KITA) in East Kalimantan. The framework integrates spatial, statistical, and machine learning techniques. Principal Component Analysis (PCA) is used to reduce the dimensionality of variables related to travel distance, total sales, and units sold, where travel distance represents the primary contributor to operational costs. K-Means Clustering is then applied to group sales potential, with the optimal number of clusters determined using the Elbow Method and validated by the Silhouette Score. Two sales potential scenarios are evaluated: with Weighted Operational Cost (WOC) and without WOC under a fixed pricing assumption. The results show notable differences between the two scenarios. With WOC, overall sales potential is predominantly Medium (64.84%), whereas without WOC it is predominantly High (51.39%). Several districts, including Berau, East Kutai, and Balikpapan, remain consistently high-potential areas, particularly for Dewalt and Stanley products. These findings highlight the importance of incorporating operational cost considerations into data-driven sales potential mapping.