Implementation of the Agglomerative Hierarchical Clustering Method in Ordering Hijab Products
DOI:
10.33395/sinkron.v8i4.14156Keywords:
Agglomerative Hierarchical; Clustering; Data Mining; Hijab; Sales Stock ManagementAbstract
The ever-evolving internet technology has an impact on various sectors, including the hijab business, where the demand for hijab products is increasing through online transactions. This research was conducted at the Kinan Hijab Store in Kota Pinang, North Sumatra, with the aim of optimizing the management of hijab product stock. The problem faced is the imbalance in the stock of hijab products, where some hijab products have excess stock that are less in demand while popular hijab products often experience a shortage of stock. To solve this problem, the Agglomerative Hierarchical Clustering method is used to group hijab products based on sales data, product type, and price. This study uses hijab sales data from May to July 2024. After the clustering process, hijab products are grouped into two categories: "Popular" and "Less Desirable". The "Popular" category includes 190 products, while the "Less Desirable" category includes 983 products. Product stock in the "Popular" category will be increased by 50% of the average sales, while stock in the "Less Desirable" category will be reduced by 25%. the effectiveness of the Agglomerative Hierarchical Clustering (AHC) method in stock planning and management by showing that it improved the inventory allocation based on customer demand patterns. The clustering method categorized hijabs into two main groups: "Popular" and "Less Preferred", based on key sales metrics such as quantity sold, price, and total sales. The implementation of the stock plan is carried out based on the sales pattern of each hijab category. Overall, the application of this method not only helps stores in understanding customer purchasing patterns but also optimizes product availability, which can ultimately increase customer satisfaction.
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