Revitalization of Jakarta SMEs through Digital Transformation: Inventory Prediction with K-NN Algorithm in SmartOkianStock Application

Small and Medium Enterprises (SMEs) are the backbone of Jakarta’s economy and make a significant contribution to Indonesia’s overall economy. However, SMEs often face various challenges that hinder their growth and productivity. These challenges include limited access to funding, lack of market intelligence, and inefficiencies in operational processes. Additionally, poorly organized inventory management hampers SMEs’ ability to meet market demand quickly and effectively. This study aims to understand the role of Digital Transformation and the application of Artificial Intelligence (AI) in enhancing SME performance, focusing on a case study of a food and beverage (F&B) SME named Okian Essentials. The research proposes a Forecasting method using the K-Nearest Neighbor (K-NN) algorithm applied in the SmartOkianStock sales application to predict products, sizes, packaging types, and the quantity of stock that can be produced in the next period. Reference data for this study is derived from 734 transactions over the past 3 months, from March to May 2024. The research findings indicate that integrating AI technology, particularly in inventory management and sales data analysis, can help SMEs improve operational efficiency and competitiveness in the market. This study contributes to expanding understanding of the role of AI technology in supporting growth and sustainability of SMEs in the digital era.