Using Supervised Machine Learning to Predict Sales in Marketplaces: Case study Predicting Sales of Padimas Bread in Marketplaces in Indonesia

Abstract

This project intends to apply supervised machine learning to anticipate sales of Padimas bread in marketplaces in Indonesia, with an emphasis on evaluating sales data to gain more profits and predict future income. Data from the Shopee, Tokopedia, and TikTok markets in 2023 was analyzed, employing techniques like exploratory sales data analysis and machine learning. The analysis findings encompass the top-selling products, the highest sales figures, regions with the most substantial sales, overall market sales, sales patterns, and revenue forecasts. The primary discoveries encompass the widespread appeal of chocolate toast, the most substantial sales of banana chocolate toast in West Java, and Shopee as the marketplace with the most significant sales and revenue. Sales trends exhibit a pattern of oscillation around an average value, but income from sales demonstrates a downward tendency until the 30th day. The strategic ramifications of this analysis encompass augmenting the production of sought-after goods, amplifying sales in specific regions, and delving into prospective marketplaces.