RANCANG BANGUN SISTEM MANAJEMEN STOCK OPNAME PADA UMKM HEERALAND DENGAN METODE PERAMALAN TIME SERIES

HeeraLand is a micro, small, and medium enterprise (MSME) engaged in agriculture, particularly in the cultivation and distribution of fresh vegetables. In its operations, inventory management of agricultural materials such as fertilizers, plant nutrients, and harvested products is still carried out manually, leading to potential issues such as data inaccuracies, stock shortages, or overstocking. This research aims to design and develop a stock opname management system that assists MSME operators in recording, monitoring, and forecasting stock needs and availability more efficiently. The system is built using the Python programming language with the Streamlit framework and implements time series forecasting methods, specifically Exponential Smoothing and Prophet, to predict the demand for supplies and products based on historical data. The main features of the system include recording stock-in and stock-out transactions, visualizing weekly stock trends, and forecasting future stock requirements. Testing results show that the system is capable of producing demand forecasts with good accuracy and supports decision-making in stock control. This system is expected to improve operational efficiency at HeeraLand MSME and help prevent shortages or surpluses of agricultural supplies.
Keywords: MSME, Stock Opname, Agriculture, Time Series, Exponential Smoothingt, Streamlit