Implementasi Sistem Peramalan Harga Saham Indeks LQ45 Menggunakan Algoritma Prophet dan Fitur Moving Average

Abstract

Volatile stock price movements in the LQ45 Index often make it difficult for investors to make investment decisions. Previous research on stock price forecasting has generally focused on static analysis of a single issuer in isolation, making it less efficient for broad market monitoring. This study develops a web-based multi-issuer forecasting system using the Streamlit framework to centrally project the price movements of the 45 constituents of the LQ45 Index. This forecasting model integrates technical indicators—moving averages (MA-5, MA-10, and MA-20)—as external regressors in the Facebook Prophet algorithm to capture momentum signals not detected by the base model. The dataset used includes daily trading history covering a maximum period of the last 5 years, adjusted according to the availability of historical data for each issuer. A strict chronological split and a rolling cross-validation mechanism were used to keep the testing honest and stop data from leaking during model validation. Test results show an average MAPE of 7.54% for a 7-day forecast horizon, 7.47% for 14 days, and 16.63% for 30 days. Overall, the system recorded an average MAPE of 10.57%, which was converted into a forecasting performance percentage of approximately 89.43% to make it easier for investors to interpret as an investment decision-making tool.