Based on data from BPS (Statistics Indonesia) for 2019-2021, the agricultural sector in Indonesia dominated employment and attracted investment interest from various parties. This study analyzes the impact of fundamental analysis and macroeconomic variables on the fluctuations in stock prices of agricultural sector companies from 2019 to 2023. The aim is to examine the effects of Return on Assets (ROA), Price-Earnings Ratio (PER), Debt to Equity Ratio (DER), and Earnings Price Ratio (EPR) on the stock price movements of agricultural sector companies listed on the Indonesia Stock Exchange (IDX). The study employs a descriptive analysis method, involving the collection, organization, and analysis of data to accurately depict the investigated issue. Data collection was conducted at the IDX from 2019 to 2023 through library research methods, using secondary data in the form of financial reports of agricultural sector companies available on www.idx.co.id. The study utilizes a simple regression analysis model with Eviews 6.0 software to process statistical and econometric data. The panel data combines time series and cross-section data, analyzed using fixed effect and random effect approaches to estimate the regression model. Estimation methods include pooled regression/pooled least squares, assuming constant coefficients for each time and space. The research results indicate that the LSDV/FEM panel regression model is the best, with variables such as DER, Earnings Per Share (EPS), PER, ROA, world oil prices, and the rupiah exchange rate collectively having a significant impact on stock prices in the agricultural sector. Additionally, classical assumption analysis shows that the data is stationary, normally distributed, free from multicollinearity, heteroscedasticity, and autocorrelation. The managerial implication of these findings is that investors should consider purchasing stocks in the agricultural sector, taking into account fundamental conditions, macroeconomic factors, and technical analysis.
Read full abstract