Articles

An Exploratory Data Analysis (EDA) Approach for Analyzing Financial Statements in Pharmaceutical Companies Using Machine Learning

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This research investigates the use of Exploratory Data Analysis (EDA) and machine learning techniques to analyze financial statements (FSs) of pharmaceutical companies. The study focuses on three major Indonesian pharmaceutical companies: Kimia Farma, Kalbe Farma, and IndoFarma. By leveraging EDA, this study aims to uncover hidden patterns and insights within financial data, such as earnings per share (EPS), return on capital employed (ROCE), net profit margin, and inventory turnover ratio. Additionally, the study employs machine learning models, including Linear Regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree, to predict financial performance metrics and trends. The performance of these models is evaluated using metrics such as Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). Among the models tested, the Decision Tree model demonstrated the highest performance, indicating high accuracy and a strong fit to the data. These results highlight the potential of data-driven approaches in improving the operational efficiency and financial stability of healthcare organizations.

Do Firms Change the Working Capital Management Policy During The Covid-19 Pandemic? Case of Transportation & Logistics and Healthcare Industries in Indonesia

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This study explores the crucial role of working capital management in balancing profitability and risk for companies. Economic conditions and sector-specific fluctuations in GDP influence working capital decisions. The transportation and logistics industry faced challenges with reduced demand, while the healthcare industry dealt with increased demand and longer payment collection periods during the pandemic. Using panel data regression on healthcare and transportation companies listed on the Indonesia Stock Exchange from 2017 to 2021, the study examines the impact of working capital management on profitability. Findings show significant correlations between working capital components and company profitability in both sectors. Specifically, before the pandemic, Days Sales Outstanding (DSO) positively affected Return on Assets (ROA), while Working Capital Financing Policy (WCFP) had a negative impact. During the pandemic, DSO and Working Capital Investment Policy (WCIP) positively influenced ROA in the transportation sector, while WCFP negatively affected it. In the healthcare sector during the pandemic, both DSO and Days Inventory Outstanding (DIO) positively affected ROA. For Net Profit Margin (NPM), the significance of working capital variables changed during the pandemic in the transportation sector, with DSO negatively impacting NPM, while WCIP and WCFP had a positive effect. In the healthcare sector during the pandemic, WCIP positively correlated with NPM, while WCFP had a negative correlation. Effective working capital management is essential for companies to navigate economic fluctuations and ensure uninterrupted operations.