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.

The Effect of Accounting Information System on the Decision-Making Process of Addis Ababa City Electric Utility’s

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One of the supporting information systems utilized in performing managerial tasks including planning, organizing, controlling, and decision-making for the better utilization of the resources available is Accounting Information Systems.  The main objective of this study was to determine the effect of Accounting Information Systems on the decision-making process in the case of Addis Ababa City Electric Utility related to inventory management, Internal control system, bill collection (sales,) and financial statements. The researcher used both primary and secondary data and used explanatory research methods. The researcher used a random sampling technique and distribute questionnaires to the Addis Ababa City Electric Utility staff and used Pearson correlation and linear multiple regression to check the relationship and effect between the variables respectively. The finding of this study showed that accounting information systems have a positive and significant effect on inventory management, financial statement, bill collection, and internal control system in the decision-making process. As a result, the researcher came to the conclusion that the accounting information system significantly and favorably influences the decision-making process. For better decision-making, the study recommends businesses employ accounting information systems.