CLASSIFICATION ANALYSIS OF TIMELINESS OF ANNUAL REPORTS USING BINARY LOGISTIC REGRESSION AND RANDOM FOREST - Erna Hayati (Sean Institute, 2023)
The timeliness of the company in publishing the annual report is one of the indicators that investors consider in assessing the company. Much important information contained in the company's financial statements is needed by investors as a basis for making investment decisions. Therefore, predictions about whether or not a company's financial reporting is timely is an important topic to help investors or other parties who need information in financial reports. In this study, the binary logistic regression method and the random forest algorithm are used as a means of classifying companies going public on the Indonesia Stock Exchange (IDX) based on timeliness in submitting their annual financial reports. The results showed that the random forest method is superior to binary logistic regression in classifying companies according to timeliness in reporting annual reports on the IDX.