Combination of Composite Performance Index and Rank Order Centroid Methods for Selecting Financial Applications - Gomes Soares, Teotino; Rusliyawati, Rusliyawati; Trianto, Joko; Candra Widyawati, Apri (STMIK Budi Darma, 2024)
In the current digital era, the selection of an effective financial management application poses a significant challenge due to the extensive variety of available options. Manual selection processes are often time-consuming and labor-intensive, requiring users to individually research and compare different applications based on limited and sometimes incomplete information. This research endeavors to develop a Decision Support System (DSS) employing a combined approach of the Composite Performance Index (CPI) and Rank Order Centroid (ROC) methods to streamline the selection of financial management applications. The CPI method integrates various performance dimensions into a single comprehensive index, facilitating a holistic evaluation of each candidate. Simultaneously, the ROC method is used to assign weights based on the ranking of criteria, thereby reducing subjectivity in determining the importance of each criterion. This research has resulted in a DSS capable of managing criteria and alternative data, evaluating alternatives, performing automatic CPI calculations, and displaying the optimal choices in a ranked format. In the conducted case study, Goodbudget achieved the highest composite index score of 114.42, followed by Money Lover with a score of 112.97, TrackWallet scoring 112.75, Budget Planner with 105.22, and Bluecoins with 100. The results from the DSS matched the manual calculations, demonstrating the reliability of the system's output. Black-box testing has demonstrated that all test cases have been executed successfully and have met the predefined functions.