Performance Analysis of the K-Medoids Algorithm in Clustering Able and Disabled Students at MAN 1 Panyabungan - Putri Augesti Lubis (Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal, 2024)
In implementing the Smart Indonesia Program (PIP), the problem faced at MAN 1 Panyabungan was that the school had difficulty in determining students who were entitled to receive the Smart Indonesia Program (PIP), this was due to the many criteria that had to be considered in determining aid recipients. The large amount of student data and the many variables used in determining recipients of the Smart Indonesia Program (PIP) have become an obstacle for MAN 1 Panyabungan. Classifying student data is very important because the process of determining scholarship recommendations involves various criteria that need to be considered and takes quite a long time, but the results do not necessarily provide the right and accurate decision. Implementing applications and systems can be a solution to speed up correct and fast decision making, and can provide the best results in selecting students according to the criteria set by the school. In grouping capable and incapable students, the K-Medoids algorithm is used. The criteria used in the data mining process are the average report card score, parents' occupation, income and number of parents' dependents.