PERANCANGAN SISTEM PENGELOMPOKAN DAN REKOMENDASI SAHAM LQ45 DENGAN K-MEDOIDS, EXPONENTIAL MOVING AVERAGE DAN WEIGHTED PRODUCT - Chandra, Alvin; Mulyawan, Bagus; Perdana, Novario Jaya (Jurnal Ilmu Komputer dan Sistem Informasi, 2021)
Stock is an instrumentation that has the fundamentals of a company. Owning a share means owning the shares of the company. Shares can be traded on the Indonesian Stock Exchange by the entire public. The LQ45 stock grouping and recommendation application is a desktop-based application that aims to assist in making investment decisions in the Indonesian Capital Market. The application is designed using the Python programming language. The application applies the KMedoids Clustering method to group stocks and Exponential Moving Average along with Weighted Products to make recommendations or sort shares. Users can enter the desired share criteria and the application will recommend according to the input criteria from the user. Testing on this application is carried out by the BlackBox testing method, questionnaire, K-Medoids Algorithm Testing and the output results of the program. From the results of the black box testing, the application results can run according to plan. In testing the K-Medoids Algorithm, the results obtained that the number of clusters determined are in accordance with the number of 2 clusters using the elbow method. And in testing the output results of the program, the results obtained are the recommendation accuracy of 80.8%.