K-Means clustering with Decision Support System using SAW: Determining thesis topic

Abstract

Thesis is an essential requirement for students to graduate. Students choose thesis topic according to their interests. In fact, many students choose inappropriate topic for their thesis and cause their thesis quality are bad. One of ways to solve the problem is to develop information system in form of Decision Support System (DSS). DSS needs data modeling and process to generate alternative decisions. Data modeling is in form of clustering using K-Means. This process generates clusters and weights to each topic. Weight is used to generate alternative decisions using Simple Additive Weighting Method. Combination K-Means and SAW can generate calculation fast to produce alternative decisions. This solution to support topic selection is excepted to contribute choosing thesis topic according to students ability.