The Use of Text Mining to Investigate Undergraduate Research Topic Clusters from 2015 to 2019

Abstract

This study investigated the clusters of research topics written by undergraduate students of Informatics Dept., Satya Wacana Christian University (SWCU) from 2015 to 2019 using text mining techniques. Eight hundred and twenty-seven (827) final year project (FYP) reports' abstracts were retrieved from the University Library database. Text-mining techniques were used for identifying topics of these reports, and developed a hierarchal connection among these topics. Student reports were grouped into two domains with four groups containing nine clusters based on abstracts analysis. The clusters obtained are web & mobile applications, desktop applications, network security, network infrastructure, random generators, implementation of web service-based cryptography, cryptography in institutions, general block chippers, and block chipper with pattern. Distributions of the research topics were discussed in relation to Friedman's tower of achievement, and its implications on the curriculum.