Pengelompokkan Profil Work Readiness Mahasiswa Teknik Industri Universitas Telkom Menggunakan Data Mining Berbasis Algoritma K-Means Clustering

This study aims to formulate a group of student work readiness profiles. Based on this profile, students' readiness to work will be identified. Grouping is done using data mining based on the k-means clustering algorithm. The work readiness profile group consists of student skills or abilities based on Critical Thinking/Problem Solving, Oral Communications, Written Communications, Teamwork/Collaboration, Diversity, Information Technology Application, Leadership, Lifelong Learning/Self Direction, and Professionalism / Work Ethics. The case study of grouping the profile of work readiness of students is carried out in the Industrial Engineering Study Program of Telkom University with the number of respondents 191 students in the class of 2014 who are currently taking level IV lectures. Based on the results of grouping by dividing into 9 clusters, it was identified that students who met the criteria as students were ready to succeed in work in cluster 7. The number of students in cluster 7 was 50 students with good academic skills, but less active in student activities in the field of reasoning and culture, while the work readiness tends to be very good. The highest work readiness score for cluster 7 is in Lifelong Learning/Self Direction and Teamwork/Collaboration capabilities. Oral Communications, and Leadership which are the benchmarks of student readiness in a career. Further research can be done by identifying groups of work readiness profiles for students at various levels so that they can be used as a reference for designing programs to improve work readiness that varies for each level.