Abstract

The Faculty of Engineering, University of Singaperbangsa Karawang (Unsika) was established in 1995, one of which is the S1 Industrial Engineering (IT) Study Program, officially registered in 1996. Currently, the faculty is trying to achieve Superior Accreditation or A. The number of applicants for the Industrial Engineering Study Program will increase in 2023, reaching 891 prospective students through the SNBT route, but the capacity can only accommodate 56 people. However, it is in demand as the 4th out of 29 study programs at Unsika. The increase in the number of students is not in line with the on-time graduation rate. This study aims to identify the results of grouping students of the Industrial Engineering Study Program (S1) using the 5C-4C (Knowledge Conversion) process and then implement the relationship with learning activities for the 2017, 2018 and 2019 batches. Next, the data is transformed into information by using the 5C knowledge conversion method: contextualization, categorization, calculation, correction, and condensing. In order to build a program that increases the percentage of students who graduate on time, this information is transformed into knowledge utilizing the 4C knowledge conversion method: comparison, consequence, connections, and conversation. In this study, the population focus is on students of the Industrial Engineering Study Program from three batches, namely 2014, 2015, and 2016. The results of grouping Industrial Engineering students using the 5C process provide a deep understanding of the characteristics and factors that affect learning achievement. This provides a solid foundation for designing appropriate programs to increase the on-time graduation rate.

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