Analysis Comparison of Data Mining Algorithm for Prediction Student Graduation Target
Rachmadita Andreswari, Muhammad Azani Hasibuan, Dela Youlina Putri, Qalbinuril Setyani
Available Online March 2019.
- https://doi.org/10.2991/icoiese-18.2019.58How to use a DOI?
- data mining, education, c4.5, fuzzy AHP, decision support system.
- The main objective of a higher education institution is to provide quality education for its students. The most important indicator to measure the quality of higher education performance is the percentage of student graduation on time. However, not all student can successfully have completed their studies during the four years of normal study period where it became problems for academic planners. So, it can affect to the study program accreditation assessment. In this study, C4.5 algorithms and fuzzy AHP are used to predict the number of students graduating on time. An analysis has conducted on how students can graduate on time and plan strategies for groups of students who are likely not to graduate on time. Furthermore, a comparative analysis of the algorithms that have been implemented which will provide more precise and accurate results. Data processing is carried out using the Rapidminer application. The results of the student graduation target analysis were found that the main factor of graduation on time using FAHP was the number of repeating courses (do not pass courses), while in C4.5 it was caused by GPA level 2. Both algorithms had a good level of accuracy, where FAHP and C4.5 were 100% and 82.24% respectively. This research can be used as a reference basis for supporting academic planners in making the right decisions for student groups produced so that all students can graduate on time.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Rachmadita Andreswari AU - Muhammad Azani Hasibuan AU - Dela Youlina Putri AU - Qalbinuril Setyani PY - 2019/03 DA - 2019/03 TI - Analysis Comparison of Data Mining Algorithm for Prediction Student Graduation Target BT - 2018 International Conference on Industrial Enterprise and System Engineering (ICoIESE 2018) PB - Atlantis Press SP - 328 EP - 333 SN - 2589-4943 UR - https://doi.org/10.2991/icoiese-18.2019.58 DO - https://doi.org/10.2991/icoiese-18.2019.58 ID - Andreswari2019/03 ER -