Classification Academic Data using Machine Learning for Decision Making Process

Authors

  • Elin Haerani Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Fadhilah Syafria Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Fitra Lestari Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Novriyanto Novriyanto Universitas Islam Negeri Sultan Syarif Kasim Riau
  • Ismail Marzuki Interdigital

DOI:

https://doi.org/10.37385/jaets.v4i2.1983

Keywords:

Data science, Decision Tree, Graduate on Time, Machine Learning

Abstract

One of the qualities of higher education is determined by the success rate of student learning. Assessment of student success rates is based on student graduation on time. Sultan Syarif Kasim State Islamic University Riau is one of the state universities in Riau, with a total of 30,000 students. Of all the active students, there are some who are not. Students who are not active in this case will affect the timeliness of their graduation. The university always evaluates the performance of its students to find out information related to the factors that cause students to become inactive so that they are more likely to drop out and what data affect students being able to graduate on time. The evaluation results are stored in an academic database so that the data can later be used as supporting data when making decisions by the university. This research used data science concepts to explore and extract data sets from databases to find models or patterns, as well as new insights that can be used as tools for decision-making. After the data was explored, machine learning concepts were used to identify and classify the data. The method used was the Decision Tree Method. The results of the study found that these two concepts can provide the expected results. Based on the test results, it is known that the attribute that influences the success of student studies is the grade point average (GPA), where the accuracy of the maximum recognition rate is 88.19%.

Keywords : Data science; Decision Tree; Graduate on Time; Machine Learning;

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Author Biographies

Elin Haerani, Universitas Islam Negeri Sultan Syarif Kasim Riau

 

 

Fadhilah Syafria, Universitas Islam Negeri Sultan Syarif Kasim Riau

 

 

Fitra Lestari, Universitas Islam Negeri Sultan Syarif Kasim Riau

 

 

 

Novriyanto Novriyanto, Universitas Islam Negeri Sultan Syarif Kasim Riau

 

 

 

Ismail Marzuki, Interdigital

 

 

 

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Published

2023-06-05

How to Cite

Haerani, E., Syafria, F., Lestari, F., Novriyanto, N., & Marzuki, I. (2023). Classification Academic Data using Machine Learning for Decision Making Process . Journal of Applied Engineering and Technological Science (JAETS), 4(2), 955–968. https://doi.org/10.37385/jaets.v4i2.1983