PERANCANGAN APLIKASI PREDIKSI MASA STUDI MAHASISWA DENGAN METODE NAÏVE BAYES DAN C4.5

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Charles Yuliansen
Bagus Mulyawan
Novario Jaya Perdana

Abstract

In college studies each study period uses a semester system where each semester of study period will obtain a Grade Point Average (GPA) in which the GPA shows the value obtained during the study period in that semester. With the right calculation the GPA can be used as a long time determinant of a student's study period. This prediction application is made using the classification method. The data used is obtained legally from the faculty and is used to carry out the training process and test applications that have been made. For the development method use the test structure method with several tools and workmanship techniques such as flowcharts, context diagrams, and relationships between tables. The programming language used in making applications is PHP, Python, the database used is MySQL. The training and testing methods used in making the application are Naïve Bayes and C4.5. The results of system testing show that using 237 student data obtained that the C4.5 method is always superior compared to the Naïve Bayes method. Addition of sex variables did not change the accuracy significantly.

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References

Simon, S. and Trisnawarman, D., 2014. Aplikasi Prediksi Status Registrasi Mahasiswa Baru Menggunakan Metode Naïve Bayes dan Algoritma C4. 5. Jurnal Ilmu Komputer dan Sistem Informasi, 2(2), pp.216-219.

Kasmir dan Jakfar. Studi Kelayakan Bisnis, Edisi kedua,(Jakarta: Penerbit Kencana Prenada Media Group, 2007),h. 178

Noir Primadona Purba , Masa Studi dan batas waktu, http://www.unpad.ac.id/pembelajaran/evaluasi-hasil-belajar-dan-batas-waktu-studi/masa-studi-dan-batas-waktu/, 6 Maret 2019

.Administrasi akademik, Petunjuk Kegiatan Administasi Akademik & kegiatan Lainnya Tahun akademik 2018/2019, (Jakarta: UNTAR, 2016), hal. 12

Solichin, Achmad. Pemrograman web dengan PHP dan MySQL. Penerbit Budi Luhur, 2016.

Srinath, K. R. "Python–The Fastest Growing Programming Language." International Research Journal of Engineering and Technology (IRJET) Volume 4 (2017).

Visa, Sofia, et al. "Confusion Matrix-based Feature Selection." MAICS 710 (2011): 120-127.

Rohith Gandhi, Naïve Bayes Classifier, https://towardsdatascience.com/naive-bayes-classifier-81d512f50a7c, 6 Maret 2019

Amin, Rafik Khairul, and Yuliant Sibaroni. "Implementation of decision tree using C4. 5 algorithm in decision making of loan application by debtor (Case study: Bank pasar of Yogyakarta Special Region)." 2015 3rd International Conference on Information and Communication Technology (ICoICT). IEEE, 2015.