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All Journal POSITIF Jurnal Sains dan Informatika
Faisal, Mohammad Reza
P3M Politeknik Negeri Banjarmasin
Computer Science & IT Engineering Mathematics

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Klasifikasi Kelulusan Mahasiswa Menggunakan Algoritma Learning Vector Quantization Kartini, Dwi; Nugroho, Radityo Adi; Faisal, Mohammad Reza
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 3 No 2 (2017): POSITIF - Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v3i2.420

Abstract

Computer Science Study Program FMIPA ULM graduates dozens of undergraduate students every year. One of the assessment criteria for the accreditation of the study program is the assessment of the duration of the study of students who graduated on time. In this research will be done classification of graduation based on the status of student study year = timely and study length 4.5 years = not on time. Classification of students passing graduation based on IP semester I, Semester II, Semester III and Semester IV that have passed. If a system can classify students' graduation as a predictor of the duration of a student study, it is expected to be a recommendation for the Academic Advisors lecturers giving advice to students who are detected in the timely graduation possibilities so that Drop Out (DO) prevention measures may be taken earlier. Accuracy results are in accordance with the test data of 70% by using α = 0.5, decrement alfa 0.35 and maxepoch = 500.
Teknik Bagging Dan Boosting Pada Algoritma CART Untuk Klasifikasi Masa Studi Mahasiswa Arrahimi, Ahmad Rusadi; Ihsan, Muhammad Khairi; Kartini, Dwi; Faisal, Mohammad Reza; Indriani, Fatma
Jurnal Sains dan Informatika Vol 5 No 1 (2019): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (626.512 KB) | DOI: 10.34128/jsi.v5i1.171

Abstract

Undergraduate Students data in academic information systems always increases every year. Data collected can be processed using data mining to gain new knowledge. The author tries to mine undergraduate students data to classify the study period on time or not on time. The data is analyzed using CART with bagging techniqu, and CART with boosting technique. The classification results using 49 testing data, in the CART algorithm with bagging techniques 13 data (26.531%) entered into the classification on time and 36 data (73.469%) entered into the classification not on time. In the CART algorithm with boosting technique 16 data (32,653%) entered into the classification on time and 33 data (67,347%) entered into the classification not on time. The accuracy value of the classification of study period of undergraduate students using the CART algorithm is 79.592%, the CART algorithm with bagging technique is 81.633%, and the CART algorithm with boosting technique is 87.755%. In this study, the CART algorithm with boosting technique has the best accuracy value.
Co-Authors Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Dwi Kartini, Dwi Fatma Indriani, Fatma Ihsan, Muhammad Khairi Radityo Adi Nugroho