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Journal : Jurnal Maritim Polimarin

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Prediksi Kelulusan Seleksi Mahasiswa Baru Jalur SBMPN Pada Politeknik Maritim Negeri Indonesia Menggunakan Jaringan Syaraf Tiruan Backpropagation Warsina Warsina; Fajarsari Kurniawan
Jurnal Maritim Polimarin Vol. 7 No. 1 (2021)
Publisher : PPPM Polimarin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (348.293 KB) | DOI: 10.52492/jmp.v7i1.11

Abstract

One of the selection routes for new student admissions at the Indonesian State Maritime Polytechnic (Polimarin) is the Joint Selection to Enter the State Polytechnic (SBMPN). Furthermore, the SBMPN selection results as the results of stage one tests and other specific tests which include interview, psychological, health, and fitness tests as stage two tests can predict the level of accuracy of passing from the required criteria. These criteria are used as variables to predict the graduation of prospective students on the SBMPN pathway conducted by Polimarin. The method used uses Backpropagation Artificial Neural Network with input variables, namely the average value of report cards from semester 1 to 5, interview scores, psychological test scores, health scores, and equality values. This system was developed with Mathlab software. Based on the results of testing the training data, the level of accuracy reaches 100% which can be classified as the best classification, with an accuracy value of 92.85 percent. This system is intended to help management predict the selection of the SBMPN route in the following year.
Co-Authors Warsina Warsina