Sunandi, Wahyu (2019) Klasifikasi Penjurusan Sekolah Menengah Atas Menggunakan Metode Backpropagation Berbasis Website (Studi Kasus: SMA Negeri 1 Mlonggo). Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Major selection for high school students is the beginning of career choice in the future. This is because the majors in high school will deliver students to further study majors before finally students determine to choose jobs in the future. The advancement of technology, especially information technology has now been applied in the method of major selectoion for high school students with a Website-Based Application. The process of major selection is done for the concentration selection according to the talents and abilities of each student. Observations conducted by the author in the form of direct interviews with Counselling teachers at Mlonggo State Senior High School 1 obtain several things, such as long time major selections, system of major selection that has been given by the curriculum, student interest and student academic grade. Artificial neural network is an information processing system that has characteristics resembling human neural networks. The artificial neural network in this study uses a method namely Backpropagation (error propagation backward). This method is one of the artificial neural network algorithms that are often used in solving complex problems. This is possible because the network with this algorithm is trained using the guided learning method. Backpropagation consists of three layers, namely: input layer, hidden layer, and output layer. With artificial neural networks with 9 cell input, 9 hidden cell, 2 cell output and 41 test data, the study results in an accuracy of 70.73%. Keywords: High School Majors, Backpropagation, Artificial Neural Networks.
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 22 Nov 2019 08:04 |
| Last Modified: | 22 Nov 2019 08:04 |
| URI: | http://eprints.uty.ac.id/id/eprint/4384 |
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