Analisa Estimasi Penyeleksian Dosen Menggunakan Metode Backpropagation (Studi Kasus STMIK Amik Riau)

Debi Setiawan

Sari


Abstract- The purpose of this study was to estimate the number of lecturers who will be selected at the end of the year. Selection of lecturers is a way to determine the productivity of lecturers. In Act No. 14 of 2005, article 67, explained that an institution can undertake unilateral termination respectfully, when it ended joint working relationship between lecturers and education providers. At private colleges, the trigger of the selection of lecturers due to the productivity and the number of students. If the number of students is insufficient faculty ratio, while increasing productivity and excellent faculty, it still will do the selection of lecturers. The problem that arises is the imbalance for lecturers who have improved performance. It is necessary for analysis of estimates in the process of selecting lecturers, lecturers and institutions in order to be able to take a stand to solve this problem. Estimation using the design pattern of artificial neural networks (ANN) and methods of propagation, with an error rate of 0.5%. Variables that will be used is the amount of students majoring in IT (Computer Science), MI (Management Information) on campus STMIK Amik Riau, the number of Lecturer (MI and TI), and the final value of faculty productivity. These five variables will be processed on the system of selecting lecturers analysis using backpropagation method, so that the results to be obtained is the number of lecturers who will be affected by the selection of lecturers on campus STMIK Amik Riau.


Kata Kunci


Estimation, Selection Lecture, Backpropagation, Artificial intelligence

Teks Lengkap:

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Referensi


I. Fithrantyo, “Start Download ­ View PDF,” 2016.

B. Setya and M. Kom, “MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING PADA PTPN XII PERKEBUNAN MALANGSARI,” no. 1110651133.

zumrotus Sya’diyah, “Peramalan Jumlah Kendaraan di DKI Jakarta dengan Jaringan Backpropagation,” Statew. Agric. L. Use Baseline 2015, vol. 1, 2015.

Sutojo, Kecerdasan Buatan. Yogyakarta: Andi, 2011.

T. B. Hotmartua, “Implementasi jaringan saraf tiruan untuk memprediksi tingkat pertumbuhan penduduk menggunakan metode back propagation,” pp. 5–9, 2013.

Andrijasa.M.F and Mistianingsih, “Jumlah Pengangguran di Provinsi Kalimantan Timur Dengan Menggunakan Algoritma Pembelajaran Backpropagation,” J. Inform. Mulawarman, vol. 5, no. 1, 2010.




DOI: https://doi.org/10.25077/TEKNOSI.v2i3.2016.129-148

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Alamat Redaksi :
Jurusan Sistem Informasi, Fakultas Teknologi Informasi
Universitas Andalas
Kampus Limau Manis, Padang 25163, Sumatera Barat

email: teknosi@fti.unand.ac.id

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Creative Commons License
This work by si.fti.unand.ac.id is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.