Peramalan Jumlah Peserta OJT di PT.POMI Menggunakan ARIMA Box-Jenkins dan Radial Basis Function Neural Network
Submission Date: 2021-08-04 20:03:42
Accepted Date: 2022-02-27 00:00:00
Abstract
On the Job Training (OJT) merupakan pelatihan dimana siswa maupun mahasiswa mempelajari suatu pekerjaan yang sesuai dengan bidangnya di perusahaan. PT.POMI merupakan salah satu perusahaan swasta yang bergerak di bidang Pembangkit Listrik Tenaga Uap (PLTU). PT.POMI memberi peluang bagi siswa maupun mahasiswa untuk melakukan OJT, tetapi tidak bisa menerima semua siswa maupun mahasiwa yang mendaftar. Oleh karena itu perlu dilakukan sebuah analisis peramalan untuk meramalkan jumlah peserta OJT di PT.POMI, yaitu menggunakan metode ARIMA Box-Jenkins dan Radial Basis Function Neural Network (RBFNN). Data yang digunakan adalah jumlah peserta OJT pada Bulan Januari 2010 hingga Desember 2020. Hasil analisis menunjukkan bahwa model ARIMA terbaik yaitu ARIMA (3,1,0) yang memiliki nilai MAPE sebesar 42,741 dan pada RBFNN memiliki nilai MAPE sebesar 41,239. Sehingga dapat disimpulkan bahwa RBFNN mampu menghasilkan ramalan jumlah peserta OJT lebih baik daripada model ARIMA.
Keywords
ARIMA; Peramalan; PT.POMI; RBFNN
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