Mathematical Model of Growth in The Number of Students in NTB Using Newton-Gregory Polynomial Method

  • Habib Ratu Perwira Negara Universitas Bumigora Mataram
  • Malik Ibrahim Universita Nahdlatul Ulama NTB
  • Kiki Riska Ayu Kurniawati Universitas Islam Negeri (UIN) Mataram
Keywords: Forecasting, Time series data, Interpolation, Newton-Gregory, Polynomials method

Abstract

This research aims to find out the mathematical model and predict the growth in the number of elementary, junior high, high school, and vocational school students in NTB Province, using the Newton-Gregory Advanced Polynomial method. The result of simulating the predicted growth of the number of elementary school students in NTB in 2020 is 319565, with MAD at 353178, MSE at 1247346996840, MAPE at 68,655. Then for the predicted growth of the number of junior high school students in NTB in 2020 of 165141 with MAD of 1876271.7, MSE amounted to 3520395492220, MAPE amounted to at 1077.7039. Furthermore, the predicted growth of the number of high school students in NTB was 399679 with MAD of 44154, MSE of 19495757160, MAPE of 42.0719. while for the results of the simulation of predicted growth in the number of vocational school students in NTB in 2020 is 3738854 with MAD of 393779, MSE amounted to 15506190084.1, MAPE amounted to 49.2027. Based on the results of this study can state that Newton-Gregory Interpolation advanced by using GUI on Matlab, can predict the growing number of elementary, junior high, high school, and vocational students in NTB by using data on the number of students in 2009-2019 and obtained mathematical models of elementary, junior high, high school, and vocational school growth.

References

Aulia, R., Sazlin, R. A., Ismayani, L., Sukiman, M., Perwira Negara, H. R., & Ayu Kurniawati, K. R. (2020). Implementasi Interpolasi Newton Gregory pada Model Matematika Penyebaran Virus Corona di Indonesia. Jurnal Pemikiran Dan Penelitian Pendidikan Matematika (JP3M), 3(1), 01–16.
Das, B., Lagrange, I., Divided, P., Newton, D., & Perbedaan, I. (2016). Interpolasi mundur Newton : Representasi dari data numerik dengan kurva polinomial. 2(10), 513–517.
Dhanapal, A. A. M. (2018). Nilai Interval Integer dari Perbedaan Newton yang dibagi dan Maju dan Kembali. 118(20), 2045–2054.
Gunawan, A. A. S., & Linggarjati, J. (2012). Pengembangan Program Aplikasi Enhanced Machine Control dengan Python untuk Metode Interpolasi Newton. ComTech: Computer, Mathematics and Engineering Applications, 3(1), 154.
Madsen, H. (2007). Time series analysis. CRC Press.
Muhammad, D. (2011). Penggunaan Metode Newton dan Lagrange pada Interpolasi Polinom Pergerakan Harga Saham : Studi Kasus Saham PT Adaro Energi Tbk .
Negara, H. R. ., Syaharuddin, Kiki Riska Ayu, K., & Habibi, R. P. N. (2019). Analysis of nonlinear models for the acceleration of increasing HDI in Asia. International Journal of Scientific and Technology Research, 8(1), 60–62.
Negara, H. R. ., Syaharuddin, R.P.N, H., & K, K. R. A. (2018). Solusi Numerik Konstruksi Scribs & GUI Berbasis Matlab. Wade Group.
Negara, H. R. ., Tamur, M., Syaharuddin, Apandi, T. H., Kusuma, J. W., & Hamidah. (2020). Computational modeling of ARIMA-based G-MFS methods: Long-term forecasting of increasing population. International Journal of Emerging Trends in Engineering Research, 8(7), 3665–3669.
Pratiwi, G. A., Jaya, A. I., & Ratianingsih, R. (2017). Aplikasi Metode Polinom Newton Gregory Maju Dan Pol Newton Gregory Mundur Dalam Memprediksi Banya Penduduk Sulawesi Tengah. Jurnal Ilmiah Matematika Dan Terapan, 14(2), 152–158.
Profesor, A. (2019). Metode Interpolasi Maju dan Mundur Newton. 3(2), 12–15.
Ryan Pratama, R.H Sianipar, K. W. (2014). Pengaplikasian Metode Interpolasi Dan Ekstrapolasi Lagrange , Chebyshev Dan Spline Kubik Untuk Memprediksi. 1(2), 116–121.
Saleh, M. N., Irwansyah, M. A., Eng, M., Anra, H. H., & Kom, M. (2017). Implementasi Peramalan Menggunakan Fuzzy Time Series pada Aplikasi Helpdesk Inventaris Perangkat Teknologi Informasi. Jurnal Sistem Dan Teknologi Informasi (JUSTIN), 1(2), 62–67.
Sanny, L., & Sarjono, H. (2013). Peramalan Jumlah Siswa / I Sekolah Menengah Atas Swasta Menggunakan Enam Metode
Forecasting. Forum Ilmiah, 10(2), 198–208.
Sucipto, L., & Syaharuddin, S. (2018). Konstruksi Forecasting System Multi-Model untuk pemodelan matematika pada peramalan Indeks Pembangunan Manusia Provinsi Nusa Tenggara Barat. Register: Jurnal Ilmiah Teknologi Sistem Informasi, 4(2), 114.
Sudarsono, A. (2016). Jaringan Syaraf Tiruan Untuk Memprediksi Laju Pertumbuhan Penduduk Menggunakan Metode Backpropagation (Studi Kasus di Kota Bengkulu). Media Infotama, 12(1), 61–69.
Published
2020-09-29
How to Cite
[1]
H. R. Negara, M. Ibrahim, and K. R. Kurniawati, “Mathematical Model of Growth in The Number of Students in NTB Using Newton-Gregory Polynomial Method”, Jurnal Varian, vol. 4, no. 1, pp. 43-50, Sep. 2020.
Section
Articles