Forecasting Daily Maximum and Minimum Air Temperatures in The Cilacap District Using Arima and Exponential Smoothing
Keywords: Temperature, forecasting, ARIMA, exponential smoothing
Abstract
This research aims to predict daily maximum and minimum air temperatures in Cilacap Regency using ARIMA and Exponential Smoothing. Data was obtained from recordings carried out by BMKG Cilacap using maximum and minimum thermometers taken from January 1, 2016, to December 31, 2021. The results show that the best forecasting model uses the ARIMA (2,1,2) model for maximum temperature and the ARIMA (1,1,1) model for minimum temperature, with the MAPE value of 2.09% for the maximum temperature and 2.44% for the minimum temperature, while the RMSE value obtained is 0.9177 for the maximum temperature and 0.8001 for the minimum temperature. Based on the ARIMA model, Cilacap's daily maximum temperature in 2022 was predicted to be around 30.6ᵒC, with a 95% confidence interval between 28ᵒC - 35ᵒC, while the minimum temperature was predicted to be around 25.1ᵒC, with a 95% confidence interval between 23ᵒC - 28ᵒC.
Downloads
References
Adnyana, I. N. T., Wijaya, I. G. P. S., & Albar, M. A. (2019). Jaringan Syaraf Tiruan Backpropagation Untuk Peramalan Suhu Minimum dan Maksimum, Kelembaban, Tekanan Udara, Jumlah Hari Hujan, dan Curah Hujan Bulanan Di Kota Mataram. J-COSINE, 3(2), 127–136.
Anwar, S. (2017). Peramalan Suhu Udara Jangka Pendek di Kota Banda Aceh dengan Metode Autoregressive Integrated Moving Average (ARIMA). Malikussaleh Journal of Mechanical Science and Technology, 5(1), 6–12.
Ardiansah, I., Fauzi Adiarsa, I., Putri, S. H., & Pujianto, T. (2021). Penerapan Analisis Runtun Waktu pada Peramalan Penjualan Produk Organik menggunakan Metode Moving Average dan Exponential Smoothing Application of Time Series Analysis in Organic Product Sales Forecasting using Moving Average and Exponential Smoothing Methods. Jurnal Teknik Pertanian Lampung, 10(4), 548–559. https://doi.org/10.23960/jtep-l.v10.i4.548-559
Aswi, & Sukarna. (2006). Analisis Deret Waktu: Teori dan Aplikasi. https://www.researchgate.net/publication/338293807
Auliasari, K., Kertaningtyas, M., & Kriswantono, M. (2019). Penerapan Metode Peramalan untuk Identifikasi Potensi Permintaan Konsumen. Informatics Journal, 4(3), 121–129.
Dahlan, N. D., & Gital, Y. Y. (2016). Thermal sensations and comfort investigations in transient conditions in tropical office. Applied Ergonomics, 54, 169–176. https://doi.org/10.1016/j.apergo.2015.12.008
Fejriani, F., Hendrawansyah, M., Muharni, L., Handayani, S. F., & Syaharuddin. (2020). FORECASTINGPENINGKATAN JUMLAH PENDUDUK BERDASARKAN JENIS KELAMIN MENGGUNAKAN METODE ARIMA. GEOGRAPHY : Jurnal Kajian Penelitian & Pengembangan Pendidikan, 8(1), 27–36. http://journal.ummat.ac.id/index.php/geography
Handoko, T. H. (2000). Dasar-dasar Manajemen Produksi & Operasi. BPFE-UGM.
Hartati. (2017). PENGGUNAAN METODE ARIMA DALAM MERAMAL PERGERAKAN INFLASI. JMST, 18(1), 1–10.
Heng, S. L., & Chow, W. T. L. (2019). How 'hot' is too hot? Evaluating acceptable outdoor thermal comfort ranges in an equatorial urban park. International Journal of Biometeorology, 63(6), 801–816. https://doi.org/10.1007/s00484-019-01694-1
Hidayah, S. L. I. A., Rusgiyono, A., & Wilandari, Y. (2015). PERBANDINGAN MODEL ARIMA DAN FUNGSI TRANSFER PADA PERAMALAN CURAH HUJAN KABUPATEN WONOSOBO. Jurnal Gaussian, 4(4), 1037–1044.
Hikmah, H., Asrirawan, A., Apriyanto, A., & Nilawati, N. (2023). Peramalan Data Cuaca Ekstrim Indonesia Menggunakan Model ARIMA dan Recurrent Neural Network. Jambura Journal of Mathematics, 5(1). https://doi.org/10.34312/jjom.v5i1.17496
Lakitan, & Benyamin. (2002). Dasar-Dasar Klimatologi. PT Raja Grafindo Persada.
Luh, N., Sri, W., Ginantra, R., Bagus, I., & Anandita, G. (2019). Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang. In Jurnal Sains Komputer & Informatika (J-SAKTI (Vol. 3). http://tunasbangsa.ac.id/ejurnal/index.php/jsakti
Meyler, A., Kenny, G., & Quinn, T. (2008). Forecasting irish inflation using ARIMA models (11359).
Middel, A., Selover, N., Hagen, B., & Chhetri, N. (2016). Impact of shade on outdoor thermal comfort—a seasonal field study in Tempe, Arizona. International Journal of Biometeorology, 60(12), 1849–1861. https://doi.org/10.1007/s00484-016-1172-5
Montgomery, D. C., Jennings, C. L., & Kulachi, M. (2008). Introduction to Time Series Analysis and Forecasting. Wiley.
Nur Hamidah, S., Salam, N., Sri Susanti, D., Kunci, K., Waktu, D., Eksponensial Holt-Winters, P., Multiplikatif, M., & Aditif, M. (2013). TEKNIK PERAMALAN MENGGUNAKAN METODE PEMULUSAN EKSPONENSIAL HOLT-WINTERS (Vol. 07, Issue 02).
Pujiati, E., Yuniarti, D., Goejantoro, R., Statistika, M., Statistika, D., Matematika, F., & Pengetahuan, I. (2016). Peramalan Dengan Menggunakan Metode Double Exponential Smoothing Dari Brown (Studi Kasus: Indeks Harga Konsumen (IHK) Kota Samarinda) Forecasting Using Double Exponential Smoothing Method Of Brown (Case Study: The Consumer Price Index (CPI) City Samarinda). Jurnal EKSPONENSIAL, 7(1).
Purba, L. I., & Al, E. (2021). Argoklimatologi. Medan: Yayasan Kita Menulis.
Rosadi D. (2009). Pemanfaatan Software Open Source R dalam pemodelan ARIMA. Seminar Nasional Matematika Dan Pendidikan Matematika, 786–795.
Rosadi D. (2016a). Analisis Runtun Waktu dan Aplikasinya dengan R. Gadjah Mada University Press.
Rosadi D. (2016b). Ekonometrika dan Analisis Runtun Waktu Terapan dengan Eviews. Andi.
Safitri, T., Dwidayati, N., & Kunci, K. (2017). Perbandingan Peramalan Menggunakan Metode Exponential Smoothing Holt-Winters dan Arima. Unnes Journal of Mathematics, 6(1), 48–58. http://journal.unnes.ac.id/sju/index.php/ujm
Safitri, T., Dwidayati, N., & Sugiman. (2017). Perbandingan Peramalan Menggunakan Metode Exponential Smoothing Holt-Winters dan Arima. UNNES Journal Of Mathematics, 6(1), 48–58.
Santoso, A. B., Rumetna, M. S., & Isnaningtyas, K. (2021). Penerapan Metode Single Exponential Smoothing Untuk Analisa Peramalan Penjualan. JURNAL MEDIA INFORMATIKA BUDIDARMA, 5(2), 756. https://doi.org/10.30865/mib.v5i2.2951
Widjajati, F. A., Soehardjoepri, S., & Fani F. (2017). MENENTUKAN PENJUALAN PRODUK TERBAIK DI PERUSAHAAN X DENGAN METODEWINTER EKSPONENSIAL SMOOTHINGDANMETODE EVENT BASED. Limits: J. Math. and Its Appl., 14(1), 25–35.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright (c) 2023 Jurnal Matematika Sains dan Teknologi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.