PERAMALAN PERGERAKAN INFLASI DI JAWA TIMUR DENGAN MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING
Keywords: east Java, forecasting , inflation, MAPE, triple exponential smoothing
Abstract
The economic growth of a nation is strongly influenced by inflation. Inflation is the continuous soaring price of goods or services. This study aims to predict the movement of inflation that will occur in East Java from January 2021 to December 2021. This study uses 48 data from the East Java Province inflation rate data from January 2017 to December 2020 sourced from the official website of BPS East Java. Predictions using the triple exponential smoothing method with forecasting evaluation using MAPE. Based on the analysis results, the parameters used are ⺠= 0,01, β = 0,09 dan γ = 0,30 which produces a MAPE value of 1.619%, which is classified as very good. The results show that the inflation forecasting from January 2021 to December 2021 is estimated at -0.13 to 0.48, with an average of 0.087. Thus, the movement of inflation in East Java from January 2021 to December 2021 is classified as low inflation, so it shows that prices and services are still stable.
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References
Armi, A. E., Kridalaksana, A. H., & Arifin, Z. (2019). Peramalan Angka Inflasi Kota Samarinda Menggunakan Metode Double Exponential Smoothing (Studi Kasus: Badan Pusat Statistik Kota Samarinda). Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer, 14(1), 21.
Choirunisa, P., & Kariyam, K. (2019). Perbandingan Metode Triple Exponential Smoothing dan Metode Seasonal Arima untuk Peramalan Inflasi Di Kota Tanjung Pandan. PROSIDING SENDIKA, 5(2).
Chusyairi, A., Pelsri, R. N. S., & Handayani, E. (2018). Optimization of exponential smoothing method using genetic algorithm to predict e-report service. 2018 3rd International Conference on Information Technology, Information System and Electrical Engineering (ICITISEE), 292–297.
Daniel, P. A. (2018). Analisis Pengaruh Inflasi Terhadap Laju Pertumbuhan Ekonomi Di Kota Jambi. EKONOMIS : Journal of Economics and Business, 2(1), 131. https://doi.org/10.33087/ekonomis.v2i1.37
Ginantra, N. L. W. S. R., & Anandita, I. B. G. (2019). Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang. J-SAKTI (Jurnal Sains Komputer Dan Informatika), 3(2), 433–441.
Hudiyanti, C. V., Bachtiar, F. A., & Setiawan, B. D. (2019). Perbandingan Double Moving Average dan Double Exponential Smoothing untuk Peramalan Jumlah Kedatangan Wisatawan Mancanegara di Bandara Ngurah Rai. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer E-ISSN, 2548, 964X.
Islamiati, N., Irfan, A. P., & Wajidi, F. (2020). Metode Triple Exponential Smoothing (TES) dalam Memprediksi Jumlah Kasus Penyakit di RSUD Majene. Seminar Nasional Informatika (SEMNASIF), 1(1), 19–27.
Kristianto, R. P., & Setyanto, A. (2018). Golden section search-multi variable algorithm for optimization parameter of triple exponential smoothing algorithm to predict sufferers of lungs disease. 2018 3rd International Conference on Information Technology, Information System and Electrical Engineering (ICITISEE), 194–198.
Latumahina, H., & Radjabaycolle, J. (2021). Peramalan Inflasi Kota Ambon Tahun 2021 Menggunakan Metode Arima Box Jenkins. PARAMETER: Jurnal Matematika, Statistika Dan Terapannya, 1(2), 118–126.
Nurvianti, I., Setiawan, B. D., & Bachtiar, F. A. (2019). Perbandingan Peramalan Jumlah Penumpang Keberangkatan Kereta Api di DKI Jakarta Menggunakan Metode Double Exponential Smoothing dan Triple Exponential Smoothing [Comparison of Forecasting the Number of Train Departure Passengers in DKI Jakarta Using Doubl. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer E-ISSN, 2548, 964X.
Prayoga, Y., Tambunan, H. S., & Parlina, I. (2019). Penerapan Clustering Pada Laju Inflasi Kota Di Indonesia Dengan Algoritma K-Means. Brahmana: Jurnal Penerapan Kecerdasan Buatan, 1(1), 24–30.
Putro, B., Furqon, M. T., & Wijoyo, S. H. (2018). Prediksi Jumlah kebutuhan pemakaian air menggunakan metode exponential smoothing (Studi Kasus: PDAM Kota Malang). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer E-ISSN, 2548, 964X.
Ramadhan, G. L., Agushinta, D., & Sussanto, H. (2021). Peramalan Inflasi Indonesia Dengan Seasonal Auto Regressive Integrated Moving Average. Sistemasi: Jurnal Sistem Informasi, 10(3), 627–636.
Rismawanti, Y., & Darsyah, M. Y. (2018). Perbandingan Peramalan Metode Moving Average dan Exponential Smoothing Holt Winter Untuk Menentukan Peramalan Inflasi di Indonesia. Prosiding Seminar Nasional Mahasiswa Unimus, 1.
Sihotang, J., & Nopeline, N. (2020). Analysis of the Influence of Interest Rate, Rupiah Exchange Value, Household Consumption, and Import on Inflation in Indonesia Period 2010.Q1 - 2018.Q4. International Journal of Science and Management Studies (IJSMS), 3(6), 81–91. https://doi.org/10.51386/25815946/ijsms-v3i6p106
Tistiawan, T. A., & Andini, T. D. (2019). Pemanfaatan metode triple exponential smoothing dalam peramalan penjualan pada PT. Dinamika Daya Segara Malang. Jurnal Ilmiah Teknologi Informasi Asia, 13(1), 69–76.
Wismarini, N. R., & Kurniawan, U. (2020). Pemodelan Inflasi di Kota Surakarta Tahun 2000-2019. PROSIDING SENDIKA, 6(1).