DOI: https://doi.org/10.21456/vol15iss1pp11-20

Analisis Perbandingan Metode Terbaik Peramalan Inflasi di Jawa Barat dengan ARIMA, Linear Regression, Triple Exponential Smoothing

*Elsa Mutiara Nuralifia  -  Universitas Gunadarma, Indonesia
Rodiah Rodiah  -  , Indonesia
Open Access Copyright (c) 2025 JSINBIS (Jurnal Sistem Informasi Bisnis)

Citation Format:
Abstract

Inflation is a crucial economic indicator, and its growth rate is always aimed to be low and stable to prevent macroeconomic disruptions that might lead to economic instability. Considering the significant impact it can have, predicting future inflation values is essential. This study focuses on forecasting inflation, particularly in the province of West Java, using the ARIMA, Linear Regression, and Triple Exponential Smoothing methods. The goal is to find the method that yields the lowest error to ensure more accurate forecasting results. The research employs inflation data from June 2009 to May 2023 in West Java, collected from the Badan Pusat Statistik (BPS) of West Java Province. The study involves several stages: (1) collecting inflation data, (2) preprocessing the data, (3) constructing forecasting models and obtaining results, and (4) comparing accuracy outcomes. After comparing the methods, it was found that the Triple Exponential Smoothing method emerged as the most effective one. This method exhibited the lowest error evaluation, with an RMSE value of 0.1719703, indicating good accuracy and suitability for forecasting inflation values in the province of West Java for the future

Fulltext View|Download
Keywords: Forecasting: West Java; ARIMA; Linear Regression; Triple Exponential Smoothing

Article Metrics:

Article Info
Section: Research Articles
Language : ID
Recent articles
Integrasi Model DeLone & McLean, UTAUT, dan HOT-Fit untuk Menilai Keberhasilan dan Keberterimaan Aplikasi LPD Mobile di Bali Prediksi Churn Pelanggan Telekomunikasi dengan Optimalisasi Seleksi Fitur dan Tuning Hyperparameter pada Algoritma Klasifikasi C4.5 The Impact of The Utilization of Electronic Payment Moderated by Financial Technology Innovation on Financial Technology Payment in Indonesia Komparasi COBIT 2019 dan ISO 27001 Terhadap Audit ISO 21001 untuk Akurasi Rekomendasi Audit SI/TI Pendidikan Benefits and Challenges of ERP Implementation in Higher Education Institutions: A Systematic Literature Review More recent articles
Most cited articles
Penerapan Green Supply Chain Management Untuk Peningkatan Kinerja Keuangan Perusahaan Sistem Informasi Geografis Berbasis Web untuk Pemetaan Sebaran Alumni Menggunakan Metode K-Means Sistem Informasi Perpustakaan Berbasis Web Application Kajian Data Mining Customer Relationship Management pada Lembaga Keuangan Mikro Support Vector Machine Untuk Klasifikasi Citra Jenis Daging Berdasarkan Tekstur Menggunakan Ekstraksi Ciri Gray Level Co-Occurrence Matrices (GLCM) More cited articles
  1. Anjasari, D.H., Listiwikono, E., Yusuf, F.I., 2018. Perbandingan Metode Double Exponential Smoothing Holt dan Metode Triple Exponential Smoothing Holt-Winters untuk Peramalan Wisatawan Grand Watu Dodol. Transformasi: Jurnal Pendidikan Matematika dan Matematika, 2(2), 12-25
  2. Arridho, M.N., Astuti, Y., 2020. Penerapan Metode Single Exponential Smoothing untuk Memprediksi Penjualan Katering pada Kedai Pojok Kedaung. Jurnal Ilmiah Intech: Information Technology Journal of UMUS, 2(2), 35-44. https://doi.org/10.46772/intech.v2i02.288
  3. Firmansyah, M.F., 2021. Analisis Pertumbuhan Ekonomi dalam Penentuan Basis Ekonomi, Isu Ketimpangan dan Lingkungan di Jawa Barat Periode 2010-2019. JAMBURA Economic Education Journal, 3(1), 8-27. https://doi.org/10.37479/jeej.v3i1.8292
  4. Fitri, A., Anwar, S., Zohra, A.F., Nasution, M.H., 2018. Peramalan Laju Inflasi Bulanan Kota Padang Menggunakan Metode Triple Exponential Smoothing. Jurnal Ilmiah Sosio-Ekonomika Bisnis, 21(2), 1-10. https://doi.org/10.22437/jiseb.v21i2.6050
  5. Krisma, A., Azhari, M., Widagdo, P.P., 2019. Perbandingan Metode Double Exponential Smoothing dan Triple Exponential Smoothing dalam Parameter Tingkat Error Mean Absolute Percentage Error (MAPE) dan Means Absolute Deviation (MAD). Prosiding Seminar Ilmu Komputer dan Teknologi Informasi, 4(2), 81-87
  6. Liantoni, F., 2022. Data Mining dan Penerapan Metode. Eureka Media Aksara: Purbalingga
  7. Madianto, S., Utami, E., Hartanto, A.D., 2021. Algoritma Triple Exponential Smoothing Untuk Prediksi Trend Turis Pariwisata Jatim Park Batu saat Pandemi Covid-19. Journal of Applied Informatics and Computing (JAIC), 5(1), 58-63. https://doi.org/10.30871/jaic.v5i1.3139
  8. Mario, M.I.T., Kartiko, Bekti, R.D., 2021. Pemodelan Generalized Space Time Autoregressive (GSTAR) untuk Peramalan Tingkat Inflasi di Pulau Jawa. Jurnal Statistika Industri dan Komputasi, 6(2), 171-184
  9. Nangi, J., Indrianti, S.H., Pramono, B., 2018. Peramalan persediaan obat menggunakan metode Triple Exponential Smoothing (TES)(studi kasus: Instalasi Farmasi rsud kab. Muna). semanTIK, 4(1), 135-142, http://dx.doi.org/10.55679/semantik.v4i1.4302
  10. Perdana, F.R., 2016. Perbandingan Metode DES (Double Exponential Smoothing) dan Tes (Triple Exponential Smoothing) untuk Peramalan Penjualan Rokok (Studi Kasus: Toko Utama). Tesis: Universitas Muhammadiyah Jember
  11. Prasetyo, V.R., Lazuardi, H., Mulyono, A.A., Lauw, C., 2021. Penerapan Aplikasi RapidMiner untuk Prediksi Nilai Tukar Rupiah Terhadap US Dollar dengan Metode Linear Regression. Jurnal Nasional Teknologi Dan Sistem Informasi, 7(1), 8-17. https://doi.org/10.25077/TEKNOSI.v7i1.2021.8-17
  12. Salim, A., Fadilla., Purnamasari, A., 2021. Pengaruh Inflasi Terhadap Pertumbuhan Ekonomi Indonesia Anggun Purnamasari. Ekonomica Sharia: Jurnal Pemikiran dan Pengembangan Ekonomi Syariah, 7(1), 17-28. https://doi.org/10.36908/esha.v7i1.268
  13. Karno, A.S.B., 2020. Prediksi Data Time Series Saham Bank BRI Dengan Mesin Belajar LSTM (Long ShortTerm Memory). Journal of Information and Information Security (JIFORTY), 1(1), 1-8. https://doi.org/10.31599/jiforty.v1i1.133
  14. Saukat, G., 2021. Inflasi Provinsi Kepulauan Riau 2021. CV. Bintang Printing: Kepulauan Riau
  15. Pebrianti, A., Utami, A.S., Putri, A.T., Fitriana, A., Istiqomah, N., 2021. Proyeksi Laju Inflasi di Indonesia dengan Metode ARIMA (Autoregressive Integrated Moving Average). https://www.researchgate.net/publication/353037444
  16. Sudibyo, N.A., Iswardani, A., Septyanto, A.W., Wicaksono, T.G., 2020. Prediksi Inflasi di Indonesia Menggunakan Metode Moving Average, Single Exponential Smoothing dan Double Exponential Smoothing. Jurnal Lebesgue: Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 1(2), 123-129. https://doi.org/10.46306/lb.v1i2.25
  17. Widiastuti, A., 2021. Dampak Pandemi Covid-19 Terhadap Pertumbuhan Ekonomi di Pulau Jawa. Jurnal Ekonomi-Qu, 11(1), 97-107

Last update:

No citation recorded.

Last update: 2025-03-10 20:22:32

No citation recorded.