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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Statistika Universitas Muhammadiyah Semarang SEEIJ (Social Economics and Ecology International Journal) Engineering, Mathematics and Computer Science Journal (EMACS)
Syarifah Diana Permai
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Journal : Engineering, Mathematics and Computer Science Journal (EMACS)

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Forecasting Poverty Ratios in Indonesia: A Time Series Modeling Approach Hidayat, Muhammad Fadlan; Henryka, Diva Nabila; Citra, Lovina Anabelle; Permai, Syarifah Diana
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 3 (2024): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v6i3.11968

Abstract

Poverty is one of the main problems still faced by Indonesia today. To help find the right solution, an annual prediction of the poverty rate in Indonesia is needed. This study uses data on the 'Ratio of the Number of Poor People in Indonesia per year from 1998 to 2023' obtained from data.worldbank.org. The prediction methods used in this study include the Naïve Model, Double Moving Average, Double Exponential Smoothing, ARIMA, Time Series Regression, and Neural Network, with a total of 26 models. Of the 26 models, only 19 models passed the model comparison stage. Based on the evaluation results using the RMSE, MAE, MAPE, and MDAE metrics, it was concluded that the NNETAR Neural Network model showed the best performance among the six methods used to predict the poverty ratio in Indonesia.
Co-Authors Ajeng Wulandari Arifin, Yulyani Citra, Lovina Anabelle Dwiputra, Kristian Faisal, Fiandra Rheza Henryka, Diva Nabila Hidayat, Muhammad Fadlan Irhamah - Kurniadi, Felix Indra Marcellino, Marcellino Nur Iriawan Pudjihastuti, Herena Purwandari, Kartika