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All Journal JURNAL SISTEM INFORMASI BISNIS IJIS - Indonesian Journal On Information System Majalah Ilmiah UNIKOM Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) International Journal of Research and Applied Technology (INJURATECH) Journal of Artificial Intelligence and Digital Business
Sumitra, Irfan Dwiguna
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Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Journal : JURNAL SISTEM INFORMASI BISNIS

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Sistem Peramalan Kebutuhan Hidup Layak Minimum (Kapita/Bulan) Kota Bandung Fahrudin, Rifqi; Sumitra, Irfan Dwiguna
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 2 (2019): Volume 9 Nomor 2 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.785 KB) | DOI: 10.21456/vol9iss2pp192-203

Abstract

The importance of inflation forecasting is used as a reference for estimating the Need for Living (KHL). If inflation can be predicted with high accuracy, it can certainly be used as the basis for government policy making in anticipating future economic activity. This study aims to produce a model of inflation data forecasting system, the forecasting results can be used as a reference for determining the Decent Living Needs (KHL) of a single worker in one month. The data used in forecasting is inflation data for January 2011 - December 2017 while the KHL data for the food and beverage category is obtained from the food price portal. The method used in this study is the SARIMA-SES hybrid method. In forecasting the inflation rate where the data is in the form of time series, the SARIMA-SES hybrid method can show more accurate forecasting results than using a single method. Based on the comparison of the overall forecasting model and by combining the SARIMA (1,0,1) (1,0,1) 12 and SES models with alpha 0,6 the smallest error value with MAD value 0,114, MSE 0,017 and 0,39% for MAPE. From these results, it was gathered that inflation forecasting in Bandung City using the SARIMA-SES hybrid method has a high accuracy value so that the results of the KHL value calculation with the forecasting inflation value approach the actual value. From these values can be used as a reference for the decision making of a single worker in fulfilling their life needs one month.
Co-Authors adang badru jaman,anggun fergina, adang badru jaman,anggun fergina Agustin, Nada Delia Arifin, Faisal Hanif Azizi, Luthfi Bachtiar, Adam Mukharil Diana Effendi Eddy Soeryanto Soegoto Estiko Rijanto Fahrudin, Rifqi Handoko, Refah Istifahani Heriadi, Herman Irawan Afrianto Mutakin, M I Naufal, M Pamungkas, D A Rahma Wahdiniwaty Reza, Donny Ruhimat, R. Sidqi, Fajar Sidqi, Fajar Sri Nurhayati Sutardjo, Ramdan Prawira Widiarto, G