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Journal : Jurnal Litbang Edusaintech

NON-HYBRID ENSEMBLE SPATIAL REGRESSION ON HUMAN DEVELOPMENT INDEX (IPM) in CENTRAL JAVA: NON-HYBRID ENSEMBLE SPATIAL REGRESSION ON HUMAN DEVELOPMENT INDEX (IPM) in CENTRAL JAVA Evi Ardiati Sazaen; Rochdi Wasono; Indah Manfaati Nur
Jurnal Litbang Edusaintech Vol. 1 No. 1 (2020): Volume 1 No 1 2020
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v1i1.4

Abstract

The human development index (HDI) is a measure to see an increase in regional development that has a very broad dimension, because it increases the quality of the population of an area in terms of life expectancy, education, and decent standard of living. In 2010 the Central Java HDI increased by 66.08% and increased by 4.44%, with the total HDI in 2017 of 70.52 percent. Spatial regression is the development of classical linear regression involving the region model. Spatial regression ensemble is a technique to be sent spasi spatial regression models by adding noise (additive noise). The type of spatial weighting used is Queen Contiguity. The selection of the best model using AIC and RMSE values. The purpose of this study is to provide an assessment of the distribution of HDI data in the Province of Central Java in 2017 and to do modeling using non-hybrid spatial ensemble regression regression. The results of this study are the SAR spatial method with ensemble giving results with AIC value of 143 and RMSE value of 1.3899 with a value of 90.09%. Significant variables on HDI are population density (X1), poverty (X2), school participation rates (X5), and average per capita per month for food and non-food (X7).
PERAMALAN INDEKS HARGA KONSUMEN KABUPATEN BANYUMAS DENGAN METODE SARIMA Arini Rizky Wahyuningtyas; Wahyu Putri Pratiwii; Rochdi Wasono; Tiani Wahyu Utami
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.77

Abstract

The CPI is used as an indicator to determine the inflation rate that can describe economic developments in a region. Uncontrolled inflation will have a direct impact on economic conditions. Therefore, it is necessary to have a method to predict the CPI so that the government can determine the right policy so that the economic condition of the community becomes more stable and improves. In this study, CPI forecasting in Banyumas Regency will be carried out using the SARIMA method. The purpose of this study is to predict the CPI in the future. This study uses CPI data from Banyumas Regency from January 2014 to August 2021 with 92 data. The results show that the SARIMA (1,1,1)(0,1,1)12 model is the right model for forecasting the CPI in Banyumass Regency. Forecasting the CPI for Banyumas Regency for the next 12 months using the SARIMA (1,1,1)(0,1,1)12 method shows a trend pattern that tends to increase or inflation will not be so high.