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All Journal MATHunesa: Jurnal Ilmiah Matematika
Widiarti Widarti
Universitas Lamung
Mathematics

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A Penerapan Metode Double Moving Average dan Double Exponential Smoothing pada Peramalan Nilai Impor Barang Konsumsi Tahun 2017-2022 Widiarti Widarti; Novi Darina; Siti Laelatul Chasanah; Eri Setiawan
MATHunesa: Jurnal Ilmiah Matematika Vol. 12 No. 01 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v12n1.p30-37

Abstract

The smoothing method is classified into two, namely the average smoothing method and the exponential smoothing method. This study examines the application of the double moving average (DMA) and double exponential smoothing (DES) methods in forecasting a data. This study uses 72 data, namely consumer goods import value data for the period January 2017 to December 2022. The method with the lowest MSE and MAPE values is used to predict the import value of consumer goods. The results obtained show that the brown double exponential smoothing method with parameter ?, which is 0.1, is the best method for predicting the import value of consumer goods in 2017-2022 with an MSE value of 60374.46 and a MAPE value of 13.66%.
KAJIAN MODEL REGRESI DATA PANEL PADA DATA INDEKS PEMBANGUNAN MANUSIA PROVINSI DKI JAKARTA TAHUN 2019-2023 Widiarti Widarti
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 01 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n1.p117-124

Abstract

Regression analysis on panel data is a regression technique that utilizes the panel data structure, which combines information from time series and cross section data. Panel data regression analysis in economics is usually used for Human Development Index (HDI) data. HDI is a measure used to assess the success of a region in developing the quality of life of its population. In panel data regression, there are three estimation models, namely CEM, FEM and REM. The CEM method assumes that the intercept and slope in the cross section and time series units are the same, the FEM method assumes that the intercept is different between cross section units, while the slope between cross section units remains the same, while the REM method assumes that differences in unit characteristics and time periods are accommodated in the residual model. As a result of this study, the best panel data regression model is using the Random Effect Model (REM) with individual effects. The variables of life expectancy, school expectancy, number of poor people and per capita expenditure are able to explain HDI in DKI Jakarta Province by 95.45%. Keywords: Panel Data Regression, HDI, Random Effect Model.
Co-Authors Eri Setiawan Novi Darina Siti Laelatul Chasanah