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All Journal Jurnal Matematika: MANTIK
Gumgum Darmawan
Universitas Padjajaran, Bandung
Mathematics

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Aplikasi Metode Singular Spectral Analysis (SSA) dalam Peramalan Pertumbuhan Ekonomi Indonesia Tahun 2017 Rina Sri Kalsum Siregar; Dina Prariesa; Gumgum Darmawan
Jurnal Matematika MANTIK Vol. 3 No. 1 (2017): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.293 KB) | DOI: 10.15642/mantik.2017.3.1.5-12

Abstract

The purpose of this study was to look at seasonal patterns in the data of Gross Domestic Product (GDP) quarterly in the year 2000-2016 and the implementation of Singular Spectral Analysis (SSA) in the data of GDP to predict the data of GDP in 2017. The SSA method used is the method of recurrent forecasting with bootstrap confidence interval to look at its beliefs of the interval. The source of data derived from the data of GDP in 2000-2016 with the base year in 2000 compiled by the Central Statistics Agency (CSA). The results showed that the SSA method can be used as a reliable method and can be valid that view from the value of MAPE size is 0.82 and the size of the tracking signal at -4.00.
Perbandingan Keakuratan Hasil Peramalan Produksi Bawang Merah Metode Holt-Winters dengan Singular Spectrum Analysis (SSA) Yogo Aryo Jatmiko; Rini Luciani Rahayu; Gumgum Darmawan
Jurnal Matematika MANTIK Vol. 3 No. 1 (2017): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.872 KB) | DOI: 10.15642/mantik.2017.3.1.13-22

Abstract

The Holt-Winters method is used to model data with seasonal patterns, whether trends or not. There are two methods of forecasting in Singular Spectrum Analysis (SSA), namely recurrent method (R-forecasting) and vector method (V-forecasting). The recurrent method performs continuous continuation (with the help of LRF), whereas the vector method corresponds to the L-continuation. Different methods of course make a difference in the accuracy of forecast results. To see the difference between the three methods is done by looking at the comparison of accuracy and reliability of forecast results. To measure the accuracy of forecasting used Mean Absolute Percentage Error (MAPE) and to measure the reliability of forecasting results is done by tracking signal. Applications are done on Indonesian red onion production from January 2006 to December 2015. Forecasting of both methods in SSA uses window length L = 39 and grouping r = 8. With α = 0.1, β = 0.001 and γ = 0.5, Holt-Winters additive method gives better result with MAPE 13,469% than SSA method. Keywords:
Peramalan Indeks Harga Konsumen dengan Metode Singular Spectral Analysis (SSA) dan Seasonal Autoregressive Integrated Moving Average (SARIMA) Deltha Airuzsh Lubis; Muhamad Budiman Johra; Gumgum Darmawan
Jurnal Matematika MANTIK Vol. 3 No. 2 (2017): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1050.728 KB) | DOI: 10.15642/mantik.2017.3.2.74-82

Abstract

Consumer Price Index (CPI) are the indicators used to measure the inflation and deflation of a group of goods and services in general. Forecasting CPI to be important as early detection in facing price hikes. This study uses the SSA and SARIMA. SARIMA a parametric model that requires various assumptions while SSA is a nonparametric technique that is free from a variety of assumptions, but both methods require seasonal patterns in the data. Based on the research results, methods of SSA with length window(L) of 24 and a grouping of 4 (1 group of seasonal and 3 groups of trends) and SARIMA models of order (0,1,1), (0,1,1) 6 is the most accurate and reliable models in forecasting CPI to the value Padang Sidempuan City. Forecasting CPI Padang Sidempuan City for the next 5 months with SSA method and SARIMA (0,1,1), (0,1,1) 6 shows the pattern of a trend is likely to increase but forecasting the 5th month with SSA method showed a surge in the value of CPI high or high inflation will occur.
Co-Authors Deltha Airuzsh Lubis Dina Prariesa Muhamad Budiman Johra Rina Sri Kalsum Siregar Rini Luciani Rahayu Yogo Aryo Jatmiko