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Widiarti Widiarti
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Mathematics

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Perbandingan Metode Bootstrap, Jacknife Jiang Dan Area Specific Jacknife Pada Pendugaan Mean Square Error Model Beta-Bernoulli Yesi Santika; Widiarti Widiarti; Fitriani Fitriani; Mustofa Usman
Jurnal Siger Matematika Vol 2, No 1 (2021): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.04 KB) | DOI: 10.23960/jsm.v2i1.2756

Abstract

Small area estimation is defined as a statistical technique for estimating the parameters of a subpopulation with a small sample size. One method of estimating small area parameters is the Empirical Bayes (EB) method.  The accuracy of the Empirical Bayes (EB) estimator can be measured by evaluating the Mean Squared Error (MSE). In this study, 3 methods to determine MSE in the EB estimator of the Beta-Bernoulli model will be compared, namely the Bootstrap, Jackknife Jiang and Area-specific Jackknife methods.  The study is carried out theoretically and empirically through simulation with R-studio software version 1.2.5033. The simulation results in a number of areas and pairs of prior distribution parameter values, namely Beta, show the effect of sample size and parameter value pairs on the Mean Square Error (MSE) value. The larger the number of areas and the smaller the initial ????, the smaller the MSE value.  The area-specific Jackknife method produces the smallest MSE in the number of areas 100 and the Beta parameter value 0.1.
Peramalan Data Time Series Seasonal Menggunakan Metode Analisis Spektral Anis Mahfud Al’afi; Widiarti Widiarti; Dian Kurniasari; Mustofa Usman
Jurnal Siger Matematika Vol 1, No 1 (2020): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.565 KB) | DOI: 10.23960/jsm.v1i1.2484

Abstract

Air transportation is now a mode of transportation that is often the first choice. Although the transportation costs are relatively expensive, it can save a lot of time to get to the destination. Therefore, predicting the number of aircraft passengers is an interesting thing to study. In this study forecasting the number of aircraft passengers at Raden Intan II Airport using spectral analysis methods. Spectral analysis is used to obtain more complete information about the time series data characteristics to examine the periodicity. After getting the periodicity the data is modeled using the ARIMA Seasonal Method. Based on the analysis results it is known that the best model for forecasting aircraft passengers at Raden Intan II Airport is Seasonal ARIMA (0,1,1) (0,1,1)3
Pemodelan Dinamis Distributed Lag Dengan Menggunakan Metode Koyck Dan Metode Almon Dora Panny Nurcahaya Sitorus; Widiarti Widiarti; Agus Sutrisno; Mustofa Usman
Jurnal Siger Matematika Vol 4, No 1 (2023): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v4i1.9210

Abstract

The distributed lag Model is a dynamic model due to the effect of a one-unit change in the value of the distributed independent variable (X) over a period of time. Distributed lag Model there are 2 types, namely: infinite lag model and finite lag model. Infinite lag modeling using koyck method and finite lag modeling using Almon method. This distributed lag Model is used to visualize the impact caused by the independent variable on the dependent variable. This study aims to apply a dynamic model of distributed lag by using the koyck transformation method and Almon transformation method to assess the effect of the rupiah exchange rate on the value of garment exports PT. Shinwon went abroad and determined the best model in Dynamic Modeling of distributed lag using the koyck transformation method and the Almon transformation method. The results showed that dynamic modeling of distributed lag with Almon transformation method is better than koyck transformation.
Aplikasi Metode Sillhouette Coefficient, Metode Elbow dan Metode Gap Staticstic dalam Menentukan K Optimal pada Analisis K-Medoids Hilda Lailatul Ramadhania; Widiarti Widiarti; La Zakaria; Nusyirwan Nusyirwan
Jurnal Siger Matematika Vol 4, No 1 (2023): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v4i1.3196

Abstract

The K-Medoids method is a non-hierarchical cluster analysis method where information on the exact number of clusters is required. The data used in this study uses simulation data from reference data on the percentage of households according to drinking water sources. The simulation data used uses a multivariate normal distribution, so that the simulation data allows for negative data. In this study, two options were carried out on negative data results, namely being zero and absolute. The method in determining the optimal number of clusters used the Sillhouette Coefficient method, the Elbow method and the Gap Statistics method. The average Dunn Index value from the data on the zeroed option produces the largest Dunn Index value in determining the optimal number of clusters using the Gap Statistic method, which is 0,125734, while in the second option data, the Dunn Index average is greatest in determining the number of clusters optimally using the Sillhouette Coefficient method, which is 0,113315.
Penerapan Model Vector Error Correction Model (VECM) pada Peramalan Data Nilai Ekspor dan Nilai Impor Seluruh Komoditas di Provinsi Lampung Tahun 2022 Mega Putri; Widiarti Widiarti; Aang Nuryaman; Warsono Warsono
Jurnal Siger Matematika Vol 4, No 2 (2023): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v4i2.12583

Abstract

Model Vector Error Correction Model (VECM) merupakan turunan dari model Vector Autoregressive (VAR) untuk data tidak stasioner dan terdapat hubungan kointegrasi. Model VAR merupakan model peramalan data deret waktu multivariat yang menghubungkan nilai peramalan dengan nilai-nilai data pada periode sebelumnya. Data deret waktu multivariat yang digunakan pada penelitian ini adalah data Nilai Ekspor dan Nilai Impor seluruh komoditas di Provinsi Lampung tahun 2015-2021. Penelitian ini bertujuan untuk melakukan peramalan pada periode Januari sampai Desember 2022 dengan model VECM. Berdasarkan data diperoleh model VECM yaitu model VECM (1) dengan nilai MAPE sebesar 17,01%.
Co-Authors Aang Nuryaman Agus Sutrisno Anis Mahfud Al’afi Dian Kurniasari Dora Panny Nurcahaya Sitorus Fitriani Hilda Lailatul Ramadhania La Zakaria Mega Putri Mustofa Usman Mustofa Usman Nusyirwan Nusyirwan Warsono Warsono Yesi Santika