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All Journal Xplore: Journal of Statistics
Agus M Soleh
Department of Statistics, IPB University
Decision Sciences, Operations Research & Management Engineering Mathematics

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Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square Khairunnisa Khairunnisa; Rizka Pitri; Victor P Butar-Butar; Agus M Soleh
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.275

Abstract

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.
Evaluasi Faktor yang Memengaruhi Usability Aplikasi Thymun Menggunakan Structural Equation Model-Partial Least Square Rahma Dany Asyifa; Agus M Soleh; Bagus Sartono
Xplore: Journal of Statistics Vol. 10 No. 3 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (906.115 KB) | DOI: 10.29244/xplore.v10i3.743

Abstract

Application development must be done by considering the usability factor of the application. Three aspects of usability measurement, namely usefulness, satisfaction, and ease of use, are latent variables that cannot be measured directly, so the appropriate analysis is the Structural Equation Model-Partial Least Square (SEM-PLS). PLS is a SEM analysis approach that does not require assumptions of data distribution and a minimum number of observations. The measurement of the usability of the Thymun application is described in two SEM-PLS models. This study aims to determine the best model and determine the effect of usefulness, satisfaction, and ease of use on the usability of the Thymun application. The data used is survey data to 44 Thymun application users. The sampling technique used was purposive sampling. The results showed that the best model has a good measure with an R-square value of 0.730 and Q2 0.453 with a Goodness of Fit 0.736. The variables of usefulness and ease of use have a significant effect on the 5% real level with path coefficient values ​​of 0.255 and 0.636. While the satisfaction variable does not have a significant effect on the 5% real level with a path coefficient of 0.058. Thymun application usability score is 76.47.
Co-Authors Bagus Sartono Khairunnisa Khairunnisa Rahma Dany Asyifa Rizka Pitri Victor P Butar-Butar