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All Journal BERKALA SAINSTEK JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Varian Parameter: Journal of Statistics
Hartayuni Sain
Department Of Statistics Tadulako University
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Parameter: Journal of Statistics

 1 
APPLICATION OF THE RASCH MODEL TO TEST TOOLS IN THE ANALYSIS OF SURVEY DESIGN Anggraini, Nini; Nabillah, Chantika; Dermawan Lonan, Herdi; Sain, Hartayuni
Parameter: Journal of Statistics Vol. 3 No. 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i1.16412

Abstract

The purpose of this study was to examine the instruments used to assess students' abilities in the designer analysis course of the statistics study program at Tadulako University. There were 90 students enrolled in this course, and the questions included 25 multiple-choice items related to survey design content. The test instrument for understanding the survey designer course was the subject of this study. The Rasch method, which is used to get fit items, is used. Winsteps software was used to carry out this analysis. In accordance with the Rasch model, the Winsteps program produced 23 items with an average value of 1.11 and -0.08 for MNSQ Outfit for person and item, respectively. In spite of the fact that the person's and the item's Outfit ZSTD values are 1.11 and 0.26, respectively, and despite the fact that the instrument's reliability, as measured by Cronbach's alpha, is 0.86, 23 of the 25 question items fit and 2 do not.
Predicting Drought in East Nusa Tenggara: A Novel Approach Using Wavelet Fuzzy Logic and Support Vector Machines Sain, Hartayuni; Fadri, Firda
Parameter: Journal of Statistics Vol. 4 No. 1 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i1.17142

Abstract

The water crisis, or what is hereinafter referred to as drought, has become a systemic and crucial problem in several regions in Indonesia. Indonesia is an agricultural country, where the presence of water is very influential so that drought can become a natural disaster if it starts to cause an area to lose its source of income due to disturbances in agriculture and the ecosystem it causes. Drought forecasting can provide support solutions in preventing the impact of drought. In this paper, we compare the performance of wavelet fuzzy logic and the support vector machine (SVM) as a supervised learning method for drought forecasting in East Nusa Tenggara. This study examines the monthly rainfall data for 1999-2015 which is the basis for calculating the drought index based on the Standardized Precipitation Index (SPI). The SPI value used is SPI-3 at a station in East Nusa Tenggara. The performance of models is compareded on R2. The results showed that R2 of wavelet fuzzy logic is smaller than one of SVMVM is better than the wavelet fuzzy logic for forecasting SPI value of drought in East Nusa Tenggara.
Co-Authors Afriza, Dini Aprilia Aisya, Cici Al Fajri, Iman Anggraini, Nini Armayani Arsal Borahima, Maharani Safira B. Dermawan Lonan, Herdi Fadjriyani Fadjryani, Fadjryani Fadri, Firda Gamayanti, Nurul Fiskia Iman Setiawan Jeffry Kusuma Junaidi Junaidi Mohammad Fajri Nabillah, Chantika Nasria Nacong Nur Azizah Nurwijayanti Radi, Aryani Rais Rais Rais Selvy Musdalifah Setiawan, Iman Sinaga, Novita Damayanti Soleha, Salma Winarti Winarti