Article Per Year (5 Year)
p-Index From 2020 - 2025
2.928
P-Index
This Author published in this journals
All Journal dCartesian: Jurnal Matematika dan Aplikasi AKSIOMA: Jurnal Program Studi Pendidikan Matematika JIPM (Jurnal Ilmiah Pendidikan Matematika) Jurnal Edukasi Matematika dan Sains Science and Technology Indonesia Jurnal Basicedu SCAFFOLDING: Jurnal Pendidikan Islam dan Multikulturalisme Imajiner: Jurnal Matematika dan Pendidikan Matematika ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Basicedu UNP Journal of Statistics and Data Science d'Cartesian: Jurnal Matematika dan Aplikasi
Permana, Dony
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : UNP Journal of Statistics and Data Science

 1 
Penerapan Rantai Markov pada Data Curah Hujan Harian di Kota Semarang Tsani, Nahda Maesya; Permana, Dony; Kurniawati, Yenni; Salma, Admi
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/189

Abstract

Rainfall is a measure of the amount of water that falls on the earth's surface in a given period of time. High rainfall can cause flooding in certain areas, while low rainfall can leave areas vulnerable to drought. Semarang City is one of the largest cities in Java Island that is often hit by floods. Efforts can be made to anticipate the risk of flooding, one of which is by studying the pattern of rainfall. This study will determine the chances of rainfall transition in Semarang City in steady state conditions using Markov chains. The results are expected to be used to anticipate the risk of flooding in Semarang City. The probability of daily rainfall transition in Semarang City in each state for the next period of time is 90.5% chance of staying in the light rain state, 7.97% chance of staying in the medium rain state and 1.50% chance of staying in the heavy rain state.
Evaluasi Faktor-Faktor Yang Memengaruhi Indeks Pembangunan Manusia Tahun 2023 Menggunakan Metode SEM-PLS Putri, Sindy Amelia; Zilrahmi; Permana, Dony; Fitria, Dina
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/214

Abstract

The human development index (HDI) is a measure of the success of development in a country. Indonesia as a developing country in 2022 has an HDI value that ranks 112 out of a total of 193 countries in the world. This indicates that there is an urgent need for evaluation in increasing the HDI value in Indonesia which leads to an increase in the quality of human development. The evaluation can be done using the Structural Equation Modeling-Partial Least Square (SEM-PLS) analysis method. With 34 Indonesian provinces as observations, there are three dimensions as variables analyzed in this paper, namely economy, education, and health. These variables are analyzed based on each indicator variable. The results of the analysis show that in the economic variable, the influential indicators are the Open Unemployment Rate, GRDP per Capita at Constant Prices, and Average Wage per Hour Worker. Then in the education variable, the influential indicators are the School Participation Rate Age 7-12, the School Participation Rate Age 13-15, the Pure Enrollment Rate for Elementary/Middle School/Package A, the Pure Enrollment Rate for Junior High School/MTs/Package B, and the Pure Enrollment Rate for Senior High School/SMK/MA/Package C. Furthermore, in the health variable, there are indicators of the Percentage of Households by Province and Source of Adequate Drinking Water, and the Percentage of Ever-Married Women Aged 15-49 Years whose Last Childbirth Processed in a Health Facility which affect the value of HDI in Indonesia in 2023.
Penerapan Partial Least Squares dan Pendekatan Robust dalam Analisis Diskriminan untuk Data Berdimensi Tinggi Rahmadina Adityana; Vionanda, Dodi; Permana, Dony; Fitri, Fadhilah
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/396

Abstract

Classical discriminant analysis, namely linear discriminant analysis and quadratic discriminant analysis, is generally known to suffer from singularity problems when exprerienced with high-dimensional data and is not robust to outliers that make the data not multivariate normally distributed. This research focuses on investigating the classification performance of discriminant analysis on high-dimensional data by applying two approaches, namely the Partial Least Square (PLS) dimension reduction approach as a solution to high-dimensional data and a robust approach with the Minimum Covariance Determinant (MCD) estimator technique that is robust to outliers. The data used for this study is Lee Silverman Voice Treatment (LSVT) data. PLS forms five optimal latent variables that represent predictor variable information. Based on the assumption test of covariance homogeneity between groups, the test statistic value is greater than the chi-square table or the p-value is smaller than the significance level, which means that the assumption is unfulfilled, so quadratic discriminant analysis is applied. The evaluation results showed that the quadratic discriminant analysis analysis model with the MCD approach on the PLS transformed data was able to achieve 81% accuracy, 71% precision, 86% recall, and 77% F1-score. These values indicate that both approaches are able to maintain the efficiency of discriminant analysis classification performance on high-dimensional and multivariate non-normally distributed data.
Co-Authors Abel, Latifa Azhar Ahmad Fauzan Amalia, Nonong Asmar, Ali Asrar, Astari Des Welyyanti Dina Fitria, Dina Dodi Vionanda Edwin Musdi Erliza, Refni Fishuri, Nufhika Fitri, Fadhilah Hamida, Zilfa Hamidah . I Made Arnawa Ikhsan, Easbi Jamaan, Elita Zusti Khairani, Devi Mardhatillah, Aulia Nurul Mawaddah, Nurul Muharromah, Arssita Nur Mukthi, Tessy Octavia Nonong Amalita Putri, Eno Dwi Putri, Sindy Amelia Rahmadila, Rahmadila Rahmadina Adityana Salma, Admi Sarkawi, M. Rafki Suherman, Suherman Syafriandi Syafriandi Syarifuddin, Hendra Tsani, Nahda Maesya Yenni Kurniawati Yerizon Yerizon Yulianti, Lyra Zafirah, Hana Zamahsary Martha Zilrahmi, Zilrahmi