Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Statistika dan Aplikasinya International Journal of Educational Research Excellence (IJERE)
Tonah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Three Paradigms for Learning Mathematics with the Aid of Artificial Intelligence: A Phenomenological Study of Prospective Teacher Students Syfa Nurfadilah; Gifa Nur Arofah; Toto Subroto; Tonah
International Journal of Educational Research Excellence (IJERE) Vol. 3 No. 2 (2024): July-December
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijere.v3i2.923

Abstract

The 21st century has seen rapid changes in educational practices, mainly due to technological advancements such as artificial intelligence. Especially in today's digital age, technology is essential in transforming education. One prominent innovation is the use of AI in the context of learning. This research aims to discover prospective teachers' learning processes using AI. In addition, this research seeks to determine the position of AI in learning mathematics for prospective teachers. The participants are Mathematics Education students of Universitas Swadaya Gunung Jati (UGJ) Cirebon. This qualitative study uses phenomenological methods by collecting data from each research subject about experiences regarding the use of AI in solving several math problems. This research provides insight into how prospective teachers can utilize AI technology in the mathematics learning process. In addition, this research is essential because it contributes to the development of technology-based pedagogy, a significant trend in global education today. This research uses data collection methods through observation, interviews, and content. The results of this study are that 3 paradigms from previous research are in line with the theory of 3 paradigms: (1) AI-directed students as recipients, (2) AI-supported students as collaborators, and (3) AI-empowered students as leaders. Most participants in this study were collaborators in these three paradigms.
LINEAR MIXED MODEL-LASSO WITH MLE AND REML ESTIMATION ON POVERTY DATA IN JAVA ISLAND Santi, Vera Maya; Indriana, Devi; Ladayya, Faroh; Tonah
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09202

Abstract

Poverty in Indonesia, especially in Java, remains a major challenge despite the island being the economic and political centre of the country. The government has made many efforts but has not been effective in overcoming poverty. The hierarchical structure of poverty data may cause higher-level clusters to be random effect. One approach that can be used to represent the relationship between the poverty rate in each regency/city in Java and the factors that influence it with the province as a random effect is a linear mixed model (LMM). The number of factors that can affect poverty results in multicollinearity. The application of LASSO is used in this study to overcome multicollinearity, select, and generate variables that are significant to poverty in Java. The data used in this study consists of 85 regencies and 34 cities in Java Island involving 20 independent variables. The results show that the factors that influence the poverty rate are average years of schooling, non-food expenditure, number of households with housing assets owned, percentage of households with a dirt floor, and percentage of households with PLN lighting. The LMM-LASSO is a linear model augmented with a LASSO penalty function to address multicollinearity and incorporates random effects into the model. This approach is suitable for modeling the poverty rate, as indicated by its smaller AIC and BIC values compared to the conventional linear mixed model. In addition, based on the ICC value, the province as a random effect contributes significantly to the variability of the data at the district/city observation level in Java Island.
Co-Authors Gifa Nur Arofah Indriana, Devi Ladayya, Faroh Syfa Nurfadilah Toto Subroto Vera Maya Santi