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All Journal SAINSMAT Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Varian Klasikal: Journal of Education, Language Teaching and Science Jurnal Statistika dan Aplikasinya Quantitative Economics and Management Studies SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Jurnal Pengabdian Masyarakat Bhinneka VARIANSI: Journal of Statistics and Its Application on Teaching and Research Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Ininnawa: Jurnal Pengabdian Masyarakat
Mar'ah, Zakiyah
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Students’ Attitude toward A Non-Digital Game-Based Learning in English for Biology Course Pratiwi, Andi Citra; Rahman, Ahmad Ardillah; Haris, Haris; Mar'ah, Zakiyah; Salsabila, Rughaya
KLASIKAL : JOURNAL OF EDUCATION, LANGUAGE TEACHING AND SCIENCE Vol 5 No 3 (2023): Klasikal: Journal of Education, Language Teaching and Science
Publisher : Fakultas Keguruan dan Ilmu Pendidikan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52208/klasikal.v5i3.1123

Abstract

addresses the appeal of game-based learning for students. Despite the prevalence of game-based learning research, limited studies focus on non-digital approaches, particularly in English for Biology courses among English as a Foreign Language (EFL) learners in higher education settings. Accordingly, this quantitative descriptive study aims to fill the research gap by exploring undergraduate students' attitude towards non-digital game-based learning in an English for Biology course. The study, conducted at the Biology Education Department, Universitas Negeri Makassar, involves 64 students who experienced non-digital game-based learning through a collaborative word-guessing game. The research instrument utilized in this study was an attitude questionnaire which demonstrates high validity and reliability. Results of data analysis indicate an overall positive attitude (72.81%) among the students towards non-digital game-based learning, emphasizing enjoyment, motivation, retention, and engagement. Students' favorable disposition could be attributed to the unconventional learning atmosphere created by game elements, including rules, challenges, feedback, and rewards. The study suggests educators consider integrating non-digital game-based learning, fostering enjoyment, engagement, and retention, while emphasizing the importance of autonomy in promoting intrinsic motivation for positive learning outcomes.
Clustering Biplot on Tourist Visits in Indonesia Muthahharah, Isma; Mar'ah, Zakiyah
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 3 No. 1 (2024): March 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i1.3890

Abstract

This research aims to find out whether or not many tourists visited Indonesia after Covid-19 by clustering. This will generate foreign exchange earnings and contribute directly to the country's economic growth. The analytical method used in this research is K-Medoids. K-Medoids is a partition clustering technique that groups a collection of n objects into k clusters by utilizing the objects in the collection of objects to represent a cluster called a medoid. The data in this research used secondary data related to foreign tourist visits to Indonesia from several publication sources in 2017-2021. The results of this research show that there were 3 clusters obtained: Cluster 1 shows the number of tourist visits visiting Indonesia in 2017, 2018 and early 2019 because the Covid-19 pandemic has not yet occurred, Cluster 2 shows that there were no tourist visits in 2020 due to the start of the Covid-19 pandemic, and Cluster 3 indicates low tourist arrivals in 2021 due to the Covid 19 pandemic which temporarily prohibited foreign tourists from visiting Indonesia.
Penerapan Analisis Regresi Spatial Durbin Model Terhadap Penyakit Tuberkulosis Di Provinsi Sulawesi Selatan Tahun 2022 Hadi, Muhammad Akhyar; Aswi; Mar'ah, Zakiyah
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 2 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm459

Abstract

By supplying geographical effects at several sites that serve as the centre of observation, the spatial regression analysis approach assesses the connection between a single variable and multiple other variables. The Spatial Durbin Model is one technique utilised in spatial regression analysis. A special instance of the spatial autoregressive model (SAR) is the spatial Durbin model, which incorporates a spatial lag into the model by adding a lag influence to the independent variables. The goal of this study is to develop a Spatial Durbin model and identify the variables that significantly affect tuberculosis (TBC) in the province of South Sulawesi. The results of this research obtained a Spatial Durbin Model regression model which was significant at a significant level of P-value <α=0.1) using variable influencing factors with a determination coefficient (R2) of 49.74%. Elements that possess a noteworthy impact on the number of Tuberculosis (TB) diseases in South Sulawesi Province are per capita income.
Spatio-Temporal Using Geographically Weighted Panel Regression for Modeling Environmental Quality Index Mar'ah, Zakiyah; Ruliana, Ruliana; Fikriani, Nurul Azurah; Ikhwana, Nur
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.5416

Abstract

The Environmental Quality Index (EQI) represents a numerical measure used to assess Indonesia’s environmental conditions and is published annually by the Ministry of Environment and Forestry. In 2019, the EQI was recorded at 66.55, reflecting a decline of 5.12 points from 71.67 in 2018. This study aimed to analyze EQI across 34 Indonesian provinces during the 2018–2022 period using the Geographically Weighted Panel Regression (GWPR) approach. Data were obtained from the official Statistics Indonesia website. The purpose of employing GWPR was to capture both spatial and temporal variations in the factors influencing EQI, recognizing that environmental dynamics differ by region. Model selection tests for panel data indicated that the Fixed Effects Model (FEM) was the most appropriate specification. Therefore, GWPR was applied in combination with FEM to improve estimation accuracy. The results showed that the significant determinants of EQI varied across provinces, highlighting the heterogeneous nature of environmental challenges. The GWPR with Fixed Effect Model achieved a global R² of 84.38%, a substantial improvement compared to the 42.52% R2 from the conventional global Fixed Effect panel regression. This finding confirmed that GWPR provided stronger explanatory power by incorporating local variations into the analysis. The study concluded that adopting GWPR is essential for more precise modeling of environmental quality. Furthermore, the results highlighted the importance of region-specific environmental policies tailored to each province’s unique conditions in Indonesia 
Comparison of Geographically Weighted Regression (GWR) and Mixed Geographically Weighted Regression (MGWR) Models (Case Study: Crime in South Sulawesi) Ridwan, Indi Nur; Sudarmin; Mar'ah, Zakiyah
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 8 No. 1 (2026)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm503

Abstract

The Geographically Weighted Regression (GWR) model operates by taking into account how the relationships between different factors change across geographic space. Meanwhile, the Mixed Geographically Weighted Regression (MGWR) model permits certain variables to exhibit spatially varying (local) effects, while other variables are assumed to have constant effects across all locations. Both models are relevant to be applied in crime studies influenced by variations in regional conditions. The objective of this study is to evaluate the GWR and MGWR approaches in selecting the best model to explain factors associated with crime cases in South Sulawesi. The data used include the number of crime cases in South Sulawesi in 2024 along with factors presumed to influence them. The investigation's outcomes suggest the GWR model demonstrates higher appropriateness compared to the MGWR model, evidenced by its reduced Akaike Information Criterion (AIC) score and a 98.44% coefficient of determination . Based on the best-fitting model, population density and the number of poor residents were identified as the main factors influencing criminality in South Sulawesi in 2024.
A Comparative Study of M-Estimation and S-Estimation in Robust Regression Models: A Case Study on Crime Rates in Indonesia Hidayat, Rahmat; Ruliana; Mar'ah, Zakiyah; Jumriani
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 14 No 1 (2026): VOLUME 14 No 1, 2026
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v14i1.60365

Abstract

Robust regression is a regression method used to handle outliers in statistical analysis. Robust regression consists of five estimation methods, namely M-estimation (Maximum Likelihood type), LMS estimation (Least Median of Squares), LTS estimation (Least Trimmed Squares), MM estimation (Method of Moments), and S-estimation (Scale). M-estimation is known for having the smallest variance among the estimators, with high efficiency reaching up to 95%, while S-estimation is based on the residual scale of M-estimation and is characterized by a high breakdown point of up to 50%. The 2022 crime rate data in Indonesia contains outliers. According to data from the Central Statistics Agency, there was a drastic increase in crime incidents in 2022, reaching 372,965 reported cases. Therefore, a comparison of robust regression estimation methods was conducted to obtain the best model that explains the factors influencing crime rates in Indonesia. This study employs robust regression using M-estimation and S-estimation with Tukey bisquare weighting. The dependent variable in this study is the number of crimes in Indonesia in 2022, while the independent variables include population density (x₁), open unemployment rate (x₂), number of poor people (x₃), mean years of schooling/MYS (x₄), and labor force participation rate/TPAK (x₅). The results indicate that S-estimation in robust regression provides the best performance among the methods analyzed.
Sosialisasi Sekolah Siaga Bencana (SSB) Sebagai Upaya Meningkatkan Kesiapsiagaan Siswa di SMA Athira Makassar Meliyana, Sitti Masyitah; Muthahharah, Isma; Mar'ah, Zakiyah; Hafid, Hardianti; Juhari, Agusalim
Ininnawa : Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026): Volume 04 Nomor 01 (Mei 2026)
Publisher : Program Studi Manajemen FEB UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/1khhs667

Abstract

Indonesia is a disaster-prone country, making early preparedness efforts essential, particularly in the school environment. This community service activity aims to improve students’ knowledge and preparedness through the socialization of the Disaster Preparedness School (Sekolah Siaga Bencana/SSB) program at SMA Athira Makassar. The methods used include interactive lectures, discussions, and evacuation simulations, with evaluation conducted using pre-test and post-test. The results show an increase in the average preparedness score from 58.9 in the pre-test to 83.8 in the post-test, indicating an improvement of 24.9 points. The highest increase was found in the understanding of evacuation procedures. These findings indicate that the SSB socialization program is effective in enhancing students’ knowledge and disaster preparedness. Therefore, this activity contributes to fostering a disaster aware culture in schools and can serve as a model for implementing education-based disaster preparedness programs.
Co-Authors Agusalim Juhari Aidid, Muhammad Kasim Aswi Aswi, Aswi Besse Khalidatunnisa Fikriani, Nurul Azurah Firdaus Daud Firdiani, Dian Hadi, Muhammad Akhyar Hardianti Hafid Haris Haris, Haris Haris, A. Sulfiana Hasnita, Hasnita Ikhwana, Nur Jumriani Meliyana R, Sitti Masyitah Meyliana, Sitti Masyitah Muthahharah, Isma Novianti, Andi Rima Pratiwi, Andi Citra Rahman, Ahmad Ardillah Rahmat Hidayat Rais, Zulkifli Ridwan, Indi Nur Ruliana Ruliana Ruliana, Ruliana Salsabila, Rughaya Sifriyani, Sifriyani Sitti Masyitah Meliyana R. Sudarmin Syalsabila, Annisa