cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Rusliadi
Contact Email
garuda@apji.org
Phone
+6282135809779
Journal Mail Official
febri@apji.org
Editorial Address
Jln. Perum Cluster G11 Nomor 17 Jl. Plamongan Indah, Pedurungan, Semarang, Provinsi Jawa Tengah, 50195
Location
Kota semarang,
Jawa tengah
INDONESIA
International Journal of Science and Mathematics Education
Published by Asosiasi Riset Ilmu Matematika dan Sains Indonesia
ISSN : 30627206     EISSN : 30627214     DOI : 10.62951
Core Subject : Education, Social,
Education Mathematics Social Sciences
This journal is a peer-reviewed and open access journal of Mathematics and Science Education. The fields of study in this journal include the sub-family of Mathematics and Science Education
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 32 Documents
 1   2   3   4 
Development of a Real-Time Air Quality Monitoring System Using IoT and Data Analytics Ahmed Boukhalfa; Mohammed Benslimane; Lynda Ghemri
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.55

Abstract

This paper introduces a real-time air quality monitoring system based on the Internet of Things (IoT) integrated with advanced data analytics. The system uses low-cost sensors to gather data on air pollutants, which are then processed using cloud computing and visualized through a web application. Field tests conducted in urban and suburban areas demonstrate the system’s effectiveness in providing accurate, real-time air quality information, enabling timely responses to pollution events.
A Comparative Analysis of Quantum Computing and Classical Computing in Solving Linear Algebra Problems Andrea Montemurro; Marco F. Durante; Silvia Giordano
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.56

Abstract

Quantum computing offers promising alternatives to classical approaches for solving complex linear algebra problems. This paper presents a comparative study of the performance of quantum algorithms versus classical algorithms in solving systems of linear equations and matrix operations. Through simulation and analysis, we demonstrate that while quantum computing holds advantages in specific problem sets, classical computing remains efficient for general applications. These findings highlight the current limitations and potential of quantum computing.
Machine Learning Approaches for Climate Change Prediction: A Comparative Study Ardea Dewantari Prasetya; Abdul Latif Rahman; Muhammad Indra Novanto
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.57

Abstract

This research explores various machine learning approaches, including deep learning and ensemble methods, to predict climate change indicators. We focus on temperature and precipitation trends using large datasets spanning multiple decades. By comparing the performance of algorithms like CNN, RNN, and random forests, we identify the most accurate models for specific climate variables. Our findings demonstrate that ensemble models provide better accuracy and reliability, especially for temperature predictions.
Mathematical Modeling of Epidemic Spread in Urban Environments Using the SEIR Model with Environmental Factors Warih Zunu Pamungkas; Adam Dista Prasetya
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.58

Abstract

This paper presents an improved SEIR (Susceptible-Exposed-Infectious-Recovered) model to simulate the spread of infectious diseases in urban environments, taking into account environmental factors such as population density, mobility, and air quality. By applying the model to a range of urban case studies, we analyze the impact of each factor on transmission rates and propose strategies for optimal intervention. The results show that cities with higher levels of mobility and pollution experience faster disease spread, which requires targeted health policies.
Optimization Algorithms for Solving Non-linear Problems in Natural Resource Management Muhammad syahrizal ibnu jihad; Yuliana Dwi Hapsari; Satrio tegar wicaksono
International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i2.59

Abstract

Natural resource management involves complex decision-making processes that often result in non-linear optimization problems. This study explores the application of genetic algorithms (GA) and particle swarm optimization (PSO) to manage resources like water and forest reserves more efficiently. We compare the effectiveness of these algorithms in achieving sustainable utilization while minimizing environmental impact. The results show that GA outperforms PSO in forest management scenarios, while PSO is more suitable for water resource distribution.
Optimizing Heart Disease Prediction : A Comparative Study of Machine Learning Models Using Clinical Data Budiman Budiman; Nur Alamsyah; Elia Setiana; Valencia Claudia Jennifer Kaunang; Syahira Putri Himmaniah
International Journal of Science and Mathematics Education Vol. 1 No. 4 (2024): December: International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i4.96

Abstract

Cardiovascular disease is a leading cause of death globally, necessitating effective predictive systems. This research aims to analyze the effectiveness of various machine learning (ML) models—Logistic Regression (LR), Random Forest (RF), Naive Bayes (NB), Support Vector Classifier (SVC), and K-Nearest Neighbors (KNN)—in predicting heart disease using publicly available health data. The study involved pre-processing data, training models, and evaluating them using accuracy, precision, recall, F1-score, and G-Mean metrics. The results show that KNN is the most reliable model, with the highest accuracy of 92%. Significant health features were identified, such as chest pain type and maximum heart rate. The study contributes to improving clinical decision support systems by identifying optimal ML models for heart disease prediction.
Effect of pH on COD Reduction in Biogas Formation Nadiareta Sitorus; Desniorita Desniorita
International Journal of Science and Mathematics Education Vol. 1 No. 4 (2024): December: International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i4.99

Abstract

Biogas is a mixture of gases formed from the decomposition of organic materials with the help of bacteria through an anaerobic fermentation process (airtight) to produce biogas in the form of methane gas (CH4) that can be managed. In biogas production, pH is one of the factors that affects the production process where an inappropriate pH will cause the performance of microorganisms in degrading organic matter into biogas to be less than optimal. This can be seen from the COD reduction produced, namely COD reduction will increase when operating conditions are at optimal pH, for this reason, conditioning the operating process according to the optimum pH is needed. So that in order to maximize the production of biogas produced, research was conducted to determine the optimum pH in the biogas production process carried out at PT AMP Plantation. In this study, biogas production data was collected so that the optimum pH in the production process carried out was known. From the research that has been carried out, the optimum pH for the biogas production process is 7, which produces the highest COD reduction of 91.78%.
The Influence Of Chemical Oxygen Demand (COD) And pH Of Pome As Biogas Raw Material On The CH4 Produced Popi Febrianti; Dwi Kemala Putri
International Journal of Science and Mathematics Education Vol. 1 No. 4 (2024): December: International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v1i4.100

Abstract

POME is liquid wastewater derived from processing of palm fruit. POME contains nitrogen, phosphate, potassium, magnesium and calcium compounds, that can be used as a good fertilizer for plantations. However, before application, POME must be processed because direct use of unprocessed POME can damage the environment. PT XYZ utilizes POME as raw material for biogas through an anaerobic fermentation process to produce alternative energy for electricity generation, however, biogas production at PT XYZ produces CH4 levels that do not meet the desired standard, namely 60%, while the value obtained is still 57%, so it can occure an incomplete combustion process in the engine. Therefore, research was carried out to analyze the influence of POME's Chemical Oygen Demand (COD) and the pH of POME as biogas raw material on the CH4 produced. Meanwhile, based on measurements of POME pH, fluctuations are caused by environmental conditions, therefore before the feed enters the biodigester, the first treatment is increasing pH until 6-7 to adjust the optimal conditions for bacteria working to break down organic substances. The results shows that the estimated potential for a Biogas Power Plant (PLTBg) with a production capacity of fresh fruit bunches (FFB) of 60 tons/hour, the high generating capacity is influenced by the large COD value, meaning that the COD value greatly influences the CH4 produced, but must also be in accordance with Other factors that influence CH4 production such as pH, temperature, stirring and others.
Development of PBL Stem-Based Science Learning E-Module to Increase Critical Thinking and Creativity in Global Warming Materials Sri Bona Ayu; Dadan Rosana
International Journal of Science and Mathematics Education Vol. 2 No. 1 (2025): March : International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v2i1.187

Abstract

The study aims to develop and evaluate STEM PBL-based science learning media to enhance students' critical thinking and creativity. The objectives include describing, producing, and assessing the feasibility, validity, practicality, and effectiveness of these media for grade VII students. This Research and Development (R&D) study follows the 4D model: define, design, develop, and disseminate. The developed media take the form of a digital Flipbook accessible via smartphones and PCs. A limited trial involved 22 students and one educator, while a field test included 51 students from SMPN 1 Binongko, Wakatobi Regency, divided into experimental and control groups. Data were collected through tests, interviews, questionnaires, and validation sheets. Feasibility, validity, and practicality were analyzed descriptively, while effectiveness was evaluated using the N-Gain, MANOVA, and Cohen's effect size tests. The results indicate that the STEM PBL-based Flipbook presents real-life problems, their causes, and solutions, encouraging critical thinking and creativity. It meets validity and feasibility criteria as assessed by expert lecturers. Educators and students also rated it as highly practical for learning. Finally, the Flipbook was found to be effective in improving students' critical thinking and creativity, with a significance value of 0.000 < 0.05.
Optimizing IT Remote Workers Mental Health Prediction using Feature Engineering Fikri Muhamad Fahmi; Budiman Budiman; Nur Alamsyah
International Journal of Science and Mathematics Education Vol. 2 No. 2 (2025): June: International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v2i2.193

Abstract

Given the increasing prevalence of mental health challenges in digital work settings, especially among IT remote workers, early detection mechanisms have become critically important. This study aims to improve the prediction accuracy of mental health conditions among IT remote workers by integrating feature engineering techniques within machine learning models. Five algorithms consisting of Random Forest, Logistic Regression, K-Nearest Neighbors, Decision Tree, and Naive Bayes were evaluated. The Random Forest model achieved the best performance, with 83% accuracy, 83% precision, 100% recall, and a 90% F1-score, followed closely by Logistic Regression with 82% accuracy. Nevertheless, the results demonstrate the feasibility of applying machine learning to support the early detection of mental health risks, offering a strong foundation for future research in predictive analytics and the development of intelligent support systems within digital work environments.

Page 2 of 4 | Total Record : 32

 1   2   3   4 

Filter by Year

2024 2025


Reset
Filter By Issues
All Issue Vol. 2 No. 4 (2025): December: International Journal of Science and Mathematics Education Vol. 2 No. 3 (2025): September: International Journal of Science and Mathematics Education Vol. 2 No. 2 (2025): June: International Journal of Science and Mathematics Education Vol. 2 No. 1 (2025): March : International Journal of Science and Mathematics Education Vol. 1 No. 4 (2024): December: International Journal of Science and Mathematics Education Vol. 1 No. 3 (2024): September : International Journal of Science and Mathematics Education Vol. 1 No. 2 (2024): June:International Journal of Science and Mathematics Education Vol. 1 No. 1 (2024): March:International Journal of Science and Mathematics Education