Proceeding of IJC-MaSTEd (International Joint Conference on Mathematics, Science, Technology, and Education)
Journal Title: The Proceedings of IJC-MaSTEd Online ISSN (e-ISSN): xxxx-xxxx Publisher: Universitas PGRI Pontianak (Managed by Faculty of MIPATEK) Publication Frequency: Yearly Language: Indonesian and English Platform: Open Journal Systems (OJS) The Proceedings of IJC-MaSTEd (International Joint Conference on Mathematics, Science, Technology, and Education) is an international, peer-reviewed conference proceedings series that publishes high-quality research and innovative educational practices in mathematics, science, technology, and interdisciplinary education. This proceedings series serves as a global scholarly platform for researchers, educators, practitioners, and policymakers to disseminate original research, theoretical insights, and practical applications addressing contemporary educational challenges. It emphasizes innovation, inclusivity, collaboration, and sustainability in teaching and learning across diverse educational contexts. The proceedings cover a broad range of topics including mathematics and science education, technology-enhanced learning, STEM/STEAM education, curriculum and assessment, teacher education, inclusive education, digital learning, and interdisciplinary studies related to global and sustainable development. All published papers are presented at the IJC-MaSTEd conference, written in English, and made openly accessible to ensure wide international visibility and impact.
Faculty of MIPATEK, Universitas PGRI Pontianak
All articles published in the Proceeding of IJC-MaSTEd (International Joint Conference on Mathematics, Science, Technology, and Education) are published as open access and are licensed under the Creative Commons Attribution–ShareAlike 4.0 International License (CC BY-SA 4.0). This license permits anyone to read, download, copy, distribute, adapt, and reuse the published work in any medium or format, including for commercial purposes, provided that proper credit is given to the original author(s) and source, a link to the license is included, and any modifications are clearly indicated. Any derivative works must be distributed under the same license (CC BY-SA 4.0). Author Rights Authors retain full copyright of their work. By submitting and publishing in the Proceeding of IJC-MaSTEd, authors grant the publisher a non-exclusive right to publish, distribute, and archive the article as part of the conference proceedings. Authors are allowed to share, deposit, and reuse their published articles for academic, educational, and research purposes, provided proper attribution is given. User Rights Users may freely access and reuse all published content without prior permission, as long as appropriate attribution is provided and the same license terms are maintained. Third-Party Material Any third-party material included in an article must be clearly identified and is not covered by the Creative Commons license unless explicitly stated. By submitting a manuscript to the Proceeding of IJC-MaSTEd, authors confirm that they agree with the open access policy and the license terms stated above.
Analysis of Multiple Choice Assessment Instruments for Grade X Students in Terms of Validity, Reliability, Difficulty Level, Distinction Power, and Distractor Effectiveness
Item analysis is one of the important steps to ensure the quality of learning evaluation instruments in measuring student learning outcomes. This study aims to analyze the quality of assessment instruments in the form of multiple-choice questions on the material of scarcity for grade X students in terms of validity, reliability, level of difficulty, discriminating power, and distractor effectiveness. The study uses a quantitative approach with a descriptive method. The instrument analyzed consists of 30 multiple-choice questions that have been tested on grade X students. Data analysis was carried out through validity tests, reliability using Cronbach's Alpha, level of difficulty, discriminating power, and distractor effectiveness. The results of the study showed that of the 30 items analyzed, 25 items (83.33%) were declared valid and 5 items (16.67%) were declared invalid. The reliability test results obtained a Cronbach's Alpha value of 0.972 which is included in the very high category. Analysis of the level of difficulty showed that 24 items (96%) were in the medium category and 1 item (4%) was in the easy category. The discriminating power analysis showed that 13 items (52%) were in the very good category and 12 items (48%) were in the good category. Meanwhile, the distractor effectiveness analysis showed that 11 items (36.67%) had all functioning distractors, while 19 items (63.33%) still had one or more non-functioning distractors. In general, the developed instrument has met the criteria for good instrument quality and is suitable for use as a learning evaluation tool, although some items and distractors still require revision to improve the quality of measurement.
Innovative and Inclusive Collaborative Approaches to Address Global Challenges in Mathematics, Science, and Technology Education
Copyright (c) 2026 Tesa Manisa, Anggi Syalom, Resty Nofini Nafesda (Author) https://creativecommons.org/licenses/by-sa/4.0
Evaluating the Practicality of Socioscientific Issues-Based Learning Materials for Environmental Pollution Topics
This study aims to develop and analyze the practicality of Socio-Scientific Issues (SSI)-based learning materials on environmental pollution topics to improve the problem-solving skills of Grade X students at SMAN 1 Hulu Gurung. The method used is Research and Development (R&D) with the ADDIE model, consisting of the Analysis, Design, Development, Implementation, and Evaluation stages. Research subjects included 15 students in a small-scale trial and 33 students in a large-scale trial selected through cluster random sampling, along with Biology teachers as respondents. Practicality data were collected through teacher and student response questionnaires and analyzed using a Likert scale. The results showed that the SSI-based learning materials were rated as very practical, with an average response questionnaire percentage of 93% from students and teachers. The small-scale, large-scale, and teacher response trials each yielded practicality percentages of 87%, 92%, and 100%, respectively, all of which fall within the very practical category. These findings indicate that the SSI-based learning materials on environmental pollution topics are feasible and practical for supporting the improvement of students' problem-solving skills in Biology learning.
Copyright (c) 2026 Eka Trisianawati, Handi Darmawan (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of Project Based Learning (Pjbl) Based Student Learning Motivation on Virus Material for Class X SMA Bina Utama Pontianak
This study aims to develop a Student Worksheet (LKPD) based on Project Based Learning (PjBL) on student learning motivation in class X virus material. The subjects of the research trial included validators of media experts and material experts, small-scale tests on 13 students, and large-scale tests on 26 students in class XB of SMA Bina Utama Pontianak. The instruments used include expert validation sheets, student response questionnaires, and learning motivation questionnaires. The validation results showed that the LKPD was declared very valid, with an average value of media expert validation of 91% and 95% of material expert validation. Small-scale tests obtained an average of 82% with a valid category. In large-scale tests, the total score obtained was 77 out of 90, with the average being in the very good category. In addition, the results of the student learning motivation questionnaire showed an increase in various motivation indicators after using the LKPD. Based on the overall findings, the Project Based Learning based LKPD developed through the Hannafin and Peck model was declared valid, practical, and has the potential to increase student learning motivation, so it is suitable for use as teaching material in learning Virus material in class X.
Copyright (c) 2026 Herditiya Herditiya, Mustika Sari (Author) https://creativecommons.org/licenses/by-sa/4.0
Ethnobotany E-Magazine Based on Dayak Kanayatn Local Wisdom on Biodiversity Material : Validity and Practicality
Study This aim For developing an ethnobotany e-magazine based plant drug Kanayant Dayak tribe and testing validity , practicality , and its effectiveness in learning Biology in matter diversity biological sciences in class X of SMA Negeri 1 Sengah Temila. The research method used is Research and development (R&D) with the Hannafin and Peck model. Validation results show that e-magazine is in very valid category , with an average percentage of 88.14% of media experts and 79.44% of expert material . Practicality test by students show very practical category with an average of 91.55%. Effectiveness test through normalized gain calculation produces score of 0.78, which indicates improvement results Study with category high . With thus , ethnobotany e-magazine This worthy used as an interesting , practical and effective learning medium For increase understanding student at a time introduce wisdom local .
Copyright (c) 2026 Mustika Sari, Eka Trisianawati, Jane Arantika (Author) https://creativecommons.org/licenses/by-sa/4.0
Integrating 3C3R Design Problem and Four-Component Instructional Design (4C/ID) into Problem-Based Learning: Addressing Students' Cognitive Load in Biology Education
Problem-Based Learning (PBL) is widely adopted in biology education; however, its implementation frequently generates excessive cognitive load for students, particularly when instructional scenarios are poorly structured or when teachers lack expertise in designing contextually appropriate problems. This study presents the development and validation of a PBL model integrated with 3C3R Design Problem (Content, Context, Connection, Research, Reasoning, Reflection) and Four-Component Instructional Design (4C/ID) frameworks, specifically designed to reduce students' cognitive load in junior high school (SMP) biology classes in Sambas Regency, West Kalimantan, Indonesia. A Research and Development (R&D) approach was employed using the Hannafin & Peck model, encompassing three phases: needs analysis, design, and development. The effectiveness of the integrated model was tested using a quasi-experimental non-equivalent pretest-posttest control group design involving 612 SMP students (n₁ = 306 experimental; n₂ = 306 control) across 20 schools. Expert validation yielded an overall validity score of 4.52 (Highly Valid), and practicality ratings from teachers (M = 4.40) and students (M = 4.29) confirmed classroom feasibility. ANCOVA results demonstrated that the integrated model produced significantly lower intrinsic and extraneous cognitive load and significantly higher germane cognitive load than conventional PBL, with large effect sizes (η²p = 0.31–0.57). These findings underscore the importance of structured instructional design frameworks in mitigating cognitive overload in complex, problems-based science learning environments.
Four-Component Instructional Design (4C/ID)
Copyright (c) 2026 Handi Darmawan, Eka Trisianawati, Mustika Sari (Author) https://creativecommons.org/licenses/by-sa/4.0
Augmented Reality in Mathematics Education: A Bibliometric Analysis
Augmented reality (AR) has emerged as a significant technology-enhanced approach in mathematics education. Despite the growing volume of publications, a comprehensive bibliometric mapping of AR research in mathematics education has yet to be published. This study conducts a bibliometric analysis to explore the trends, key contributors, and future directions of AR research in mathematics education from 2016 to 2025. Data were retrieved from the Scopus database and analysed using VOSviewer software. A total of 190 open-access journal articles published in English were selected after three stages of filtering. The results reveal substantial publication growth, particularly from 2020 onward, with a sharp increase in 2024 and 2025 (46 articles each year). Indonesia is the most productive country (40 articles), followed by Malaysia (30) and the United States (20). Lavicza Z. from Johannes Kepler University Linz is the most productive author (6 articles). Keyword co-occurrence analysis identified five research clusters: AR technology and student learning, STEM education, mathematics and educational technology, geometry and teaching, and mobile AR. Emerging and underexplored themes include computational thinking, spatial ability, game-based learning, and higher education contexts. These findings provide a comprehensive map of the field and a foundation for future research directions.
Copyright (c) 2026 Hodiyanto Hodiyanto, Kwajalynne Costales Alegre Alegre (Author) https://creativecommons.org/licenses/by-sa/4.0
Analysis of Digital Teaching Material Needs Using Book Creator in ICT Subjects for Grade IX
This study aimed to determine the need for digital teaching materials using the Book Creator application in the Information and Communication Technology (ICT) subject in ninth grade. The study employed a qualitative descriptive approach to obtain an overview of the need for digital teaching materials in learning activities. Structured interviews involving ninth grade teachers and students served as data sources during the data collection stage. The interviews were used to gather information regarding the current use of teaching materials, obstacles encountered during the learning process, and the need for more engaging and interactive teaching materials. The study concluded that the learning resources used in ICT instruction are still dominated by printed textbooks and teacher explanations in class. This situation is considered not to fully support active and engaging learning for students. Both teachers and students expressed the need for digital teaching materials that can present material in various formats, such as text, images, audio, and video, to facilitate conceptual understanding and increase learning motivation. The Book Creator application is considered to have potential for use in the development of digital teaching materials due to its ability to integrate various multimedia elements and its ease of use. Therefore, the development of Book Creator-based digital teaching materials is considered crucial to support more effective ICT learning and align with developments in educational technology.
Copyright (c) 2026 Agnes Nantot, Sri Koriyati, Erni Fatmawati (Author) https://creativecommons.org/licenses/by-sa/4.0
Traces of Local Knowledge: An Ethnobotanical Study of Plant Utilization and Local Wisdom of Dayak Communities in West Kalimantan
This research aims to describe the local knowledge of the Dayak people in West Kalimantan in the use of plants and reveal the role of local wisdom in maintaining the sustainability of ethnobotanical knowledge. The research uses a descriptive qualitative approach with ethnobotanical methods. Data collection was carried out through open interviews, participatory observations, and transects with purposively selected key informants, namely indigenous leaders, buyers, and elderly residents who understand traditional knowledge about plants. The data were analyzed descriptively by grouping plants based on categories of use and interpreting the socio-cultural meanings that accompanied them. The results of the study show that the Dayak people use a variety of plants for traditional medicine, food, traditional rituals, as well as ecological and material needs. The types of plants that are widely used include lemongrass, betel nut, ginger, kencur, galangal, soursop leaves, Dayak onions, pandan, bamboo, and areca nut. The use of plants not only has a practical function, but also contains symbolic, spiritual, and ecological values inherent in people's lives. Local wisdom serves as the basis for conservation practices through customary rules, taboos, selective harvesting, and respect for certain forest areas and plants that are considered culturally important. Ethnobotanical knowledge is passed down orally and through direct intergenerational practice, although it currently faces the challenges of modernization and declining involvement of younger generations. This study confirms that the local knowledge of the Dayak people is an important cultural and ecological asset to be documented, preserved, and developed as part of efforts to conserve biodiversity and strengthen the cultural identity of indigenous peoples.
Copyright (c) 2026 Nawawi Nawawi, Jemon Jemon, Betris Deviola, Eka Trisianawati (Author) https://creativecommons.org/licenses/by-sa/4.0
Enhancing Pre-Service Physics Teachers’ Knowledge in Designing 4C-Oriented Problem-Based Learning through an Interactive Reading Strategy with Electronic Learning Materials
This study aims to investigate the effectiveness of an interactive reading strategy supported by electronic learning materials in improving pre-service teachers’ knowledge in designing physics instruction based on a 4C-oriented PBL model. This study employed a pre-experimental design with a one-group pretest–posttest approach. The participants were 24 pre-service physics teachers enrolled in a physics teaching planning course in a physics education program. Data were collected using multiple-choice knowledge tests administered before and after the intervention, as well as interview sheets. The data were analyzed using descriptive statistics, Rasch model analysis, and normalized gain (N-gain) to determine the level of improvement. The results indicate that the implementation of the interactive reading strategy supported by electronic learning materials significantly improved students’ knowledge in designing 4C-oriented PBL instruction. The mean posttest score was higher than the pretest score, with an N-gain value of 0.82, categorized as high. In addition, the distribution of knowledge levels shifted substantially from low and very low categories before the intervention to high and very high categories after the intervention. These findings suggest that the integration of interactive reading strategies with electronic learning materials is effective in facilitating self-regulated learning and strengthening instructional design competence. This approach can be considered an alternative strategy to support the development of pre-service teachers’ pedagogical knowledge, particularly in designing physics instruction aligned with 21st-century skills.
Copyright (c) 2026 Nurhayati Nurhayati, Wahyudi Wahyudi, Dwi Fajar Saputri, Eti Sukadi, Erwina Oktavianty (Author) https://creativecommons.org/licenses/by-sa/4.0
Analysis of Interaction Patterns in Augmented Reality-Based Physics Learning
Augmented Reality (AR) has been increasingly integrated into physics education, providing an immersive and interactive learning experience. While numerous studies have examined AR’s impact on conceptual understanding, engagement, and motivation, limited research has explored the dynamic interaction patterns that emerge when AR is used over multiple learning sessions. This study investigates the evolving interaction patterns among students, teachers, and AR technology in a physics learning environment. Specifically, it examines how student-student, student-teacher, and student-AR interactions change across six AR-enhanced learning sessions on magnetism. A qualitative research approach was employed, involving 36 high school students from West Kalimantan, Indonesia. Data were collected through video-recorded classroom observations, interaction mapping, and field notes. Interaction frequency analysis and qualitative coding were applied to assess engagement trends and learning strategies over time. The findings indicate that student-student interactions fluctuated, with a noticeable decrease in session three, followed by a recovery in later sessions. Student-teacher interactions increased progressively, suggesting a growing reliance on teacher guidance as learning tasks became more complex. Meanwhile, student-AR interactions remained relatively stable, with peaks at the beginning and end of each session, indicating initial exploration and final knowledge validation phases. This study highlights the temporal dynamics of collaborative learning in AR-supported environments, emphasizing the need for strategic integration of AR and teacher scaffolding. The results provide valuable insights for designing more effective AR-based instructional strategies that sustain meaningful student engagement over multiple sessions.
Copyright (c) 2026 Nurussaniah Nurussaniah, Maurish Sofie Rahmi Batita, Nindya Juwita Utimadini (Author) https://creativecommons.org/licenses/by-sa/4.0
Experimental Test of the Use of Montessori-Based Positive-Negative Educational Games on the Mathematical Connection Skills of Students with ADHD
The purpose of this study was to determine the mathematical connection ability of ADHD students after using the positive negative game application based on the Montessori method that has been developed. This research method is Pre Experimental using the One-Shot Case Study Design research design. Based on calculations related to classical completeness, 6 students completed and 1 student did not complete the KKM for mathematics subjects set for Phase D level (equivalent to junior high school) in SLB C for students with special needs, namely a score of 65. Based on the data obtained 85.71% of students completed classically. This means that the learning media of the Positive Negative Educational Game Application Based on the Montessori Method is effective in the learning process. So it can be concluded that the mathematical connection ability of ADHD students is completed classically after participating in learning with the Positive Negative Educational Game Application Based on the Montessori Method which is in accordance with the objectives of this study
Copyright (c) 2026 Utin Desy Susiaty, Muhamad Firdaus (Author) https://creativecommons.org/licenses/by-sa/4.0
Emergent Geometry in Ikan Keturi Piring: A Generative Ethnomathematical Model of Cultural Cognition
The persistent disconnection between abstract geometry and students’ lived cultural experience—particularly in Indonesian junior high school contexts—continues to limit meaningful mathematical understanding. Although ethnomathematics has established that mathematical ideas are embedded in cultural practices, existing studies remain largely descriptive and fail to explain how geometric reasoning emerges or how it can be systematically integrated into instruction. Addressing this gap, this study investigates the geometric structures embedded in the cultural practice of Ikan Keturi Piring, the mechanisms through which these structures emerge, and their transformation into meaningful geometry learning. Using a qualitative approach with focused ethnography, data were collected through participant observation, semi-structured interviews, and documentation involving 12 participants, including practitioners, cultural elders, and mathematics teachers. The findings indicate that geometric reasoning—reflected in circularity, radial symmetry, proportional spacing, and implicit angular partitioning—emerges through iterative spatial regulation guided by cultural principles of balance and harmony. These results demonstrate that geometry is not merely learned as formal abstraction but constructed as a culturally mediated cognitive process that links cultural activity with mathematical reasoning. Theoretically, this study advances ethnomathematics toward a generative epistemological framework that models the emergence of geometry from the interaction between cultural rules and cognitive constraints. Practically, it provides a pedagogical pathway, such as analyzing circular arrangements and determining central angles (360° divided by the number of elements), to support contextual and embodied learning. This study redefines geometry as a culturally grounded system that transforms how mathematical knowledge is understood and taught.
Copyright (c) 2026 Jamilah Jamilah, Sandie Sandie, Abang Thamren (Author) https://creativecommons.org/licenses/by-sa/4.0
Multi-Temporal Shoreline Change Detection Using Satellite Imagery and GIS for Abrasion and Accretion Assessment in Mempawah Coast
This study examines the spatio-temporal dynamics of coastal erosion and accretion in Mempawah, West Kalimantan, from 1972 to 2025, using multi-temporal satellite imagery, GIS analysis, and field validation. The results reveal a critical shift from net erosion (1972–1990) to net accretion (2000–2025), driven by the synergistic implementation of breakwaters and mangrove restoration. Coastal villages like Mempawah Hilir and Kuala Secapah experienced severe erosion (139,04 ha in 2010–2020) due to high-energy waves and limited sediment supply, while riverine villages such as Sungai Kunyit benefited from sediment deposition, achieving minimal erosion (2,01 ha) and significant accretion (26,59 ha). Breakwaters proved effective in villages with >90% coverage (e.g., Sungai Duri I, II), reducing erosion to near zero, but were less effective in areas with partial coverage (e.g., Sungai Bakau Besar Laut, 10,13%). Mangroves played a complementary role, dissipating wave energy and trapping sediments, particularly in Tanjung (2.897,62 m thickness). However, agricultural expansion and urbanization disrupted sediment pathways, exacerbating erosion in some areas while enhancing accretion in others. The Kapuas River sustained accretion in Peniti Luar and Pulau Panjang, whereas shorter rivers failed to offset sediment loss. Integrated watershed-coastal management is essential to address these disparities, as highlighted by global best practices. This study offers a template for sustainable coastal management in data-scarce regions.
Copyright (c) 2026 Mustofa Mustofa, Wiwik Cahyaningrum, Nadine Andara Septiani (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of a Website-Based Tuition Payment Information System at Boedi Oetomo High School, Pontianak
This study aims to design, create, produce products and determine the feasibility of a website-based tuition payment information system. This study uses the Research and Development (R&D) method through the stages of analysis, design, development, implementation, and evaluation. Before being implemented to users, the system was first validated by media experts and practitioner experts. The subjects of this study were students of grades X and XI of SMA Boedi Oetomo Pontianak, totaling 22 students. Data collection techniques used direct communication techniques, indirect communication, documentation techniques with unstructured interview data collection tools, questionnaires and documentation. The data analysis technique used was quantitative descriptive statistical analysis techniques. The results of product validation by 2 media expert validators were 92% with the criteria of "Very Feasible", and practitioner experts were 99% with the criteria of "Very Feasible", and the results of implementation to students had an average percentage of 85% with the category of "Very Good" criteria so that it can be concluded that the development of a website-based tuition payment information system at SMA Boedi Oetomo is feasible to be used as an information system.
Copyright (c) 2026 Vindo Feladi, Ilham Tri Jaya, Satrio Husaini Wibowo (Author) https://creativecommons.org/licenses/by-sa/4.0
Students’ Needs Analysis for Video-Based Learning in Python Programming at Madrasah Aliyah
This study aims to analyze students’ needs for video-based learning in Python programming at Madrasah Aliyah. The research employed a quantitative descriptive approach using a survey method. The participants were students who had learned or were currently learning Python programming. Data were collected through a Likert-scale questionnaire covering indicators such as the need for learning media, preferences for video-based learning, difficulties in understanding the material, and learning style compatibility. The data were analyzed using descriptive statistics, including percentages and mean scores. The results indicate that all indicators fall into the high category, with percentages above 80%. This finding suggests that students have a strong need for video-based learning to support their understanding of Python programming. Learning videos are perceived as effective in helping students comprehend abstract concepts, enhancing learning motivation, and facilitating independent learning. This study concludes that the development of multimedia-based learning videos is essential to improve the effectiveness of Python learning in Madrasah Aliyah. Therefore, designing learning media that align with students’ needs and characteristics is crucial to support the quality of education in the digital era.
Copyright (c) 2026 Dini Oktarika, Winna Dharmayanti, Muhamad Arpan (Author) https://creativecommons.org/licenses/by-sa/4.0
Enhancing Vocabulary in Preschoolers: Teaching English Through Songs
This action research investigated the effectiveness of using songs to enhance English vocabulary among young learners. The study involved nine participants consisting of three children aged five years old and six children aged six years old. The research followed the action research cycle of planning, action, observation, and reflection. English songs related to daily greetings and routines, body parts and movements, animals, vegetables and numbers were used as teaching tools during the lessons. Data were collected through pre-test and post-test assessments, classroom observations, and the researcher’s reflective journal. The findings showed an improvement in pupils’ vocabulary knowledge, with the average score increasing from 6.4 in the pre-test to 11.9 in the post-test. Observations also indicated increased participation, enthusiasm, and confidence among pupils during song-based activities. The study concludes that using songs is an effective and engaging strategy for improving English vocabulary learning among young learners.
Copyright (c) 2026 Christy Anak Manggi, Helen Edward Brandah, Dolly Anak Edy Jemat (Author) https://creativecommons.org/licenses/by-sa/4.0
Implementation of PBL-STEAM Model to Improve Student Learning Outcomes on The Material Environmental Pollution
A multidisciplinary approach in education through STEAM needs to be optimized to improve contextual learning outcomes and impact real life. Efforts should be made to integrate the PBL and STEAM models in learning related to the environment. The purpose of this study is to analyze the application of the PBL-STEAM model in improving student learning outcomes related to environmental pollution materials. The method in this study is a quantitative descriptive study with a pretest-posttest control group design. The PBL model is applied to student group control, and the PBL-STEAM model is applied to student group experiments on materials pollution environment. Data collection techniques include tests, observations, and interviews. Samples in this study are students in class VII semester two at one of the school media in the first country in Sambas Regency and Bengkayang Regency, West Kalimantan Province. The sampling technique is in the form of purposive sampling. Data analysis techniques with count N-Gain score, and percentage score results observation and interviews. Found that there is an improvement in scores in the group experiment compared to the group control, with the N-Gain score in the category height. The sheet results observation of learning activities and interview questionnaire sheets in the form of student response sheets showed a high category. Conclusion: This study, namely the implementation of the PBL-STEAM model, can improve student learning outcomes in environmental pollution. It is hoped that PBL- STEAM can also be applied to other materials.
Copyright (c) 2026 Intan Kusumawati, Adenia Wirasti, Aril Aril, Miqdad Rafi, Wati Wati, Kamal Indah (Author) https://creativecommons.org/licenses/by-sa/4.0
Hoax News Detection on Urban Issues Using Naive Bayes with Chi-Square Feature Selection
The rapid spread of hoax news in digital media has become a serious concern because it can mislead the public, influence opinions, and potentially trigger social unrest, particularly in urban-related issues. The increasing volume of online information also makes manual verification difficult, highlighting the need for automatic hoax detection systems using machine learning approaches. This study aims to develop a hoax news detection model using the Multinomial Naive Bayes algorithm combined with Chi-Square feature selection to improve classification efficiency. The dataset consists of 1,000 Indonesian news articles related to urban issues, consisting of hoax and factual news collected through web scraping from fact-checking websites and online news portals. The research process includes text preprocessing stages such as case folding, tokenizing, stopword removal, and stemming, followed by TF-IDF feature extraction. Chi-Square feature selection was applied to reduce feature dimensionality by selecting the most relevant terms. The dataset was divided into training and testing sets using an 80:20 ratio. Model performance was evaluated using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The experimental results show that the Multinomial Naive Bayes model without feature selection achieved the highest accuracy of 98.5%. Meanwhile, the application of Chi-Square feature selection with 200 selected features achieved an accuracy of 90.5%, while using 100 features resulted in an accuracy of 86.5%. These results indicate that although feature selection slightly reduces classification performance, it significantly reduces feature dimensionality while maintaining acceptable performance. Overall, this study demonstrates that Multinomial Naive Bayes is effective for hoax news classification, while Chi-Square feature selection provides an efficient alternative when dimensionality reduction is required.
Copyright (c) 2026 Bimli, Wilda Susanti (Author) https://creativecommons.org/licenses/by-sa/4.0
A Convolutional Neural Network Approach for Multi-Class Waste Image Classification
Waste management has become an increasingly important global issue, requiring effective solutions to support proper waste sorting and recycling processes. Manual waste classification is often inefficient and prone to human error, particularly when dealing with large volumes of waste. In recent years, image classification using deep learning techniques has emerged as a promising approach to automatically identify different types of waste based on their visual characteristics. This study aims to develop and implement a Convolutional Neural Network (CNN) model for multi-class waste image classification. The proposed model utilizes a transfer learning approach based on the EfficientNetV2 architecture. The model was trained using a publicly available waste image dataset obtained from Kaggle consisting of 4,752 images across multiple waste categories. The research process includes data preprocessing, image augmentation, model training, and a series of experimental scenarios to analyze the influence of different hyperparameter configurations, including variations in dropout rate, fine-tuning layers, learning rate, dense layer structures, and L2 regularization. Experimental results show that the best-performing configuration, which applies dropout rates of 0.3 and 0.2, achieved an accuracy of 94.03% with a weighted F1-score of 0.9399. To further evaluate the model’s practical performance, the selected model was tested using 30 real-world waste images captured directly from the surrounding environment. The testing results indicate that the proposed CNN model is capable of classifying waste images effectively and demonstrates promising potential for implementation in automated waste sorting systems.
Copyright (c) 2026 Raymond Chandra, Irwan Irwan, Yenny Desnelita, Dewi Nasien (Author) https://creativecommons.org/licenses/by-sa/4.0
Mathematical Modelling of Tuberculosis with Vaccination and Saturated Incidence Rate in Indonesia
This study was motivated by the high incidence of tuberculosis (TB) in Indonesia over the years. Various preventive intervention strategies have been developed to reduce the spread of TB among vulnerable populations. However, tuberculosis continues to contribute significantly to mortality in Indonesia. In this study, a deterministic mathematical model is proposed to describe population dynamics by combining vaccine efficacy and vaccination rates. This model includes individuals in both infectious and latent states. Individuals in the latent stage are not infectious and do not show clinical symptoms, but they carry Mycobacterium tuberculosis bacteria in their bodies. This latent state can progress to active TB when the immune system weakens. Therefore, the latent population acts as a reservoir of infection that can contribute to the emergence of new TB cases in the future. Based on TB data from Indonesia, sensitivity analyses and numerical simulations were conducted to examine the effect of variations in vaccine efficacy and vaccination rates on transmission dynamics involving the latent and infectious populations. The results showed that increasing vaccine efficacy significantly reduced the size of the latent population, which in turn decreased the transmission rate among infected individuals. Furthermore, higher vaccine efficacy reduces the controlled reproduction number affected by latent and infected groups, thereby limiting the spread of TB in susceptible populations. Furthermore, increased vaccination rates reduce the controlled reproduction number associated with latent individuals, contributing to the suppression of disease transmission. These findings highlight the importance of developing vaccines with higher efficacy and expanding vaccination coverage as key strategies for controlling and ultimately eliminating tuberculosis in the community
Copyright (c) 2026 Indriasri Raming, Syamsuddin Toaha, Firman (Author) https://creativecommons.org/licenses/by-sa/4.0
Structural Strength Analysis and Mold Fan Blade Design Optimization using Finite Element Analysis
This study aims to analyze the structural performance of a fan blade and its injection molding mold prior to the manufacturing stage using a Computer-Aided Design (CAD) and Computer-Aided Engineering (CAE) simulation approach. The scope of the study includes three-dimensional modeling of the fan blade and injection mold, a mesh study to obtain convergent simulation results, and mechanical response analysis under torsional and compressive loading conditions. Finite Element Analysis (FEA) was performed using SolidWorks Simulation with variations of fan blade materials, namely ABS, PA Type 6, and PEEK, as well as mold materials consisting of cast alloy steel, cast carbon steel, and cast stainless steel. The simulation results indicate that a mesh size of 6 mm provides stable von Mises stress values with an average error of 0.05%. An increase in applied torque on the fan blade results in a linear increase in stress and displacement, where PEEK exhibits the best structural stability with the smallest deformation. In the injection molding simulation, increasing compressive force leads to a linear increase in von Mises stress in both the cavity and core, with the maximum stress occurring in the core mold made of cast stainless steel. Furthermore, the simulation identifies several critical regions experiencing maximum stress, particularly in the fan blade shaft area.
Copyright (c) 2026 Azka Tristan Virsano Kusuma, Fakhri Tri Wibowo, Abdillah Sabari, Evan Agit Prianto, Stefanus Nathanael Mahesa, Dandun Mahesa Prabowoputra (Author) https://creativecommons.org/licenses/by-sa/4.0
Bridging the Gap in Deep Learning Implementation: Design of Scientific Investigation Training for Science Teachers
The transformation of science education within the Deep Learning policy framework requires a fundamental reconstruction of teachers’ pedagogical practices toward authentic, reflective, and contextual scientific inquiry. This study aims to develop the content and design of a Deep Learning–Based Scientific Inquiry training model for science teachers to bridge the gap between policy expectations and classroom practices. A context analysis study was conducted using qualitative document analysis of the Regulation of the Minister of Education No. 1 of 2026 on Process Standards, the Academic Manuscript of Deep Learning, the Science Learning Outcomes document, and theoretical frameworks on levels of inquiry and teacher professional development. Data were analyzed through reduction, categorization, and conceptual synthesis to formulate an epistemologically and pedagogically coherent training model. Findings indicate that deep learning in science positions science process skills as the epistemological pathway for constructing conceptual understanding through the cycle of understanding–applying–reflecting. However, classroom practices remain predominantly procedural, resembling cookbook laboratory activities. To address this challenge, the DINAMIS training model (Identification–Integration–Analysis–Simulation–Implementation–Self Reflection) was developed by adapting the Experiential Learning Cycle into a discipline-specific professional development framework. The model demonstrates vertical coherence (from conceptual understanding to reflective practice) and horizontal integration (deep learning principles, science process skills, and levels of inquiry). Conceptually and practically, this training design has the potential to strengthen science teachers’ conceptual and implementative capacities in facilitating authentic inquiry, thereby enhancing students’ scientific literacy and higher-order thinking skills.
Copyright (c) 2026 Asep Agus Sulaeman (Author) https://creativecommons.org/licenses/by-sa/4.0
Strengthening Early Childhood Environmental Education and Community Awareness for Sustainable Marine Ecotourism in the Togean Islands National Park, Indonesia
The development of marine ecotourism in Togean Islands National Park offers a strategic pathway to balance environmental conservation and local economic development. However, its sustainability is constrained by low community awareness, limited participation, and insufficient environmental understanding. This study aims to analyze the role of community awareness and early environmental education in supporting sustainable marine ecotourism development. This research employs a qualitative approach combined with the Analytical Hierarchy Process (AHP). Data were collected through literature review, field observations, and stakeholder analysis, while comparative analysis was conducted with Komodo and Bunaken National Parks. The findings show that local livelihoods remain dependent on extractive activities, reflecting limited awareness of conservation benefits. Nevertheless, pilot ecotourism initiatives indicate that increased community engagement can reduce destructive practices and diversify income sources. Environmental education, particularly at an early stage, plays a crucial role in shaping pro-conservation behavior. AHP results identify environmental education as the top strategic priority, followed by community empowerment. This study proposes an integrated framework linking awareness, education, behavior, participation, and sustainable livelihoods. It concludes that sustainable marine ecotourism requires an integrated approach combining environmental education, community empowerment, and inclusive governance to align conservation objectives with socio-economic benefits.
Copyright (c) 2026 Iin Maulina, Novindra (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of a High-Speed Vessel Design Using a Combination of Optimal Shape and Materials Based on 3D Modeling
Indonesia, as a maritime country, has a vast territorial sea that requires efficient sea transportation. Fast boats are an important solution to support sea transportation mobility, patrols, and logistics activities. Fast boat design needs to consider hull shape and the selection of appropriate materials to produce optimal, stable, and efficient structural performance. This study was conducted to analyze the effect of hull geometry and material type variations on the structural strength of fast boats through 3D modeling based on Finite Element Analysis (FEA) in design software. Three hull shapes were analyzed, namely V-shaped hulls, round hulls, and flat hulls. The three shapes were then adjusted to three material options, namely aluminum alloy, AISI 1036 steel, and titanium. Each model was given an external load of 1,000 N as a simulation of the force acting on the structure, so that the stress values, deformation levels, and strains that appeared in each combination of shape and material could be obtained. Based on the simulation results, it was found that the V-shaped hull using aluminum material showed the best performance, with the smallest deformation value and a relatively higher strength-to-weight ratio compared to other combinations. Aluminum was chosen as the best material because it has a lower density, good corrosion resistance in marine environments, and provides higher energy efficiency compared to steel and titanium. In conclusion, the V-shaped hull design and aluminum material can be recommended as a superior fast boat design concept in terms of structural strength, operational stability, and motion efficiency when operating in water.
Copyright (c) 2026 Veda Fauzan Wardiansah, Muhammad Farisan Zhafiri, Dandun Mahesa Prabedaowoputra (Author) https://creativecommons.org/licenses/by-sa/4.0
The Influence of Quality Policies and Digital Learning Ecosystems on Human Resource Competitiveness in the Industry 5.0 Era
Digital transformation in education had been recognized as important for improving learning quality and strengthening human resource competitiveness in the industry 5.0 era, yet a gap had persisted between policy and classroom implementation. This study aimed to examine the effects of digital-based education quality policies and digital learning ecosystems on human resource competitiveness and to identify the most influential factor. A quantitative explanatory approach had been applied. Data were collected through closed questionnaires, structured interviews, and documentation involving 68 teachers at SMAN 3 Pontianak using total sampling. Analysis was conducted using SEM-PLS to assess relationships among variables. The results showed that digital-based quality policies had significantly influenced competitiveness (β = 0.37; p < 0.001), while digital learning ecosystems had exerted a stronger effect (β = 0.42; p < 0.001). Both variables jointly explained 51% of the variance. The study concluded that the digital learning ecosystem had been the most dominant factor and highlighted its critical role in enhancing education quality and human resource competitiveness.
Copyright (c) 2026 Noviah Dwi Putranti, Eko Handoyo, Fathur Rokhman, Nina Oktarina (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of a Contextual E-book Integrated with 3D Images of Pico hydro Rainwater for Alternative Energy Materials to Improve Learning Independence of Students at SMA Negeri 3 Simpang Hilir
This study aimed to examine: (1) the design of a contextual e-book integrated with 3D picohydro rainwater images for alternative energy materials; (2) the feasibility of the e-book for supporting students’ learning independence; (3) the effectiveness of the e-book in improving learning independence; and (4) students’ learning independence profiles before and after its use. The study used the ADDIE development model, consisting of Analysis, Design, Development, Implementation, and Evaluation. The analysis stage covered performance, concept, student, and learning objective analysis. The design stage focused on preparing the e-book, teaching modules, and learning independence instruments. The development stage involved expert validation, revisions, and limited trials. The implementation stage used a quasi-experimental non-equivalent pretest-posttest control group design. The evaluation stage assessed all stages of the study. The participants were 94 students of SMA N 3 Simpang Hilir. The developed products included teaching modules, e-books, feasibility sheets, student response questionnaires, and learning independence tests. Data were analyzed descriptively and inferentially using MANOVA at a 0.05 significance level. The findings showed that the developed e-book design was contextual and 3D-based, the e-book was feasible to use, it effectively improved students’ learning independence, and students’ learning independence improved after implementation.
Copyright (c) 2026 Janariani Janariani, Supahar Supahar (Author) https://creativecommons.org/licenses/by-sa/4.0
Comparative Analysis of Machine Learning Algorithm and Feature Selection on Student Grade Small Datasets
Assessment of student academic performance is an important aspect in improving the quality of the learning process in higher education. With the development of Machine Learning (ML) techniques, predictive analysis of student assessment data can be carried out more accurately and efficiently. This research aims to analyze the comparative performance of several ML algorithms and evaluate the effectiveness of various feature selection techniques on student assessment datasets. The dataset used is a limited dataset that contains attributes that represent components of student academic assessment. The research process includes determining cross-validation, applying ML algorithms, applying feature selection techniques, and performance evaluation. The ML algorithms compared are Naïve Bayes, K-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Tree, Random Forest, and AdaBoost. Several feature selection techniques used are Information Gain (IG), Gain Ratio (GR), Gini Dicrease (GD), ReliefF. Evaluation of the performance of the ML algorithm uses the Confusion Matrix in the form of accuracy, precision, recall and F1-score, while the performance evaluation of the feature selection technique uses Spearman Correlation. Experimental results show that the SVM algorithm shows the best performance followed by k-NN. However, based on computing time testing, the Tree algorithm shows the fastest time. Apart from that, the comparison results of feature selection techniques show that Gini Decrease has the best correlation. The findings of this research contribute to selecting a more effective educational data analysis method and can be a reference for developing ML algorithms in student academic evaluation
Copyright (c) 2026 Agus Wantoro, Nur Aminudin, Dita Septasari, Ningsiah Ningsiah, Ikna Awaliyani (Author) https://creativecommons.org/licenses/by-sa/4.0