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Jurnal Penelitian Pendidikan IPA (JPPIPA)
Published by Universitas Mataram
ISSN : 24602582     EISSN : 2407795X     DOI : -
Core Subject : Science, Education, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics
Science Educational Research Journal is international open access, published by Science Master Program of Science Education Graduate Program University of Mataram, contains scientific articles both in the form of research results and literature review that includes science, technology and teaching in the field of science. The Science Educational Research Journal is published twice in a year in January and July editions. The editors receive writing in Indonesian or English, either from the university or from outside the university.
Arjuna Subject : -
Articles 6,882 Documents
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Development of a Three-Tier Higher Order Thinking Skills (HOTS) Assessment Instrument on Acid Base Material Assisted by Gimkit Ananda Emyliah; Jusniar; Ramlawati
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.15993

Abstract

This study aims to describe the development process of a HOTS three-tier assessment instrument on acid-base material assisted by Gimkit and to find out the validity, reliability, and practicality of the HOTS three-tier assessment instrument on acid-base material assisted by Gimkit that was developed. The data source for the validity test came from 2 validators, while the reliability and practicality tests came from 2 subject teachers and 31 11th-grade students of Merdeka 2 at SMA Negeri 1 Campalagian. The reliability and practicality trials were conducted in the even semester of the 2025/2026 academic year. The research method used was a research and development (R&D) with the Plomp model, which includes the preliminary investigation phase through observation and interviews, the design and realization phase covering the design and creation of the HOTS three-tier assessment instrument on acid-base material, and the test, evaluation, and revision phase including validity tests and limited trials to find out reliability and practicality. The developed instruments consist of: (1) instrument grid, (2) HOTS three-tier assessment instrument, (3) answer key, (4) validity sheet, and (5) perception questionnaire. The results show that the HOTS three-tier assessment instrument product is highly valid with an inter-rater reliability value of 1.00, reliable, and very practical. Based on the results, it can be concluded that the instrument can be an important reference for teachers in assessing students’ cognitive aspects and misconceptions.
Development of a Project-Based Learning E-Module with a Deep Learning Approach for Elementary Science Learning Endang Susilowati; Arif Rahman Aththibby; Dasrieny Pratiwi; Friska Octavia Rossa
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.16020

Abstract

This study developed a Project-Based Learning (PjBL) e-module integrated with a deep learning approach for teaching the human respiratory system in elementary school. The research employed the 4D model: define, design, develop, and disseminate. At the define stage, curriculum demands, learner characteristics, concepts, and learning tasks were analyzed. The design stage aligned PjBL syntax with contextual problems, a simple lung-model project, scientific literacy activities, reflective prompts, and assessment instruments. Product quality was examined through validation by three material experts and three media experts, followed by a limited practicality test. The material experts awarded a total of 78 of 80 points (97.50%), and the media experts awarded a total of 76 of 80 points (95.00%), resulting in a mean feasibility score of 96.25%, categorized as very feasible based on the predetermined feasibility criteria. Practicality reached 91% according to three teachers and 89% according to fifteen Grade V students, with a mean score of 90%, categorized as very practical based on the predetermined practicality criteria. The findings indicate that the module is content-appropriate, visually organized, navigable, and operationally usable for limited elementary science learning. Its main contribution is the explicit pedagogical alignment among project stages, conceptual connections, evidence-based reasoning, and reflection. A controlled effectiveness study remains necessary before causal claims can be made regarding gains in problem-solving and scientific literacy.
Comparative Analysis of Convolutional Neural Network (ResNet-50) and Vision Transformer (ViT-B/16) for Histopathological Image Classification of Colorectal Cancer Muhammad Fazly Qusyairy; Habibullah Akbar; Wahyu Purnama Magribi; Khusnul Fajri Rhomadon
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.14880

Abstract

The diagnosis of colorectal cancer (CRC) through histopathological images requires high accuracy to support appropriate clinical decisions. Although Convolutional Neural Networks (CNN) have become the gold standard in medical image analysis, the emergence of Vision Transformer (ViT) architecture offers a new paradigm based on global attention mechanisms (self-attention) that is claimed to be superior on large-scale datasets. However, the effectiveness of ViT-B/16 on medical datasets with limited sample sizes and high texture variation remains debatable. This study aims to comprehensively evaluate the performance of the ViT-B/16 architecture compared to ResNet-50 on the NCT-CRC-HE-100K histopathology dataset, which consists of 9 network classes. The performance of both models was tested using equivalent training scenarios. The evaluation was conducted multidimensionally, covering classification metrics (Accuracy, F1-Score), training stability, feature space separability (t-SNE), visual interpretability (Grad-CAM), and computational efficiency. The experimental results show that ResNet-50 significantly outperforms ViT-B/16 with a test accuracy of 93.24%, compared to ViT-B/16 which only achieves 57.11%. The t-SNE analysis revealed that ViT-B/16 failed to form well-separated feature clusters due to a lack of inductive bias to recognize local features such as cell membrane edges. Failure analysis shows that ViT-B/16 often misclassifies adipose cells as mucus and smooth muscle as tumors. In terms of efficiency, ResNet-50 is 5.8 times lighter in storage size and has lower inference latency. This study concludes that CNN-based architecture (ResNet-50) is still far superior, more stable, and more feasible for clinical implementation than ViT-B/16 in the context of medium-scale histopathological image classification.
Problem Based Learning on Socio-Scientific Issues to Strengthen Students’ Environmental Care Character at Ban Buketamong School Friendship 128, Cho Airong, Narathiwat, Thailand Taufik Hidayat; Ainun Mardiyah Lubis; Syahruddin Aritonang; Maryam bnesa; Darwis Lubis
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.14902

Abstract

This study aims to analyze the effect of Problem Based Learning integrated with socio-scientific issues on strengthening students’ environmental care character at Ban Buketamong School Friendship 128, Cho Airong, Narathiwat, Thailand. The research employed a pre-experimental one-group pretest–posttest design involving 30 Grade 8 students. Data were collected using a 25-item environmental care character questionnaire and analyzed through descriptive statistics and a paired sample t-test. The results showed that the mean score increased from 67.37 in the pretest to 82.80 in the posttest. The paired sample t-test indicated a significant difference between pretest and posttest scores (p < 0.05), with a large effect size (Cohen’s d = 10.28). These findings demonstrate that Problem Based Learning based on socio-scientific issues significantly enhances students’ environmental awareness, responsibility, participation, and sustainable behavior. The integration of authentic environmental problems into learning activities provides meaningful opportunities for students to develop responsible attitudes and moral reflection toward environmental challenges. Therefore, this instructional approach is recommended to promote environmental care character among junior secondary school students.
The Effect of Digital Literacy and Self-Regulated Learning on Students’ Academic Achievement at Saiburi ChaengPrachakarn School, Pattani, Southern Thailand Erdiansyah; Ainun Mardiyah Lubis; Syahruddin Aritonang; Mayeeta Hawae; Aslamiyah Rambe
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.14903

Abstract

This study examined the effects of digital literacy and self-regulated learning on students’ academic achievement at Saiburi ChaengPrachakarn School, Pattani, Southern Thailand. A quantitative explanatory correlational design was employed with 30 secondary school students selected through proportional random sampling. Data were collected using validated questionnaires on digital literacy and self-regulated learning, while academic achievement was measured using students’ semester examination scores. Descriptive statistics and multiple linear regression were used for data analysis. The findings revealed that digital literacy positively and significantly influenced academic achievement (β = 0.491, p < 0.05). Self-regulated learning also had a positive and significant effect (β = 0.503, p < 0.05). Simultaneously, both variables significantly predicted academic achievement (F = 304.077, p < 0.001), explaining 95.7% of the variance (R² = 0.957). These results indicate that students with stronger digital competence and self-regulated learning skills achieve better academic outcomes. Strengthening both competencies is therefore essential for improving academic performance in technology-integrated secondary education.
Reading, Finding, Discussing, and Talking Learning Model with Socio-Scientific Issues and Islamic Values for Scientific Literacy Zuhair Abdullah; Dian Rif’iyati; Andhin Oktovania Ramadhani
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.14908

Abstract

This study aims to develop a Reading, Finding, Discussing, and Talking (RFDT) learning model that encompasses socio-scientific issues and Islamic values to improve students' scientific literacy. This model is considered more comprehensive in developing students' knowledge and skills. The research method used is research and development (R&D) with the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The sample in the study amounted to 48 students taken using a simple random sampling technique. Data were collected through observation techniques, interviews, validation questionnaires, and scientific literacy tests, then descriptive analysis was carried out using normalized gain and inferential analysis using an independent t-test. The results showed that the developed model was considered very valid by experts with an average score of 4.43. The application of the model showed an increase in acquisition scores in the experimental class compared to the control class, although the t-test results did not show a significant difference (p > 0.05). Several possible causes for the insignificant t-test results include the small number of samples and teachers still in the adaptation stage to the model. However, this model received a positive response from students so it is suitable for use in integrative, contextual, and religious learning.
Consumption-Based Water Footprint Analysis of Food and Non-Food Sectors for Sustainable Management of the Jambo Aye Watershed Nabila Sam Dwitara; Purwana Satriyo; Syahrul Syahrul
Jurnal Penelitian Pendidikan IPA Vol 12 No 6 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i6.14912

Abstract

Water is a vital resource that supports the sustainability of life and the economic activities of communities. This study analyzes the water footprint (WF) of food and non-food consumption as a basis for water resource management in the Jambo Aye Watershed, Aceh Province, Indonesia. A quantitative descriptive approach was applied using secondary data on household food and non-food consumption from the National Socio-Economic Survey (SUSENAS) of Statistics Indonesia (BPS) and population data for 2023 and 2024. The WF was calculated by multiplying the per capita consumption of each commodity by its virtual water coefficient, adopting the standardized global coefficients of the Water Footprint Network (Mekonnen & Hoekstra), and aggregating the results at the watershed scale; the analysis employed total (aggregate) virtual water values without disaggregating the green, blue, and grey components. The results show that the WF of food consumption reached 688.90 million m³ in 2023 and increased by 8.27% to 745.84 million m³ in 2024, accounting for more than 99% of the total WF, with rice as the main contributor. The WF of non-food consumption was considerably smaller, rising by 9.11% from 3.00 million m³ in 2023 to 3.28 million m³ in 2024, driven mainly by housing and household facilities. These findings indicate that water resource management in the Jambo Aye Watershed should prioritize improving water-use efficiency in the food sector, particularly rice-based agriculture, to support the long-term sustainability of water resources
Evaluation of Soil Degradation Due to Land Use Change Using Geospatial Analysis in the Ecological Zone of North Konawe Regency Safiun; Widiatmaka; Dwi Putro Tejo Baskoro
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.15216

Abstract

Land use change is one of the major factors affecting environmental quality, particularly soil degradation. North Konawe Regency has experienced rapid regional development characterized by the expansion of agricultural land, oil palm plantations, settlements, and mining activities. This study aimed to evaluate soil degradation caused by land use change in the ecological zone of North Konawe Regency during 2003, 2013, and 2023. The results showed that forest area decreased from 451,821.4 ha (88.0%) in 2003 to 432,564.5 ha (84.3%) in 2013 and further declined to 421,032.7 ha (82.0%) in 2023. The reduction of 30,788.7 ha of forest area indicates an increasing extent of degraded land due to land conversion. In contrast, oil palm plantations increased from 3,413.0 ha to 24,986.4 ha, while mining areas expanded from 424.3 ha to 12,463.2 ha. Converted lands, particularly mining areas, showed higher levels of soil degradation characterized by reduced soil porosity and permeability. The findings indicate that increasing land use intensity contributes directly to soil degradation in North Konawe Regency.
Growth Response of Cocoa Seedlings (Theobroma cacao L.) to Concentration and Application Interval of Forest Organic Fertilizer Novi Mailidarni; Jauhari Jauhari
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.15277

Abstract

Vegetation plays an essential role in regulating soil fertility through nutrient cycling, organic matter accumulation, and interactions with soil microorganisms. This study aimed to evaluate the chemical characteristics and soil fertility status under vegetation dominated by Mimosa invisa L., Crotalaria anagyroides L., and Imperata cylindrica L. Beauv. in Baitussalam District, Aceh Besar Regency, Indonesia. Soil samples were collected from the 0–20 cm layer using a non-factorial randomized block design with five replications. Soil chemical analyses included pH, organic carbon, total nitrogen, available phosphorus, exchangeable potassium, calcium, magnesium, sodium, cation exchange capacity (CEC), exchangeable sodium percentage (ESP), and exchangeable hydrogen. Data were analyzed using analysis of variance (ANOVA), followed by the Least Significant Difference (LSD) test at the 5% significance level. The results showed that vegetation type significantly affected available phosphorus and exchangeable calcium but had no significant effects on soil pH, total nitrogen, exchangeable potassium, magnesium, sodium, CEC, ESP, or exchangeable hydrogen. Soils under Mimosa invisa generally exhibited higher soil pH, organic carbon, total nitrogen, CEC, and exchangeable calcium than those under Crotalaria anagyroides and Imperata cylindrica. High exchangeable sodium and ESP values across all vegetation types indicated persistent effects of seawater intrusion following the 2004 Indian Ocean tsunami. These findings demonstrate that vegetation type influences nutrient cycling and selected soil chemical properties, with leguminous vegetation showing greater potential to improve soil fertility. The study provides valuable information for developing sustainable soil management and ecological restoration strategies in tropical coastal ecosystems.
Machine Learning-Based Prediction of Cayenne Pepper Price Dynamics in Local Markets of East Lombok Wardatul Aeni; Elisa Anggraeni; Hartrisari Hardjomidjojo
Jurnal Penelitian Pendidikan IPA Vol 12 No 7 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i7.15301

Abstract

Fluctuations in cayenne pepper prices in local markets are difficult to predict and often create uncertainty in farmers' decision-making. This study analyzes cayenne pepper price dynamics and develops a Random Forest-based prediction model using weekly price data (2021–2024) from four markets in East Lombok Regency: Pancor, Aikmel, Paok Motong, and Sakra. Predictor features included lagged prices (24 weeks), rolling mean and standard deviation (4-, 8-, and 12-week windows), and seasonal sine–cosine transformations. The dataset was split chronologically into training (80%) and testing (20%) sets to preserve temporal dependencies. The model achieved R² values of 0.86–0.93, with MAE of IDR 2,657–4,206 per kg and RMSE of IDR 3,519–4,946 per kg. It captured general price trends and seasonal patterns well but showed limited accuracy in predicting extreme price spikes, likely due to the inherent limitation of tree-based algorithms in extrapolating beyond historical training ranges and the absence of external variables such as supply volume. These findings indicate that cayenne pepper price dynamics follow learnable historical patterns, and the model has potential as a data-driven decision-support tool to help reduce, though not eliminate, market uncertainty and support local food security

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