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Jurnal Pendidikan Informatika dan Sains
Published by IKIP PGRI Pontianak
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Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Physics
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Articles 518 Documents
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Classification of molly ornamental fish using VGG16 architecture Adikara Alif Nurrahman; Dedy Hermanto
Jurnal Pendidikan Informatika dan Sains Vol. 14 No. 2 (2025): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v14i2.9889

Abstract

Molly fish (Poecilia sphenops) is one of the ornamental fish species that is widely cultured. This study aims to develop a classification system for ornamental molly fish using the VGG16 model, trained with on-the-fly data augmentation techniques (flip, zoom, rotation, and translation). The dataset used consists of 1,750 images of molly fish, divided into seven different species: Black, Blue Electric, Calico, Dalmatian, Golden Black, Platinum, and Sunkist. Data augmentation is performed dynamically during the training process without saving the transformation results, aiming to increase data diversity and help the model recognize patterns more accurately. The experimental results show that the optimal combination of parameters, namely a learning rate of 1e-5, a batch size of 32, and 50 epochs, achieved a training accuracy of 97.80%, validation accuracy of 99.61%, and test accuracy of 99.62%. Additionally, very high precision (99.63%), recall (99.62%), and F1-Score (99.62%) values were achieved. Although there were minor classification errors in the "Black" class predicted as "Sunkist," these errors were minimal and did not affect the overall results. This study shows that with the right parameter settings and the use of augmentation techniques, the VGG16 model can provide classification results with fairly high accuracy for molly ornamental fish. This model also has the potential to be applied in the ornamental fish aquaculture industry, particularly in image-based automatic detection systems.
Analysis of ChatGPT-5's scientific explanation ability in solving direct current circuit problems Depa Zulpianti; Judyanto Sirait; Lanang Maulana Aminullah
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.9987

Abstract

This study examined GPT-5's ability to construct scientific explanations when solving direct-current (DC) circuit problems. The analysis focused on whether the model could provide correct claims, relevant evidence, and logically connected reasoning grounded in physics concepts. A qualitative descriptive design was employed, with GPT-5 accessed through ChatGPT Plus as the unit of analysis. The model responded to six image-based multiple-choice items adapted from a basic DC-circuit assessment. The items addressed electric current, potential difference, and electric power as represented by bulb brightness in series and parallel circuits. To standardize the elicited responses, each item was presented in a new conversation together with the same structured prompt requiring a claim, evidence, and reasoning. The responses were evaluated using an analytic rubric with a maximum score of five per item. GPT-5 obtained 30 out of 30 points, corresponding to 100% across the six items. Its responses consistently selected the correct option, applied appropriate equations and circuit principles, and connected the evidence to the claim through coherent reasoning. These findings indicate that, under the specific prompting conditions and limited item set used in this study, GPT-5 demonstrated strong scientific explanation performance in basic DC-circuit contexts. Nevertheless, the findings should not be generalized to other physics topics, prompt formats, or AI systems without further investigation.
Analysis of first-year university students' conceptual understanding of direct current electric circuits Judyanto Sirait
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10012

Abstract

The concept of direct current (DC) electricity is taught from elementary school through higher education. The concepts covered include electric current, voltage (potential difference), and electric circuits in series and parallel configurations. However, students often experience difficulties in understanding these concepts, and such misconceptions frequently persist into university education. Therefore, this study aimed to analyze first-year university students’ conceptual understanding of direct current electric circuits. A descriptive survey with qualitative explanation was employed to investigate students’ conceptions in depth, involving 107 participants. Students completed multiple-choice questions and were asked to provide written explanations for each selected answer. The analysis revealed that more than 50% of the students were unable to answer the questions correctly. Most students believed that a battery is a constant source of electric current. In addition, many students assumed that adding more batteries would always increase the voltage regardless of the battery configuration. Furthermore, students demonstrated difficulties in understanding the behaviour of bulbs in series and parallel circuits. These findings indicate that first-year university students hold significant misconceptions related to direct current electricity. Therefore, educators need to implement instructional approaches that effectively support students in constructing scientifically accurate concepts of DC electric circuits.
Application of the generative learning model assisted by e-modules and PhET simulations to improve students' problem-solving skills on straight-line motion material for Grade XI at SMA YPK Agnes Selvia Putri; Haratua Tiur Maria Silitonga; Firdaus Firdaus
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10026

Abstract

This study aims to determine the effectiveness of implementing a generative learning model assisted by e-modules with PhET simulation in improving students' problem-solving skills on the topic of straight-line motion in Grade XI of SMA YPK. The researcher employed a quantitative approach with a pre-experimental research design, specifically the one-group pretest-posttest design. The sample in this study consisted of all 12 Grade XI students from SMA YPK Pontianak. Data collection techniques included tests and observations. The tests administered were a pre-test and a post-test. The instruments used in this study were the test instruments and a teaching module containing Student Worksheets (Lembar Kerja Peserta Didik) and a Lesson Plan (Rencana Pelaksanaan Pembelajaran). Data analysis in this study utilized the Wilcoxon Signed Rank Test to determine the mean difference between the pretest and posttest scores, and the N-Gain test was used to determine the magnitude of the learning model's effectiveness. The results of the Wilcoxon Signed Rank Test showed an Asymp. Sig. (2-tailed) value of 0.002 (< 0.05), indicating that there is a significant difference between the pretest and posttest scores. This means that the treatment given had a significant effect on improving students’ problem-solving skills. This finding is supported by the N-Gain calculation, which produced an average N-Gain value of 0.73, indicating that the effectiveness falls into the high category.
Needs analysis for developing a STEM-PBL-based student worksheet (LKPD) in physics learning on Newton's second law at the senior high school level Juwita Priyanti; Erwina Oktavianty; Naim Sulaiman
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10084

Abstract

This study aims to analyze the needs for developing a STEM-PBL-based Student Worksheet (LKPD) on Newton's Second Law at the senior high school level. As the initial stage of a research and development process, the needs analysis provides a foundation for producing a modern and effective worksheet aligned with the demands of twenty-first-century learning. A survey method was employed, involving 125 grade XI students selected through purposive sampling, together with several physics teachers in Pontianak. Data were collected using a validated needs-analysis questionnaire distributed via Google Form. The results show that physics learning remained dominated by the lecture method and conventional media such as textbooks and PowerPoint, so that student engagement was not optimal. Nevertheless, most students had positive experiences with worksheets that helped them understand the material, and both students and teachers expressed strong interest in the STEM approach and the Problem-Based Learning (PBL) model, which were perceived as engaging, contextual, and supportive of critical thinking and problem-solving skills. These findings indicate that developing a STEM-PBL-based LKPD is needed as an instructional-material innovation appropriate to the demands of the twenty-first century.
Gamification of West Kalimantan local wisdom through a visual-interactive interface: Development of an inclusive edugame for deaf students Irwan Adhi Prasetya; Novi Aryani Fitri; Muhammad Faqih Dzulqarnain; Muhamad Syafarudin Ilham
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10144

Abstract

This study aims to develop an inclusive cooking-themed edugame based on West Kalimantan culture for deaf students through the integration of a visual-interactive interface, a BISINDO avatar, and local cultural content. The development employed the ADDIE model, comprising needs analysis, interface design, and Unity-based prototype creation involving 3D modeling, rigging, and initial integration of BISINDO animation. The edugame was designed to be interactive, multimodal, and readily accessible in accordance with the characteristics of users with special needs. The implementation and validation results indicate that the edugame falls within the highly feasible category, with an acceptance rate of 80.94%. Overall, the edugame received positive user responses regarding readability, interactivity, clarity of instructions, and the appropriateness of its cultural content. This study demonstrates that the integration of gamification, BISINDO, and local wisdom has the potential to serve as an inclusive and adaptive learning strategy for deaf students
Development of an IoT based automatic fish feeding system for Nile tilapia culture in a recirculating aquaculture system Slamet Rahayu; Mohammad Iqbal; Roni Suhartono; Bagus Rino Arfian
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10276

Abstract

Feed is the single largest cost component in Nile tilapia aquaculture, frequently accounting for more than sixty percent of total production costs. However, in most Indonesian smallholder operations, feed is still dispensed manually based on visual estimation. Existing Internet of Things feeders reported in the literature generally automate the timing of feed delivery but do not provide feedback on the actual amount of feed dispensed. They are also rarely evaluated in a Recirculating Aquaculture System, where uneaten feed increases the load on the biofilter. This study addresses this limitation by designing, implementing, and experimentally evaluating an Internet of Things based automatic feeder with closed loop gravimetric dosing integrated into a Recirculating Aquaculture System for Nile tilapia culture. The system combines an ESP32 microcontroller, a load cell sensor, a servo actuated feed gate, a BTS7960 controlled direct current auger, and a real time clock scheduling module. A web based interface enables real time adjustment of feed ration and feeding schedule. The feeder was evaluated over ten dispensing cycles using a target ration of fifty grams, and its performance was compared with manual feeding during a rearing trial. Gravimetric dosing achieved an average error of two point four percent and an average dosing accuracy of ninety seven point six percent, with an average deviation of one point two grams per feeding cycle. During the rearing trial, the experimental group consumed twelve kilograms of feed, whereas the control group consumed fourteen kilograms, representing a feed reduction of fourteen point three percent. The experimental group also achieved a feed conversion ratio of one point four six, compared with two point zero zero in the control group. Survival reached ninety two point five percent in the experimental group and eighty one percent in the control group. Mean individual body weight increased from two hundred forty five grams in the control group to two hundred eighty grams in the experimental group. Size uniformity also improved, with the coefficient of variation decreasing from fifteen percent to eight percent. These findings demonstrate that integrating gravimetric feedback into an Internet of Things based feeder provides measurable feed savings beyond scheduling automation alone and offers a practical and appropriate technology solution for small scale Nile tilapia production in Recirculating Aquaculture Systems.
Artificial intelligence as a writing scaffold: Higher education students' experiences with AI-supported academic writing Dedi Irwan; Bintang Septia Permata Darosta; Faldi Tri Arrival; Nur Lu’lu’il Maknunah; Widia Agustina
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10370

Abstract

The rapid adoption of artificial intelligence (AI) in higher education has reshaped students’ academic practices, particularly in relation to academic writing. While prior studies have largely examined attitudes or perceived effectiveness of AI-based tools, limited attention has been given to how AI-supported writing unfolds as a learning process shaped by student agency, contextual constraints, and reflective practice. Addressing this gap, the present study adopts a qualitative, process-oriented perspective to explore how higher education students experience and perceive the use of ChatGPT in supporting academic writing. Using a qualitative research design, semi-structured interviews were conducted with nine higher education students representing language studies, social sciences, and exact sciences. Data were analysed thematically to capture patterns related to writing support, perceived learning processes, challenges, and students’ strategies for reflective and critical AI use. The findings indicate that ChatGPT supports academic writing by reducing initial barriers to writing, enhancing engagement and motivation, and providing personalised feedback that facilitates language development and revision. Students reported improvements in writing quality and increased confidence, suggesting that AI can function as both cognitive and affective scaffolding. However, these benefits were accompanied by concerns regarding rigid or inconsistent AI-generated responses, uneven technological competence, and limited institutional guidance. Importantly, students demonstrated critical awareness by evaluating AI outputs and combining them with other academic sources, highlighting reflective and responsible use rather than passive reliance. Overall, the study conceptualises AI-supported academic writing as a dynamic and mediated learning process rather than a discrete technological intervention. By proposing a process-oriented qualitative model, this study contributes to ongoing debates on AI in higher education and underscores the need for pedagogical strategies and institutional frameworks that promote ethical, reflective, and learning-oriented integration of AI technologies.
Cyber intrusion detection model using deep learning based on augmented image-based feature construction Mauludil Asri M. Cane; Kusrini Kusrini; Melwin Syafrizal
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10499

Abstract

Network intrusion detection remains a critical challenge in cybersecurity, particularly due to the increasing volume and complexity of network traffic. To address this issue, this study develops a deep learning framework that transforms tabular NSL-KDD data into image representations using the Lightweight Multi-feature Image Generator for Tabular Data (LM-IGTD). In addition, Homogeneous Noise Generation (HoNG) is applied to enrich feature diversity prior to processing. The transformed data are then classified using a Convolutional Neural Network (CNN) under a binary classification scheme to distinguish between normal and attack activities. Experimental results on the KDDTest+ dataset show that the proposed approach achieves an accuracy of 81.81%, an F1-score of 81.51%, and a ROC-AUC of 95.11%. The results indicate that LM-IGTD significantly contributes to improving the model’s ability to distinguish between classes, particularly in terms of ROC-AUC, while HoNG enhances classification performance in terms of accuracy and F1-score. However, a trade-off is observed between improved classification accuracy and the model’s probability ranking capability. Overall, these findings highlight that LM-IGTD provides an effective feature representation strategy, while HoNG offers a complementary contribution depending on the evaluation metric prioritized.
Pengembangan media pembelajaran berbasis AR (augmented reality) pada materi topologi jaringan semester genap kelas X Akuntansi SMKN 1 Jelai Hulu Ilham Kurnia Septiadi; Matsun Matsun; Chandra Lesmana; Muhamad Arpan
Jurnal Pendidikan Informatika dan Sains Vol. 14 No. 2 (2025): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v14i2.10532

Abstract

Penerapan teknologi dalam pendidikan tidak hanya berfokus pada peningkatan akses informasi, tetapi juga memperkaya metode pengajaran yang memungkinkan visualisasi data secara lebih mendalam. Oleh karena itu, penelitian ini bertujuan untuk mengetahui proses pengembangan, kelayakan, respon siswa, serta keefektifan media pembelajaran berbasis Augmented Reality (AR) di SMKN 1 Jelai Hulu. Penelitian ini menggunakan metode penelitian Research and Development (R&D) dengan pendekatan Define, Design, Development, dan Disseminate (4D). Penelitian ini mengumpulkan data dengan metode observasi, wawancara, angket (kuesioner), tes (pretest dan posttest), dan dokumentasi. Penelitian ini memperoleh hasil uji kelayakan oleh validator ahli materi sebesar 90% dengan kategori sangat layak, hasil uji kelayakan oleh validator ahli desain sebesar 87,77% dengan kategori sangat layak, hasil respon dari 17 orang siswa kelas X Akuntansi sebesar 89,01% dengan kategori sangat baik, serta hasil pretest sebesar 62,64 dan hasil posttest sebesar 90 yang menunjukkan bahwa media pembelajaran berbasis Augmented Reality (AR) efektif dalam meningkatkan hasil belajar.

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