Edutic - Scientific Journal of Informatics Education
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Development of a Web-Based Online Judge for Java Programming Examinations to Enhance Interactive Learning Environments
Full text linkThis paper addresses the challenges in traditional programming assessment, such as scalability and delayed feedback. We present the development of a web-based examination platform for the Java programming language. The system is designed with a decoupled architecture, integrating the CodeMirror editor to create an interactive learning environment and leveraging the Glot.io API for secure, sandboxed code execution. This approach mitigates security risks associated with evaluating untrusted code and provides students with real-time, automated feedback. The resulting platform offers a robust, secure, and pedagogically enhanced solution for online programming assessment, improving both the efficiency for instructors and the learning experience for students
Development of a Web-Based Information System Integrated with Artificial Intelligence and Gamification of the Jokotole Folklore to Strengthen Character Education and Multiliteracy of Junior High School Students in Madura
Full text linkLiteracy and character education in schools still often use conventional methods that are less appealing to students and do not utilize technology relevant to the local culture. This problem causes students to have low motivation to learn and difficulty understanding material based on folklore. This study aims to develop a Web-Based Information System Integrated with Artificial Intelligence and Gamification of the Jokotole Folklore as an interactive learning medium that is appropriate to the cultural context of Madura. The research method used a waterfall model that included needs analysis, system design, implementation, testing, and maintenance. The resulting product was the "Lakaran Jokotole" platform, which contained folk tale material, an AI chatbot feature, gamified quizzes, mini games, and a teacher dashboard. The results of the expert system validation test showed a functionality percentage of 100% (highly valid), while the user trial results obtained a usability score of 90% (highly feasible). These findings indicate that the system has fulfilled technical and pedagogical aspects and is effective as a medium for multiliteracy learning and character education for junior high school students in Madura
Inovasi Model Intrusion Detection System (IDS) menggunakan Double Layer Gated Recurrent Unit (GRU) dengan Fitur Berbasis Fusion
Full text linkIntrusion Detection System (IDS) merupakan komponen penting dalam menjaga keamanan jaringan dari ancaman siber. Dengan meningkatnya jumlah dan kompleksitas serangan, diperlukan metode deteksi yang lebih akurat dan efisien. Dalam penelitian ini, diusulkan model IDS berbasis Double Layer Gated Recurrent Unit (GRU) yang dirancang untuk meningkatkan akurasi deteksi dan mengurangi kesalahan prediksi. Arsitektur GRU ganda memungkinkan pengambilan fitur temporal yang lebih baik dari data lalu lintas jaringan. Model ini diuji menggunakan dataset standar IDS, dan hasil eksperimen menunjukkan bahwa metode ini mampu mencapai tingkat akurasi yang lebih tinggi dibandingkan dengan model GRU tunggal dan metode pembelajaran mesin konvensional. Selain itu, penerapan proses feature fusion di antara dua lapisan GRU memberikan kontribusi signifikan terhadap peningkatan akurasi dan pengurangan tingkat false positive rate (FPR). Temuan ini mengindikasikan bahwa arsitektur yang diusulkan efektif dalam mendeteksi serangan jaringan secara real-time dengan efisiensi komputasi yang lebih baik
Optimizing UKT Prediction Based on Socio-Economic Features: A Multimodel Evaluation with Feature Selection Srategies
Full text linkDetermining the tuition fee group (UKT) for new students in Indonesian public universities represents a complex challenge requiring an equitable, data-driven approach. This study introduces an integrative feature selection strategy that combines five popular techniques Chi-Square, Recursive Feature Elimination (RFE), LASSO Regression, Random Forest Importance, and Exploratory Factor Analysis (EFA) to extract the most relevant attributes from 53 socioeconomic variables of prospective students at Universitas Negeri Surabaya. As a novelty, the study identifies intersecting features consistently selected by all five methods and evaluates their impact on the performance of five classification algorithms: Support Vector Machine (SVM), Decision Tree, Random Forest, K-Nearest Neighbor (KNN), and Naïve Bayes. Experimental results demonstrate a significant improvement in accuracy, with SVM increasing from 0.7550 to 0.7810. These findings confirm that integrative feature selection can optimize model performance while reducing data complexity. This study provides a replicable methodological contribution for developing transparent and adaptive classification systems based on socioeconomic data in higher education contexts
Analisis Penerimaan Teknologi Kecerdasan Buatan dalam Pembelajaran Pemrograman Web: Pendekatan Model Penerimaan Teknologi
Full text linkIn the rapidly evolving digital era, the application of artificial intelligence (AI) technology in education, particularly in web programming learning, presents new challenges and opportunities. This study aims to explore students' perceptions of using AI in web programming education by employing the Technology Acceptance Model (TAM) as a theoretical framework. The research method used is a quantitative approach with a survey design, involving 47 students from the Information Technology Education Study Program at Mojosari Institute of Technology. The analysis results indicate that students have a positive perception of the ease of use and usefulness of AI, as well as a strong intention to continue using this technology in their learning. Despite the challenges in implementing AI, the findings suggest that AI has significant potential to enhance the effectiveness of web programming education. This research is expected to provide insights for the development of more effective curricula and teaching strategies
Implementation of ResNet50 Based on Transfer Learning for Sugarcane Leaf Disease Detection
Full text linkSugarcane (Saccharum officinarum) is a vital commodity in Indonesia’s sugar industry and is highly susceptible to leaf diseases such as Mosaic, RedRot, Rust, and Yellow, which significantly reduce yield quality and quantity. This study proposes an automatic disease classification system using the ResNet50 architecture with a transfer learning approach, offering a more systematic evaluation compared to previous studies that typically tested only a single configuration or focused on other crops. The dataset consists of 3,250 RGB images across five classes after preprocessing and augmentation to address class imbalance. Eight model configurations were evaluated by combining epoch values (20, 40) and learning rates (0.0001, 0.001, 0.01, 0.1). The best performance was achieved by the configuration with 20 epochs and a learning rate of 0.0001, producing an accuracy and F1-score of 97%. The model was further deployed into a Flask-based web application to demonstrate practical usability. However, this study is limited by the use of a single controlled dataset, so model performance may vary under real-field conditions such as different lighting, camera angles, and leaf damage severity. Future research should include field data evaluation to strengthen model generalization
The Effect of Problem-Based Learning Model Assisted by Scratch in Grade VII Informatics Learning on Critical Thinking Skill
Full text linkThis study aims to determine the effect of the Scratch-assisted Problem-Based Learning (PBL) model on the critical thinking skills of seventh-grade students in Informatics subject, specifically on computational artifact development. The research employed a quantitative approach with a quasi-experimental design, using a pretest-posttest control group. The research sample consisted of two classes: an experimental class that implemented the Scratch-assisted PBL model, and a control class that used a conventional learning model. The critical thinking assessment instrument was developed based on five indicators from Facione: interpretation, analysis, evaluation, inference, and explanation. Data were analyzed using an independent samples t-test to determine the significance of the differences between the groups. The results of the independent samples t-test showed a statistically significant difference between the experimental and control groups (t(38) = 3.45, p = 0.004). The mean posttest score of the experimental group increased significantly from 62.4 to 83.6, with a large effect size (Cohen's d) of 1.24. The research sample consisted of 40 seventh-grade students divided into two groups. The inference and explanation indicators showed the highest improvement. In addition to the score improvement, project-based learning with Scratch also facilitated 21st-century skills such as collaboration, problem-solving, and student digital agency. The integration of Scratch provided space for computational thinking, solution visualization, and self-reflection. This study recommends the use of digital-based PBL models as an innovative learning strategy aligned with the Merdeka Curriculum
Comparison of Elbow and Silhouette Methods in Optimizing K-Prototype Clustering for Customer Transactions
Full text linkThis research presents a comparative analysis of the Elbow and Silhouette methods to identify the ideal number of clusters in applying the K-Prototypes algorithm for customer grouping using purchase transaction data. The K-Prototypes algorithm is employed due to its ability to handle both numerical and categorical data simultaneously. Customer purchase transaction data from the Point of Sale (POS) system is analyzed through preprocessing, feature transformation, and attribute segmentation stages before being clustered using the K-Prototypes algorithm. To identify the optimal cluster count, this study employs two methods: the Elbow and the Silhouette method. The results indicate that the Elbow method produces 2 clusters with a model evaluation score of 0.6368, while the Silhouette method suggests 2 clusters with a slightly lower score of 0.6186. In terms of computational efficiency, the Elbow method also demonstrates a faster processing time results highlight the significance of choosing an appropriate method for identifying the ideal number of clusters, ensuring it aligns with the specific goals of the analysis, whether emphasizing superior inter-cluster distinction or favoring a more parsimonious model configuration
Efektivitas Modul Pembelajaran Komunikasi Data dan Jaringan Komputer Berbasis PBL untuk Meningkatkan Pemahaman Jaringan Komputer Mahasiswa PTI
Full text linkKompetensi dalam bidang Komunikasi Data dan Jaringan Komputer menjadi semakin krusial, mengingat pertumbuhan pesat teknologi informasi dan komunikasi. Materi tentang jaringan komputer sendiri merupakan dasar yang diajarkan mata pelajaran informatika tingkat menengah, begitu pula di perguruan tinggi pada program studi informatika. Oleh karena itu, penting untuk merancang modul pembelajaran yang tidak hanya mengajarkan teori, tetapi juga mendorong mahasiswa untuk menerapkan pengetahuan mereka dalam konteks praktis. Penelitian ini bertujuan untuk mengevaluasi efektivitas modul Problem Based Learning (PBL) yang dirancang khusus untuk pembelajaran Komunikasi Data dan Jaringan Komputer. Dengan menerapkan metode Research Development dan desain 4-D (Four D Models), penelitian ini melibatkan empat tahap: pendefinisian, perancangan, pengembangan, dan penyebaran. Hasil dari penelitian menunjukkan bahwa modul PBL yang dikembangkan, yang mengintegrasikan video pembelajaran animasi, video tutorial, infografis, dan dukungan mentor, memiliki validitas sangat tinggi dengan skor 90,5% dan meningkatkan pemahaman serta keterampilan praktis mahasiswa secara signifikan. Nilai rata-rata mahasiswa meningkat dari 70,2 sebelum penggunaan modul menjadi 85,7 setelah penggunaan modul. Kesimpulannya, modul PBL interaktif ini efektif dalam mengatasi kesenjangan antara teori dan praktik dalam pembelajaran jaringan komputer, sehingga layak diimplementasikan dalam kurikulum Pendidikan Teknik Informatika
Pengaruh Model Pembelajaran Inkuiri Terbimbing Terhadap Hasil Belajar Siswa Pada Mata Pelajaran Informatika Di SMK
Full text linkThe learning process has an influence in achieving significant learning outcomes, including learning media, learning motivation and learning models, learning models are a learning plan that will take place which contains a learning design. The learning model refers to the learning method that will be used, including learning objectives, learning stages, learning environment, and classroom management. To improve learning outcomes, it is necessary to improve the model that influences learning outcomes, where the learning model greatly influences learning outcomes, this can improve learning outcomes significantly. In the learning that took place at the Antarctic 1 Sidoarjo school, there were students who were hyperactive and less conducive due to several things including students who did not like to be restrained and needed more attention to be able to implement conducive learning, in overcoming this problem, the researcher chose a guided inquiry learning model to improve learning outcomes, this is because this learning model is more fun with learning that is packaged in a question, which is able to improve students' understanding by asking questions to satisfy their curiosity, in implementing this model the researcher used the One Group Pretest Posttest research design, by giving the same treatment to a population with two meetings, starting with giving recognition to the Pretest and ending with the Posttest. Then the data is processed to see the effect of giving treatment in the population. Hypothesis testing using the paired t-test formula (T-Paired) produces a decision that is rejected H0, the calculation of the influence with the eta square test from the table of criteria results shows a large influence. It can be concluded that there is an influence on student learning outcomes in informatics subjects using the guided inquiry learning model