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All Journal Jurnal Sains Teknologi dan Sistem Informasi Jurnal Manajemen Informatika dan Bisnis Digital
Rizal Nurzuli
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Computer Science & IT

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Pengembangan E-Media Augmented Reality Berbasis Inquiry-Based Learning untuk Meningkatkan Minat Belajar Visualisasi Sejarah Manusia Purba Mohamad Furqon; Ira Palupi Ayuningtyas; Fadilah Falah Syifa; Rizal Nurzuli; Pramesti Rahmadiyani
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 5 No. 2 (2025): Oktober 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v5i2.5906

Abstract

This study aims to develop and evaluate the effectiveness of an Augmented Reality (AR)-based learning media using an Inquiry-Based Learning (IBL) model to enhance history learning interest among Grade X students at SMA NU Hasyim Asy’ari Tarub. The research was motivated by the low student interest caused by monotonous and traditional teaching methods. Employing a Research and Development (R&D) approach with the ADDIE model, the media was designed to feature interactive 3D objects of prehistoric humans, including Homo Soloensis, Pithecantropus erectus, and Homo Florensiensis, supplemented with audio and video. The application was developed using Unity 3D and Vuforia for Android devices. Validation from material, media, and language experts yielded scores of 49, 49, and 46 respectively, categorizing the media as "highly feasible." Classroom implementation garnered a very positive response with an average score of 116.4 from 26 students. A paired sample t-test comparing pre-test and post-test scores showed a statistically significant increase in learning interest, with a mean score difference of 14.40 at a 95% confidence level. These findings conclude that the AR-IBL learning media is highly effective and suitable for increasing student engagement and interest in history.
Support Vector Machine sebagai Sistem Pendukung Keputusan Pemilihan Jurusan Berbasis Website pada SMK NU Hasyim Asy’ari Tarub Rizal Nurzuli; Fadilah Falah Syifa; Robiatul Adawiyah
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 2 (2025): November 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i2.6850

Abstract

The process of determining students’ majors in vocational high schools plays a crucial role in shaping their academic development and future career readiness. However, manual decision-making often leads to inaccuracies due to subjective judgments and limited data analysis. This study aims to develop a more accurate and objective major classification model by integrating the Support Vector Machine (SVM) method with Particle Swarm Optimization (PSO). The dataset consists of 292 student records, including academic scores in Mathematics, Indonesian Language, English, and Science, as well as interest questionnaire results. Initial testing using SVM produced an accuracy of 79.76%, indicating that the model’s parameters were not yet optimal. PSO was then applied to optimize the key parameters C and Gamma, resulting in a significant improvement in model performance. The optimized SVM–PSO model achieved an accuracy of 97.20%, with a precision of 96.33%, recall of 95.22%, and an F1-score of 95.77%. These results demonstrate the capability of PSO to enhance SVM’s pattern-recognition performance and address class imbalance issues, particularly for minority majors. Overall, the integration of SVM and PSO is proven to be effective as a Decision Support System, providing schools with accurate, data-driven recommendations for student major placement.
Co-Authors Fadilah Falah Syifa Ira Palupi Ayuningtyas Mohamad Furqon Pramesti Rahmadiyani Robiatul Adawiyah