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All Journal JURIKOM (Jurnal Riset Komputer) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA
Putu Hendra Suputra
Universitas Pendidikan Ganesha, Singaraja
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Pengembangan Media Pembelajaran Neuroanatomi Berbasis WebXR (Website Extended Reality) dengan Pendekatan Aksesibilitas dan Optimalisasi Gede Bramanda; I Gede Partha Sindu; Putu Hendra Suputra
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.9954

Abstract

This study aims to develop and evaluate a WebXR (Website Extended Reality)-based learning media specifically designed for medical students at Universitas Pendidikan Ganesha. Neuroanatomy learning is a crucial yet challenging component of medical education, often difficult to comprehend due to limited learning media, the scarcity of cadavers, and the abstract nature of the SOBOTA anatomical atlas. The primary contribution of this research lies in the integration of an affordable and easily accessible web-based immersive platform, which simultaneously resolves technical constraints such as motion sickness and stuttering on standalone devices. Behind a well-structured and designed foundation, this media operates on a server-based infrastructure and runs on HTML5 technology architecture to deliver flexible, real-time data accessibility directly through the browser. Technical optimization was implemented in the form of FPS stabilization (FPS Locking) and dynamic resolution scaling to maximize the computing capacity of the Snapdragon XR2 chipset on Meta Quest 2. This application was built using the Multimedia Development Life Cycle (MDLC) framework. The assessment results show that the application has very high validity from both material and media experts, achieving an overall score of 1.00 based on the Gregory matrix. Furthermore, user experience testing using the User Experience Questionnaire (UEQ) with medical students yielded an "Excellent" rating across all dimensions, with the Stimulation dimension receiving the highest score (2.46), placing this application within the top 10% of products globally. The findings indicate that the developed WebXR media effectively offers immersive appeal and can serve as a high-quality, interactive, and cross-platform alternative practical tool for neuroanatomy introduction.
Klasifikasi Jenis Kelamin Berbasis Citra Mata Menggunakan Vision Transformer ViT dengan Strategi Discriminative Fine-Tuning Gde Made Hanura; Putu Hendra Suputra; Ni Putu Novita Puspa Dewi
Journal of Computer System and Informatics (JoSYC) Vol 7 No 3 (2026): May 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v7i3.9778

Abstract

Face-based biometric identification systems have significant limitations when a subject’s face is covered, whether due to mask usage after the COVID-19 pandemic or face veils for cultural and religious reasons. This creates real security gaps, as evidenced by the gender-disguise infiltration incident at Masjid Jannatul Firdaus in Makassar. In such situations, the eyes remain the only consistently exposed biometric feature. This study proposes the application of Vision Transformer (ViT-B/16) pretrained on ImageNet-21K with a progressive fine-tuning strategy based on the discriminative learning rate principle to classify gender from eye images. The Female and Male Eyes dataset from Kaggle consists of 11,525 eye images divided into training (64%), validation (16%), and testing (20%) sets. Experiments were conducted in two series: Series B tested variations in the number of unfrozen transformer blocks (0–6), and Series C tested discriminative learning rate ratios between the classifier and encoder (5:1, 10:1, 3:1). The optimal configuration with 6 unfrozen blocks and a 3:1 ratio achieved 95.70% accuracy, 97.67% precision, 92.69% recall, and 0.9569 weighted F1-score, surpassing MobileNet (93.90%) and K-Nearest Neighbor (68.81%). These results indicate that ViT with discriminative fine-tuning is effective for gender classification from eye images and has potential for biometric security applications.
Pengembangan Multimedia Interaktif Berbasis Visual Tiga Dimensi untuk Pembelajaran Numerasi Anak Tunagrahita Ayu Kristin Natalia Sinaga; I Ketut Purnamawan; Putu Hendra Suputra
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10227

Abstract

This study aims to develop three-dimensional visual-based interactive multimedia to be used as a learning aid for numeracy among children with intellectual disabilities. The study was conducted at the Cahaya Impian Masa Depan (CIMD) Foundation. The research method employed the Multimedia Development Life Cycle (MDLC), which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The developed multimedia is capable of displaying three-dimensional animal visualizations, interactive audio, numeracy quizzes, adn a reward system,which are designed to help students understand numerical concept more concretely. Testing was conducted through three evaluations: a content expert review, a media expert review, and a user responses evaluation using the Usability Metric for User Experince (UMUX) method. The study participants consisted of two teachers and 15 students with intellectual disabilities as users of the learning media. The content expert review yielded a validity percentage of 92,86%, classified as highly valid, and the media expert review yielded a validity percentage of 90%, classified as highly valid. Additionally, the user response evaluation yielded a UMUX score of 84,16% which falls into the Excellent category and Grade A. The research findings indicate that three-dimensional visual-based interactive multimedia possesses excellent usability, is easy to use, and is suitable as an alternative learning medium for numeracy education for children with intellectual disabilities. This study contributes by providing a learning medium designed based on the characteristics of children with intellectual disabilities and the learning needs identified at the Cahaya Impian Masa Depan (CIMD). The developed multimedia is expected to serve as a reference for the development of interactive learning media in inclusive education as well as special education institutions.
Evaluasi Arsitektur Long Short-Term Memory untuk Klasifikasi Gestur Tangan Dinamis Berbasis MediaPipe Sebagai Kendali Presentasi Putu Gede Dimas Witjaksana; I Nyoman Saputra Wahyu Wijaya; Putu Hendra Suputra
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10711

Abstract

Advances in Human-Computer Interaction (HCI) are driving the use of more natural interaction methods through hand gesture recognition technology. Dynamic gestures have an advantage over static gestures because they contain temporal information such as direction and movement patterns hat is more representative in conveying a command. However, the development of dynamic gesture recognition models still faces challenges in maintaining generalization capabilities for new users, necessitating an evaluation scheme capable of measuring model performance more representatively. This study aims to develop a dynamic hand gesture classification model for controlling PowerPoint presentations based on MediaPipe Hands, MediaPipe Pose, and Long Short-Term Memory (LSTM). The research stages included video data collection, hand and shoulder landmark extraction, data normalization using the midpoint of both shoulders as a reference point, training of eight variations of the LSTM architecture, and evaluation using the Leave-One-Subject-Out Cross-Validation (LOSO-CV) scheme, such that each participant took turns serving as test data to evaluate the model’s generalization ability toward new users. Test results show that the Baseline 1 (B1) architecture delivers the best performance with an average accuracy of 95.77%, precision of 96.03%, recall of 95.90%, and an F1-score of 95.84%, Analysis of the confusion matrix shows that most gestures were correctly recognized, while misclassifications occurred primarily in the “idle” class and for some gestures with similar hand poses. The results of the study indicate that the combination of MediaPipe and LSTM is capable of building a dynamic hand gesture classification model that maintains consistent classification performance in cross-subject testing.
A Analisis Tingkat Kepuasan Konsumen Pada Pelayanan PT. AXZ Furniture Di Media Internet Menggunakan Metode VADER dan ARM Ida Ayu Laksmi; I Made Candiasa; Putu Hendra Suputra
JURIKOM (Jurnal Riset Komputer) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9322

Abstract

Bali Art Furniture is one of the companies in Bali that exports furniture and home decoration products. During its operation, this company utilises various internet media platform services such as websites, Facebook Marketplace, Instagram, WhatsApp Business, Pinterest, and Google to communicate online with consumers. As the company has grown over time, it has recruited many employees to increase its capacity to provide services. The company has never conducted a systematic evaluation of customer service satisfaction, either internally or externally. Based on this phenomenon, a customer satisfaction analysis was conducted using customer comment data. Customer service satisfaction was evaluated using the VADER and ARM methods as a basis for comparing the effectiveness of these methods. Based on the analysis of the two methods, the VADER method produced an accuracy of 34%, while the ARM method produced an accuracy of 64%. The evaluation results using the confusion matrix of the VADER model showed that positive comments were more recognisable by the system than negative and neutral comments, as seen from the positive recall value of 0.90, which was greater than the negative and neutral recall values. Meanwhile, the evaluation results using the ARM method showed that neutral comments were more recognisable by the system than positive and negative comments, as seen from the neutral recall value of 0.88, which was greater than the positive and negative recall values. Thus, the highest accuracy results in the ARM model became the guideline in making recommendation results.
Co-Authors Ayu Kristin Natalia Sinaga Gde Made Hanura Gede Bramanda I Gede Partha Sindu I Ketut Purnamawan I Made Candiasa I Nyoman Saputra Wahyu Wijaya Ida Ayu Laksmi Ni Putu Novita Puspa Dewi Putu Gede Dimas Witjaksana