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I Gede Pasek Suta Wijaya
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Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram Jl. Majapahit 62, Mataram, Lombok, NTB
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INDONESIA
Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA )
Published by Universitas Mataram
ISSN : -     EISSN : 26570327     DOI : https://doi.org/10.29303/jtika
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Jurnal Teknologi Informasi, Komputer dan Aplikasinya disingkat dengan JTIKA diterbitkan oleh Program Studi Teknik Informatika Fakultas Teknik Universitas Mataram sebagai wadah publikasi hasil penelitian original dalam di bidang teknologi informasi, ilmu komputer dan aplikasinya. JTIKA adalah open access jurnal dengan online ISSN 2657-0327 dan proses review secara blind dan peer-review yang dilakukan oleh sekurang-kurangnya 2 orang reviewer. JTIKA memiliki Jumlah terbitan sebanyak 2 kali dalam setahun yaitu pada bulan Maret dan September. Tujuan utama JTIKA adalah sebagai media untuk mempublikasikan artikel hasil penelitian, inovasi aplikasi, studi perbandingan yang berkualitas baik dan mengikuti perkembangan dan tren teknologi baru dibidang Teknologi informasi, Komputer adan Aplikasinya. Artikel yang dipublikasikan pada JTIKA dapat ditulis dalam bahasa Indonesia maupun bahasa Inggris.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 209 Documents
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PERFORMANCE ANALYSIS OF MULTILINGUAL AND MONOLINGUAL MODELS IN PREDICTING INDONESIAN LANGUAGE EMOTION USING TWITTER DATASET Paramarta, Muhammad Magistra Apta; Dwiyansaputra, Ramaditia; Rassy, Regania Pasca
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.482

Abstract

Although Indonesia has the third largest population in the world, the number of datasets available in the field of text processing in Indonesian is still very limited. Therefore, this research utilizes the ability of multilingual models that can be trained with multiple languages to predict emotions based on low-resource language such as Indonesian. Several training scenarios were conducted to evaluate the transferability and performance of these multilingual models compared to the monolingual IndoBERT model. The experimental results show that XLM-R outperforms mBERT and achieves competitive performance to IndoBERT, with XLM-R and IndoBERT achieving F1-score of 0.7793 and 0.7733 respectively. XLM-R also demonstrates competitive results on other evaluation metrics. These findings suggest that XLM-RoBERTa could be a promising alternative for emotion detection in languages with limited resources, such as Indonesian.
ANALISIS PERFORMA INDOBERTWEET DAN DISTILBERT PADA ANALISIS SENTIMEN DENGAN DATASET BERLABEL MANUAL DAN OTOMATIS Kansha, Lyudza Aprilia; Suta Wijaya, I Gede Pasek; Bimantoro, Fitri
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.484

Abstract

Tourism in North Lombok, particularly the Gili Islands (Trawangan, Air, and Meno), plays a significant role in the regional economy. Understanding public sentiment through social media is crucial for improving tourism services and management. This study compares the performance of two transformer-based models IndoBERTweet and DistilBERT in sentiment analysis of tourism-related tweets from X (Twitter). The dataset used consists of 3,159 preprocessed Indonesian-language tweets, labeled through both manual annotation and automatic classification using DistilBERT. IndoBERTweet was evaluated on both manual and automatic labels, while DistilBERT was only applied to the manually translated dataset. Experimental results show that IndoBERTweet with manual labeling achieved an F1-score of 72.98% and demonstrated more balanced performance across all sentiment classes. Meanwhile, DistilBERT showed lower F1-scores overall (max. 57%) but performed efficiently in terms of computational time. Automatic labeling showed weak agreement with manual annotation (only 31.8% match), leading to bias in model learning, particularly the failure to detect neutral sentiment. Evaluation using new test sentences yielded 80% prediction accuracy, yet revealed that IndoBERTweet struggles with implicit sentiment or subtle dissatisfaction. This research highlights IndoBERTweet's effectiveness in Indonesian sentiment analysis and emphasizes the trade off between computational efficiency and contextual accuracy in lightweight models like DistilBERT.
PERANCANGAN SISTEM MODUL REGISTRASI PADA SISTEM INFORMASI MANAJEMEN RUMAH SAKIT (STUDI KASUS : RUMAH SAKIT UNIVERSITAS MATARAM) Askit, Baiq Ratna; Widiartha, Ida Bagus Ketut; Rosika, Herliana
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.488

Abstract

This paper presents the design and evaluation of a user-centered registration module for a hospital information system, implemented with a microservices architecture to enable independent development and seamless integration of registration, scheduling, and payment services. A prototype was assessed with 50 participants using the System Usability Scale (SUS) and the User Experience Questionnaire (UEQ). The prototype achieved a SUS score of 78.9, indicating good usability. UEQ results showed excellent ratings in attractiveness, efficiency, stimulation, and novelty, while clarity and dependability scored good, revealing opportunities to improve navigation and instructional messaging. The modular microservices approach enhances scalability, maintainability, and performance. Future work will incorporate load testing, integration testing, and accessibility evaluations to further optimize system robustness and user satisfaction.
PERANCANGAN UI/UX PROTOTYPE MODUL PEMBAYARAN SIMRS UNIVERSITAS MATARAM DENGAN PENDEKATAN KOLABORATIF EXTREME PROGRAMMING DAN USER-CENTERED DESIGN Husna, Nabila Ummul; Widiartha, Ida Bagus Ketut; Rosika, Herliana
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.489

Abstract

This study aims to optimize the hospital payment process at Mataram University Hospital by designing a user-friendly interface for the payment module in the HMIS. Utilizing a combined approach of XP and UCD, the research identifies opportunities to enhance user experience and streamline payment transactions. Data collection involved literature reviews, staff interviews, and observations, highlighting user needs and system limitations. The redesigned payment module is intended to facilitate structured patient transaction management while ensuring accurate financial reporting. Initial prototype testing using SUS and UEQ methods showed high usability scores, with the SUS score reaching 82 with an “excellent” grade scale and 5 out of 6 aspects of UEQ falling within the “Excellent” category range, indicating that the design was in the top 10%. The novelty aspect is in the "Good" category, indicating that 10% of other systems score better and 75% of other systems score worse. Although it did not reach “Excellent”, the system still showed an adequate level of novelty.
PENGEMBANGAN SISTEM REKOMENDASI UNTUK SIMULASI RAKIT KOMPUTER MENGGUNAKAN ALGORITMA GENETIKA BERBASIS WEBSITE Maulana, Vieri Arief; Haromainy, Muhammad Muharrom Al; Nurlaili, Afina Lina
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 2 (2025): September 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i2.491

Abstract

This research develops a web-based recommendation system for computer assembly simulations using genetic algorithms. The system is designed to assist users in selecting optimal computer components based on their available budget and desired performance. Component data were collected from e-commerce platforms and online sources, then preprocessed using Min-Max normalization to ensure balanced data scaling. The system was developed using Laravel for the frontend interface and Flask API for computational processing of the genetic algorithm. System evaluation was conducted using the System Usability Scale (SUS) method involving 21 respondents, resulting in an average score of 86.67, which falls into the "Excellent" category and Grade B on the usability scale. Additionally, performance comparisons with prebuilt systems from online stores show that the recommendation system produced assemblies with lower costs and higher performance. The implementation of selection, crossover, and mutation in the genetic algorithm effectively evaluates component combinations to achieve optimal configurations. This research contributes to the development of intelligent optimization-based systems that simplify the computer assembly process, particularly for novice users with limited technical knowledge and constrained budgets.
EYE DISEASE CLASSIFICATION USING DEEP LEARNING: A COMPARATIVE STUDY OF MOBILENETV2, XCEPTION, AND EFFICIENTNET-B0 Agustini, Latifa Zahra; Bimantoro, Fitri; Dwiyansaputra, Ramaditia
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.518

Abstract

This study presents a comparative analysis of three convolutional neural network (CNN) architectures—MobileNetV2, Xception, and EfficientNet-B0—for classifying retinal fundus images into four categories: Cataract, Diabetic Retinopathy, Glaucoma, and Normal. Using a dataset of 4,217 images, the models were trained with transfer learning, image augmentation, and regularization techniques, and evaluated through 5-fold cross-validation. EfficientNet-B0 achieved the highest mean accuracy (0.85) and demonstrated stable performance across all metrics, while MobileNetV2 provided competitive accuracy with lower computational requirements, making it suitable for resource-limited environments. Xception showed the lowest and least stable performance, indicating a higher tendency to overfit. External validation with clinical images revealed a significant drop in accuracy for all models, highlighting challenges related to domain shift and limited generalization. Grad-CAM analysis also showed difficulties in detecting subtle pathological features in Diabetic Retinopathy and Glaucoma. The study is limited by the small dataset size, reliance on a single data source, and the absence of additional clinical information. Future work should incorporate larger and more diverse datasets, apply domain adaptation strategies, and integrate multimodal clinical data to enhance robustness and clinical applicability.
PENGEMBANGAN SISTEM INFORMASI MONITORING PRAKTIK KERJA LAPANGAN BBPOM MATARAM DENGAN METODE RAPID APPLICATION DEVELOPMENT Adinata, Bagas; Agitha, Nadiyasari; Widiartha, Ida Bagus Ketut
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.527

Abstract

The Mataram National Agency of Drug and Food Control (BBPOM Mataram) requires an information system to manage internship participants’ data more effectively. The administrative process has been carried out manually, which often leads to inefficiency and potential errors in data storage. This study aims to develop a web-based information system that integrates the entire internship process, including application submission, entrance selection through pre-test, attendance recording, daily activity documentation, and final score calculation based on attendance and activities. The system was developed using the Rapid Application Development (RAD) method, which emphasizes iterative prototyping and user feedback to accelerate the development process. System testing was conducted using the black-box testing method to evaluate the functionality of each feature according to the requirements. In addition, usability testing was performed using the System Usability Scale (SUS), resulting in a score of 79,16, which indicates that the system is considered Good in terms of usability. The test results show that all system features function properly and meet the specified requirements. The implementation of this system supports BBPOM Mataram in improving efficiency, accuracy, and integration in managing internship participant data.
PENGEMBANGAN SISTEM INFORMASI PORTOFOLIO PEMBELAJARAN UNTUK MENDUKUNG MANAJEMAN CAPAIAN PEMBELAJARAN MATAKULIAH BERBASIS OBE (STUDI KASUS DI PROGRAM STUDI TEKNIK INFORMATIKA) Anjarwani, Sri Endang; Ali Albar, Moh; Bimantoro, Fitri; Agitha, Nadiyasari; Zafrullah M., Ahmad; Gerald Dennaya HD, Muh.
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.530

Abstract

The Information Technology Study Program (PSTI) implements an OBE-based curriculum to measure graduate achievement (CPL) and course learning achievement (CPMK), requiring lecturers to compile learning achievement reports in the form of portfolios at the end of each semester. The compilation of portfolios is supplemented with CPL and CPMK results calculated using Microsoft Excel. During the preparation of the report, difficulties arise when changing data that affects the formula. Not all lecturers understand the available formulas and equations. The purpose of this research is to develop an information system to support the preparation of lecturers' course learning portfolio reports. The method used is Extreme Programming, which is an Agile software development approach with the stages of Planning, Design, Coding, Testing, and Release Phase (Deploy). This research resulted in a Learning Portfolio Information System to Support OBE-Based Course Learning Achievement Management (Case Study in the Informatics Engineering Study Program). In this information system, lecturers can manage CPL, CPMK, Sub_CPMK, Assessment, Evaluation, Results, and Portfolio data. From testing using User Acceptance Testing, the results obtained were an average of 37% strongly agree, 43% agree, and 19% somewhat agree. Therefore, it can be said that the information system created can be used properly.
KLASIFIKASI PENYAKIT PNEUMONIA PADA X-RAY PARU-PARU MENGGUNAKAN MODEL HYBRID GRAY LEVEL CO-OCCURRENCE MATRIX DAN ARTIFICIAL NEURAL NETWORK Rahmadi, Amdila; Wijaya, I Gede Pasek Suta; Irfan, Pahrul
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.534

Abstract

Pneumonia is a leading cause of morbidity and mortality, particularly in children, requiring rapid and accurate diagnosis. This study proposes a hybrid classification model that combines Gray Level Co-occurrence Matrix (GLCM) texture feature extraction with an Artificial Neural Network (ANN) to analyze chest X-ray images. The dataset consisted of 3,150 images, balanced using random undersampling. GLCM features were extracted across multiple distances and four orientations, generating 19 texture features per image. Seven experimental scenarios were conducted to evaluate ANN architectures with 2, 3, and 4 fully connected layers to identify the most effective configuration. The best-performing model achieved an accuracy of 91.50%, with precision, recall, and F1-score of 0.91, demonstrating consistent performance in distinguishing normal and pneumonia cases. Due to its relatively low computational complexity, this approach is suitable for low-resource healthcare settings. Future work will focus on expanding the dataset and validating the model with clinical data to enhance real-world applicability.
PEMBELAJARAN INTERAKTIF SISTEM TATA SURYA MELALUI AUGMENTED REALITY DALAM PENDIDIKAN DASAR Pradana, Awang; Radiansyah, Radiansyah
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 8 No 1 (2026): Maret 2026
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v8i1.540

Abstract

This study aims to design and develop interactive learning media based on Augmented Reality (AR) for solar system material, targeting sixth-grade students at SDN 012 Tarakan. The media development was carried out using the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. This media was created using the Unity and Vuforia SDK platforms, equipped with 3D objects and audio explanations to aid student understanding. The study involved 26 sixth-grade students through purposive sampling. The material presented included an introduction to the eight planets, the Sun, and the Moon. whereas the functionality test (Blackbox Testing) revealed that 16 application features functioned well. The media expert validation results obtained an average score of 94%, and the material expert validation reached 81.66%, both of which were in the very feasible category. Student responses were also very positive, with an average of 96.09%. Thus, this AR-based learning media is deemed effective, engaging, and suitable for use in the learning process at SDN 012 Tarakan.

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