cover
Contact Name
I Gede Pasek Suta Wijaya
Contact Email
gpsutawijaya@unram.ac.id
Phone
+62370631712
Journal Mail Official
jtika@unram.ac.id
Editorial Address
Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram Jl. Majapahit 62, Mataram, Lombok, NTB
Location
Kota mataram,
Nusa tenggara barat
INDONESIA
Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA )
Published by Universitas Mataram
ISSN : -     EISSN : 26570327     DOI : https://doi.org/10.29303/jtika
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.
Articles 195 Documents
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.