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I Gede Surya Rahayuda
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Sekretariat JNATIA Gedung FMIPA Lantai 1, Program Studi Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana
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INDONESIA
Jurnal Nasional Teknologi Informasi dan Aplikasinya
Published by Universitas Udayana
ISSN : 29863929     EISSN : 30321948     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
JNATIA (Jurnal Nasional Teknologi Informasi dan Aplikasinya) adalah jurnal yang berfokus pada teori, praktik, dan metodologi semua aspek teknologi di bidang ilmu komputer, informatika dan teknik, serta ide-ide produktif dan inovatif terkait teknologi baru dan teknologi informasi. Jurnal ini memuat makalah penelitian asli yang belum pernah diterbitkan. JNATIA (Jurnal Teknologi Informasi dan Aplikasinya) diterbitkan empat kali setahun (Februari, Mei, Agustus, November).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 71 Documents
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Perancangan User Interface Platform Sosial Literasi Bookwormer dengan Metode Design Thinking Ni Kadek Arimbi Wirasetia; I Ketut Gede Suhartana; I Komang Arya Ganda Wiguna
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p18

Abstract

Reading is a fundamental skill for intellectual growth and critical thinking development, yet Indonesia faces significant literacy challenges with only 1 out of 1000 the population reads regularly according to UNESCO data and the Indonesian National Assessment Program revealing that merely 6.06% of students possess good literacy skills. The majority of social media platforms promoting instant gratification through short-form contents have further decreasing attention spans and reading habits. This study aims to design “Bookwormer”, a social literacy platform that supports reading habits through book exploration, community engagement, and distraction-free environment. The study used Design Thinking methodology, consists of five steps: Empathize, Define, Ideate, Prototype, and Test. A prototype was developed, featuring a home page, trending books exploration, reading clubs, and personal library with reading goal statistics. Usability testing using System Usability Scale (SUS) with 20 participants yielded an average score of 81.25, indicating excellent usability. Bookwormer is able to address identified user needs and contributes in improving digital literacy culture in Indonesia.
Klasifikasi Kualitas Daun Teh Menggunakan Metode Support Vector Machine Bayu Fadjar Dwi Puta; I Ketut Gede Suhartana; Putu Praba Santika
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p19

Abstract

Tea leaf quality serves as the fundamental determinant of both sensory characteristics and commercial competitiveness in the global tea market. However, manual assessment of tea leaf quality remains limited by observer subjectivity and inconsistent classification. This study aims to develop an automatic tea leaf quality classification system based on leaf maturity using a digital image processing approach.The method employed is Support Vector Machine (SVM) with a combination of three feature extraction techniques: color histogram for color features, Gabor filter for texture features, and Histogram of Oriented Gradients (HOG) for shape features. The dataset consists of 4,272 tea leaf images classified into four quality classes: Premium Grade, Standard Grade, Basic Grade, and Reject Grade. Principal Component Analysis (PCA) was applied for dimensionality reduction while maintaining 95% data variance. Testing results show an accuracy of 84.53% with an F1-score of 84.56%, demonstrating the effectiveness of the system in automatically classifying tea leaf quality
Analisis Sentimen Gemini AI Menggunakan Multinomial Naïve Bayes dengan TF-IDF dan BoW Yeremi Kornelius Purba; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p03

Abstract

The development of artificial intelligence Large Language Models, such as Gemini AI, has attracted widespread public attention. The advanced development of Gemini AI is inseparable from valuable public reviews for product evaluation, but the massive amount of reviews makes manual analysis inefficient. This study aims to conduct sentiment analysis on Gemini AI application reviews using the Multinomial Naïve Bayes classification algorithm. The primary focus is to compare the performance of two feature extraction methods: Term Frequency-Inverse Document Frequency (TF-IDF) and Bag-of-Words (BoW). A total of 1,000 reviews were collected from the Google Play Store, which, after undergoing preprocessing and data labelling, resulted in 438 data points for analysis. The model evaluation results show that TF-IDF feature extraction provides superior performance with an accuracy of 88% and an F1-Score of 93%, compared to BoW, which produces an accuracy of 84% and an F1-Score of 91%. These results indicate that the TF-IDF feature extraction method is more effective in analysing the sentiment of Gemini AI app reviews using Multinomial Naïve Bayes.
Klasifikasi Chord Musik Menggunakan Gabungan Fitur Domain Waktu, Frekuensi, dan MFCC Ni Made Anita Widyastini; I Gede Arta Wibawa; I Putu Satwika
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p10

Abstract

This study presents a chord classification system that combines audio features from three different domains: time, frequency, and Mel-Frequency Cepstral Coefficients (MFCC). The purpose is to improve the accuracy of identifying musical chords from audio signals, which often contain overlapping sounds and instrument variations. The dataset used consists of major and minor chord audio clips sourced from Kaggle. Each audio file undergoes preprocessing, including resampling and signal normalization, followed by feature extraction from the three domains. The extracted features are then merged into a single vector and classified using the Random Forest algorithm. The model is evaluated using accuracy, precision, recall, F1-score, and confusion matrix. Results show that the model performs well in detecting major chords (F1-score 0.83), but has lower recall for minor chords (F1-score 0.68). The overall accuracy is 77%, indicating that combining features from multiple domains enhances classification performance. This method shows potential for future development in audio signal analysis and music recognition systems.
Rancang Bangun Aplikasi ‘ekoSaku’ dengan Menggunakan Metode Design Thinking Ni Luh Juli Yetti; I Ketut Gede Suhartana; Ida Bagus Gede Sarasvananda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p12

Abstract

Indonesia continues to face serious waste management issues, particularly with non-organic waste. According to the National Waste Management Information System (SIPSN), the total waste generation in 2024 reached 34,214,607.36 tons across 317 districts and cities. This study presents the design of a mobile-based application called ekoSaku, aimed at facilitating the digital collection and exchange of recyclable waste between users and agents. The development process applies the Design Thinking methodology, consisting of five stages: empathize, define, ideate, prototype, and test. User needs were identified through questionnaires distributed to 15 respondents, focusing on daily waste-handling behavior and digital expectations. These insights shaped the app’s core features such as waste photo uploads, home pickups, price setting by agents, transaction tracking, and a point-based reward system. The prototype was evaluated using the System Usability Scale (SUS), with an average score of 81, indicating excellent usability. The results show that ekoSaku offers a user-friendly and effective approach to digital waste management.
Perancangan Ontologi: Representasi Pengetahuan Tanaman Pangan di Indonesia Putu Krisna Udayana; Gst. Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p04

Abstract

Indonesia’s food security is increasingly challenged by factors such as climate change, rapid population growth, and heavy reliance on imported food products. Despite being one of the most biodiverse countries in the world, Indonesia has not fully utilized the potential of its native food crops. One of the major obstacles is the lack of organized and well-documented knowledge about these plants, as most of the information is still transmitted orally and scattered across various sources. To address this issue, this study introduces an ontology-based knowledge representation model for Indonesian food crops. The model is developed using the Methontology approach and implemented through the Protégé platform. It includes key classes such as Plant, PlantTaxonomy, PlantFactors, and FoodCropCategory, encompassing 100 individuals, 29 object properties, and 5 data properties. This ontology organizes important information such as taxonomic classification, planting season, soil type, altitude preferences, scientific names, and crop categories. The reasoning ability of the ontology was evaluated using SPARQL queries to determine its capability to answer domain-specific questions. The results demonstrated that the ontology could effectively represent semantic relationships and retrieve relevant knowledge. This structured and semantically enriched model is expected to enhance digital documentation, promote knowledge sharing, and support intelligent systems for managing food crop information in Indonesia.
Pengembangan UI/UX Aplikasi Pinjam MIPA dengan Pendekatan Design Thinking I Nyoman Suryadana; I Gede Santi Astawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p05

Abstract

This study presents the design and development of the Pinjam MIPA application as a digital system to support inventory management and borrowing activities among student organizations at the Faculty of Mathematics and Natural Sciences, Udayana University. The current manual process for borrowing often leads to data loss, unstructured schedules, and limited monitoring of inventory items. By applying the design thinking methodology, which consists of the empathize, define, ideate, prototype, and test stages, a user-centered solution was created to address these challenges. The application includes features such as digital inventory tracking, structured borrowing procedures, scheduling, and historical transaction records.. Usability testing with the System Usability Scale method produced an average score of 80.75, categorized as excellent, indicating that the application meets user expectations for ease of use and functionality. This work demonstrates that a design thinking approach can effectively improve efficiency, transparency, and accuracy in managing the lending of goods among student organizations. Future development may enhance notification features and real-time monitoring to further improve the system.
Evaluasi Kinerja TextRank dan LexRank Berbasis TF-IDF dan Word2vec untuk Text Summarization Albertin Caecilia Djema; I Gusti Ngurah Anom Cahyadi Putra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p15

Abstract

Text summarization is a crucial task in natural language processing, aiming to extract essential information from lengthy texts. The choice of summarization method significantly influences the quality of the generated summary. This study evaluates the performance of the TextRank and LexRank algorithms, both combined with TF-IDF and Word2Vec-based word representation techniques. The IndoSum dataset was used as the benchmark, with preprocessing steps including text cleaning, case folding, tokenization, and vector transformation using Word2Vec and TF-IDF weighting. The ROUGE metric was employed to assess summarization quality. Experimental results indicate that the TextRank algorithm, when integrated with TF-IDF and Word2Vec, achieves higher ROUGE scores compared to LexRank in generating extractive summaries.
Pemodelan Pengetahuan Produk Body Moisturizer Menggunakan Pendekatan Ontologi Semantik Sherly Martha Revania; I Made Widhi Wirawan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p06

Abstract

Indonesia's tropical climate poses significant challenges to skin health, particularly regarding body moisturizer selection. The abundance of products with varying ingredients and benefits often confuses consumers in choosing suitable products for their specific skin needs. This research develops a semantic ontology model for body moisturizer domain using the Methontology approach to provide structured and interconnected knowledge representation. The ontology was implemented using Protégé 5.6.5 and validated through Hermit Reasoner for consistency verification and SPARQL queries for functional testing. The developed ontology consists of 1 main class with 8 subclasses, 159 individuals, 3 data properties, and 14 object properties, covering essential aspects such as skin types, benefits, active ingredients, textures, and usage contexts. Evaluation results demonstrate that the ontology successfully responds to competency questions with accurate and contextually relevant results. The semantic model enables systematic organization of body moisturizer information, facilitating better product selection based on individual skin characteristics and environmental conditions in Indonesia's tropical climate.
WellGrown: Aplikasi Pencegah Stunting Melalui Pengaturan Pola Makan Berbasis Design Thinking Dian Resvina; I Ketut Gede Suhartana
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p11

Abstract

Child stunting is a chronic nutritional issue that hampers physical and cognitive development, particularly during the first 1,000 days of life (HPK). In Indonesia, although the stunting rate declined from 24.4% in 2021 to 21.6% in 2022, it remains a major public health challenge. Currently, 30.8% of children under five are stunted, 10.2% suffer from wasting, and 48.5% of pregnant women are anemic. In response, the Indonesian government has set a national target to reduce the stunting rate to 14% by 2024, using a cross-sectoral approach focused on the HPK period. The root causes of stunting include inadequate nutritional intake, limited knowledge, and improper parenting practices. To support these efforts, technological innovation plays a vital role. The WellGrown mobile application, developed using the Design Thinking approach, aims to assist prospective parents by offering accessible health and nutrition guidance for pregnant women and children up to two years of age. With this strategy, monitoring and evaluation during the HPK period can become more efficient. The System Usability Scale (SUS) score for WellGrown is 82.5, reflecting its high usability and user satisfaction.

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