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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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Bali
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 316 Documents
 28   29   30   31   32 
Sistem Penjualan Merchandise Berbasis Aplikasi Mobile I Dewa Gede Partha Wijaya; I Made Widiartha
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p26

Abstract

The rapid growth of mobile technology has revolutionized various industries, including merchandise sales. This paper presents a study on the development of a mobile applicationbased merchandise sales system aimed at replacing manual recording reports by merchandisers and expanding the range of reportable data. By harnessing the capabilities of mobile devices, the research focuses on analyzing merchandisers' requirements and designing user-friendly interfaces. Through thorough testing and evaluation, the system showcases its reliability and functionality. This study contributes to the existing body of knowledge by offering valuable insights into the advantages and challenges of adopting mobile technology in merchandise sales. 
Penyusunan Sistem Rekomendasi Produk Diecast Mobil Dengan Metode Content-Based Filtering (CBF) Anak Agung Aditya Nugraha; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p25

Abstract

The growing popularity of diecast car collections has created a demand for efficient recommendation systems to assist collectors in discovering new products. This study focuses on the development of a content-based filtering (CBF) recommendation system for diecast car products. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) and cosine similarity techniques to calculate the relevance between products and user preferences. By analyzing the textual features of diecast car products, such as brand, model, and specifications, the CBF system generates personalized recommendations based on similarity scores. The evaluation of the system's performance demonstrates its effectiveness in providing accurate and relevant recommendations, which enhance the user experience and facilitate the exploration of the diecast car market. 
Implementasi Aplikasi “SahabatAnabul” Berbasis User Centered Design Sebagai Website Pangkalan Informasi Anabul Ni Luh Putu Ayu Siwastuti Cayadewi; Made Agung Raharja
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p24

Abstract

Currently, many people keep animals in their homes. Most of the animals they have are dogs and cats. Thus, they need a lot of information about the animals they keep. Therefore, to make it easier for people to find information about Anabul, an information website about Anabul was created, starting from the types of Anabul, its characteristics, what Anabul needs, and others. This journal produces a website based SahabatAnabul application. SahabatAnabul is a website to share all information about anabul, especially for dogs and cats. The resulting website can help people who have pets or want to know information about the types of dogs and cat breeds that exist in the world. 
Pengembangan Model Ontologi Cerita Rakyat Bali Ni Made Julia Budiantari; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p23

Abstract

This research aims to develop an ontology related to the domain of Balinese folklore. Balinese folklore is an important part of Bali's cultural heritage and has moral values, as well as being an inspiration in art and performance. Ontology is a method to organize and categorize information in a structured way, and has been widely applied in various fields. However, research on the ontology of Balinese folklore is still limited. This research will propose and develop a comprehensive and structured ontology model for Balinese folklore. The steps to be taken include analysis of relevant ontologies, development of an ontology schema, organization and classification of information, and testing and validation of the ontology model built. The method used in this research is methontology, which includes the stages of specification, knowledge acquisition, conceptualization, integration, evaluation, and documentation. The result of this research is a structured Balinese folklore ontology that has been evaluated using SPARQL queries. This ontology can be used as a source of information and reference in learning and utilizing Balinese folklore 
Analisis Sentimen Gambar pada Media Sosial dengan Pendekatan Deep Learning Ronaldito Juan Bantaras T.; Made Agung Raharja
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p22

Abstract

Sentiment analysis of images on social media using a deep learning approach is an interesting research topic in the field of artificial intelligence. It involves data collection, training deep neural network models, testing and evaluation, and application and analysis on social media. The results of this analysis provide valuable insights to users in understanding user responses to content, detecting evolving sentiment trends, and providing important insights for business purposes and decision-making. Deep learning offers a strong and effective method for understanding emotional expressions within images shared on social media platforms. 
Analisis Performa Algoritma K-Nearest Neighbor dalam Klasifikasi Tingkat Kerontokan Rambut Gede Dikka Widya Prana; Luh Gede Astuti
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p21

Abstract

Hair loss can lead to baldness and affect one's self-confidence. Normally, hair falls out in 80-120 strands per day, and the average number of hair follicles on the head is around 100,000. If the amount is reduced by 50%, it can be considered a disorder. Therefore, a classification of hair loss levels is necessary to determine appropriate actions. Previous study has shown that the KNearest Neighbor algorithm is capable of classifying various diseases. In this study, the Luke Hair Loss Dataset from the website kaggle.com, consisting of 400 data points, was used. To evaluate the method's feasibility, a confusion matrix was employed. The objective of this research is to analyze the performance of the K-Nearest Neighbor algorithm. Several scenarios were utilized, including testing the model before and after SMOTE oversampling, testing before and after data normalization, testing based on different K values, and testing with varying ratios of training and testing data. The results of this study indicate that the K-Nearest Neighbor algorithm achieved the highest accuracy value of 0,9853, precision of 0,9886, recall of 0,9833, and f1-score of 0,9856. 
Klasifikasi Genre Musik Menggunakan Support Vector Machine Berdasarkan Spectral Features I Gusti Agung Ngurah Diputra Wiraguna; Luh Arida Ayu Rahning Putri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p20

Abstract

This research focuses on music genre classification based on spectral features and SupportVector Machine (SVM). Features such as Spectral Centroid, Spectral Rolloff, Spectral Flux, and Spectral Bandwidth are extracted from MP3 music audio. The dataset comprising 4 music genres is utilized for training and testing the system. The extracted spectral features are fed into the SVM classifier to predict the genre of test samples. Python and machine learning are both used in developing the system while the experimental results demonstrate the effectiveness of SVM in accurately classifying music genres based on the current extracted features. The proposed approach contributes to automated music genre classification systems, facilitating music organization, recommendation, and retrieval. This research promotes advancements in music information retrieval and enhances user experience in music-related applications. 
Perancangan Ontologi Semantik Representasi Digital Oleh - Oleh Khas Bali Ngakan Made Alit Wiradhanta; Ida Bagus Made Mahendra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p19

Abstract

Bali Island, also known as the Island of the Gods, is a popular tourist destination for those who want to enjoy its breathtaking natural beauty. However, many tourists face difficulties in finding authentic Balinese souvenirs to bring back home. To address this issue, a system is needed to assist tourists in easily and quickly finding information about unique Balinese souvenirs using ontology, a semantic web knowledge base. The semantic web is a website development approach aimed at automation and understanding the meaning and relationships of data, resulting in a web experience tailored to visitors' preferences. This research aims to develop an ontology model to be used in the domain of Balinese souvenirs. The ontology design is developed using the Protégé application, where the ontology model is structured with hierarchical classes, slots, properties, and other elements. It is expected that this ontology model will provide information related to semantic web-based application metadata pertaining to Balinese souvenirs. 
Uji Performansi Algoritma LR dan RFR pada Implementasi Sistem Prediksi Harga Rumah I Putu Teddy Dharma Wijaya; Ida Bagus Dwidasmara
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p18

Abstract

Currently the house has become one of the needs that must be met. The price of a house is the main parameter that determines whether a person or organization buys or invests. In general, house prices are influenced by several factors, including building area, land area, number of bedrooms, number of bathrooms and number of garages. Currently, there are many websites devoted to providing information about buying and selling houses. This of course makes it easier for someone when looking for a house with the desired specifications without the need to come directly to the location. However, the house buying and selling platform does not provide a house price prediction feature that is in accordance with user specifications. This means someone who is planning to buy a house does not get an initial idea of the costs that must be spent to own the desired home. Therefore, in this study, researchers will design a web app-based house price prediction system that can make it easier for users to get predictions of the desired house price. In this study the prediction algorithms to be used are linear regression and random forest. Both algorithms will be analyzed for their performance and then the algorithm with the best level of accuracy will be applied as a predictive model which will be integrated with the user interface display. 
Perhitungan Nilai Besaran Fisis Mammografi Jenis Histopatologi IDC dan ILC Anak Agung Ngurah Frady Cakranegara; Ida Ayu Gde Suwiprabayanti Putra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
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.2023.v01.i03.p17

Abstract

In this study, the main objective was to calculate the range of physical values contained in mammography X-ray images and determine the physical quantities that are significant in differentiating between the histopathological types of ILC (Invasive Lobular Carcinoma) and IDC (Invasive Ductal Carcinoma). The research method involved collecting data from 152 mammograms consisting of 7 ILCs and 145 IDCs from doctor Sutomo Surabaya's radiology database. The range of physical values such as entropy, contrast, second angular moment, differential invest moment, mean, deviation, entropy of Hdiff, angular moment of Hdiff, and mean of Hdiff are calculated and compared between ILC and IDC using the Anova statistical test. The results showed that there were differences in the range of physical quantity values between ILC and IDC. Significant parameters in differentiating the two types of histopathology are mean1, mean2, mean3, and mean4. In conclusion, IDC has a higher peak than ILC, and the range of ILC physical quantities is higher than IDC. 

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