cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
I Gede Surya Rahayuda
Contact Email
igedesuryarahayuda@unud.ac.id
Phone
+6289672169911
Journal Mail Official
jnatia@unud.ac.id
Editorial Address
Sekretariat JNATIA Gedung FMIPA Lantai 1, Program Studi Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana
Location
Kota denpasar,
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
 22   23   24   25   26 
Prediksi Kenaikan Penduduk Jawa Timur Menggunakan Metode Long Short Term Memory Atiqur Rozi; Muhammad Rohman Irsyadi; Sandy Nicholas; Anggraini Puspita Sari
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 3 (2024): JNATIA Vol. 2, No. 3, Mei 2024
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.2024.v02.i03.p02

Abstract

This research aims to develop a prediction model for population increase in East Java using the Long Short Term Memory (LSTM) method. Historical population data from the previous period will be used as input to train the LSTM model. This approach is expected to produce accurate predictions about population growth in the East Java region. The LSTM method was chosen due to its ability to handle sequential data and long-term memory, which is in line with the characteristics of demographic data. This research will involve data pre-processing, LSTM model building, and model performance evaluation using relevant metrics. The results of this research are expected to contribute to a better understanding of population growth trends in East Java and provide a basis for more informed decision-making in future regional development planning and social policy. 
Implementasi Algoritma A (Star) untuk Menentukan Rute Jarak Terpendek Melisa Tryastie; Yukandri; Lia Nelda; Ressa Priskila; Viktor Handrianus Pranatawijaya
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 3 (2024): JNATIA Vol. 2, No. 3, Mei 2024
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.2024.v02.i03.p01

Abstract

In this research, the implementation of the A star algorithm is used to find efficient routes, reduce the travel time, and optimize the use of existing road infrastructure at waypoints. The A star algorithm uses the concept of Open List and Close List, which helps to reduce the number of rechecks on the points travelled, thus speeding up the search process. The A star algorithm stops when there are no more points on the open list or when the end point has been determined. This research method uses primary data, which consists of five street locations in Palangka Raya city, as nodes and combines the distance between the street points. The implemented program uses the A Star algorithm to calculate the shortest route and displays the path along with the distance. The purpose of this research is to achieve the shortest route and calculate the distance travelled for the waypoints. 
Analisis Sentimen Twitter Pengaruh Tokoh Politik dengan Menggunakan Metode K-Nearest Neighbor I Made Surya Adi Palguna; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p25

Abstract

Public opinion towards political figures can consist of positive and negative sentiments. Besides that, social media has developed which can be used as a forum for public opinion, one of which is Twitter. From this public opinion, sentiment analysis is formed which uses a classification algorithm. This work leverages the K-Nearest Neighbor (KNN) algorithm, which classifies data based on its similarity to existing data points. Tweets undergo preprocessing, followed by TFIDF weighting for keyword importance and confusion matrix calculations for calculate the evaluation of algorithm. By analyzing the nearest neighbors, sentiment values are assigned. The KNN model achieved an accuracy of 84,06% for k = 5, precision of 86,70% for k = 5, recall of 95,89% for k = 7, and F1-score of 90,93% for k = 5, demonstrating its effectiveness in assessing sentiment and influence through Twitter data. This research contributes to the field of political communication by offering a robust method for analyzing public opinion and gauging the influence of political figures on social media platforms. 
Klasifikasi Kualitas Buah dengan Menggunakan Convolutional Neural Network (CNN) Studi Kasus Dataset Fresh and Rotten Classification I Gede Diva Dwijayana; I Putu Fajar Tapa Mahendra; Ivan Luis Simarmata; Gst. Ayu Vida Mastrika Giri
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p24

Abstract

This research aims to develop a deep learning model for fruit quality classification using Convolutional Neural Network (CNN) with the Fresh and Rotten Classification dataset. Two CNN models are compared, with the first model serving as the baseline and the second model resulting from parameter tuning based on the first model. The results indicate that increasing the number of epochs improves the model accuracy, as evidenced by the first model achieving 91% accuracy with 10 epochs and 93% accuracy with 15 epochs. Similar patterns are observed in the second model, with 87% accuracy at 10 epochs and 90% accuracy at 15 epochs. Despite the second model involving the addition of layers and parameters, its accuracy tends to be lower compared to the first model. The research emphasizes that increasing the number of epochs enhances model performance, while adding layers does not always lead to significant improvements, depending on the model's complexity and dataset characteristics. The first model, trained with 15 epochs, demonstrates the highest accuracy, approaching results from similar previous studies. This evaluation provides valuable insights for developing a CNN-based fruit classification model on the Fresh and Rotten Classification dataset. 
Tinjauan Literatur tentang Cloud Computing dan Artificial Intelligence (AI) Potensi dan Tantangan Ganes Wisnu Cahya Bagaskara; Nono Heryana
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p23

Abstract

Artificial intelligence (AI) has become a key element in industrial development and plays a crucial role in driving the integration of emerging technologies such as graphic processing units, Internet of Things, blockchain, and cloud computing in the new era of big data and Industry 4.0. The integration of cloud computing and artificial intelligence (AI) holds great potential across various fields. By combining the flexible and scalable nature of cloud computing with the complex data analysis capabilities of artificial intelligence, this technology can provide innovative solutions in data processing, decision-making, and process automation. However, there are challenges to be addressed in integrating these two technologies, and the use of cloud computing and AI also presents potential negative implications. Further research is needed to optimize the benefits offered by this integration while addressing associated constraints and risks. 
Pengamanan Data Tekstual dengan Kombinasi Vigenere Cipher dan Caesar Cipher Luh Arimas Pertiwi; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p22

Abstract

Problems in data security is an important aspect in maintaining data storage, especially data stored in digital form. This is due to very rapid progress in the field of computer science with the open-system concept that has been widely used, so that this can make it easier for someone to destroy data, especially data stored in digital form without having to be known by the data custodian. In this case the researcher found a problem in using one algorithm, namely the Caesar cipher in data security, where there is a Brute force attack that tries all possible key combinations to crack a password. In the context of the Caesar Cipher, brute force can be used to try all possible shifts of letters and find a key that produces a plausible decrypted text. This study aims to maximize the security of textual data by combining two algorithms in it, in which the algorithm used is the Vigenere Cipher and the Caesar Cipher. The result of this research is that textual data that is secured becomes more difficult to understand for third parties who may want to manipulate data. 
Pengenalan Nada Piano Dengan Algoritma Short Time Fourier Transform (STFT) I Putu Yoga Laksana Putra; I Gusti Agung Gede Arya Kadyanan
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p21

Abstract

In the field of music, sheet music notation represents the graphical representation of the melody or harmony of a song. However, manually transcribing complex piano music can be challenging. In this research, we propose the application of Short-Time Fourier Transform (STFT) as a method for piano note recognition. STFT, a spectral analysis technique, is useful for analyzing frequency changes in time-varying signals such as music signals. The literature review reveals successful implementations of STFT in chord recognition and gamelan notation detection, with accuracies ranging from 60% to 90%. The research methodology includes a literature review, data collection of piano audio samples, feature extraction using Fast Fourier Transform (FFT), and system design involving preprocessing, segmenting the signal, feature extraction using STFT, signal processing using filters or thresholding, and mapping frequencies to piano notes. This research aims to provide an effective method for piano note recognition using STFT, contributing to automated music transcription and facilitating the learning and playing of piano music. 
Desain Antarmuka Berbasis Pengguna pada Aplikasi Komik Mobile Studi Kasus pada Aplikasi NanoComic Naurah Adinda Putrie Amanda; Luh Gede Astuti
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p20

Abstract

NanoComic is an online platform that enables users to read comics online. The purpose of this research is to design a user interface and user experience based on mobile devices, aligning with the increasing interest in reading comics nowadays. The method employed in this study is the system usability scale, which is used to measure the extent to which the system can be easily used from the subjective perspective of users through the completion of Likert-scale questionnaires. Consequently, this application is expected to address the existing issues within the community. 
Perancangan User Interface dan User Experience Website KosIN dengan Pendekatan Design Thinking Ida Bagus Ari Widhiana; Luh Gede Astuti
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p19

Abstract

The need for education or employment drives people to move to other areas that offer greater access to education or job opportunities. Individuals who move to a new area for higher education or job search often face challenges in finding accommodations that meet their needs. The increasing number of newcomers has led to a growing demand for housing. The main constraint is that individuals must physically go to the location to search for accommodations like boarding houses ("kos" in Indonesian). Therefore, innovation is needed by leveraging technology that can provide a solution to the challenges faced. The solution to this problem is to create a boarding house search application. The method used in this research is Design Thinking. Design Thinking aims to understand the problems and user needs, so that the developed application is truly beneficial for the users. For its testing, the Usability Testing method is used to assess to what extent a product can be used by specific users based on effectiveness, efficiency, and user satisfaction. 
Akurasi Klasifikasi Kualitas Wine Menggunakan Algoritma Random Forest dengan Min-Max Normalization Putu Putri Pratiwi; Ida Bagus Made Mahendra
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
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.2024.v02.i02.p18

Abstract

In this research, we will discuss the use of the Random Forest algorithm in classifying wine quality using Min-Max normalization. The data obtained will be subjected to data preprocessing and data normalization using Min-Max Normalization which is then applied to the Random Forest algorithm. This algorithm was chosen because it can provide good accuracy for the classification process. Data normalization and preprocessing are needed to produce a classification model with better accuracy. Min-Max normalization is used because it can improve the performance of the Random Forest algorithm in increasing accuracy. 

Page 24 of 32 | Total Record : 316

 22   23   24   25   26 

Filter by Year

2023 2026


Reset
Filter By Issues
All Issue Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026 Vol. 4 No. 1 (2025): JNATIA Vol. 4, No. 1, November 2025 Vol. 3 No. 4 (2025): JNATIA Vol. 3, No. 4, Agustus 2025 Vol. 3 No. 3 (2025): JNATIA Vol. 3, No. 3, Mei 2025 Vol. 3 No. 2 (2025): JNATIA Vol. 3, No. 2, Februari 2025 Vol. 3 No. 1 (2024): JNATIA Vol. 3, No. 1, November 2024 Vol. 2 No. 4 (2024): JNATIA Vol. 2, No. 4, Agustus 2024 Vol. 2 No. 3 (2024): JNATIA Vol. 2, No. 3, Mei 2024 Vol. 2 No. 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024 Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023 Vol. 1 No. 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023 Vol. 1 No. 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023 More Issue