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Analisis Perbandingan Enkripsi File Teks Berformat .txt dan .docx Menggunakan Algoritma AES Kennardy Andrew Limartha; I Gede Arta Wibawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 2 (2025): JNATIA Vol. 3, No. 2, Februari 2025
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.2025.v03.i02.p10

Abstract

In this research, the Advanced Encryption Standard (AES) algorithm is used to encrypt text files. Data stored in various formats has the potential to cause the size of the data on the data storage device to become large and does not necessarily guarantee the security of the data. One method of data security is to encrypt data. This research utilizes data in text file format with data types in the form of ".txt" and ".docx" which refer to the file size for testing. Based on the test results, it shows that the AES encryption method provides good results for text file formats. The time required for the encryption process using the AES algorithm is influenced by each different file size, the larger the file size used, the longer the computing time required and vice versa. 
Klasifikasi Tingkat Keparahan Kecelakaan Lalu Lintas Menggunakan Random Forest Classifier I Gusti Ngurah Bagus Lanang Purbhawa; I Gede Arta Wibawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 1 (2024): JNATIA Vol. 3, No. 1, November 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.v03.i01.p07

Abstract

Traffic accidents are a common problem that often occurs. Many factors cause and determine the severity of traffic accidents. These factors can include road conditions, weather, light conditions, driver age, and the cause of the accident. In this study, researchers will try to apply the Random Forest method to classify the severity of traffic accidents. The Random Forest method was chosen because of its excellent ability to handle high-dimensional data and tolerance for overfitting. The dataset used in this research was taken from Kaggle, consisting of 12316 records and 32 features covering various attributes related to traffic accidents. Before applying random forest, it is necessary to carry out a preprocessing stage on the dataset to remove irrelevant features, fill in empty values and divide the data into training and testing data. The results of this research show that Random Forest can produce a good level of in classifying the severity of traffic accidents with 92% accuracy. This shows the potential of this method as a useful tool in the analysis and prediction of traffic accidents. Therefore, this research makes a significant contribution to efforts to improve road safety. 
Analisis Microinteractions pada Aplikasi Manajemen Keuangan dengan Metode System Usability Scale Ni Wayan Diyarini; I Gede Arta Wibawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 4 (2024): JNATIA Vol. 2, No. 4, Agustus 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.i04.p05

Abstract

Financial management is essential for personal financial well-being, yet financial literacy remains low in Indonesia. To improve usability, this study analyzes microinteractions in existing financial management applications by using System Usability Scale (SUS) methode. Through literature review, observation, and online surveys, microinteraction effectiveness is assessed, revealing areas for improvement. Results indicate a SUS score of 40, suggesting poor usability. Thus, redesigning the application is recommended to enhance usability and user experience, fostering better financial management practices. 
Klasifikasi Citra Elektrokardiogram untuk Deteksi Penyakit Jantung Menggunakan Metode GLCM dan SVM Andreas Panangian Tamba; I Gede Arta Wibawa
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.p09

Abstract

Heart disease is a major cause of death worldwide. Electrocardiogram (ECG) is a common method used to detect heart abnormalities. Analyzing ECG signals requires expertise and can be time-consuming. This study investigated the use of machine learning to classify ECG images for heart disease detection. The proposed method utilizes Gray Level Co-occurrence Matrix (GLCM) for feature extraction such as Dissimilarity, contrast, energy, ASM, homogeneity and Correlation. Meanwhile using Support Vector Machine (SVM) for the classification. We achieved an accuracy of 99.61% using this approach. The results suggest that the combination of GLCM and SVM can be a valuable tool for ECG image classification and potentially aid in early and accurate diagnosis of heart disease. 
Penerapan Metode Kompresi Wavelet dalam Pengolahan Data Gambar untuk Mengurangi Ukuran File Ni Putu Suci Paramita; I Gede Arta Wibawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 4 (2023): JNATIA Vol. 1, No. 4, Agustus 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.i04.p29

Abstract

Currently more and more computer users the increase in the number of computer users has led to an increase digital data user. One of the most used digital data today is digital images. The smallest element of a digital image is called pixels. The higher the number of pixels, the higher the digital resolution picture. The higher the pixel count, the larger the digital image file size. Resulting in fast full data storage capacity.Image data compression is an important process in data processing and storage, especially with the increasing use of images in various applications and platforms. This study aims to apply the Wevalet compression method in processing image data to reduce file size. The Wevalet compression method combines the wavelet transform with an adaptive and efficient compression breaking procedure, to form significant compression without significant sacrifice of image quality. 
Implementasi Algoritma A (Star) dengan Graf untuk Menentukan Rute Terpendek Distributor Kopi I Putu Andi Wiratama Putra; I Gede Arta Wibawa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 1 No. 4 (2023): JNATIA Vol. 1, No. 4, Agustus 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.i04.p06

Abstract

In this research, the A Star algorithm is employed to find the most efficient route for goods distribution. Distributors encounter challenges in ensuring timely deliveries due to the presence of multiple destinations spread across different regions. Congestion further adds to the complexity of determining the shortest path. The A Star algorithm utilizes the distance-plus-cost function to prioritize the order of visiting points. This study utilizes primary data, comprising five shop locations in the Tabanan city, as nodes and incorporates the distances between the shops. The implemented program utilizes the A Star algorithm to compute the shortest route and present the path along with its corresponding distance. The objective of this research is to attain the shortest route and calculate the distance covered for the coffee distributor. 
Implementasi Metode Certainty Faktor Untuk Rekomendasi Pembelian Hp Komang Arsa Wiguna; I Gede Arta Wibawa
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.p28

Abstract

In this study, the implementation of the Certainty Factor (CF) method was carried out to provide consumers with more accurate cell phone purchase recommendations. This method combines expert knowledge and user data to produce more reliable recommendations. The implementation process involves collecting relevant HP feature data, establishing rules based on expert knowledge, calculating confidence factors (CF) based on the level of expert confidence and suitability of user data, and merging the CFs of all rules to produce a final recommendation. Through testing and evaluation, the Certainty Factor method is proven to be able to provide accurate HP purchase recommendations and assist consumers in choosing a HP that suits their preferences and needs. However, this research still requires further development to improve the accuracy of recommendations and to conduct tests with larger and more diverse datasets to ensure the effectiveness and validity of this method in the context of H purchase recommendations. 
Penerapan RMS Contrast sebagai Penentu Citra Terbaik Berdasarkan Tingkat Kontras Shiennyta Florensia Adiriyanto; I Gede Arta Wibawa
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.p07

Abstract

This research centers on the objective of identifying the finest image from a burst shot through the utilization of Root Mean Square (RMS) contrast as a guiding metric. The primary focus lies in selecting the visually captivating image by assessing the contrast levels present in each individual shot. By conducting calculations of the RMS contrast values, the optimal image can be determined. The core purpose of this study is to employ RMS contrast as a reliable criterion for selecting the most outstanding image from a burst shot, thereby guaranteeing the production of high-quality visuals, and aiding in the organization and decluttering of smartphone galleries. This research holds significance in addressing the growing need for efficient and effective image selection methods, ensuring that users can effortlessly identify and showcase the best images captured in burst mode. By embracing the power of RMS contrast analysis, individuals can confidently curate their image collections with exceptional visual content while optimizing limited storage space on their smartphones. 
Co-Authors Adiartika, Made Harry Dananjaya Adiriyanto, Shiennyta Florensia Anak Agung Gede Agung Angga Aditya Anak Agung Istri Ngurah Eka Karyawati Anak Agung Istri Ngurah Eka Karyawati Anak Agung Putra Adnyana Andreas Panangian Tamba Apriana, I Komang Gede Apsari, Made Sri Ayu Bib Paruhum Silalahi Cokorda Rai Adi Pramartha Danandjaya, Gede Bagus Diyarini, Ni Wayan Dwijayana, I Gede Diva Gede Astuti, Luh Giri, Gst. Ayu Vida Mastrika Gst. Ayu Vida Mastrika Giri I Dewa Made Bayu Atmaja Darmawan I Dewa Ngurah Tri Hendrawan I Gede Santi Astawa I Gede Tendi Ariyanto I Gusti Agung Gede Arya Kadyanan I Gusti Ngurah Anom Cahyadi Putra I Gusti Ngurah Bagus Lanang Purbhawa I Ketut Gede Suhartana I Komang Gede Apriana I Komang Gede Apriana, I Komang Gede Apriana I Made Ryan Prana Dhita I Made Widiartha I Made Widiartha I Putu Andi Wiratama Putra I Putu Ryan Paramaditya I Putu Satwika I Wayan Gede Gemuh Raharja R.L. I WAYAN SANTIYASA I Wayan Widya Premananda Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Ida Bagus Made Mahendra Ida Bagus Made Wiguna Tedja Sukmana Ilham Arsy Dwi Atmojo Jaya, Cokorda Gde Teresna Kadek Diah Pramesti Kartika Noviyanti, Komang Kennardy Andrew Limartha Komang Ari Mogi Komang Arsa Wiguna Kurnia Amerta, I Made Pegi Luh Arida Ayu Rahning Putri Luh Gede Astuti Made Bayu Maha Krisna Siaka Mega Saputra, I Gede Widiantara Michael Tanaya Ngurah Agus Sanjaya ER Ni Ketut Sukardiasih Ni Luh Komang Indira Pramesti Ni Made Anita Widyastini Ni Putu Suci Paramita Ni Wayan Diyarini Ni Wayan Yulia Damayanti Paramita, Ni Putu Suci Pradnyawati, Putu Indah Pradyto, Kadek Dwitya Adhi Prasetyo Adi Utomo Prathama, Wayan Adhitya Premananda, I Wayan Widya Putra, Angga Pramana Putra, I Putu Andi Wiratama Putra, Ida Bhujangga Bagus Dili Putu Bagus Dio Pranata Qaris Ardian Pratama Raharja, Made Agung Setiawati, Ni Ketut Intan Shiennyta Florensia Adiriyanto Siaka, Made Bayu Maha Krisna Sidi, Widya Dharma Tamba, Andreas Panangian Vyasa, I Made Satya Wiguna, Komang Arsa Wijaya, Arvanchrist Charlie Wiratama Putra, I Putu Andi Wisnawa, Agus Yauw James Fang Dwiputra Harta Yauw, Yauw James Fang Dwiputra Harta