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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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Kota denpasar,
Bali
INDONESIA
Jurnal Nasional Teknologi Informasi dan Aplikasinya
Published by Universitas Udayana
ISSN : 29863929     EISSN : 30321948     DOI : -
Core Subject : Science,
Computer Science & IT
JNATIA (Jurnal Nasional Teknologi Informasi dan Aplikasinya) merupakan jurnal yang berfokus pada teori, praktik dan metodologi seluruh aspek teknologi di bidang ilmu dan teknik komputer serta ide-ide produktif dan inovatif terkait teknologi baru dan sistem informasi. Jurnal ini memuat makalah penelitian asli yang belum pernah dipublikasikan dan telah melalui jurnal double-blind review. JNATIA (Jurnal Teknologi Informasi dan Penerapannya) diterbitkan empat kali setahun (Februari, Mei, Agustus, November).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 255 Documents
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Analisis Sentimen pada Teks Berbahasa Bali Menggunakan Metode Multinomial Naive Bayes dengan TF-IDF dan BoW Wibawa, Putu Widyantara Artanta; Pramartha, Cokorda Rai Adi
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 1 (2023): JNATIA Vol. 2, No. 1, November 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Many people want a fast and efficient search method as technology advances. A song search is one example of this kind of search. A song is a collection of sing-along lyrics with rhythms and melodies for many to enjoy. Due to the large number of song lovers, some people are often constrained by the title of the song to be sung. This is caused by one factor, namely only memorizing some of the lyrics of the song to be sung. Given these problems, in this study a solution was developed, namely the application of identifying song titles based on input from the user's lyrics. The algorithm used by researchers in this study is the Boyer-Moore Algorithm, which is considered better in terms of matching substrings in longer texts. The research method used includes literature study, data collection, implementation, and testing. The implementation results show that the system successfully recognizes song titles with high accuracy based on the given piece of lyrics. In conclusion, this study proves that the development of a song title identification system based on snippets of lyrics using the website-based Boyer-Moore algorithm is an effective method. This system can help users recognize song titles based on the snippets of lyrics they remember with high accuracy. Keyword: song, lyrics, boyer-moore
Klasifikasi Teks Spam dengan Algoritma Support Vector Machine dan Chi – Square Tpoy, Getzbie Alfredo; Muliantara, Agus
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Spam messages are messages that contain false information, commonly regarding events, banking, insurance, bills, advertisements, and viruses. To address the issue of spam, classification can be performed on the received messages. Classification can be done by separating texts that contain spam messages from texts that contain legitimate (ham) messages. In this study, spam text classification was conducted using the Support Vector Machine algorithm, feature selection using Chi-Square. The Chi-Square feature selection method was performed using percentages of 20%, 40%, 60%, and 80%, with accuracy, precision, recall, and F1-Score as the measured values. The result of study obtained was an accuracy of 98.82% with an F1-Score of 93.05% at a feature selection percentage of 60%, using the RBF kernel. Feature selection with percentages of 20%, 40%, and 80% resulted in accuracies of 97.93%, 98.29%, and 98.02%, respectively. These accuracies were better compared to the accuracy without feature selection, which was 97.57%. Keywords: Chi - Square, spam, support vector machine
Klasifikasi Ulasan Aplikasi TikTok Menggunakan Algoritma K-Nearest Neighbor dan Chi Square Aisyah Putri, Sandrina Ferani; Supriana, I Wayan
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

TikTok application has achieved extraordinary popularity among users around the world, which has been downloaded by more than 500 million users with 16 million reviews and received a rating of 4.4 out of 5 on the Google Play Store. In this study, we will analyze user sentiment towards the TikTok application reviews. These reviews can be a benchmark for users to find out information about user experience and become a race for application developers to improve performance or quality. For that we need a method to describe the reviewer efficiently so that it is easier to understand the reviewer. In this study, the authors used a comparison of the KNN algorithm with the effect of feature selection to carry out the classification. Classification of application reviews into two classes, positive reviews, and negative reviews. In this classification, it is found that using Chi Square feature selection can produce the highest accuracy, with k = 9 value of 86.22% whereas without Chi Square feature selection it only produces the highest accuracy with k = 11 value of 77.04%. Keywords: TikTok, Classifier, Analysis Sentiment, K-Nearest Neighbor, Chi Square
Implementasi Algoritma K-Means Clustering dalam Penentuan Klasifikasi Tingkat Pembangunan Perekonomian di Provinsi Bali Sandi, Wijaya Kusuma; Dwidasmara, Ida Bagus Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 2 (2023): JNATIA Vol. 1, No. 2, Februari 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2023.v01.i02.p02

Abstract

Inequality in economic development is one of the problems faced by regencies/cities in Bali Province. Even though Bali is one of the provinces with a fairly large economic contribution in Indonesia, most of its economic resources are still centered in one area. This study aims to form a cluster of districts/cities in Bali Province based on the performance of regional human and economic development using the K-Means Clustering method in order to support an even distribution of economic development in Bali by making regional-based policies that are in adaptability to the level of the economy. The study result showed that three clusters were formed with the first cluster consisting of Klungkung, Karangasem, Bangli, and Jembrana regencies, the second cluster consisting of Badung Regency and Denpasar City, and the third cluster consisting of Gianyar, Buleleng, and Tabanan regencies. Keywords: Pembangunan Ekonomi, K-Means Clustering, Bali
Sistem Pendukung Keputusan Menentukan Karyawan Kontrak Menjadi Karyawan Tetap dengan Algoritma Regresi Linier Berganda Astrawan, Anak Agung Made Krisna; Suhartana, I Ketut Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 1 (2023): JNATIA Vol. 2, No. 1, November 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

This study aims to aid in decision-making for determining the employment status of contract employees versus permanent employees using the Multiple Linear Regression algorithm. The analysis shows that the independent variables, including Work Experience (X1), Education Length (X2), and Attendance (X3), strongly influence the dependent variable of Employee Status (Y). With a coefficient of determination of 0.734, the model explains 73.4% of the variation in Employee Status based on these variables. The integrated decision support system facilitates decision-making by providing recommendations based on user inputs. Application testing confirms the system's effectiveness in assisting decisions regarding the eligibility of contract employees for permanent employment. Overall, this research contributes to informed and accurate decision-making in employee status determination. Keywords: Decision Support System, Multiple Linear Regression
Analisis Sentimen Gambar pada Media Sosial dengan Pendekatan Deep Learning T, Ronaldito Juan Bantaras; Raharja, Made Agung
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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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. Keywords: Sentiment analysis, image analysis, social media, deep learning
Rancang Ontology Untuk Sistem Pencarian Produk Smartwatch Berbasis Web Sematic Suryaningsih, Ni Luh Eka Eka
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

The increasing popularity of smartwatches in the digital era has highlighted the need for efficient and relevant search systems to assist users in selecting the right product. Semantic Web technology, specifically ontology-based approaches, offer a promising solution for optimizing smartwatch product searches. This research aims to design an ontology for a Semantic Web-based smartwatch product search system using the Methontology methodology. The designed ontology enables users to search for smartwatches based on preferences such as brand, price, features, and specifications. The ontology facilitates the development of a recommendation system for personalized smartwatch suggestions. The evaluation of the ontology through SPARQL queries demonstrates its effectiveness in representing smartwatch product information. This research contributes to enhancing user experiences and decision-making processes when purchasing smartwatches. Keywords: Semantic Web, ontology, smartwatch, product search, Methontology, recommendation system, SPARQL queries
Algoritma Advanced Encryption Standard (AES-128) Dengan Mode ECB Dalam Pengamanan File Simangunsong, Haposan; Raharja, Made Agung
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Data Protection is one of the important things to protect, important messages and information from corruption, compromise or loss so that messages and information remain safe. Encryption and decryption techniques are considered to be able to secure data properly by protecting files from being easily read or seen by unauthorized parties. In this case, the authors used a cryptography symmetric algorithm called Advanced Encryption Standard (AES) and Electronic Code Book (ECB) as a solution to existing problems. The AES algorithm process is divided into four steps, the first step is SubBytes, the second step is ShiftRows, the third step is MixColums and the las step is AddRoundKey. And using the SHA algorithm as the hashing function. The algorithm is applied to a web application and using python as a programming language. Advanced Encryption Standard (AES) Algorithm with ECB Mode can be implemented to encrypt and decrypt files. The use of AES will encrypt every 128bit block of the file until it becomes a ciphertext which is an array of encrypted bytes. The decryption process using the AES algorithm with ECB mode will decrypt every 128 bits of the ciphertext to produce the original byte array file. AES with ECB mode which is implemented in the python programming language can be used to encrypt media files such as images, audio and video with a good level of security.
Penerapan Metode Kompresi Wavelet dalam Pengolahan Data Gambar untuk Mengurangi Ukuran File Paramita, Ni Putu Suci; Wibawa, I Gede Arta
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Currently more and more computer users theincrease in the number of computer users has led to an increase digital data user. One of the most useddigital 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, toform significant compression without significant sacrifice of image quality. Keywords: images, compression, Wevalet
Dampak Penggunaan Anotasi Penamaan yang Berbeda pada Kinerja NER Saputra, I Made Widi Arsa Ari; Supriana, I Wayan
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

In developing the NER model, naming annotations are used as an important part of the training process. The impact of using different naming annotations on NER performance has been a concern in the research community. So,the writer wants to once again, test the impact of using different naming annotations using the spaCy library on English documents. Using 2 naming schemes namely BIO and IOBES, using the spaCy model to get 0.96 accuracy for BIO and 0.95 for IOBES. Keywords: NER, Person Entity, spaCy, BIO, IOBES, Named Entity Annotation

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