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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,
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 166 Documents
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Implementasi Steganografi Citra Gambar pada Sertifikat Hak Kekayaan Intelektual (HKI) Ni Putu Anita Dewi; Made Agung Raharja
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

Information-based technology in the digital era 4.0 currently has a very high influence on life. Many activities are carried out online, for example, meetings, lectures, ordering food, ordering transportation, applying for jobs and sending important files. Not a few of these online activities require image file transactions such as sending Intellectual Property Rights (IPR) image files. There are irresponsible people who can misuse someone's copyrighted work to carry out certain interests. Therefore, the IPR file used must be inserted with a message so that if something unexpected happens, it can quickly identify the culprit. Steganography is a method of inserting information into digital data to protect data ownership. This system will run on the website, create using JavaScript Framework that is React.js.
Klasifikasi Lirik Lagu Bertema Lingkungan dengan Metode Naive Bayes Putu Ode Irfan Ardika; I Gusti Ngurah Anom Cahyadi Putra
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

Awareness of the importance of protecting the environment is becoming increasingly important in this modern era. Humans as inhabitants of the earth have a responsibility to protect and maintain the natural environment,they live in. Songs can be one of theimportant roles that can help awaken people to start protecting the environment they live in. This research makes it easy to find songs that have the theme of protecting the environment by classifying song lyrics. This research will create a system that can classify environment-themed song lyrics using the Naive Bayes method with a Multinomial model. The results of the Naïve Bayes test with the Multinomial model get the best results on the composition of the training data and test data of 10.90 which produces a recall score of 38%, precision of 90.4%, F1 score of 53.5%, while for accuracy it gets the best score on the composition of 90:10 with a yield of 75%. Keywords: Text Processing, TF-IDF, Naive Bayes, Lyrics
Deteksi Sarkasme dan Ironi pada Twitter dengan Mengunakan Metode CNN Arvanchrist Charlie Wijaya; I Gede Arta Wibawa
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

Sarcasm refers to the use of words with meaning opposite of what is written or said. With this ambiguity, it could be difficult to tell if the message is sarcastic or not. This paper aim to give some method to detect sarcasm in message, especially in a tweets from Twitter. In this paper we will use a convolutional neural network method to classify the tweets. In this paper we got the accuracy of 73,8% training and 74,6% for validation.
Implementasi Algoritma KNN untuk Memprediksi Performa Siswa Sekolah I Made Ryan Prana Dhita; Gst. Ayu Vida Mastrika Giri
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

One of the factors that influences students' graduation rates is their performance in learning. Predicting graduation rates based on student performance has the benefit of analyzing academically underperforming students and providing support to students who face difficulties in the learning process. There are several factors to consider in predicting students' graduation rates, such as academic grades, attitudes, and social factors. However, these factors alone are not sufficient to effectively predict students' performance, and educators also struggle to identify which factors affect students' performance.To predict the performance of school students, the K-Nearest Neighbor (KNN) method is utilized. The K-Nearest Neighbor method is often used in classifying students' performance due to its simplicity and ability to produce significant and competitive results. In this research, the prediction of students' graduation rates is carried out using the KNN method.The results of implementing the prediction of students' performance using the KNN method can serve as a reference for students to improve their achievements and assist educators in considering future teaching materials. Keywords: KNN, K-Nearest Neighbor, Students Performance, Student
Implementasi Logika Fuzzy Tsukamoto Pada Sistem Penentuan Suhu AC Dalam Suatu Ruangan Fransiska Christina Sio Da Silva; Agus Muliantara
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

Pada dasarnya setiap manusia mengeluarkan kalori bukan hanya diluar ruangan saja dan melakukan aktivitas yang berat tetapi di dalam ruangan ber-AC pun manusia pasti akan mengeluarkan kalori, oleh karena itu pemakaian AC dalam suatu ruangan sangat dibutuhkan agar ruangan terasa lebih nyaman untuk beraktivitas, semakin banyak jumlah orang dalam suatu ruangan, besarnya ruangan tersebut, seberapa besar suhu diluar ruangan sangat berpengaruh terhadap suhu AC yang digunakan sehingga sangat penting dalam menjaga suhu ruangan tersebut agar tidak terlalu dingin maupun terlalu panas. Dengan menggunakan logika fuzzy tsukamoto dapat ditentukan suhu optimal yang dapat digunakan untuk mengatur suhu AC dalam suatu ruangan tertutup berdasarkan jumlah orang, besarnya ruangan dan besarnya suhu di luar ruangan. Sehingga suhu dalam suatu ruangan yang optimal dapat memberikan pengaruh yang positif bagi kesehatan tubuh manusia.
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 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

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. Keyword: Sheet music notation, Short-Time Fourier Transform (STFT), Piano note recognition, Fast Fourier Transform (FFT), Automated music transcription
Aplikasi Ekstraksi Fitur Citra Buah Berbasis Website Menggunakan Metode Histogram I Made Wahyu Purnama Putra; I Wayan Supriana
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

Image recognition and feature extraction of fruits using histogram methods have garnered significant attention in the fields of agriculture, food industry, and image processing. The Histogram method is an effective approach in automatically identifying unique characteristics of each fruit. Previous studies have demonstrated the success of histogram method in fruit image recognition based on color, texture, and shape. In this research, we propose the use of histogram method for fruit image feature extraction. We utilize secondary data consisting of fruit images such as apple, banana, mango, orange, papaya, melon, and watermelon, obtained from publicly available research datasets. We conduct a literature review to deepen our understanding of the histogram method and implement feature extraction steps such as mean, standard deviation, energy, entropy, and skewness. The authors developed a web-based application using Python programming language with the Django framework to perform fruit image feature extraction. This application allows users to upload fruit images, perform image pre-processing, and extract features using the histogram method. The extracted feature results are stored in a database for further use. Through this application, we successfully extract features from fruit images, such as banana, using the histogram method. The extracted feature results include mean, standard deviation, energy, entropy, and skewness. These results can be utilized in further research and training machine learning models to recognize and classify various types of fruits with high accuracy. Keywords: fruit image recognition, feature extraction, histogram method, image pre-processing, web-based application.
Prototype Aplikasi Edukasi Cyberbullying Berbasis Mobile Android Fiki Nur Rahman; Shendy Aditayahya Wardana; Pradityo Utomo
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

As technology develops rapidly, it has not only positive but also negative impacts; one of the negative impacts is the case of cyberbullying. Cyberbullying is an unpleasant action towards other people on the internet. One way to reduce cyberbullying is to create educational applications about cyberbullying. This application will provide an explanation of what cyberbullying is and how to prevent cyberbullying by providing an explanation that is light and easy to understand. This application is based on Android mobile, so it can more easily reach more users, using Java programming and display design using figma. Keywords: Cyberbullying, Education Application, Mobile Android
Efektifitas Algoritma K-NN dan Random Forest Dalam Mengenali Gender Berdasarkan Suara Berlin Pratama; I Ketut Gede Suhartana
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

Human beings have the ability to recognize one's gender through hearing and vision. In computer science this is called sound analysis, but often human sounds differ from the original after processing by computer. In this case, we try to differentiate human voices by gender using the K-Nearest Neighbor and Random Forest algorithms. The K-Nearest Neighbor algorithm has an accuracy of 76%, while Random Forest has an accuracy of 97%.
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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

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