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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, 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
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Perancangan Alat Pemberian Pakan Ikan Otomatis Pada Aquarium Berbasis Mikrokontroller AT89S52 I Gusti Bagus Ngurah Agung Brian Wijaya; Ida Ayu Gde Suwiprabayanti Putra
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.p17

Abstract

An important factor in keeping fish in an aquarium is the timeliness of feeding fish. Most of those who have a hobby of raising fish are worried about the feeding that must be done every day. Based on this, this final project designed and manufactured an automatic fish feeding device based on the AT89S52 microcontroller. So, a tool was designed that makes it easier to feed the fish automatically according to a predetermined schedule. The supporting components for scheduling fish feed include making a minimum circuit for the AT89S52 system as the brain of this tool which will later be loaded with a program using assembler language, RTC (Real Time Clock) as a timer, DC motor to rotate the valve opener for fish feed. 
Dampak Penggunaan Anotasi Penamaan yang Berbeda pada Kinerja NER I Made Widi Arsa Ari Saputra; I Wayan Supriana
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.p16

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. 
Optimasi SVM untuk Klasifikasi Warna Investigasi Terhadap Pengaruh Fungsi Kernel dan Penyetelan Parameter Pande Gede Dani Wismagatha; I Wayan Santiyasa
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.p15

Abstract

Color plays a crucial role in visual applications such as object recognition, image processing, computer vision, and computer graphics. Support Vector Machine (SVM) algorithms have gained attention for color classification due to their ability to handle complex data. SVM, a machine learning algorithm for classification and regression, aims to find optimal decision boundaries. In color classification using SVM, color data is represented by feature vectors, and SVM learns patterns to classify colors accurately. The SVM algorithm demonstrates a high accuracy rate, with an average accuracy of approximately 85% in color detection. This indicates the SVM's ability to effectively separate and classify colors with precision. SVM is proven to be effective in handling non-linear color data by utilizing kernel functions to transform the feature space into higher dimensions, enabling accurate classification of complex color data. The outstanding performance of the SVM algorithm in color detection presents vast potential applications in color recognition, image processing, computer vision, and computer graphics. SVM offers accurate and reliable solutions for object classification based on color characteristics in various contexts. 
Analisis Celah Keamanan Jaringan WPA dan WPA2 dengan Menggunakan Metode Penetration Testing Albert Okario; I Putu Gede Hendra Suputra
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.p14

Abstract

With the rapid development of communication and information technology, wireless local area network (WLAN) security has become crucial and a major concern, as data traffic is transmitted without the need for cables. Internet-connected network devices are inherently insecure and can be exploited by crackers or hackers. When data communicates or connects in the data traffic, where data is sent and passes through a series of terminals to reach its destination, an irresponsible user has the opportunity to modify or intercept the data. Therefore, designing a WLAN network connected to the internet must be carefully planned to minimize undesirable incidents. The weakness of the IEEE 802.11 network that uses WEP encryption tends to make the encryption code more easily discoverable by hackers. Based on the aforementioned background, we conducted this research to identify vulnerabilities or security flaws in WPA and WPA2-PSK networks using penetration testing methods. 
Perbandingan Algoritma Forward Chaining dalam Sistem Pakar Rekomendasi Peminatan Bidang Teknologi Putu Agus Dharma Kusuma; I Made Widiartha
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.p13

Abstract

This research aims to compare the forward chaining algorithm with the Backward Chaining, Breadth-First Search (BFS), and Depth-First Search (DFS) algorithms in the context of an expert system for recommending specialization in the field of technology. The primary focus of this study is to analyze the runtime performance of each algorithm and determine the algorithm that provides the fastest runtime. The research methodology involves implementing the four algorithms in an expert system that provides recommendations for technology field specialization based on rules and user responses. The data used in the study consists of specialization rules in the technology field and user responses related to their interests in those fields. The results of the study demonstrate that the forward chaining algorithm outperforms the Backward Chaining, BFS, and DFS algorithms in terms of runtime performance. This indicates that the forward chaining algorithm is more efficient in generating technology field specialization recommendations. Based on the findings of this research, it is recommended to use the forward chaining algorithm in the development of expert systems for technology field specialization. This algorithm can assist users in obtaining recommendations quickly and efficiently, thereby enhancing user experience and the effectiveness of the expert system in providing suitable technology field specializations based on user interests. 
Perbandingan Berbagai Metode Segmentasi dan Mechine Learning pada Makanan Tradisional Sumatera Utara Anugrah Ignatius Sitinjak; I Made Widiartha
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.p12

Abstract

This study investigates the categorization of traditional North Sumatran dishes using various segmentation methods. The goal is to participate and participate in the preservation of North Sumatran culture. The study covers 34 types of traditional North Sumatran dishes originating from various regions. Food images are processed using segmentation techniques such as Sobel, Prewitt, Robert, Scharr, and Canny filters. The data set is then used in traditional machine learning algorithms, including Random Fortst, Decision Tree, and four SVM algorithms, for classification purposes. Among the algorithms with the highest performance, the Random Forest algorithm with Robert's segmentation method achieves outstanding results on dataset testing, with 85.52% accuracy, 84.63% recall, 83.77% precision, and 82.49% f1 score. The execution time for most of the best performing algorithms is around 1 minute on average. In addition, the Random Forest algorithm with the Canny operator achieves 81.51% accuracy, 84.97% recall, 86.81% precision, and 85.61% f1 score on dataset testing. The Random Forest algorithm with the Sobel operator obtains an accuracy of 78.41%, a recall of 65.28%, a precision of 62.33%, and an f1 score of 63.71%. Among the four SVM algorithms, the Sigmoid SVM with the Scharr operator achieves the highest performance in its category across all classification metrics. The importance of insight into the traditional cuisine of North Sumatra is invaluable. Emphasizing the importance of this research in promoting the preservation and introduction of traditional North Sumatran food. 
Identifikasi Salt and Pepper Noise pada Citra dengan Metode Median Filter Steven Gerald Parsaoran Berutu; I Komang Ari Mogi
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.p11

Abstract

Noise is a common issue in image processing that can degrade the quality and clarity of images. In this research, we propose a method for identifying the levels of salt and pepper noise in images using the median filter technique. The median filter is a non-linear filtering approach that effectively reduces noise by replacing the pixel values with the median value of neighboring pixels. In our approach, we apply the median filter to the image and observe the changes in the pixel values. By analyzing the differences between the original image and the filtered image, we can determine the extent of salt and pepper noise present in the image. The proposed method offers a reliable and efficient way to quantify the level of salt and pepper noise. Experimental results on various images demonstrate the effectiveness of the proposed method in accurately identifying and quantifying salt and pepper noise levels. The method provides valuable insights into the amount of noise present in images, enabling better understanding and further processing of the image data. 
Klasifikasi Kematangan Buah Apel dengan Ekstraksi Fitur Haralick dan KNN I Kadek Bagus Deva Diga Dana Putra; I Ketut Gede Suhartana
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.p10

Abstract

This research aims to classify the ripeness level of apple fruits based on texture features using the Haralick method and color features using histograms. A dataset of 76 apple fruit images was collected. In the preprocessing stage, the apple images were converted to grayscale, followed by the application of a median filter to remove salt and pepper noise, and histogram equalization to enhance image contrast. Texture features were extracted using the Haralick method to obtain contrast, correlation, energy, homogeneity, and entropy features. Color features were extracted using histograms to obtain mean, standard deviation, skewness, and kurtosis. A K-Nearest Neighbor (KNN) model with k = 6 was used for classification. The evaluation results showed an accuracy of 89.47%, precision of 93.75%, recall of 93.75%, and F1-score of 93.75%. This research indicates that texture and color features can effectively classify the ripeness level of apple fruits. Future research can explore more diverse datasets and parameter adjustments to further improve model performance. 
Klasifikasi Lirik Lagu Bertema Lingkungan dengan Metode Naive Bayes Putu Ode Irfan Ardika; I Gusti Ngurah Anom Cahyadi Putra
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.p09

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 the important 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% 
Perancangan Prototype Aplikasi Deteksi dan Pelacakan Manusia pada Video Valentin Gea Affila Pradika; I Gusti Agung Gede Arya Kadyanan
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.p08

Abstract

The detection and tracking of humans in videos have gained significant attention due to their applications in various fields such as surveillance, activity recognition, and human-computer interaction. This article presents the design and development of a prototype application for human detection and tracking in videos. The use of the prototype methodology allows for early feedback, demonstrates the functionality and features, facilitates effective collaboration, and helps save time and costs in the development process. By following this methodology, the prototype application for human detection and tracking in videos is expected to provide accurate and reliable results, meeting the needs of users in various domains. 

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