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All Journal Jurnal Ilmu Komputer E-Journal of Tourism (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Buana Informatika Jurnal Teknologi Informasi dan Ilmu Komputer JUTIK : Jurnal Teknologi Informasi dan Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Eduvest - Journal of Universal Studies Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
Ngurah Agus Sanjaya ER
Universitas Udayana
Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Neuroscience Social Sciences Other

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Klasifikasi Kateogori Cerita Pendek Menggunakan Support Vector Machine M. Faisal Afandi; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 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.v02.i01.p23

Abstract

Short stories are fascinating literary works to read because they present concise narratives that don't require readers to spend a lot of time to complete a story. Although the stories are short, determining the story category still requires careful reading to understand the content. However, it can become challenging when there is a large number of stories to be classified. Therefore, this research aims to develop a system that can automatically classify short story texts. The method used in this research is SVM (Support Vector Machine). The research is conducted to assist in automatically classifying short stories and create a system that bridges people to enjoying written works while enhancing literacy. The data used consists of short stories in the categories of romance, horror, and religion. The best-performing model is obtained through the training and validation process using new data. The results of testing the SVM method with a 70:30 data scenario, and hyperparameter C=10, gamma = 0.1 with kernel rbf or gamma = scale with kernel linear, yield an accuracy of 96% with a precision of 96.72%, recall of 96.36%, and an f1-score of 96.40%. 
Implementasi Metode AHP dan VIKOR untuk Sistem Pendukung Keputusan PHK Ida Bagus Gede Basudewa Weda; Ngurah Agus Sanjaya ER
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 3 (2025): JNATIA Vol. 3, No. 3, Mei 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.i03.p24

Abstract

Employee termination, or Pemutusan Hubungan Kerja (PHK) in Indonesian, is a complex and sensitive process that profoundly affects both employees and companies. While necessary for organizational viability, terminations can have adverse effects on employees, including unemployment and emotional distress. Hence, it is crucial to approach termination decisions objectively. This study implements the Analytical Hierarchy Process (AHP) and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodologies within a decision support system framework for PHK. AHP facilitates criterion weighting, while VIKOR aids in alternative ranking. Using employee datasets from Kaggle, AHP determines criterion importance, while VIKOR assesses employee ranking based on diverse criteria. The method successfully ranks the alternatives based on the labels. The values v=0 has the lowest termination percentage 5,6% at Q2 and v=0,75 has the highest termination percentage 98%. The implementation aims to provide insights for readers and support companies in making objective termination decisions. 
Implementasi Internet of Things dengan Smart Faucet pada Sistem Irigasi Subak Bali Ida Bagus Rahadi Putra; Ngurah Agus Sanjaya ER
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.p26

Abstract

This research proposes the implementation of the internet of things with smart faucets in Bali's Subak irrigation system by using algorithms used to implement the internet of things. Sensors including temperature sensors, soil moisture sensors, rainfall sensors, and water level sensors, are installed to monitor real-time environmental and crop conditions. The data collected from these sensors is used in algorithms that are used to optimize water usage according to crop needs and environmental conditions. The results of this study show that there is a reduction in water wastage and an increase in water use efficiency with more accurate control. The optimized irrigation system ensures a water supply that matches the needs of the plants, improves plant growth, and reduces the risk of disease. Users can monitor and control the irrigation system remotely through the website, providing accurate information about the condition of the plants and their water needs. It is an innovative solution to improve crop yields, plant health, and water use efficiency in Bali's Subak irrigation systems. 
Pengembangan Model Ontologi Pada Domain Oleh-Oleh Khas Bali Putu Ardi Sudarmika; Ngurah Agus Sanjaya ER
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.p26

Abstract

Bali's typical souvenirs not only represent a high cultural heritage but also serve as a primary attraction for tourists. However, detailed information on these souvenirs remains limited, making it challenging for users to choose. To enhance accessibility, the concept of representing Bali's souvenir data in ontology-based knowledge emerged. The aim is to provide references to tourists by regularly structuring an ontology model. Knowledge about Bali's souvenirs is represented using RDF in triple concepts of subject, predicate, and object, accessible through SPARQL. The development process employs the methodology methodology, encompassing specification, knowledge acquisition, conceptualization, integration, implementation, evaluation, and documentation phases. The outcome is an ontology model featuring 4 classes, 3 Object Properties, data properties, 34 ontographs, and 28 individuals or instances, offering regularly relevant information about Bali's souvenirs. This method utilizes Protégé 5.5.0 software and a search-based application for testing its efficacy. 
Analisis Sentimen dengan Logistic Regression untuk Deteksi Kata pada Livin’ by Mandiri Ni Made Gita Satviki Nirmala; Ngurah Agus Sanjaya ER
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.p25

Abstract

Livin by Mandiri is one of the most frequently used mobile banking. To find out the quality of the application, you can carry out sentiment analysis from reviews. The data taken from the Google Play Store was 6334 data from January 2022 to December 2022. The training data and test data used had a ratio of 80:20. This data goes through preprocessing and then TF-IDF weighting is carried out. After that, the analysis used logistic regression which produced 91.5% with C = 0.75. As well as getting negative sentiment results, namely precision 89%, recall 95%, f1-score 92%. Meanwhile, positive sentiment produces 94% precision, 88% recall, 91% f1-score. There is a word detection program that can help search for keywords including positive sentiment or negative sentiment from the Livin by Mandiri application. 
Implementasi Algoritma Yolo untuk Deteksi Buah Durian dan Manggis I Putu Aditya Pradana; Ngurah Agus Sanjaya ER
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.p26

Abstract

This study aims to implement the YOLOv8 algorithm in detecting images of durian and mangosteen fruits. The research methodology includes literature review, image collection, data processing, YOLOv8 algorithm implementation, model evaluation on validation data, and drawing conclusions. Image collection is done through online sources, and data is processed through annotation, pre-processing, and augmentation using the Roboflow platform before exporting to YOLOv8 format. The algorithm implementation is carried out in Google Colab with model training, object detection, and evaluation stages on validation data. Evaluation results include accuracy, recall, precision, and F1 score values, with model performance evaluated using mean average precision (mAP) metric. The results indicate that the model can recognize objects well, with a mAP above 0.27%. This study successfully implements YOLOv8 for durian and mangosteen fruit detection with satisfactory evaluation results. 
Perlindungan pada Citra Motif Kain Songket dengan Teknik Watermarking Menggunakan RSA Encryption dan MSB Steganography I Wayan Gede Gemuh Raharja RL; Ngurah Agus Sanjaya ER
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.p26

Abstract

This research develops a watermarking steganography technique using the MSB method to protect songket cloth motifs. In the MSB-based steganography method for embedding watermarks in images, the MSB transformation is used to replace data bits in image segments with secret data bits. The embedded watermark functions as an identification mark that is difficult to remove or change without destroying the authenticity of the original motif. Accuracy testing using PSNR and MSE produced an average PSNR of 75.177 dB and MSE of 0.0018, which shows that this technique is effective in maintaining the authenticity and integrity of Songket cloth motifs. 
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. 
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. 
Klasifikasi Emosi Lirik Lagu Dengan Long Short Term Memory dan Word2Vec I Putu Diska Fortunawan; Ngurah Agus Sanjaya ER
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.p24

Abstract

This research focuses on the classification of emotions in song lyrics using LSTM (Long ShortTerm Memory) and Word2Vec embedding. Emotion classification in lyrics plays a crucial role in music recommendation systems, sentiment analysis, and understanding the affective aspects of music. The study explores the effectiveness of LSTM, a type of recurrent neural network (RNN), in capturing the sequential dependencies and patterns in lyrics, combined with Word2Vec embedding to represent the semantic meaning of words.The dataset consists of a collection of song lyrics labeled with 2 emotions. The lyrics are preprocessed and converted into word vectors using the Word2Vec model. The LSTM model is then trained on the preprocessed lyrics data, aiming to predict the corresponding emotion category for a given set of lyrics. Experimental results demonstrate that the proposed approach achieves a maximum accuracy of 72.8% in classifying emotions in song lyrics. The LSTM model leverages the sequential information in the lyrics to capture the emotional context effectively. The Word2Vec embedding enhances the representation of words, allowing the model to understand the semantic relationships between words and better discriminate between different emotional categories. 
Co-Authors Abel Gilang Saputra Abimanyu, Cokorda Gde Aditya Nugraha, Anak Agung Aditya Premana Putra Adu, Enga Prinda Afandi, M Faisal Agus Muliantara Agus Muliantara Agustiana, Ni Putu Arisya Albertus Ivan Suryawan Anak Agung Aditya Nugraha Anak Agung Istri Ngurah Eka Karyawati Anak Agung Sinta Trisnajayanti Anggita S, Ni Putu Ayu Sherly Arimbawa, I Gede Ayu Kadek Nadya Oktaviana Budiantari, Ni Made Julia Candra Mahatagandha, Pijar Cokorda Gde Abimanyu Cokorda Pramartha Cokorda Rai Adi Pramartha Darmayasa, I Nengah Oka Farin Istighfarizky Firman Ali Eka Atmojo Fortunawan, I Putu Diska Gede Krisna Surya Artajaya Gede Nicholas Tejasukmana Putra Gede Sukadarmika Gemuh Raharja RL, I Wayan Gede Giri, Gst. Ayu Vida Mastrika Gst. Ayu Vida Mastrika Giri Gusti Ayu Vida Mastrika Giri Gusti Ayu Vidjaretha Wardana Gusto Gibeon Ginting Hairul Lana HARI MULYAWAN I Dewa Made Bayu Atmaja Darmawan I Dewa Made Candra Wiguna Marcelino I Dewa Made Candra Wiguna Marcelino I Gede Arta Wibawa I Gede Santi Astawa I Gede Wira Kusuma Jaya I Gst. Bgs. Arya Yudiastina I Gusti Agung Gede Arya Kadyanan I Gusti Ngurah Anom Cahyadi Putra I Kadek Agus Andika Putra I Kadek Gowinda I Ketut Gede Suhartana I Ketut Satriawan I Komang Ari Mogi I Komang Surya Adinandika I Made Ady Wirawan I Made Ari Widiarsana I Made Satria Bimantara I Made Surya Adi Palguna I Made Widiartha I Made Widiartha I Nengah Oka Darmayasa I Putu Aditya Pradana I Putu Diska Fortunawan I Putu Edy Suardiyana Putra I Putu Gede Hendra Suputra I Wayan Gede Gemuh Raharja R.L. I Wayan Gede Gemuh Raharja RL I WAYAN SANTIYASA I Wayan Sugiana Ida Bagus Gede Basudewa Weda Ida Bagus Gede Dwidasmara Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Ida Bagus Made Surya Widnyana Ida Bagus Rahadi Putra Karel Leo Rivaldo Komang Krisna Jaya Nova Antara Kurniadi, Kenny Luh Arida Ayu Rahning Putri Luh Arimas Pertiwi Luh Gede Astuti Luh Gede Astuti Luh Gede Tresna Dewi Luh Putu Eka Nadya Wati LUH PUTU IDA HARINI M. Faisal Afandi Made Agus Hendrayana Made Darma Yunantara Made Hanindia Prami Swari Made Widiartha Negara, I Made Wahyu Guna Ni Luh Komang Indira Pramesti Ni Made Alisya Putri Hapsari Ni Made Ary Esta Dewi Wirastuti Ni Made Ayu Wirasih Ni Made Dian Kurniasari Ni Made Gita Satviki Nirmala Ni Made Julia Budiantari Ni Putu Ambalika Dewi Ni Putu Intan Cahyani Ni Putu Vina Amandari Nirmala, Ni Made Gita Satviki Palguna, I Made Surya Adi Palla, Hans Rio Alfredo Pertiwi, Luh Arimas Pijar Candra Mahatagandha Pradana, I Putu Aditya Pradiptha, I Gde Made Hendra Putra, Gede Bagus Prawira Putri, Riana Pramesti Putu Ardi Sudarmika Raharja, Made Agung Riana Pramesti Putri Safira Sinta Wahyuni, Ni Made Suryawan, Albertus Ivan Wayan Citra Wulan Sucipta Putri Yasa, I Gede Cahya Purnama