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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Journal of ICT Research and Applications JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Teknologi Informasi dan Pendidikan International Journal of Engineering and Emerging Technology Indonesian Journal of Electrical Engineering and Computer Science Jurnal Bali Membangun Bali Makara Journal of Technology Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
I ketut Gede Darma Putra
Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Sketching Expert System for Crime Investigation Purposes Bagus Yudistira; I Ketut Gede Darma Putra; Anak Agung Kompyang Oka Sudana
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5655-5660

Abstract

The presence of police sketcher play an important role in making investigation in purpose of making arrestment to fugitive or suspect. The lacking presence of police sketcher is making a lack in investigation process, because lack of information gathered for the further process. This limitation is overcome by developing an expert system using gadget as a helping device to making sketch, with adding sketcher knowledge. Sketching method already been used since long time in process of investigation and effective making the result. The result of expert system on case given showing the system to real object which made sketching reach 85% of accuracy level.
Establishment Code Hand Palm (Palm Code) 2D Gabor-Based Method Darma Putra, I Ketut Gede; Bhuana, Wira; Erdiawan, Erdiawan
Makara Journal of Technology Vol. 15, No. 2
Publisher : UI Scholars Hub

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Abstract

Establishment Code Hand Palm (Palm Code) 2D Gabor-Based Method. Palmprint is relatively new in physiological biometrics. Palmprint ROI segmentation and feature extraction are two important issues in palm print recognition. This paper introduces two steps in the center of mass moment method for ROI segmentation that will be applied in the Gabor 2D filter to obtain palm code as palmprint feature vector. Normalized Hamming distance was used to measure the similarity degrees of two feature vectors of palmprint. The system was tested using database 1000 palmprint images generated from 5 samples from each of the 200 persons randomly selected with ROI 64 x 64 and 128 x 128 pixel. Experiment results show that this system can achieve high performance with a success rate about 98.7% (FRR = 1.17%, FAR = 0.11%, T = 0.376) with ROI 64 x 64 pixel.
The Implementation of Hybrid Neuro Fuzzy Membership Function Analysis for Predicting Player Emotional Intelligence of Balinese Game Model I Nyoman Putu Suwindra; I Ketut Gede Darma Putra; Made Sudarma; Nyoman Putra Sastra
International Journal of Engineering and Emerging Technology Vol 6 No 2 (2021): July - December 2021
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

This paper aims to examine the application of Neuro fuzzy membership function analysis to predict the emotions of children who like to play games. The game that has been developed is a type of game based on Balinese local wisdom, which innovates the Balinese culture-based legend I Rajapala. Rajapala who married an angel had a son named Durma. Rajapala and Durma are used as game characters that can be played on behalf of game players. Game-factor and emotional variable data were collected using a questionnaire integrated into the game system, as well as motivational data from points achieved and the use of time recorded in the game system. The data were analyzed by Sugeno Neuro Fuzzy system with hybrid and backpropagation methods. The results obtained are as follows: (1) Emotional Balinese game players can be predicted from game-factors and motivations of game players. This was shown from the FIS output (Eo) of the neuro fuzzy training analysis and the RMSE (Eo=36.8; RMSE=4.6610), the testing analysis was (Eo=33.0; RMSE=4.4528), and the checking analysis was (Eo=37.8; RMSE=4.7479) with a difference of less than 13% (training=2.72%; testing=3.0%, and checking=12.77%). In other words, if it is analyzed descriptively was (M=37.83; SD=5.3573), the output of neuro fuzzy is obtained more than 87.23%. (2) The emotional level of the child was categorized as a positive, the child's motivation was moderate and the response to the game was positive. These findings can be taken into consideration in choosing the type of game to be played in order to increase motivation and control children's emotions. Besides that, innovating games based on local wisdom is expected to preserve local Balinese culture.
Effect on signal magnitude thresholding on detecting student engagement through EEG in various screen size environment I Putu Agus Eka Darma Udayana; Made Sudarma; I Ketut Gede Darma Putra; I Made Sukarsa
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4850

Abstract

In this study, a new method was developed to detect student involvement in the online learning process. This method is based on convolutional neural network (CNN) as a classifier with an emphasis on the preprocessing process combined with a new feature in the form of signal magnitude area (SMA) thresholding. In this study, the data used as training data is a public dataset that emphasizes the decomposition of electroencephalography (EEG) signals into individual signal processing. Twenty subjects were taken to be used as test data, with each subject watching online learning lectures in the field of computer science on three different devices, either with a flat screen, a curved screen or a smartphone screen that is smaller than two standard computer monitors. Based on the study's results, it is known that the change in screen size is inversely proportional to the level of student attention, the smaller the screen, the lower the student's attention. For classification results, the model equipped with SMA thresholding outperformed the standard classifier by 8.33% with a test set of 20 people.
Design and Development of a Web-Based Plastic Waste Recycling Information System case study: Bali Pet Collection Center I Putu Jordi Astika; Dwi Putra Githa; I Ketut Gede Darma Putra
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 2 (2023): Vol. 11, No. 2, August 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i02.p07

Abstract

A plastic recycling company is an industry that specializes in recycling plastic waste into processable plastic pellets. The current business process still relies on conventional methods for recording activities within the company. The objective of this research is to design and develop a web-based information system for plastic waste recycling. The waterfall methodology employed as the software development method. The system is tested using black box testing and user acceptance testing (UAT) and measured using Likert's summated Rating (LSR) method. The results of the black box testing indicate that the system functions well. Furthermore, the results of the UAT demonstrate that the system as a whole receives highly positive responses and is considered successful.
Multi Task Deep Learning with Transformer Encoder Decoder for Semantic Segmentation Indah, Komang Ayu Triana; Darma Putra, I Ketut Gede; Sudarma, Made; Hartati, Rukmi Sari
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.1978

Abstract

Visual understanding is one of the core elements of computer vision consisting of image classification, object detection, and segmentation. The system applies a multilayer process to obtain complex image and video understanding using deep learning methods to convert the images to text. Therefore, this study aimed to extract video in the form of frames followed by the application of Transformer and Inception V3 architectures to the image captioning process. The synchronization was based on Multi-task Deep Learning method developed by combining Convolutional Neural Network (CNN) system in the image area, Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) in the sentence area, Caption Content Network (CCN), and Relational Network Context (RCN). Moreover, Transformer Encoder-Decoder architecture was used in the process of labeling and determining the relationships between objects. The results of the image-to-text conversion process were determined by comparing prospective translated text with one or more references. This was achieved using accuracy and loss validation tables to provide graphical comparisons between the number of epochs and losses. The test results showed that the validation data accuracy was 70.166% while the loss was 22,648% and this showed more epoch iterations led to greater validation accuracy.Keywords— Visual Understanding, Transformer, Encoder, Decoder
Intelligent Web-Based Application for Personalized Obesity Management Wijayakusuma, I Gusti Ngurah Lanang; Sudarma, Made; I Ketut Gede Darma Putra; Oka Sudana; Minho Jo
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9151

Abstract

Obesity is a serious global problem due to its association with various chronic diseases. This study explores the utilization of machine learning in particular deep learning technology to predict Body Mass Index (BMI) from individual photos to create an efficient solution for assessing obesity. Using the ResNet152 model and K-Fold Cross Validation, this application integrates filters on individual photos to improve prediction accuracy. The application was developed using React JS for the front end, PHP and MySQL for the backend and database management, and Python as the core of the machine learning system. The application that tested using blackbox method, to see all features is functioning and the web application prototipe is passed all the test scenario.
Automated Generation of Folklore Short Stories Using T5 Transformer Model Pirade, Evangelika; Darma Putra, I Ketut Gede; Singgih Putri, Desy Purnami
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10582

Abstract

High reading interest plays an important role in increasing knowledge and fostering a stronger literacy culture. With the growing access to information and technology, reading interest is also expected to improve through innovative and interactive platforms. However, traditional reading materials often fail to attract younger generations who are more engaged with digital content. To address this challenge, one of the efforts undertaken is the development of a modern platform that provides a collection of short stories enriched with cultural and educational values, tailored to appeal to contemporary readers. This study aims to design and implement a short story generation system using a Transformer-based language model, specifically T5 (Text-to-Text Transfer Transformer). The model is fine-tuned using a curated dataset of folktales from various regions, with the goal of producing relevant, engaging, and coherent narrative texts. The generation process is supported by pre-processing techniques to structure the data into narrative components such as introduction, conflict, climax, and resolution. The generated stories are then evaluated through human evaluation methods, including questionnaires and User Acceptance Testing (UAT), to assess their quality, coherence, engagement, and cultural relevance. This ensures that the system not only produces technically valid texts but also delivers narratives that are meaningful and enjoyable for readers. Ultimately, this study contributes to the promotion of literacy by presenting local wisdom and traditional values from diverse cultures through stories in a more modern, engaging, and accessible format for the younger generation.
Comparing Data Preprocessing Strategy on T5 Architecture to Classify ICD-10 Diagnosis Lanang Wijayakusuma, I Gusti Ngurah; Sudarma, Made; Darma Putra, I Ketut Gede; Sudana, Oka; Astutik, Dian
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6919

Abstract

Manual ICD-10 coding in healthcare systems remains time-consuming, error-prone, and inefficient, particularly in resource-constrained settings. This study investigates the effect of various preprocessing strategies on the performance of the Text-to-Text Transfer Transformer (T5) model for primary diagnosis classification using structured clinical data. A total of 7,263 clinical records were collected from two high-density regions in Bali (Badung and Gianyar) between January 2023 and March 2024, then converted into descriptive text prompts for model training. Four experimental scenarios combined variations of input features and label configurations, comparing T5 with Oversampling against T5 with Easy Data Augmentation (EDA) plus Oversampling. Results showed that T5 with Random Oversampling consistently outperformed the EDA-based configuration across all scenarios, with performance gaps ranging from 8% to 19%. Scenario 4, which excluded body system features and the semantically overlapping E860 label, achieved the highest balance, reaching 84.7% accuracy, 85.1% precision, 84.7% recall, and 84.3% F1-score. Conversely, the EDA-based approach reduced training time by up to 72%, indicating a clear trade-off between performance and efficiency. Both configurations frequently misclassified semantically similar codes within the same ICD-10 categories, underscoring the difficulty of distinguishing clinically related diagnoses. Overall, the results suggest that careful selection of preprocessing strategies can enhance transformer-based medical text classification, while striking a balance between model performance and training efficiency. This work may serve as an initial reference for developing more efficient semi-automated medical coding systems in the Indonesian regional healthcare context.
Determining Tuna Grade Quality Based on Color Using Convolutional Neural Network and k-Nearest Neighbors I Gede Sujana Eka Putra; Ahmad Catur Widyatmoko; I Ketut Gede Darma Putra; Made Sudarma; A. A. K. Oka Sudana
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 16 No. 02 (2025): Vol.16, No. 02 August 2025
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2025.v16.i02.p02

Abstract

One of the main commodities that Indonesia exports is tuna. Indonesia's inadequate handling of food safety is demonstrated by a number of instances when the United States has rejected Indonesian fishery goods and food poisoning incidences. Fish quality grade is currently determined by manual inspection which has risk human mistake. According to Robert DiGregorio, four tuna grade classifications exist: grade 1, 2+, 2, and 3. The purpose of this study is to assess the tuna meat's quality according to its color. The procedure involves pre-processing images, training datasets, and classifying them using the Convolutional Neural Network (CNN) and k-Nearest Neighbors algorithms. CNN pre-processing involves converting the image into HSV color space and training the CNN model using 240 training datasets and 74 testing datasets. CNN’s accuracy was 84% higher than k-Nearest Neighbors' which was 54%. Additionally, a comparison of the classification accuracy of CNN, VGG (Visual Geometry Group) 16, and AlexNet revealed that CNN outperformed the others with an accuracy of 84%, followed by VGG16 with 70% and AlexNet with 66%.
Co-Authors A. A. K. Oka Sudana Adie Wahyudi Oktavia Gama Agung Udayana Putra Ahmad Catur Widyatmoko Anak Agung Ketut Agung Cahyawan Wiranatha Anak Agung Kompiang Oka Sudana Anindya Santika Devi Ariana, Anak Agung Gede Bagus Arsa, Dewa Made Sri Arya Widyaningrat, Made Gunawan Astutik, Dian Bagus Yudistira Citra Arum Sari Desak Ayu Savita Desak Ayu Sista Dewi Desy Purnami Singgih Putri Dewa Agung Krishna Arimbawa P Dewa Ayu Nadia Taradhita Dewa Made Sri Asra Dwi Putra Githa Dwi Rusjayanthi, Dwi Erdiawan Erdiawan Erdiawan Erdiawan Erdiawan Erdiawan, Erdiawan G M Arya Sasmita Gede Eridya Bayu Gede Ngurah Pasek Pusia Putra Gede Riska Wiradarma I Dewa Gede Wahya Dhiyatmika I Gede Aditya Nugraha I Gede Galang Surya Prabawa I Gede Hendra Parwata I Gede Suarjana I Gede Sujana Eka Putra I Gede Sujana Eka Putra, I Gede Sujana Eka I Gusti Ayu Agung Diatri Indradewi I Gusti Ayu Triwayuni I Gusti Made Ngurah Ardi Yasa I Gusti Ngurah Dwiva Hardijaya I Kadek Erik Priyanto I Kadek Surya Widiakumara I Ketut Adi Purnawan I Made Agus Dwi Suarjaya I Made Aris Satia Widiatmika I Made Budi Adnyana I Made Budi Sentana I MADE SUDARMA I Made Sukafona I Made Sukarsa I Made Sukarsa I Made Sunia Raharja I Made Suwija Putra I Made Suwija Putra, I Made I Made Yudha Arya Dala I N Satya Kumara I Nyoman Eddy Indrayana I Nyoman Gede Arya Astawa I Nyoman Gunantara I Nyoman Piarsa I Nyoman Putu Suwindra I Nyoman Satria Paliwahet I Putu Adi Purnawan I Putu Agung Bayupati I Putu Agus Eka Darma Udayana I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Agus Eka Pratama I Putu Arya Dharmaadi I Putu Bayu Krisnawan I Putu Indra Permana I Putu Jordi Astika I Putu Satwika Putra I Putu Yoga Pertama Yasa I Wayan Agus Surya Darma I Wayan Budi Sentana I Wayan Gunaya I Wayan Muka I Wayan Ryon Waryanta I Wayan Wahyu Gautama Ida Ayu Dwi Giriantari Ida Ayu Putu Febri Imawati Ida Bagus Nyoman Yoga Ligia Prapta Kadek Adi Praptha Kadek Suar Wibawa Komang Ayu Triana Indah Komang Budiarta Lie Jasa Linawati Linawati Luki Ardiantoro M Sudarma Made Adi Widyatmika Made Sudarma Made Sudarma Made Sudarma Mimin F Rohmah Minho Jo Minho Jo Minho Jo Naser Jawas Ni Kadek Ariasih, Ni Kadek Ni Kadek Dwi Rusjayanthi, Ni Kadek Ni Kadek Riska Sadini Ni Komang Surya Cahyani Putri Ni Komang Sutiari Ni Komang Widyasanti Ni Luh Gede Pivin Suwirmayanti, S.Kom, MT, Ni Luh Gede Pivin Ni Made Ary Esta Dewi W Ni Made Ary Esta Dewi Wirastuti Ni Made Ika Marini Mandenni Ni Putu Ayu Oka Wiastini Ni Putu Chendy Widya Santi Ni Putu Intan Waindika Dharma Ni Putu Ratindia Apriyanti Ni Putu Sutramiani Nyoman Purnama, Nyoman Nyoman Putra Sastra Nyoman S Kumara Nyoman Sumerta Yasa Perdana, I Putu Iduar Pirade, Evangelika Purnamaswari, Anak Agung Arimas Putra, I Made Suwija Putri Isma Oktawiani Putu Githa Pratiwi Putu Manik Prihatini Putu Putri Wrestra Saridewi putu roy nurbhawa Putu Wira Buana Ricky Aurelius Nutanto Diaz, Ricky Aurelius Riskiyanti, Zuraida Malini Cantika Risky Aswi R, Risky Rosalia Hadi Rukmi Sari Hartati Rukmi Sari Hartati Siti Helmyati Sulya Arya Wasika Tri Ginarsa, I Nyoman Adi Wayan Oger Vihikan Wijayakusuma, I Gusti Ngurah Lanang Wira Bhuana Wira Bhuana, Wira Wiranatha, AA.Kt. Agung Cahyawan Yandi Perdana Yogiswara Dharma Putra Yudiadewi, Made Aprisintia Yusliza Binti Mohd Yasin