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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Reviu Akuntansi dan Keuangan Jurnal Ilmu Komputer Jurnal SPEKTRUM Ecotrophic, Journal of Environmental Science Krisna: Kumpulan Riset Akuntansi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JURNAL MANAJEMEN AGRIBISNIS PROSIDING CSGTEIS 2013 Jurnal Ilmiah Mahasiswa FEB TEMA (Jurnal Tera Ilmu Akuntansi) Infestasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Akuntansi Aktual JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Science and Informatics Engineering (J-Cosine) Logic : Jurnal Rancang Bangun dan Teknologi Jurnal Teknologi Informasi dan Pendidikan International Journal of Engineering and Emerging Technology Jurnal Manajemen Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology International Journal of Management Science and Information Technology (IJMSIT) Reviu Akuntansi, Keuangan, dan Sistem Informasi Jurnal SPEKTRUM KREATIF: Jurnal Pengabdian Masyarakat Nusantara Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Made Sudarma
Udayana University
Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Strategi Penyetelan Hyperparameter untuk YOLOv8n dalam Pemantauan Lalu Lintas Pasca-Kecelakaan Real-Time I Nyoman Eddy Indrayana; Made Sudarma; I Ketut Gede Darma Putra; Anak Agung Kompiang Oka Sudana
Jurnal Teknologi Informasi dan Pendidikan Vol. 19 No. 2 (2026): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v19i2.1132

Abstract

Traffic accidents continue to provide a considerable difficulty in contemporary transportation systems, frequently leading to vehicle damage and heightened risks for pedestrians on streets. Precise and instantaneous identification of post-accident scenarios is thus crucial for facilitating swift response and sophisticated traffic management. This research introduces a streamlined object detection methodology utilizing YOLOv8n to recognize six essential traffic-related categories: bus, automobile, damaged vehicle, motorbike, pedestrian, and truck. The main aim is to examine the impact of hyperparameter modification on detection efficacy, specifically in recognizing damaged automobiles as signs of post-accident situations. Twelve model configurations were created by systematically altering three hyperparameters: learning rate (0.01, 0.001, and 0.0001), batch size (32 and 64), and optimizer type (Adam and MuSGD). All models underwent training for 200 epochs with a dataset derived from actual traffic situations, augmented by techniques such as grayscale transformation, blurring, and rotation. The performance evaluation utilized precision, recall, F1-score, mAP50, and mAP50:95. The findings indicate that hyperparameter selection substantially influences convergence stability and detection accuracy. The optimal model attained a mAP50 of 0.905 and a mAP50:95 of 0.751, utilizing a learning rate of 0.01, a batch size of 64, and the Adam optimizer. Moreover, substantial items like cars, buses, and trucks were identified with high precision, whereas damaged vehicles and pedestrians necessitated more meticulous calibration due to increased visual variability.The findings indicate that optimized lightweight models can attain competitive performance, rendering them appropriate for real-time intelligent traffic monitoring applications.
Smart Stego: A Web Application for Hiding Secret Data in Images with LSB and CNN I Gede Totok Suryawan; Made Sudarma; I Ketut Gede Darma Putra; Anak Agung Kompiang Oka Sudana
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1008

Abstract

This study develops a web-based steganography model to insert the identity of artisans in the form of palmprint images into the image of gringsing ikat woven cloth as a medium for ownership authentication. The method used in the insertion process combines a Convolutional Neural Network and the Least Significant Bit. In contrast, extracting or re-introducing palmprint images from stego images is carried out using a CNN-based classification model. This system was tested with two scenarios; in the first scenario, one palmprint image was inserted into 26 different cloth motifs, while in the second scenario, one cloth motif was inserted into 99 different palmprint images. The test results showed that the system produced consistent confidence values for all cloth motifs in the first scenario. In contrast, in the second scenario, the system achieved an average confidence of 93.5% and a recognition accuracy of 87%. The developed application has proven to be efficient with a reduction in stego image size of up to 66% while maintaining the quality of the stego image, as well as a speedy average execution time of 0.15 seconds for insertion and 0.09 seconds for extraction. These findings prove that the developed steganography model can effectively insert and re-recognize identity images (palmprints) in woven cloth images and has the potential to be applied as an image-based craft product ownership verification system.
EEG-Based Focus Analysis to Evaluate the Effectiveness of Active Learning Approaches I Putu Agus Eka Darma Udayana; Made Sudarma; I Ketut Gede Darma Putra; I Made Sukarsa; Minho Jo
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1068

Abstract

Electroencephalography (EEG) has emerged as a non-invasive and objective technique for monitoring brain activity in real time, widely applied to measure cognitive states such as concentration and alertness. Its ability to capture brain responses during learning processes makes EEG a promising tool to evaluate student engagement more accurately than conventional methods. This study investigates the effectiveness of two active learning methods, Project-Based Learning (PjBL) and Problem-Based Learning (PBL), in the context of English tutoring for elementary students using EEG signals as a cognitive indicator. A total of 20 students aged 8–12 years from ThinkerBee Learning Centre Bali participated in the study. EEG data were recorded using the Muse 2 Headband while students completed test-based tasks designed for each learning method. The EEG signals were preprocessed using bandpass filtering, Continuous Wavelet Transform (CWT), and frequency band decomposition. Concentration scores were then calculated using two approaches: a heuristic method based on the Beta/(Theta + Alpha) ratio and a Long Short-Term Memory (LSTM) model. The heuristic method produced average scores of 0.3991 (PjBL) and 0.3822 (PBL), with a 4.42% difference, while the LSTM model showed a more substantial difference, with scores of 0.5454 (PjBL) and 0.4265 (PBL). A Spearman correlation test between EEG-derived scores and students’ academic results yielded a perfect correlation value of 1.0000, indicating a strong relationship between cognitive engagement and learning outcomes. These results demonstrate the potential of EEG as a reliable tool for objectively assessing learning effectiveness in primary education contexts.
Comparison of image enhancement methods for pratima theft detection using artificial intelligence Made Sudarma; Ni Wayan Sri Ariyani; I Putu Agus Eka Darma Udayana; Ida Bagus Gde Pranatayana; Lie Jasa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp213-228

Abstract

The theft of pratima in Balinese temples threatens the spiritual and cultural balance of the community. These sacred objects, regarded as manifestations of God in Hinduism, hold profound religious significance, and their loss represents both material and spiritual desecration. To address this issue, this study investigates a security system that leverages image enhancement for low-light detection. Four techniques—contrast limited adaptive histogram equalization (CLAHE), adaptive histogram equalization (AHE), histogram equalization (HE), and gamma correction—were evaluated to improve image quality. CLAHE yielded the lowest mean squared error (MSE) of 21.16 and the highest peak signal-to-noise ratio (PSNR) of 38.13 dB. For object detection, VGG-19 and AlexNet were assessed. The best configuration, VGG-19 with HE, reached 83.33% accuracy and 93.75% recall, and achieved a receiver operating characteristic area under the curve (ROC AUC) of 0.90±0.02 across five runs. Thresholds derived from the ROC analysis were selected using the Youden J statistic to balance sensitivity and specificity. The approach outperformed lightweight and classical baselines in AUC, indicating superior discrimination under low illumination. These findings show that superior image quality does not always align with higher detection accuracy, and they highlight the importance of pairing effective enhancement with robust detectors for temple security. The study contributes practical insights for preserving Balinese cultural and spiritual heritage by strengthening efforts to protect pratima against theft.
Herbal Leaf Identification for Balinese Lontar Usada Knowledge Preservation Using YOLOv8 Object Detection I Nyoman Hary Kurniawan; Ngurah Indra Erawan; Made Sudarma
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16254

Abstract

Indonesia is a megabiodiversity country with more than 30,000 documented medicinal plant species. Much of this ethnobotanical knowledge is preserved in the Lontar Usada Bali, a traditional Balinese manuscript that records the medicinal uses of plants. However, preserving this knowledge is challenging due to the declining number of traditional practitioners and the difficulty of identifying medicinal plants in natural habitats. This study proposes a deep learning-based medicinal plant detection system using the YOLOv8 architecture to identify 12 classes of medicinal plant leaves in Taman Usada Bali. A total of 1,344 images containing 3,230 annotated leaf objects were collected under diverse lighting and background conditions. To improve model generalization, horizontal flipping, vertical flipping, rotation, Mosaic, and MixUp augmentations were applied. Five YOLOv8 variants (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) were evaluated using Precision, Recall, F1-score, mAP50, and mAP50–95 metrics. Experimental results showed that all models achieved high detection performance, with YOLOv8m obtaining the highest mAP50–95 score of 0.8676. However, Cost Benefit Analysis (CBA) using the Weighted Sum Model (WSM) identified YOLOv8n as the optimal model. Although YOLOv8m achieved the highest accuracy, YOLOv8n obtained the highest WSM score (2.6400) by balancing detection performance (mAP50–95 of 0.8464         ) and computational efficiency. With a 6 MB model size, 2.7 ms inference time, and 1.559 hours of training, YOLOv8n is suitable for real-time mobile and edge-computing applications. The novelty of this study lies in integrating Lontar Usada Bali taxonomy into a structured dataset, applying WSM for model selection, and enhancing detection robustness through Mosaic and MixUp augmentation.
Rancang Bangun Aplikasi Pengenalan Pupuh Bali Menggunakan Metode Mel Frequency Cepstral Coefficients I Dewa Gede Budi Dharma Prabhawa; Duman Care Khrisne; Made Sudarma
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 1 (2019): June 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.058 KB) | DOI: 10.29303/jcosine.v3i1.237

Abstract

Pupuh is a basic of Tembang for someone that can later be used for further learning to a higher level that is Sekar Madya and Sekar Agung. Balinese culture is an important feature to determine the ethnicity identity of a group. Then it should be the Balinese use and preserve Pupuh that has been inherited by the ancestors. The media for Balinese Pupuh learning will be using an Android device with MFCC method. To attract the interest of young peoples to learn Balinese Pupuh, then this Balinese Pupuh learning system based-Android was created. This application will use the sound recorded by Android devices and sent to the Python server for systematic calculations, then returned to the Android devices and will get the correct or wrong answer which according to server calculation. By developing this Balinese Pupuh learning system, expected can help the teachers or Balinese language teachers to teach their students about Balinese Pupuh on a mobile and practical.
Classification of Ceremonial Plants with Vision Transformer Ida Bagus Kade Dwi Suta Negara; I Ketut Gede Darma Putra; Made Sudarma; I Made Sukarsa
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.7992

Abstract

The rapid advancement of computer vision technology has accelerated the adoption of artificial intelligence in agriculture, particularly for plant image classification tasks. However, the identification of ceremonial plants remains challenging due to the high visual similarity among species and the continued reliance on manual identification methods, which are time-consuming and require expert knowledge. Unlike previous studies that primarily focused on general crop species or plant disease classification, this study specifically investigates the application of the Vision Transformer (ViT) model for the classification of ceremonial plants, which represent culturally significant plant species with distinctive yet visually similar characteristics. An experimental approach was employed using a dataset of 1,244 ceremonial plant images representing seven classes, with the data divided into training, validation, and testing sets at proportions of 70%, 15%, and 15%, respectively. A pretrained Vision Transformer model was fine-tuned by adapting its classification head to the target classes and evaluated using accuracy, precision, recall, F1-score, and confusion matrix metrics. The experimental results demonstrate that the proposed model achieved a test accuracy of 97.33% and an average class accuracy of 97.01%, indicating its effectiveness in learning complex visual representations and accurately distinguishing visually similar ceremonial plant species. These findings demonstrate the feasibility of Vision Transformer for culturally specific plant recognition and provide a reliable baseline for the development of intelligent ceremonial plant identification systems, contributing to the digital preservation of traditional botanical knowledge and AI-based plant recognition applications.
Co-Authors A. A. K. Oka Sudana A.A Ngurah Narendra A.A Raka Novi Aristi Adi Darmawan Ervanto Adinata Mas Pratama Agus Aan Jiwa Permana Agus Dharma Ahmad Catur Widyatmoko Ajeng Anandra Anak Agung Kompiang Oka Sudana Anak Agung Ngurah Prawira Yudha Andrew Sumichan Andrew Sumichan Ari Kamayanti Ariyady Kurniawan Muchsin Asri Prameshwari Casya Nova Nitali Ginting Charolina Devi Oktaviana Soleman Charolina Devi Oktaviana Soleman Dandy Pramana Hostiadi Darma Kotama, I Nyoman Darma Putra Dea Novim Kartikasari Dewa Ayu Putri Wulandari Dewa Made Wiharta Dima Nurfitri Apriani Dita Rizky Prahayuningtyas Duman Care Khrisne Erwin Saraswati Faraz Muhammad Aulia Fauziah, Farah Ferry Angga Irawan Gde Brahupadhya Subiksa Hanif Prio Ariantono Hardi yusa Hisyam Rahmawan Suharno Hisyam Rahmawan Suharno I Dewa Gede Budi Dharma Prabhawa I Dewa Made Krisnayana I Dewa Nyoman Anom Manuaba I Dewa Nyoman Anom Manuaba I Gede Abi Yodita Utama I Gede Adnyana I Gede Harsemadi I Gede Herry Juniartha I Gede Sujana Eka Putra I Gede Totok Suryawan I Gede Totok Suryawan I Gede Wira Darma I Gst Agung Alit Wismaya I Gusti Agung Gede Mega Perbawa I Gusti Agung Indrawan I Gusti Agung Komang Diafari Djuni Hartawan I Gusti Kade Harta Kesuma Wijaya I Gusti Made Panji Indrawinatha I Gusti Ngurah Adhy Pradhana I Gusti Ngurah Agung Jaya Sasmita I Gusti Ngurah Agung Surya Mahendra I Gusti Ngurah Agung Surya Mahendra I Gusti Ngurah Gede Agung Suniantara I Gusti Ngurah Rai Dharma Widhura I Gusti Rai Agung Sugiartha I Kadek Agung Bagus Satria Bumi Kelana I Kadek Arya Wiratama I Kadek Dwi Gandika Supartha I Kadek Sastrawan I Kadek Yuda Setiadi I ketut Gede Darma Putra I Ketut Putra Swastika I Komang Yogi Sutrisna I Made Adi Bhaskara I Made Arsa Suyadnya I Made Artawan I Made Budi Sentana I Made Cakra Pustaka1 I Made Dwi Ardiada I Made Dwi Jendra Sulastra I Made Gede Yudiana I Made Gede Yudiyana I Made Oka Widyantara I Made Sukarsa I Made Sukarsa I N Satya Kumara I Nyoman Adi Putra I Nyoman Eddy Indrayana I Nyoman Gunantara I Nyoman Hary Kurniawan I Nyoman Putu Suwindra I Putu Adi Pradnyana Wibawa I Putu Agung Bayupati I Putu Agus Eka Darma Udayana I Putu Agus Eka Darma Udayana I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Agus Priska Suryana I Putu Alit Putra Yudha I Putu Arya Putrawan I Putu Astya Prayudha I Putu Gd Sukenada Andisana I Putu Gede Panji Badra Mahayana I Putu Oka Wisnawa I Putu Putra Diyastama I Putu Putrayana Wardana I Putu Sugi Almantara I Putu Warma Putra I Wayan Agus Surya Darma I Wayan Eka Krisna Putra I Wayan Suarna Ida Ayu Dwi Giriantari Ida Ayu Listia Dewi Ida Ayu Putu Febri Imawati Ida Bagus A. Swamardika Ida Bagus Agung Eka Mandala Putra Ida Bagus Dwijaya Kesuma Ida Bagus Gde Pranatayana Ida Bagus Gede Manuaba Ida Bagus Gede Widnyana Putra Ida Bagus Kade Dwi Suta Negara Ida Bagus Leo Mahadya Suta Ida Bagus Leo Mahadya Suta Ida Bagus Leo Mahadya Suta Ida Bagus Surya Paramarta IGAM Yoga Mahaputra Irvan Dinda Prakoso Irwansyah Cahya Irwansyah Cahya Adha L Iskandar, Adi Panca Saputra Isnan Murdiansyah IW Dani Pranata Jauzaa Maylia Suhendro Josep Geas Sapalatua Kadek Ary Budi Permana Kadek Ary Budi Permana Kadek Ary Budi Permana Kadek Ary Budi Permana Kheri Arionadi Shobirin Komang Agus Putra Kardiyasa Komang Ayu Triana Indah Komang Budiarta Komang Budiarta Komang Budiarta Komang Isabella Anasthasia Komang Nova Artawan Komang Oka Saputra Komang Sri Utami Lanang Bagus Amertha Lanang Bagus Amertha Leonardus Guido Adi Wungo Lie Jasa Linawati Linawati Luh Gede Putri Suardani Luh Ria Atmarani M. Azman Maricar Made Dinda Pradnya Pramita Made Dinda Pradnya Pramita Made Pasek Agus Ariawan Made Pradnyana Ambara, Made Pradnyana Made Sri Indradewi Adnyana Manuh Artana Michael Tanduk Langi Londong Allo Minho Jo Minho Jo Minho Jo Muhammad Ridwan Satrio Murpratiwi, Santi Ika Naser Jawas Nengah Widiangga Gautama Ni Ketut Novia Nilasari Ni Komang Sri Julyantari Ni Komang Sukri Antariani Ni Luh Gede Pivin Suwirmayanti, S.Kom, MT, Ni Luh Gede Pivin Ni Luh Ratniasih, Ni Luh Ni Made Ananda Putri Pratiwi Ni Made Ari Lestari Ni Made Dwi Antari Ni Putu Sutramiani Ni Wayan Lusiani Ni Wayan Sri Ariyani Nurkholis - Nyoman Gede Yudiarta Nyoman Paramaita Nyoman Pramaita Nyoman Putra Sastra Nyoman Swastika Dharma Pande Made Sutawan Philipus Novenando Mamang Weking Purwania Ida Bagus Gede Putri Sintya Dewi Putri Suardani Putu Agung Ananta Wijaya Putu Angelina Widya Putu Arya Mertasana Putu Bagus Satria Paramartha Putu Risanti Iswardani Putu Wirya Kastawan Putu Wulandari R. Sapto Hendri Boedi Soesatyo Reni Surmayanti Ricky Aurelius Nutanto Diaz, Ricky Aurelius Rifky Lana Rahardian Risky Aswi Ramadhani Rizal W.H. Siagian Rizky Muharram Julyanto Rodrick Benediktus Kainama Roekhudin, Roekhudin Rukmi Sari Hartati Rukmi Sari Hartati Saputra, Aggry Tria Hikmah Fratiwi Vony Wahyunurani Wahyudin Wahyudin Wayan Gede Ariastina Wikan Pradnya Dana, Gde Y. Yuliati Yogiswara Dharma Putra Yogiswara Dharma Putra Yoni Yogiswara Yudhistira Bayu Perkasa Zulfachmi, Zulfachmi