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Identifikasi Jenis Kayu Berdasarkan Fitur Tekstur Local Binary Pattern Menggunakan Metode Learning Vector Quantization Ni Made Yeni Dwi Rahayu; Made Windu Antara Kesiman; I Gede Aris Gunadi
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 10 No. 3 (2021)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v10i3.40804

Abstract

Pada umumnya pengenalan jenis kayu masih dilakukan dengan menggunakan indera penglihatan dan penciuman. Hal tersebut dapat mempengaruhi proses jual beli dimana waktu yang dibutuhkan untuk pengenalan kayu menjadi lebih lama sehingga menyebabkan proses bisnis menjadi kurang efektif. Penelitian ini bertujuan untuk membangun suatu model machine learning untuk proses identifikasi jenis kayu berdasarkan fitur teksur citra pada kayu. Metode Local Binary Pattern (LBP) digunakan dalam proses ekstraksi ciri untuk menghasilkan vektor ciri yang dijadikan data input pada proses klasifikasi citra dengan menggunakan metode Learning Vector Quantization (LVQ). Parameter yang digunakan pada metode LBP meliputi numpoint dan radius dengan nilai 1 sampai 10. Hasil penelitian dari metode ini didapatkan akurasi tertinggi 68,33% pada numpoint 2 dan radius 1. Hasil pengujian yang cukup rendah dapat dipengaruhi oleh beberapa faktor yaitu jumlah citra latih dan terdapat beberapa citra kayu memiliki pola yang hampir sama.
Detecting the Same Pattern in Choreography Balinese Dance Using Convolutional Neural Network and Analysis Suffix Tree I Komang Hendra Trinium Jaya; Made Windu Antara Kesiman; I Made Gede Sunarya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 3 (2022): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24461

Abstract

The Balinese dances that are popular today were created by maestros who have existed since time immemorial. To develop the dances made by the existing maestro, one must know the characteristics of each dance based on the motion used. The help of digital image processing and string algorithm analysis methods will help to determine the characteristics of a dance. The algorithm used for dance analysis is the Suffix Tree, where the suffix tree is one of the algorithms that can be used to find patterns from input strings. The string to be analyzed is a series of codes performed by the classifier. The classifier used is Convolutional Neural Network. This method uses an image as its input, which will later perform convolution operations and perform a full-connected layer. The results were obtained using the Convolutional Neural Network method with Alexnet architecture as the classification and confusion matrix to calculate the level of accuracy of the test set, the best accuracy for the head is by using parameter learning rate 0.001, epoch 150, and RGB color space obtained 95% accuracy, 88% precision, 78% recall, and 82% f1-score. For the full body, using a learning rate of 0.01, epoch 150, and RGB color space, the accuracy is 85%, precision is 79%, recall is 64%, and f1-score is 69%. For the legs, using a learning rate of 0.001, epoch 150, and RGB color space, the accuracy is 92%, precision is 84%, recall is 59%, and f1-score is 65%. The results of the suffix tree analysis between codes that use ground truth and classification results have similar values, although the results of the movement patterns obtained by the suffix tree algorithm have not varied, which is dominated by class A because class A is the dominant class in each dance.
PENGEMBANGAN FILM ANIMASI 3 DIMENSI TUDE THE SERIES “BULLYING” Fikri Haikal; Made Windu Antara Kesiman; P Wayan Arta Suyasa
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 11 No. 2 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk : (1)  menghasilkan rancangan dan mengimplementasikan hasil film animasi 3D Tude the series Bullying. (2)  mengetahui respon masyarakat terutama anak-anak terhadap film animasi 3D Tude the series tentang Bullying. Jenis penelitian yang digunakan dalam penelitian ini yaitu  menggunakan jenis penelitian R&D (Research and development) dan model penelitian menggunakan Multimedia Development Life Cycle (MDLC), yang memiliki 6 tahapan yaitu consept (pengonsepan), design (desain), materialcolecting (pengumpulan bahan), assembly (pembuatan), testing (pengujian), dan distribution (pendistribusian). Penelitian ini melibatkan anak-anak dengan  usia 6 hingga 12 tahun. Pengambilan data dilakukan dengan menggunakan kuesioner/angket. Teknik analisis yang digunakan menggunakan uji validitas ahli dan mendapat hasil untuk ahli isi sebesar 1.00, dan ahli media 1.00.  Film animasi 3D Tude the series “Bullying” merupakan film animasi 3 Dimensi yang bertujuan untuk memberikan pemahaman. dalam film ini terdapat arahan dan pesan moral terkait tentang sikap bullying/perudungan yang dikemas dalam bentuk film animasi 3D Tude the series bullying.  Hasil penelitian menunjukan hasil rancangan dan implementasi konten pengembangan “Film Animasi 3D Tude The Series – Bullying” yang berhasil diterapkan berdasarkan hasil uji validasi dari ahli isi,, dan ahli media dengan nilai rata-rata 1.00 dengan kriteria Sangat Valid. Serta respon anak- anak dengan umur 6 – 12 tahun diantaranya 40% menilai sangat positif dan 60% menilai positif dengan  presentase tersebut maka film animasi 3D Tude The Series –Bullying. Kata Kunci : Film, tude, bullying.
Recognition of Balinese Traditional Ornament Carving Images with Convolutional Neural Network and Discrete Wavelet Transform Ni Luh Putu Kurniawati; Made Windu Antara Kesiman; I Made Gede Sunarya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i3.24360

Abstract

Balinese carvings are less known to the public due to the lack of information about Balinese carvings. Minimum information about Balinese carvings can be overcome by utilizing advances in information technology in the field of image processing, namely the introduction of Balinese carving patterns. In the pattern recognition model of an image, there are several things that can be analyzed, such as the recognition method used, feature extraction, including the model in preprocessing to reduce noise in a Balinese carving image. In this study, the Convolutional Neural Network (CNN) was used to classify Balinese carving images combined with Discrete Wavelet Transform (DWT) in extracting image features. The introduction was made to 25 categories of Balinese carving ornaments. Tests are generated based on the level of accuracy generated in the testing process. Analysis of the results was carried out on the resulting model, namely the analysis of the combination of CNN with DWT and without DWT. Testing the data set with 212 training data and 129 testing data using all DWT channels. Based on the results of the tests that have been carried out, it is found that using the DWT extraction feature produces a higher testing accuracy value, namely 35.66% for 25 classes and 74, 42% for 3 carving classes. Meanwhile, without using DWT, it produces an accuracy value of 32.56% for 25 classes and 66.67% for 3 carving classes. In future research, it is hoped that there will be an improvement in the data set and good shooting with a balanced and adequate number for the 25 carving classes that have been obtained.
KOMPARASI METODE SVM, K-NN DAN NBC PADA ANALISIS SENTIMEN I Gede Hendrayana; Dewa Gede Hendra Divayana; Made Windu Antara Kesiman
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 4 No. 1 (2023): Jurnal Indonesia : Manajemen Informatika dan Komunikasi (JIMIK)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) AMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v4i1.157

Abstract

The beauty of Bali raises many comments about how a trip to Indonesia is not complete without going to Bali. In the tourism industry the application of tourist satisfaction and perspective is very important, but most of them still apply surveys. The survey-based approach has weaknesses such as operational costs, the potential for data duplication, and a lack of comprehensiveness. Sentiment analysis of natural tourism objects is performed by classifying positive and negative comments in the Jatiluwih tourist comment dataset. The focus of this panel's sentiment analysis is on comments related to the Natural Tourism Attractiveness Criteria. According to the Directorate General of Forest Protection and Nature Conservation in 2003, the criteria for natural tourism objects are tourist attraction, market potential, accessibility, socio-economic environmental conditions, public services, climate conditions, supporting facilities and infrastructure, and the availability and safety of clean water. This study compares the SVM, K-NN, and NBC methods. This study aims to provide a comprehensive analysis of the performance of each method using the confusion matrix. The results showed that the K-NN method was superior to SVM and NBC in terms of testing accuracy and precision, where accuracy on K-NN gave a value of 93.4%, SVM 93.1%, and NBC 87.9%.
The Effect of Employment Status in the UTAUT Model on the Use Behavioral of E-Office Users: Case Study at Politeknik Pariwisata Bali Putu Ayu Puspitawati; Made Windu Antara Kesiman; Sariyasa Sariyasa
Jurnal Info Sains : Informatika dan Sains Vol. 13 No. 02 (2023): Jurnal Info Sains : Informatika dan Sains , Edition September  2023
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Under the auspices of the Ministry of Tourism and Creative Economy, Politeknik Pariwisata Bali as a State University implements E-Government through the implementation of electronic administration in the E-Office application. E-Office facilitates the issuance of assignment letters, the reporting of tasks, the application for leave, and the recording of daily performance through E-Logbook. Despite the fact that E-Office has been adopted since 2020, it is known that user resistance to the system persists. In this study, the Unified Theory of Acceptance and Use of Technology (UTAUT) model is employed to characterize the factors that influence the acceptance and utilization of E-Office at the Politeknik Pariwisata Bali. In this analysis, the employment status variable was added to the UTAUT model. It is anticipated that the uniqueness of employment status contributed to the development of the UTAUT model will be a novel aspect of this research, allowing it to make a significant scientific contribution, particularly to the study of the UTAUT model. The five stages of Structural Equation Modeling (SEM), namely model specification, model identification, model estimation, model testing, and model modification, will be applied to model development. A total of 158 respondents with ASN and PTT employment status at Politeknik Pariwisata Bali have completed the questionnaire to capture data. The results indicate, based on the t-statistic value, that performance expectations (PE), effort expectations (EE), social factors (SI), and facility conditions (FC) have a significant impact on system utilization behavior (UB). While employment status has a positive but insignificant effect on user desire (BI), this effect is insignificant.
Balinese Shadow Puppet Characters Detection In The Wayang Peteng Performance Using The Yolov5 Algorithm I Gusti Ngurah Bagus Putra Asmara; Made Windu Antara Kesiman; Gede Indrawan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.65906

Abstract

To generate greater public interest in Balinese shadow puppet performances, it is crucial to explore novel ways of educating viewers about the characters showcased in the plays, as many individuals may need to become more familiar with them. In Object Detection, an algorithm is called You Only Look Once (YOLO). This research utilizes the YOLOv5 algorithm to detect Balinese shadow puppet characters in the "wayang peteng" performances. The dataset consists of 5040 images, divided into training, validation, and test data, with a ratio of 7:2:1 (This ratio helps in effectively training and evaluating the YOLOv5 model on a diverse set of data). Four YOLO models are trained, each with a different number of epochs (a single iteration of training when the entire dataset has been passed forward and backward through the neural network), resulting in 12 models. All models are tested using the test data images to obtain precision, recall, and mean Average Precision (mAP) metrics. Additionally, three videos measure the average frames processed per second. The research findings reveal that the YOLOv5n model with 200 epochs achieves the best results, with a precision value of 1, recall of 1, mAP@0.5 of 0.995, mAP@0.5-0.95 of 0.985, and 128.20 frames per second.
Document Validation for Cooperation Agreement Documents at The Undiksha Cooperation and Public Relations Agency (Badan Kerja Sama dan Kehumasan) using Local Binary Pattern (LBP) and YOLOv5 Methods Komang Jepri Kusuma Jaya; Made Windu Antara Kesiman; I Made Dendi Maysanjaya
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.66070

Abstract

A cooperation agreement document managed by BKK Undiksha is a conventionally managed document. With the implementation of the Kampus Merdeka - Merdeka Belajar curriculum in 2021, the number of incoming cooperation agreement documents has increased rapidly, making the collection of document data much longer and inefficient. Therefore, there is a need for a scheme that can automatically validate collaboration documents. The document validation scheme was developed using the Local Binary Patterns and YOLOv5 methods. The data used in the development is primary data from BKK Undiksha in 2021, where two agencies collaborate. The development result is the document validation model collaboration using the Local Binary Pattern and YOLOv5 methods with the best accuracy results of 95.36%, and the ability of the model to detect the number of seal, stamp and signature components is 90.73%.
Analysis of User Satisfaction with E-Learning Services During the Covid-19 Pandemic Using the PIECES Framework I Putu Agus Eka Yatna Cipta; Made Windu Antara Kesiman; I Gede Aris Gunadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2557

Abstract

During the Covid-19 pandemic, the education sector has been able to provide assistance for the continuation of the learning process through e-Learning services. E-Learning is an online-based learning and teaching process that utilizes information technology services. E-Learning is specially designed by the institution and integrated with academic progress data to offer the best support to students who have become increasingly familiar with information technology during the pandemic, addressing its limitations. The objective of this research is to measure user satisfaction with the e-Learning service using the PIECES framework. The PIECES framework consists of Performance, Information/data, Control/security, Efficiency, and Service categories. The PIECES framework is employed for analyzing the information system and consists of six variables: performance, information, economic, control, efficiency, and services. Data was collected through questionnaires distributed to 368 students from different graduation years, spanning from 2018 to 2021, who are users of the e-Learning service. Based on the gathered data analysis, the average satisfaction levels for each variable are as follows: performance scored 3.75, information scored 3.82, economic scored 3.84, control scored 3.74, efficiency scored 3.7, and services scored 3.84. Combining these values and referencing Kaplan and Norton, it can be concluded that the overall user satisfaction level with e-Learning falls into the satisfied category
Panji Sakti “The King of Buleleng” : Game 3D Cerita Rakyat Berbasis Desktop Pratama, Putu Gilang; Santyadiputra, Gede Saindra; Antara Kesiman, Made Windu
INSERT : Information System and Emerging Technology Journal Vol. 1 No. 2 (2020)
Publisher : Prodi Sistem Informasi, FTK, Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/insert.v1i2.31040

Abstract

Game 3D cerita rakyat berbasis desktop ini menceritakan tentang riwayat hidup dari Panji Sakti atau sering dikenal juga sebagai Ki Barak Panji Sakti yang merupakan raja pertama Buleleng. Akan tetapi masih banyak masyarakat yang tidak mengetahui tentang cerita rakyat Panji Sakti. Terbukti dari angket yang disebar peneliti. Selain itu media untuk menceritakan cerita rakyat Panji Sakti masih dalam bentuk buku, dimana ini merupakan bentuk kuno di zaman yang sudah modern. Yang mengakibatkan kurangnya minat untuk mengetahui cerita Panji Sakti itu sendiri. Tujuan dari penelitian ini adalah untuk mengimplementasikan rancangan game 3D cerita rakyat Panji Sakti yang nantinya dapat menambah minat masyarakat untuk melestarikan cerita rakyat Panji Sakti. Game 3D cerita rakyat ini menggunakan metode Game Development Life Cycle. Hasil akhir dari game ini berupa program executable.
Co-Authors A. A. Istri Ita Paramitha Adhi Suarjana, I Kadek Adi Saputra Yasa, I Gede Adi Yoga Dewantara, I Made Adnyana, I Putu Wandra Agung Istri Ariningrat, I Gusti Agus Eka Wilantara, Putu Agus Jayadi Putra, Kadek Agus Kamiana Agus Kristiawan, I Gde Made Agus Nyoman Reditya Ary Prasetya Agus Sutrisna, I Kadek Ajeng Wulandari Pratama Ajiwerdhi, Anak Agung Gde Putra Alfin Nur Anak Agung Gde Putra Ajiwerdhi Ananta Satriadi, Kadek Andika, I Gede Andreana, I Made Dwi Anggara, I Made Dika Ardipa, Gede Sukra Ari Kamelia Dewi, Ni Made Ari Mahendra, I Komang Ari Putra, Ida Bagus Gede Arimbawa, I Gusti Ngurah Putra Arisma Dewi, Komang Ayu Ary Wahyuningsih, Ni Made Ayu Ary Widayanti, Putu Aryasih, Putu Putri Asmara, I Wayan Dana Astuti, Ni Putu Pasek Wida Ayu Nirma Lestari, Gusti Bagus Maha Putra, I Gusti Bunga Anindya, Made Candra Adi Pranata, Gede Chrisnapati, Padma Nyoman Chrisnapati, Padma Nyoman Cipta, I Putu Agus Eka Yatna David Setiawan David Setiawan, David Dessy Seri Wahyuni Dewa Gede Hendra Divayana, Dewa Gede Hendra Dewa Putu Doniawan Dewi, Made Sulatri Dewi, Ni Putu Dita Ariani Sukma Dewi, Ni Putu Sri Indra Padma Diani, Ni Komang Doniawan, Dewa Putu Dwi Purniyati, Gusti Ayu Dwi Suparyanta, Kadek Eka Saptaridevi, Ni Luh Endra Wiartika P, I Made Evi Wellyastini, Kadek Fikri Haikal Gd Tuning Somara Putra Gde Angga Putra Sutanjaya Gede Aditra Pradnyana Gede Agus Putra Yasa Gede Candra Adi Pranata Gede Indrawan Gede Saindra Santyadiputra Gede Saindra Santyadiputra, Gede Saindra Gede Sukra Ardipa Gede Widiartana Yasa Gusti Ayu Dwi Purniyati Gusti Ayu Nirma Lestari Hady Permana S, Putu Trisna Haryantara, I Nyoman I DEWA AYU MADE SARTINI I Gde Made Agus Kristiawan I Gede Adi Saputra Yasa I Gede Adi Saputra Yasa I Gede Agus Pebriana I Gede Aris Gunadi I Gede Arya Sudarmayana I Gede Bendesa Subawa I Gede Bintang Arya Budaya I Gede Hendrayana I Gede Mahendra Darmawiguna I Gede Rusdy Mahayana Putra I Gede Sastra Kurniawan I Gede Sudirta I Gede Sudirta, I Gede I Gede Sudirtha I Gusti Agung Istri Ariningrat I Gusti Ayu Agung Diatri Indradewi I Gusti Bagus Maha Putra I Gusti Ngurah Bagus Putra Asmara I Kadek Adhi Suarjana I Kadek Agus Sutrisna I Kadek Yostab Mariyantoni I Ketut Resika Arthana I km. Lanang Oka Wiryawan I Komang Ari Mahendra I Komang Hendra Trinium Jaya I Made Adi Yoga Dewantara I Made Agus Wirahadi Putra I Made Angga Darma Putra I Made Ardwi Pradnyana I Made Arya Riananda Putra I Made Dika Anggara I Made Dwi Andreana I Made Endra Wiartika P I Made Gede Sunarya I Made Putrama I Made Restu Arta Jaya I Made Yoga Yudisthira Sandra I Md. Dendi Maysanjaya I Nyoman Haryantara I Putu Agus Eka Yatna Cipta I Putu Gede Karwina Styawan I Putu Sujana Atmaja I PUTU WANDRA ADNYANA I Putu Wira Adnyana I Wayan Dana Asmara I Wayan Pandu Wibawa S I Wayan Pio Pratama Ida Ayu Putu Purnami Ida Ayu Widiyanthi Ida Bagus Gede Ari Putra Ida Bagus Redy Santiawan Ida Purnamasari, Putu Ika Hendriana, Komang Indradewi, Gusti Ayu Agung Diatri Intan Pebriyanti Jaya, I Made Restu Arta Juliawan, Komang Gede Satria Kaban, Ekinnisura Kadek Agus Jayadi Putra Kadek Ananta Satriadi Kadek Dwi Suparyanta Kadek Evi Wellyastini Kadek Wikan Paramasila Kadek Yota Ernanda Aryanto Kamiana, Agus Karwina Styawan, I Putu Gede Ketut Agustini Ketut Gede Widia Pratama Putra Ketut Satria Ketut Tri Sutrisna Oka Ketut Widiantara Komang Ayu Arisma Dewi Komang Gede Satria Juliawan Komang Ika Hendriana Komang Jepri Kusuma Jaya Komang Setemen Komang Sudana Yasa Pande Komang Sudana Yasa Pande Kurniansyah, Adrian Lanang Nugraha, Made Luh Putu Eka Damayanthi Luh Putu Eka Damayanthi Luh Sri Darmaningsih M.Cs S.Kom I Made Agus Wirawan . Made Bunga Anindya Made Lanang Nugraha Made Sulatri Dewi Mahendri Pramadewi, Pande Made Mariyantoni, I Kadek Yostab Maryati, Ni Made Rai Maryati, Ni Made Rai Mika Karmila, Ni Komang Natih, I Dewa Gede Agung Wibhisana Ni Kadek Pande Dwika Liona Ni Komang Mika Karmila Ni Komang Oktari Permata Sari Ni Komang Sriasih Ni Luh Kadek Tristiana Pratiwi Ni Luh Nita Sari Ni Luh Putu Kurniawati Ni Made Ari Kamelia Dewi Ni Made Ayu Ary Wahyuningsih Ni Made Rai Maryati Ni Made Yeni Dwi Rahayu Ni Nyoman Sugihartini Ni Putu Bali Pratiwi Ni Putu Pasek Wida Astuti Nining Rahayuningsih Niti, Made Ayu Asri Nugraha, Putu Zasya Eka Satya Nugrahini, Ni Putu Prita Nur, Alfin Nyoman C, Padma Nyoman C, Padma Nyoman Chrisnapati, Padma Nyoman Juli Budiartawan Oka Wiryawan, I km. Lanang Oky Sanjaya, Kadek P. WAYAN ARTA SUYASA Padama Nyoman Crisnapati Padma Nyoman C Padma Nyoman Chrisnapati Padma Nyoman Crisnapati Padma Nyoman Crisnapati Pande Dwika Liona, Ni Kadek Pande Made Mahendri Pramadewi Pandu Wibawa S, I Wayan Pebriana, I Gede Agus Pebriyanti, Intan Permana S, Putu Trisna Hady Pramadewi, Pande Made Mahendri Pratama, Putu Gilang Pratiwi, Ni Putu Bali Prianka Vedanty, Putu Pusparani, Diah Ayu Putra Yasa, Gede Agus Putra, Gd Tuning Somara Putra, Kadek Agus Jayadi Putu Agus Eka Wilantara Putu Angga Sudyatmika Putu Ary Widayanti Putu Ayu Puspitawati Putu Hendra Suputra Putu Ida Purnamasari Putu Putri Aryasih Putu Soni Ermawati Putu Trisna Hady Permana S Putu Yuditia Riani Putu Yuli Krisnawati Rahayuningsih, Nining rahmi, rugayatur Reditya Ary Prasetya, Agus Nyoman Redy Santiawan, Ida Bagus Rinaldi Munir rugayatur rahmi Saputri, Tesya Saragih, Andi Siaputra Sari, Ni Luh Nita Sariyasa . Sartini, I Dewa Ayu Made Sastra Kurniawan, I Gede Satria Juliawan, Komang Gede Satria, Ketut Sindu, I Gede Partha Soni Ermawati, Putu Sri Darmaningsih, Luh Sriasih, Ni Komang Sudarmayana, I Gede Arya Sujaya, Made Agus Panji Sulatri Dewi, Made Sumantara, I Gusti Lanang Trisna Suputra, I Komang Hery Abdi Surya Diputra, I Gusti Nyoman Anton Surya, I Putu Bayu Ananta Sutanjaya, Gde Angga Putra Sutrisna Oka, Ketut Tri Taufik Ismail Taufik Ismail Tristiana Pratiwi, Ni Luh Kadek Wiartika P, I Made Endra Widiantara, Ketut Widiantara, Ketut Widiyanthi, Ida Ayu Wikan Paramasila, Kadek Winaya, Ayu Nyoman Waisantini Wira Adnyana, I Putu Wismawan, Komang Hendra Wulandari Pratama, Ajeng Yasa, Gede Widiartana Yoga Yudisthira Sandra, I Made Yogi Aditya Yostab Mariyantoni, I Kadek Yuditia Riani, Putu Yuli Krisnawati, Putu