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Analisis Sentimen Data Provider Layanan Internet Pada Twitter Menggunakan Support Vector Machine Dengan Penambahan Algoritma Levenshtein Distance Ida Bagus Nyoman Wijana Manuaba; Gede Rasben Dantes; Gede Indrawan
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 5 No. 2 (2022): Volume V - Nomor 2 - Maret 2022
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/siskom-kb.v5i2.261

Abstract

Komentar pada data twitter mengandung banyak opini terkait suatu objek atau topik. Dari kumpulan komentar, dapat dilakukan analisis sentimen menggunakan Support Vector Machine untuk memperoleh hasil klasifikasi positif dan negatif. Data yang digunakan berkaitan dengan provider atau penyedia jaringan internet yang ada di Indonesia. Penambahan algoritma Levenshtein Distance pada tahap text preprocessing bertujuan untuk meningkatkan hasil klasifikasi. Tahapan Proses klasifikasi meliputi, pengumpulan data menggunakan API twitter, penghapusan duplicate data, pemberian label data, tahap text preprocessing (convert emoticon, cleansing, case folding, stemming, stopword removal, and tokenizing, penerapan algoritma Levenshtein Distance, stopword removal lanjutan, convert negation), feature extraction (TF-IDF), serta proses klasifikasi menggunakan Support Vector Machine.Hasil pengujian dengan menggunakan confusion matrix, menunjukan peningkatan hasil klasifikasi yang lebih baik setelah menggunakan algoritma Levenshtein Distance pada tahap text preprocessing. Nilai accuracy mengalami peningkatan sebesar 2%, recall positif 3%, recall negatif 1%, precision positif 1%, dan precision negatif 2%. Tetapi kecepatan waktu proses pada tahap text preprocessing dengan penambahan algoritma Levenshtein Distance lebih lambat sebesar 295,606 detik, jika dibandingkan tanpa adanya penambahan algoritma Levenshtein Distance.
LBtrans-Bot: A Latin-to-Balinese Script Transliteration Robotic System based on Noto Sans Balinese Font Gede Indrawan; Ni Nyoman Harini Puspita; I Ketut Paramarta; Sariyasa Sariyasa
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1247-1256

Abstract

Balinese script writing, as one of Balinese cultural richness, is going to extinct because of its decreasing use. This research is one of the ways to preserve Balinese script writing using technological approach. Through collaboration between Computer Science and Balinese Language discipline, this research focused on the development of a Latin-to-Balinese script transliteration robotic system that was called LBtrans-Bot. LBtrans-Bot can be used as a learning system to give the transliteration knowledge as one aspect of Balinese script writing. In this research area, LBtrans-Bot was known as the first system that utilize Noto Sans Balinese font and was developed based on the identified seventeen kinds of special word. LBtrans-Bot consists of the transliterator web application, the transceiver console application, and the robotic arm with its GUI controller application. The transliterator used the Model-View-Controller architectural pattern, where each of them was implemented by using MySQL database (as the repository for the words belong to the seventeen kinds of special word), HTML, PHP, CSS, and Bootstrap (mostly for the User Interface responsive design), and JavaScript (mostly for the transliteration algorithm and as the controller between the Model and the View). Dictionary data structure was used in the transliterator memory as a place to hold data (words) from the Model. The transceiver used batch script and AutoIt script to receive and trasmit data from the transliterator to the GUI controller, which control the Balinese script writing of the robotic arm. The robotic arm with its GUI controller used open-source mDrawBot Arduino Robot Building platform. Through the experiment, LBtrans-Bot has been able to write the 34-pixel font size of the Noto Sans Balinese font from HTML 5 canvas that has been setup with additional 10-pixel length of the width and the height of the Balinese script writing area. Its transliterator gave the accuracy result up to 91% (138 of 151) testing cases of The Balinese Alphabet writing rules and examples document by Sudewa. This transliterator result outperformed the best result of the known existing transliterator based on Bali Simbar font, i.e. Transliterasi Aksara Bali, that only has accuracy up to 68% (103 of 151) cases of the same testing document. In the future work, LBtrans-Bot could be improved by: 1) Accommodating more complex Balinese script with trade off to the limited writing area of robotic system; 2) Enhancing its transliterator to accommodating the rules and/or examples from the testing document that recently cannot be handled or gave incorrect transliteration result; enriching the database consists of words belong to the seventeen kinds of special word; and implementing semantic relation transliteration.
Latin-to-Balinese Script Transliteration Method on Mobile Application: A Comparison Gede Indrawan; I Ketut Paramarta; Ketut Agustini; Sariyasa Sariyasa
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp1331-1342

Abstract

Balinese script writing, as one of Balinese cultural richness, is going to extinct because of its decreasing use. This research is a way to preserve it through collaboration between Computer Science and Language discipline, that focused on accuracy comparison of Latin-to-Balinese script transliteration method on mobile application as a ubiquitous learning media. From few research in this area, there are only two existing methods to be compared, i.e. each on Android mobile application that were called Belajar Aksara Bali (BAB), and Transliterasi Aksara Bali (TAB). The comparison was based on The Balinese Alphabet writing rules and examples document by Sudewa. Through the experiment, TAB has outperformed BAB since TAB has passed over 68% (103 of 151) cases, while BAB has passed over only 39% (59 of 151) cases. This research contributes on a comprehensive accuracy comparison analysis of Latin-to-Balinese script transliteration method, specifically on mobile application, since there is no such study. This research also contributes on those methods improvement possibility. In the future, this research can be used as a reference for improvement of any Latin-to-Balinese script transliteration method by taking care on thirteen kind of special words that were found during this comparison study.
Optimization of Adaptive Genetic Algorithm Parameters in Traveling Salesman Problem I Kayan Herdiana; I Made Candiasa; Gede Indrawan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 4 No. 2 (2022): Article Research Volume 4 Number 2, July 2022
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v4i2.1581

Abstract

The TSP problem is one where a seller visits multiple destinations at the same time and they are only allowed to visit once. The purpose of this TSP is to shorten the shortest distance, thereby minimizing time and cost. There are various methods to solve the TSP problem, including greedy algorithm, brute force algorithm, hill climbing method, ant algorithm, and genetic algorithm. Each process in a genetic algorithm is affected by several parameters, including population size, maximum generation, crossover rate, and mutation rate. The purpose of this study is to apply genetic algorithms to the traveling salesman problem optimization, calculate the maximum influence of generation, chromosome number, crossover rate and mutation rate on the optimal genetic algorithm, calculate the range of chromosome number, population size, crossover rate and mutation rate for genetic algorithm in the traveling salesman problem and calculate the effect of adaptive genetic algorithm parameters on genetic algorithm results. Based on the results obtained from research and testing, the four parameters of the genetic algorithm are positively correlated with fitness results while negatively correlated with execution time performance where each adaptive parameter applied provides more optimal fitness results than static parameters. The four adaptive parameters that are applied together give optimal results, both fitness which reaches 1.0% and time reaches 38.7%.
Implementasi Metode Electre Dalam Penentuan Platform yang Tepat dalam Rangka Mewujudkan Flipped Learning di SMK Bali Dewata seftian rusditya; Dewa Gede Hendra Divayana; Gede Indrawan
JURNAL ILMU KOMPUTER INDONESIA Vol 7, No 1: Februari 2022
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jik.v7i1.3600

Abstract

Pembelajaran menggunakan model flipped classroom erat kaitannya dengan penggunaan teknologi seperti internet. Pemanfaatan internet dalam pembelajaran dapat membantu peserta didik mengeksplorasi ilmu pengetahuan secara lebih luas. Hal tersebut dapat dilihat dari hasil angket yang diberikan pada peserta didik SMK Bali Dewata Denpasar. Namun dari berbagai materi yang dipelajari selama satu semester tersebut ditemukan beberapa materi yang sulit dipahami oleh peserta didik. Pemilihan platform flipped classroom bertujuan untuk memilih salah satu media pembelajaran yang tepat dalam mentransformasi pengetahuan peserta didik sehingga dapat mencapai tiap-tiap dimensi pengetahuannya secara utuh. Metode penentuan pemilihan platform flipped classroom menggunakan metode ELECTRE (Elimination and Choice Expressing Reality). Hasil dari penelitian ini menghasilkan kesimpulan bahwa platform Google Classroom adalah yang tepat untuk digunakan dalam flipped learning berdasarkan fitur, harga, serta kuisioner dari pengguna platform.Kata kunci: SMK Bali Dewata, Flipped Learning, ELECTRE
PENGEMBANGAN TRANSLITERASI TEKS AKSARA BALI KE LATIN MENGGUNAKAN FINITE STATE MACHINE Cokorda Oka Birawidya; Gede Indrawan; I Gede Aris Gunadi
JURNAL ILMU KOMPUTER INDONESIA Vol 7, No 1: Februari 2022
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jik.v7i1.3851

Abstract

Pelestarian penulisan Aksara Bali dapat dilakukan dengan memanfaatkan kemajukan teknologi informasi, seperti model transliterasi teks latin ke dalam Aksara Bali atau Aksara Bali ke teks latin. Pada penelitian ini digunakan font Noto Serif Balinese yang berbasis UNICODE. Hasil implementasi yang dilakukan menunjukkan bahwa aplikasi berhasil dikembangkan dalam melakukan transliterasi melalui keyboard Aksara yang sudah dikembangkan. Finite state machine pada penelitian ini digunakan untuk mendapatkan nilai UNICODE dari tiap karakter dari teks Aksara Bali dengan mengecek karakter yang ada pada setiap state nya. Hasil pengujian pada blackbox testing menunjukkan bahwa aplikasi yang dihasilkan masih memiliki bug pada beberapa proses transliterasi dan fungsional keyboard yang disediakan. 2. Berdasarkan kuesioner System Usability Scale yang diberikan kepada 20 responden, didapatkan skor akhir sebesar 75.25. Skor yang didapatkan menunjukkan bahwa aplikasi sudah memuaskan pengguna karena skor akhir yang dihasilkan lebih tinggi dari skor standar miminal system usability scale yakni 68. Adapun berdasarkan skor tersebut, maka aplikasi yang dihasilkan termasuk dalam kategori “Acceptable” dengan skala grade “C”. Penelitian selanjutnya dapat difokuskan pada perbaikan bug atau error yang masih ada.
PERBANDINGAN EVALUASI USABILITY PADA APLIKASI SMART BINA TARUNA WIRATAMA MENGGUNAKAN HEURISTIC EVALUATION DAN CONCURRENT THINK ALOUD Putu Eka Parianthana; Gede Indrawan; I Gede Aris Gunadi
Jurnal Teknologi Informasi dan Komputer Vol 8, No 2 (2022): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

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

Abstract

ABSTRACTThe Smart BTW application is a mobile-based platform to make it easier for users to prepare themselves for the SKD/TKD selection based on the Computer Assessment Test (CAT). In the span of 1 year of using the Smart BTW Application, there are problems related to the user interface so that further evaluation is needed for its development. One of the user-based evaluation methods that can be used is usability evaluation. Usability evaluation can be done based on experts and users. Based on the study conducted, the evaluation based on expert and user will be compared using Heuristic Evaluation and Concurrent Think Aloud techniques. Heuristic evaluation will involve 5 experts who serve as application evaluators, while the user experience evaluation uses a minimum of 20 respondents. In the heuristic evaluation, 20 lists of problems felt by each evaluator were also generated. In Concurrent Think Aloud, 7 lists of problems experienced by users are generated when working on the given task scenario. Development for further research, other techniques in usability testing can be used, such as Performance Measurement to compare the evaluation results between experts and application users based on quantitative data.Keywords: evaluation, usability, heuristics, think aloud.ABSTRAKAplikasi Smart BTW merupakan platform berbasis mobile untuk mempermudah para pengguna dalam mempersiapkan dirinya menghadapi seleksi SKD/TKD berbasis Computer Assesment Test (CAT). Pada rentang waktu 1 tahun penggunaan Aplikasi Smart BTW, terdapat permasalahan yang berkaitan dengan antarmuka pengguna sehingga diperlukan evaluasi lanjutan untuk pengembangannya. Salah satu metode evaluasi berbasis pengguna yang dapat digunakan adalah evaluasi usability. Evaluasi usability dapat dilakukan berbasis pakar dan pengguna. Berdasarkan kajian yang dilakukan, akan dibandingkan evaluasi berbasis pakar dan pengguna menggunakan teknik Evaluasi Heuristik dan Concurrent Think Aloud. Evaluasi Heuristik akan melibatkan 5 orang ahli yang bertugas sebagai evaluator aplikasi, sedangkan pada evaluasi pengalaman pengguna, minimal menggunakan 20 responden. Pada evaluasi heuristik, dihasilkan juga 20 daftar permasalahan yang dirasakan oleh setiap evaluator. Pada Concurrent Think Aloud dihasilkan 7 daftar permasalahan yang dirasakan oleh pengguna saat mengerjakan skenario tugas yang diberikan. Pengembangan untuk penelitian selanjutnya, dapat digunakan teknik lain dalam usability testing, seperti Performance Measurement untuk membandingkan hasil evaluasi antara pakar dan pengguna aplikasi berdasarkan data kuantitatif.Kata Kunci: evaluasi, usability, heuristik, think aloud.
Expert System Using Certainty Factor Method For Adjustment Of Learning Styles With Students I Putu Aris Sanjaya; I Gede Aris Gunadi; Gede Indrawan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2068

Abstract

Alignment of students with learning styles greatly affects the quality of learning of students in educational units. With good learning quality, the passing rate of students in an educational unit will also increase and can produce quality graduates. So far, the learning process implemented in this school has been going well when viewed based on the number of students graduating with the number of students present, but so far no further research has been conducted regarding this suitability so that the effectiveness of student learning is still not optimal. Based on this, the research objective is to build an Expert System with the Certainty Factor method to adjust the learning styles of students at SMK PGRI 5 Denpasar. Based on the results that will be obtained through the system designed and built in this research, it is hoped that it will make it easier for educators to prepare learning models and strategies that will be given to students from the results of determining student learning styles. The research results obtained from the test results show 100% suitability in giving dominant results to students' learning styles. In this study the students who were used as the test sample had different learning style percentage accuracy so that it could be used to determine the right learning style for each student.
Klasifikasi Pelayanan Kesehatan Berdasarkan Data Sentimen Pelayanan Kesehatan menggunakan Multiclass Support Vector Machine Moh. Heri Setiawan; I Gede Aris Gunadi; Gede Indrawan
Jurnal Sistem dan Informatika (JSI) Vol 17 No 1 (2022): Jurnal Sistem dan Informatika (JSI)
Publisher : Direktorat Penelitian,Pengabdian Masyarakat dan HKI - Institut Teknologi dan Bisnis (ITB) STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/jsi.v17i1.512

Abstract

Penelitian ini bertujuan untuk melakukan klasifikasi pada data sentiment pelayanan Kesehatan menggunakan Multiclass SVM pendekatan One versus One (OvO) dengan fitur unigram dan bigram. Sumber data sentimen berasal dari data laporan survei kepuasan pelayanan puskesmas denpasar 2021 oleh Center for Public Health Innovation (CPHI) FK UNUD. Ekstraksi fitur menggunakan TF-IDF satu term/unigram dan dua term/bigram lalu kemudian diolah menggunakan Support Vector Machine OvO. KFold Cross Validation digunakan untuk membagi data latih dan data tes sekaligus memvalidasi model. Hasil yang didapatkan pada proses pengklasifikasian data train SVM OvO unigram didapatkan skor akurasi 97,09%, presisi 97,97%, recall 96,90%, dan f1-score 97,40%, sedangkan pada SVM OvO bigram didapatkan skor akurasi 97,91%, presisi 98,56%, recall 37,39%, dan f1-score 37,79%. Pada pengklasifikasian data tes didapatkan SVM OvO unigram mendapatkan skor akurasi 68,77%, presisi 73,13%, recall 61,67%, dan f1-score 64,13%, sedangkan SVM OvO bigram mendapatkan skor akurasi 47,92%, presisi 66,41%, recall 37,39%, dan f1-score 37,79%. Perbedaan skor yang jauh pada data train dan data tes dikarenakan adanya overfitting, sehingga perlu adanya seleksi fitur sebelum fitur digunakan sebagai masukan untuk SVM. Selain itu dapat disimpulkan SVM OvO dengan menggunakan fitur unigram memiliki performa lebih baik dibandingkan dengan SVM OvO dengan menggunakan fitur bigram.
FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUASAN MAHASISWA DALAM SISTEM PERKULIAHAN PADA MASA COVID-19 DI ITB STIKOM BALI Kadek Enny Rusmala Dewi; I Made Candiasa; Gede Indrawan
Media Bina Ilmiah Vol. 17 No. 12: Juli 2023
Publisher : LPSDI Bina Patria

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

Abstract

This research aims to identify the significant factors that contributes on students’ satisfaction in the lecturing system in terms of service quality dimension, which include reliability, assurance, responsiveness, empathy and physical evidence (tangibles). This study employed a quantitative correlational approach with an ex post facto design. The population of this study consisted of 348 ITB STIKOM Bali Campus students in the academic year 2021/2022. Using the Slovin formula and proportional random sampling, a sample size of 186 is determined and selected. This study collects data regarding service quality and student satisfaction using questionnaires. The method of analysis employed is simple regression analysis and multiple regression. The results indicate that: (1) the reliability dimension contributes significantly to student satisfaction, (2) the assurance dimension contributes significantly to student satisfaction, and (3) the responsiveness dimension can contribute significantly to student satisfaction. (4) the empathy dimension contributes significantly to student satisfaction (5) The tangibles dimension contributes significantly to student satisfaction. (6) Concurrently, there is a substantial contribution. Service quality dimensions have a significant effect on student satisfaction (7), and empathy is the most influential service quality factor influencing student satisfaction in the lecture system during the Covid-19 pandemic (46.19%). The determination test revealed that 90.30% of student satisfaction was influenced by service quality dimensions, with the remaining 9.70% influenced by other variables.
Co-Authors Ade Prayoga, I Made Ade Surya Indrawan Aditya, Eka Adnyana, I Putu Iwan Krisna Agus Adiarta,ST,MT . Agus Ariwanta, I Putu Yesha Agustini, Ni Wayan Eva Ahmad Asroni Ahmad Asroni, Ahmad Al-Fauga, Muh. Ambara, Made Anak Agung Candra Widyaningsih Anandita, Ida Bagus Gede Andika, I Gede Anop Sudiatmika Arditaloka, I Wayan Angga Arimbawa, Gusti Putu Arya Arsa, Putu Suka Artayasa, I Kadek Dwi Artha, I Gede Mony Aryani, Wayan Aryawan, I Komang Budi Mas Astawa, I Gede Karya Benhard Sitohang Christina Purnama Yanti Cokorda Oka Birawidya Damiati Dananjaya, Md Wira Putra Daniel Eka Saputra Daniel Kevin Alexander Dea Sillviari, Ni Putu Dede Desnantha Putra Denny Nathaniel Chandra Dewa Gede Hendra Divayana, Dewa Gede Hendra Dewa, I Dewa Gede Budiastawa Dewi, Ni Wayan Jeri Kusuma Dewi, Suzy Puspita Dhruvayoti Tiirtheshvara Dika Anggara, I Made Diva Palguna Erna Supriathi, Ni Kadek Evi Yuliana, Evi Gede Rasben Dantes Gede Suweken Gemara Adhiyasa Parahita Nugraha Gusti Ngurah Joniartawan Hakimi, Musawer Hendra Trinium Jaya, I Komang Herdiana, I Kayan Hery Heryanto I Dewa Ayu Indah Saraswati I Gede Andika I Gede Aris Gunadi I Gede Bara Yuda Gautama I Gede Indra Suwardika I Gede Nurhayata I Gusti Agung Istri Pradnya Prameswari I Gusti Ngurah Bagus Putra Asmara I Kadek Juni Arta I Kadek Wahyu Sudiatmika I Kadek Wihendradinata I Kayan Herdiana I Ketut Paramarta I Ketut Pramarta I Ketut Suja I Komang Adyanata I Komang Deny Supanji I Made Agus Oka Gunawan I Made Agus Widiana Putra I Made Candiasa I Made Edy Listartha I Made Wahyu Dwi Wismayana I Made Windu Segara Kurniawan I N. Jampel I Nyoman Saputra I Nyoman Suarka I Nyoman Sukajaya I Nyoman Sukaraja I Nyoman Triadi Wiguna I Putu Aris Sanjaya I Putu Aris Sanjaya, I Putu Aris I Putu Okta Priyana I Putu Prima Ananda I Putu Yoga Indrawan I W. Widiana I Wayan Adi Wiratama I Wayan Aditya Wiguna I Wayan Dodi Putra Artawan I Wayan Rosiana Ida Ayu Mirah Cahya Dewi Ida Bagus Nyoman Wijana Manuaba Ida Bagus Prayoga Bhiantara Ida Putu Ayu Hemy Eka Yani Joniartawan, Gusti Ngurah Juliantara. KW, Pande Putu Ode Juni Arta, I Kadek Juniastra, Made Gde Kadek Enny Rusmala Dewi Kadek Teguh Wahyu Dewantara Kadek Wibawa Kadek Yota Ernanda Aryanto Kadek Yunita Dewi Ketut Agustini Ketut Nila Arta Ketut Udy Ariawan Komang Gde Hendra Kusuma Putra Kurniawan, I Made Windu Segara Kusuma Wardana, Kadek Lemes, I Nyoman Limbong, Kevin Gary Luh Joni Erawati Dewi M.Cs S.Kom I Made Agus Wirawan . M.T. S.T. I Wayan Sutaya . Made Agus Panji Sujaya Made Ambara Made Hery Santosa Made Santo Gitakarma Made Windu Antara Kesiman Made Yuda Sadewa Mahadewi, Luh Putu Putrini Mahadewi, Luh Putu Putrini Mentayani, Ni Putu Anik Moh. Heri Setiawan Muhammad Alwan Nursuhaida Ni Luh Made Uti Tiasmi Ni Made Ayu Juli Astari Ni Made Rai Arini Permatasari Ni Nyoman Harini Puspita Ni Putu Eka Apriyanthi Ni Putu Ria Anggreni Ni Wayan Jeri Kusuma Dewi Ni Wayan Wardani Nugraha, I Gede Pradipta Adi Nyoman Jampel Nyoman Santiyadnya Palguna, Diva Pande Made Mahendri Pramadewi Parahita Nugraha, Gemara Adhiyasa Parwata, I Gusti Putu Adi Pracasitaram, I Gede Made Surya Bumi Pracasitaram, I Gede Surya Bumi Praja Setiawan Pramadewi, Pande Made Mahendri Pramarta, I Ketut Pranata, Putu Ade Pratama, Putu Aditya Pringgadhana, I Made Lanang Putra Purnama, M. Rokhman Putera, Hagi Semara Putra, I Gusti Putu Agung Arka Putra, Rian Permana Yatmika Putu Ade Pranata Putu Eka Parianthana Putu Suka Arsa Raditya Pramita, I Putu Agus Ratna Mei Vidya Richo, Rolando Alex Sandhiyasa, I Made Subrata Sanjaya, Kadek Oki Sanjaya, Kadek Oki Saputra, Daniel Eka Sariyasa . seftian rusditya Seftian Rusditya Setemen , Komang Setiawan, Kadek Reda Setiawan, Praja Sillviari, Ni Putu Dea Sogen, Afrianto T.L Sudestra, I Made Ardi Sudiatmika, Anop Sujaya, Made Agus Panji Sukla Mandika, Ketut Gde Sumarno, I Wayan Supanji, I Komang Deny Suparsa, I Made Surata, I Nyoman Susena, I Gede Ardika Suzy Puspita Dewi Taufik Akbar Taufik Akbar Tjahyanti, L.P.A.S Utami, Ni Luh Putu Sri Wardani, Ni Wayan Wayan Andre Pratama Wayan Eka Ariawan Wibawa, Kadek Widya Dharma Sidi Wiguna, I Kadek Arta Wijaya, Putu Agung Ananta Wikanta, I Made Indra Adhi Winardana, Made Winarini, Ni Luh Wirawan Nathaniel Chandra Yani Yani Yulia Mariasmi Kiuk