p-Index From 2021 - 2026
12.956
P-Index
This Author published in this journals
All Journal Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Telematika : Jurnal Informatika dan Teknologi Informasi JUSIFO : Jurnal Sistem Informasi INFORMAL: Informatics Journal Proceeding of the Electrical Engineering Computer Science and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal Jurnal Informatika Universitas Pamulang Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal RESISTOR (Rekayasa Sistem Komputer) International Journal of Natural Science and Engineering Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JURIKOM (Jurnal Riset Komputer) Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar JE (Journal of Empowerment) Jurnal Mantik REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) Indonesian Journal of Data and Science Journal of Computer Networks, Architecture and High Performance Computing IJISTECH JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology Journal of Technology and Informatics (JoTI) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Info Sains : Informatika dan Sains JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal Multidisiplin Madani (MUDIMA) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Pengabdian Masyarakat Indonesia (JPMI) Digital Transformation Technology (Digitech) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Eduvest - Journal of Universal Studies Journal of Software Engineering and Information System (SEIS) Faedah: Jurnal Hasil Kegiatan Pengabdian Masyarakat Indonesia Bulletin of Informatics and Data Science Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) TECHNOVATE Galaksi KOMET Journal Abdimas Paspama Service
Claim Missing Document
Check
Articles

Customer Satisfaction Analysis of PLN Mobile Services Using the Naïve Bayes Classifier Method I Komang Arya Ganda Wiguna; Ani Nida’ia Mustafida; Putu Praba Santika; Made Suci Ariantini; I Gede Iwan Sudipa
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.855 KB)

Abstract

This research was conducted to determine customer satisfaction with the PLN Mobile application service by employing the Nave Bayes Classifier algorithm in order to precisely determine the level of customer satisfaction with the PLN Mobile application service based on customer data collected through the PLN Mobile application. Using a questionnaire issued to consumers who use the PLN Mobile application, the author collects data for this study. The purpose of the author's research is to acquire the outcomes of data analysis using the Nave Bayes Classifier equation. Class "Yes (Satisfied)" and Class "No (Not Satisfied)" were established by the authors of this study to measure consumer satisfaction with PLN Mobile application services. To determine the classification of satisfaction, the author employs the factors of gender, age, and occupation, in addition to sixteen of the author's own assertions. Based on studies utilizing the Nave Bayes Classifier, the authors obtained a precision of 90.48%.
Implementation Of The Mapping System For Student Practical Work Locations Using Mobile Gis Indra Pratistha; I Nyoman Alit Arsana; I Gede Iwan Sudipa
Jurnal Mantik Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i2.2769

Abstract

In the learning process, students in lectures do not only acquire theoretical material but students are also required to do practical work in companies. Practical work is intended so students can find out real problems in the field, increase knowledge and improve hard and soft skills. In its implementation, students can apply for practical work based on the choice of the location of the intended company, the system that has been running already accommodates the business process of applying for practical work. Still, there is no feature to find out the location distribution of practical work students. This study aims to utilize the API (application programming interface) on the Google Maps API and GPS (Global Positioning System) services to see the distribution of suitable work locations for INSTIKI students. The benefits of research to find suitable work locations for students at STIKI Indonesia are very important, considering that practical work is carried out in all regions in Indonesia, including remote areas. The application is built using mobile and web platforms to assist student users in submitting practical work data and coordinator users in monitoring the distribution of practical work students in several companies where practical work is located.
Analisis Sensitivitas Metode AHP Dan TOPSIS Dalam Pemilihan Objek Wisata di Kabupaten Karangasem I Gede Iwan Sudipa; I Kadek Hardiatama; Christina Purnama Yanti; I Komang Arya Ganda Wiguna
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2152

Abstract

Bali is a well-known tourist destination, but Karangasem is not widely known to the public. Tourist objects are selected as Multi-Attribute Decision Making (MADM). This study analyzes the MADM problem, namely the selection of tourist objects using the Analytical Hierarchy Process (AHP) and The Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. Method testing is done by conducting a sensitivity analysis to determine the most sensitive method in selecting tourist objects. The sensitivity analysis on 10 trials by changing the weight of the criteria by adding values ​​from 1 to 2 shows that the AHP method produces a ranking change of 440 with a percentage of 5.6%. While the TOPSIS method has a ranking change of 292 with a percentage of 3.77%. The results show that the AHP method is more sensitive to changes in weight, so relevant decision-making in selecting Karangasem Regency tourism objects can be carried out using the AHP method.
Evaluation of Lontar Prasi Bali Application based on Augmented Reality Using User Experience Questionnaire I Gede Iwan Sudipa; Putu Wirayudi Aditama; Christina Purnama Yanti
East Asian Journal of Multidisciplinary Research Vol. 1 No. 9 (2022): October 2022
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/eajmr.v1i9.1531

Abstract

The digitalization era supports the use of technology to preserve and strengthen local culture, such as using Augmented Reality (AR) to visualize Lontar Prasi figures and stories. To design and operate the Lontar Prasi Bali AR application optimally based on user demands, User Experience (UE) testing was conducted on 56 respondents with 8 questions on the application using User Experience Questionnaire (UEQ)  test shows that the average pragmatic and hedonic quality is 1.94, meaning the application is good at providing user pleasure and comfort. The Lontar Prasi Bali AR app provides above-average results (Excellent) and matches user expectations.
Detection of Student Drowsiness Using Ensemble Regression Trees in Online Learning During a COVID-19 Pandemic I Putu Agus Eka Darma Udayana; Ni Putu Eka Kherismawati; I Gede Iwan Sudipa
Telematika Vol 19, No 2 (2022): Edisi Juni 2022
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v19i2.7044

Abstract

Online lectures are mandatory to deal with the implementation of education during the COVID-19 pandemic. This significant change certainly creates a different experience for students. Regarding online learning, several public health experts and ophthalmologists say that residual radiation from electronic screens is causing an epidemic of eye fatigue. Research on smart classrooms actually appeared several years ago, but in reality it has not been implemented according to the planned concept. The current smart classroom research environment only uses outdated methods, which make the computer system incongruent (such as decision trees in video feeds) or only to the level of empirical studies or blueprints, which are not much help for other academic footing or reference materials. to students. This study aims to build an intelligent system that can evaluate students' attention during online classes, use teaching videos as learning feeds and input for predictions and also use advanced algorithms in several computational domains, namely face segmentation, landmarking, PERCLOS observations, Yawning and decision analysis using Ensemble Regression Trees to detect students' sleepiness, which is expected to patch up the shortcomings of the PERCLOS algorithm and the problems found in the single regression tree-based implementation. Based on the results of the tests that have been carried out, the system developed has been able to observe sleepy objects in learning videos with an accuracy of 80% so that later it can be a lesson for teachers why there are students who are sleepy during online classes either because of uninteresting material or other reasons.
Penilaian Aspek Keaktifan Belajar Mahasiswa Menggunakan Metode ORESTE I Gede Iwan Sudipa; Pandu Adi Cakranegara; Mustika Wati Alfia Ningtyas; Efendi Efendi; Ahmad Jurnaidi Wahidin
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 6 No. 3 (2022): Volume 6 Nomor 3 Agustus 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v6i3.11628

Abstract

Prestasi belajar merupakan tolak ukur maksimal yang telah dicapai peserta didik dalam melakukan proses belajar. Salah satu faktor yang mempengaruhi prestasi belajar adalah keaktifan belajar. Keaktifan belajar mahasiswa ditunjukkan dengan penilaian yang dilakukan dosen pada proses belajar mengajar berlangsung. Terdapat penilaian keaktifan mahasiswa yang didasarkan pada setiap kemampuan individual mahasiswa, setiap dosen pengajar memiliki kriteria masing-masing dalam menentukan nilai keaktifan setiap mahasiswa yang diajar di setiap mata kuliah. Kriteria ini sangat menentukan dalam penentuan keputusan khususnya dalam pemberian nilai keaktifan mahasiswa. Tentu bukan hal yang mudah untuk membuat suatu standar multi kriteria dalam penentuan keputusan. Pada penelitian ini mengusulkan rancangan model penentuan keputusan multi kriteria dalam penilaian keaktifan mahasiswa dengan model hirarki keputusan. Penentuan atribut penilaian pada setiap kriteria dengan skoring nilai 0-100. Metode pendukung keputusan yang digunakan yaitu metode ORESTE dengan teknik pengurutan alternatif berdasarkan kriteria sesuai dengan tingkat kepentingan setiap kriteria serta penggunaan Besson-Rank dalam membuat skala prioritas dari setiap indikator kriteria. Dari hasil perhitungan terhadap 5 alternatif mahasiswa diperoleh  nilai distance score sebesar 11,706149 untuk alternatif terbaik dengan pengurutan nilai dari nilai terkecil  ke terbesar.
Aplikasi Digital Kearifan Lokal Tarian dan Busana Tari Bali Berbasis Android Putu Wirayudi Aditama; I Dewa Gede Agung Pandawana; Rizkita Ayu Mutiarani; Dewa Ayu Novi Swijayanti; I Gede Iwan Sudipa
JUSIFO : Jurnal Sistem Informasi Vol 8 No 1 (2022): JUSIFO (Jurnal Sistem Informasi) | June 2022
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v8i1.12095

Abstract

Bali has various types of traditional dances with their distinctive functions and clothing depending on the dance's function, story, and movement. UNESCO recorded 9 Balinese dances from every district in Bali. But along with the times, one of the local wisdom in the form of Balinese dance is starting to become unattractive to the younger generation. The purpose of the research is to create a Balinese dance mobile application, so that it can preserve local wisdom of dance and dance clothing and the application can be a medium of information for the younger generation while keeping abreast of technological developments. This study uses primary and secondary data collection methods: interviews, observation, documentation, and literature study. The results of the study are in the form of an android-based application that can be downloaded for users and can be used by the younger generation to recognize and know the history of Balinese dance, classification of Balinese dance, types of dances, functions, clothing used, accompaniment instruments, and staging time for every detail of 9 types of Balinese dances and the fashion used. This application has gone through the process of testing the system's functional requirements validation with valid status.
Sentiment Analysis Using Backpropagation Method to Recognize the Public Opinion I Komang Arya Ganda Wiguna; Putu Sugiartawan; I Gede Iwan Sudipa; I Putu Yudi Pratama
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 4 (2022): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.78664

Abstract

 Improve the service quality of tourism actors by conducting sentiment analysis on digital platforms owned by tourism businesses and collecting negative sentiments to improve the quality of services from companies owned by tourism businesses. The growth of the hospitality industry in Indonesia is experiencing rapid growth every year. The tourism industry, part of the hospitality industry, also does not escape the influence of positive and negative sentiments. One method to perform accurate sentiment analysis is Backpropagation Neural Network. Based on the results of tests on the neural network, the best accuracy is obtained when using one hidden layer with the first layer of 10 neurons. The learning rate is 0.000002, where the accuracy is 71.630%. More epochs do not guarantee better accuracy. Based on the results of the research that has been done, suggestions for further researchers are to analyze the review dataset processing method so that it gets a cleaner dataset and is expected to improve better accuracy.
Sistem Pengambilan Keputusan Penentuan Jurusan Pada Jenjang Sekolah Menengah Atas Menggunakan Model Yager Made Leo Radhitya; I Gede Iwan Sudipa; I Putu Hery Setiawan; I Putu Hendika Permana; I Nyoman Tri Anindia Putra
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 2 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.5274

Abstract

Education is very important in supporting the intelligence of each individual, from an early age it starts to recognize many things in each level of education. Knowledge and abilities continue to develop until determining interest in the right major according to the values, abilities, desires and character of each individual student. In reality, the process of determining majors, especially at the high school level, is carried out in grade X, but this process can be done when students register, for example at Dharma Praja Denpasar High School. There are assessment criteria used in the process of determining students' major interests, namely the Average Report Card Score (C1), Science Test Score (C2), Social Science Test Score (C3) and Psychological Test Score. Applying the Yager model so that the process of determining the weight of the criteria can be done with the concept of a pairwise comparison matrix, another advantage is the process of calculating the intersection of alternative values on each alternative so that it can produce suggestions for majoring interests. The study used 5 alternative students with suggestions for majoring in science and social studies. The results showed that the Yager model could provide recommendations for the best majoring options for 5 alternatives, namely alternative A1 for science majors with a value of 2.19067, while alternatives A2, A3, A4 and A5 obtained recommendations for social studies majors. Features of the web-based major determination decision support system produce the ability to manage alternative data, criteria, alternative values, majoring processes, final results and there are test features that students can do on the system, making it easier for students to make majors and schools to recapitulate the process of determining majors. The results of blackbox testing for a total of 8 scenarios show that the system functionality is running well.
Implementation of Artificial Neural Network on Sales Forecasting Application Ketut Jaya Atmaja; Ida Bagus Nyoman Pascima; I Made Dwi Putra Asana; I Gede Iwan Sudipa
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 4 (2022): Desember: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

Sales forecasting is an effort to fulfill customer demands. The existence of a sales forecast, can help trade business owners in carrying out stock management to deal with customer demands in the future. Data owned in the past is used in predicting and estimating a condition in the future. Quantitative data used as a reference in the forecasting process can be time series data based on a certain period containing the number of sales. Artificial Neural Networks (ANN) are one of the human efforts to model the way the human nervous system functions in carrying out certain tasks. This modeling is based on the ability of the human brain to organize brain cells called neurons. Neurons are information processing units that are the basis of artificial neural network operations. ANN can be used to solve forecasting problems based on continuous data such as time series data from a sale based on a certain period. The research stages that will be carried out consist of analyzing needs, training the model, testing the model, forecasting sales.
Co-Authors A.A. Tri Wulandari Mayun Achmad Selamat Fauzi Aditama Kadek Aditama, Dewa Made Marta Agus Perdana Windarto Ahmad Jurnaidi Wahidin Alfiah, Agry Ali Zainal Abidin Alaydrus Ali, Raihan Andika, I Gede Ani Nida’ia Mustafida Aniek Suryanti Kusuma, Aniek Suryanti Apriana, Ketut Adhi Arianto Muditomo Aripurnama, I Kadek Ade Aristana, Made Dona Wahyu Arslayandi, Fiqhan Artha, I Putu Mahesa Kama Aryati, Komang Sri Asana, I Made Dwi Putra Asana, Made Dwi Putra Atmaja, I Gede Bagastia Widi Atmaja, Ketut Jaya B. Herawan Hayadi Bagus Kusuma Wijaya Bagus Kusuma Wijaya Cakranegara, Pandu Adi Cakranegara, Pandu Adi Cetiawan, Arie Christina Purnama Yanti Christina Purnama Yanti Christina Purnama Yanti Christina Purnama Yanti Christina Purnama Yanti Darma Setiawan Putra Darmika, Kadek Jaya Deddy Kurniawan Desak Made Dwi Utami Putra Desak Putu Diah Kumala Dewi Devi Valentino Waas Devi Valentino Waas Devi Valentino Waas Devi Valentino Waas Dewa Ayu Novi Swijayanti Dewa Gede Agung Gana Kumara Dewantara, Rizki Dewi, Ni Kadek Feby Puspita Dewi, Ni Luh Putu Berliana Dirgayusari, Ayu Manik Dwi Putra Asana Dwijaputra, I Kadek Dwiki Setiawan Efendi Efendi Eka Ayu Purnama Lestari Emy Yunita Rahma Pratiwi Erlina Putri, Ni Putu Mita Fajar Muharam Fajriana, Fajriana Gede Surya Mahendra Gunawan, I Komang Agus Bryan Gustiadi Gustiadi Hamid Wijaya Handika, I Putu Susila Hardiatama, Kadek Harjanti, Trinugi Wira Herry Rachmat Widjaja Hidayatulloh, Fachmi Hugo, Veronika Novia I Dewa Gede Agung Pandawana I Gede Sudiantara I Gede Totok Suryawan I Gede Totok Suryawan I Gusti Agus Adek Putra Ardiwinata I Gusti Made Ngurah Desnanjaya I Kadek Adiana Putra I Kadek Dwi Gandika Supartha I Kadek Hardiatama I Kadek Surya Arimbawa I Komang Arya Ganda Wiguna I Komang Arya Ganda Wiguna I Komang Arya Ganda Wiguna I Komang Arya Ganda Wiguna I Komang Wiratama I Komang Wiratama I Komang Wiratama I Made Angga Wijaya I Made Dwi Putra Asana I Made Dwi Putra Asana I Made Muryasa I Made Oka Widyantara I Made Subrata Sandhiyasa I Nyoman Alit Arsana I Nyoman Alit Arsana I Nyoman Alit Arsana I Nyoman Jayanegara I Nyoman Tri Anindia Putra I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Candra Jumariana I Putu Eka Giri Gunawan I Putu H Permana I Putu Hendika Permana I Putu Hendika Permana I Putu Hery Setiawan I Putu Yudi Pratama I Wayan Dani Pranata I Wayan Dharma Suryawan I WAYAN SUDIARSA I Wayan Sudiarsa Ida Bagus Ary Indra Iswara Ida Bagus Gede Sarasvananda Ida Bagus Gede Sarasvananda Ida Bagus Nyoman Pascima Ika Arfiani Indra Pratistha Iwan Adicandra J.A, Qurrotul Ainia Jatila , I Gede Mahesa Putra Jaya, I Made Krisna Jayadi, I Dewa Gede Wahyu Jimmy H Moedjahedy Jullev Atmadji, Ery Setiyawan Kadek Ari Prayoga Putra Kencana Putri, Ida Ayu Putu Calista Ketut Jaya Atmaja Ketut Ngurah Semadi Ketut Sepdyana Kartini Khoirun Nisa Komang Kurniawan Widiartha Krinayanti, Ni Putu Kusuma Dewi, Ni Wayan Jeri Kusuma, Kadek Ngurah Adi Laksono Trisnantoro Lalu Puji Indra Kharisma Legito . Libraeni, Luh Gede Bevi Made D W Aristana Made Dona Wahyu Aristana Made Dona Wahyu Arsitana Made Leo Radhitya Made Suci Ariantini Mahardika , Dewa Gede Candra Maharianingsih, Ni Made Maulidah, Salsa Bila Jihan Meinarni, Ni Putu Suci Meliana, Putu Mita Melyawati, Ni Luh Putu Mesran, Mesran Moh. Erkamim Muammar Khaddafi Muh. Fahrurrozi Muhammad Habibi Muni, Gede Dharma Sahasra Murti , Ayu Jihwani Mustika Wati Alfia Ningtyas Ni Komang Dani Juniantari Ni Luh Putu Ayu Cintia Utami Ni Luh Wiwik Sri Rahayu Ginantra Ni Made Chintya Sasri Ni Made Dwi Puspitawati Ni Made Maharianingsih Ni Made Sri Dadi Sukerthi Ni Putu Eka Kherismawati Ni Putu Eka Kherismawati Ni Putu Widantari Suandana Ni Putu Yuniawati Yunia Ni Wayan Suardiati Putri Nicodemus Mardanus Setiohardjo Nofirman, N Noris, I Kadek Novaria, Rachmawati Pande Putu Sukma Awantari Pande, Ni Kadek Nita Noviani Partama, I GD. Yudha Perani Rosyani Pramawati, I.D.A Tantri Pramita, Dewa Ayu Kadek Pranata, I Wayan Dani Priadinata, I Putu Bramasta Puspitayani, Ida Ayu Dwi Putra, I Kadek Nurcahyo Putra, Putu Agus Febri Sedana Putra, Putu Satria Udyana Putri, Rozza Maudina Ayuwan Putu Hendra Premana Putu Praba Santika Putu Praba Santika Putu Praba Santika PUTU SUGIARTAWAN Putu Sugiartawan Putu Sugiartawan Putu Wirayudi Aditama Putu Wirayudi Aditama Putu Wirayudi Aditama Putu Wirayudi Aditama Rachmat Radhitya, I Made Leo Radhitya, Made Leo Revan Dwi Hanza Rezania Agramanisti Azdy, Rezania Agramanisti Rhaishudin Jafar Rumandan Riana, Roni Rikcy Sanusi Rini Komalasari risaldi, risaldi Riska Aryanti Rizkita Ayu Mutiarani Robbi Rahim Sandhiyasa, I Made Subrata Sandika, I Kadek Budi Sanusi, Rikcy Savitri, Ni Kadek Wiliya Sekarsari, Yulia Ayu Semadi, Ketut Ngurah Sepriano Sepriano Septiawan, I Kadek Jerry Sri Aryati, Komang Sudiani, Ni Made Sugiarta, Putu Agus Arya Sastra Sugihya Artha Dwipayani Sumiyatun Sunarya, I Wayan Susatyo Adhi Pramono, Susatyo Adhi Tika, I Gede Bagus Arya Merta Tukino, Tukino Tuti Marjan Fuadi Wahyudi, I Putu Alfin Teguh Wayan Gede Suka Parwita Welda Widiantara, I Komang Widiantari, Ni Komang Mira Widiari, Ni Putu Diva Septa Widiartha, Komang Kurniawan Widyatama, I Dewa Gede Surya Wiguna, I Komang Arya Ganda Wijaya, Bagus Kusuma Winatha, Komang Redy Wulandari, Dewa Ayu Putri Yarimani Laia Yohana Jun Yuri Prima Fittryani, Yuri Prima