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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Reviu Akuntansi dan Keuangan Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmu Komputer Jurnal SPEKTRUM Majalah Ilmiah Teknologi Elektro Ecotrophic, Journal of Environmental Science 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 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 International Journal of Engineering and Emerging Technology Jurnal Manajemen Indonesian Journal of Electrical Engineering and Computer Science Reviu Akuntansi, Keuangan, dan Sistem Informasi Majalah Ilmiah Teknologi Elektro KREATIF: Jurnal Pengabdian Masyarakat Nusantara Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Made Sudarma
Udayana University
Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Mechanical Engineering Social Sciences

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Clustering History Data Penjualan Menggunakan Algoritma K-Means Yogiswara Dharma Putra; Made Sudarma; Ida Bagus Alit Swamardika
Jurnal Teknologi Elektro Vol 20 No 2 (2021): (Juli-Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2021.v20i02.P03

Abstract

The company has a desire to develop an increase in its business so that it is not eroded by the very tight business competition. PT. Baliyoni Saguna is a company engaged in information technology and telecommunications which currently helps its customers to provide the best solutions according to customer needs. Product quality is a major factor in keeping customers alive and satisfied with the products provided by PT. Baliyoni Saguna. These products need to be reviewed in order to have a reference in creating the best products. Clustering is a method that can be used to see the level of sales that have been made based on the formed clusters. The K-Means algorithm is a method capable of processing sales history data owned by PT. Baliyoni Saguna in forming groups according to the item category of the item. The K-Means algorithm is able to provide convenience in processing large data so that it can be processed more quickly and efficiently. The results of the application of the K-Means algorithm formed 3 clusters representing the most desirable, least desirable, and least desirable categories. In the most desirable category there are 5 total items, 4 in the interested category there are 4 total items, and 14 items less desirable. These results are expected to help in creating quality goods so as to maintain product quality and customer satisfaction. Keywords – Clustering, K-Means Algorithm, PT. Baliyoni Saguna
Implementasi Algoritma C5.0 pada Penilaian Kinerja Pegawai Negeri Sipil Putu Wirya Kastawan; Dewa Made Wiharta; Made Sudarma
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2018.v17i03.P11

Abstract

Employees become the spearhead of every Company, whether it is run the business on manufacture or service. The position and role of public government employees as an element of civil servant obligate them to provide fair public services. Refers to those facts, the performance of public government employees needs to be well managed. The algorithm C5.0 is one of the decision tree algorithm which can process the employees performance data become an input for decision-making. Based on evaluation result of 184 employees performance datas, there was a high accurracy data in level 96.08%. Due to that result, the algorithm system can be developed become e-performance system which can predict or giving an advice in order to decision-making processes whether for assigning promotion, ranking or giving performance allowances.
Sistem Monitoring Kehadiran Perkuliahan Menggunakan Face Detection Dengan Algoritma Viola Jones Zul Fachmi; Made Sudarma; Lie Jasa
Jurnal Teknologi Elektro Vol 18 No 1 (2019): (Januari - April) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2019.v18i01.P18

Abstract

Presence of lectures is an important factors to take the final exam. It is necessary to have a presence system with computer vision technology that is capable to handling problems manually. Computer vision technology used is face detection and recognition in order to monitor attendance data system. The face detection process in this study uses the Viola-Jones algorithm, and this algorithm has four stages, namely Haar Like Feature, Integral Image, Adaboost learning and Cascade classifier. The results of this study Viola-Jones algorithm successfully applied to the face detection process and in the face recognition process using the KNN (K-Nearest Neighbor) method with an accuracy rate of 94.79%.
Analisis Perilaku Mean Dataset Perubahan Garis Pantai pada Hasil Spasialtemporal Metode Empirical Orthogonal Function (EOF) Ida Ayu Putu Febri - Imawati; Made Sudarma; I Nyoman Satya Kumara
Jurnal Teknologi Elektro Vol 16 No 1 (2017): (January - April) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

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Abstract

The purpose of this study is to apply EOF method on shoreline change resulting spatialtemporal analysis mode 1 and also to to prove the mean behavior on the spatial or temporal of its EOF outcomes. The data used was obtained from shoreline coordinates of shp file of the Bali island map and the result of breaking waves study, by using a one-dimensional modeling  yielded dataset or prediction shoreline changes during 91 months. Calculation EOF 1, the input matrix or dataset was initially not reduced by the mean but EOF 2 vice versa. Each matrix receive the same treatment were calculated covariance, eigen value, eigen vector and principal component. EOF calculations obtained the last five eigen value, the last five eigen vector, trace, principal component and variant data. Based on the results obtained were compared parameters of two matrices mentioned before. Spatially results both of  EOF 1 and EOF 2 shows the same eigen vector represented by the first mode of eigen vector. Similarly, the eigen value, trace and variance of data, produce the same information. Significant difference occurs in the principal component (temporal). EOF 1 shows that the value of the first month produces a positive value, second month until month 91th output are minus.  EOF 2 shows the value of the principal component the first month until the 37th month are in a positive position, then from month 38th to month 91th yielded negative results. Nevertheless EOF 1 and EOF 2 showed shoreline changes tend to be erosion.Tujuan dari penelitian ini adalah menerapkan metode EOF pada perubahan garis pantai sehingga menghasilkan analisis spasialtemporal mode ke-1 dan juga untuk membuktikan perilaku mean pada hasil spasial atau temporal hasil EOF tersebut. Data yang digunakan diperoleh dari koordinat garis pantai file shp dari peta pulau Bali dan hasil studi gelombang pecah, dengan menggunakan pemodelan satu dimensi menghasilkan dataset atau prediksi perubahan garis pantai selama 91 bulan. Perhitungan EOF 1, matriks input atau dataset awalnya tidak dikurangi dengan rata-rata tetapi EOF 2 sebaliknya. Setiap matriks menerima perlakuan yang sama dihitung covariance, eigen value, eigen vektor dan principal component. Dari perhitungan EOF diperoleh eigen value lima terakhir, eigen vcktor lima terakhir, trace, principal component dan variance data. Berdasarkan hasil yang diperoleh dibandingkan parameter dua matriks sebelumnya.Secara spasial hasil EOF 1 ataupun EOF 2 menunjukkan nilai eigen vector yang sama yang diwakili oleh eigen vector mode pertama. Demikian pula pada  eigen value, trace dan varian data,  EOF 1 dan EOF 2 menghasilkan informasi yang sama. Perbedaan yang siginifikan terjadi pada principal component (temporal). Dari EOF 1 didapatkan bahwa nilai temporal bulan ke-1 menghasilkan nilai positif, bulan ke-2 hingga bulan ke-91 output bernilai minus. Pada EOF 2 nilai principal component ke-1 hingga bulan ke-37 berada pada posisi positif, selanjutnya dari bulan ke-38 hingga bulan ke-91 menghasilkan nilai negatif.  Meskipun demikian  EOF 1 dan EOF 2 tetap menunjukkan garis pantai yang cenderung mengalami  erosi.DOI: 10.24843/MITE.1601.16 
Genetic K-Means Algorithms, ASSU Analisis Peningkatan Kompetensi Mahasiswa Menggunakan Model Pembelajaran ASSURE berbasis Project-Based Learning Asri Prameshwari; Rukmi Sari Hartati; Made Sudarma
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2018.v17i03.P16

Abstract

Sistem pembelajaran yang telah diterapkan dan dikembangkan bertujuan untuk meningkatkan, menguasai, memahami, dan menerapkan materi belajar untuk kemudian dijadikan suatu kompetensi dasar. Penelitian ini menganalisa hasil peningkatan kompetensi mahasiswa dalam mata kuliah teknologi informasi di STIKes Wira Medika Bali pada jenjang S1 Keperawatan dengan menggunakan sistem pembelajaran ASSURE berbasis Project-Based Learning. Metode yang digunakan dalam pengelompokkan hasil peningkatan tersebut menggunakan Genetic K-Means Algorithms, Metode ini dipilih karena mempunyai kinerja lebih optimal dari K-Means sederhana. Algoritma ini yang menggunakan natural selections untuk opitimalisasi menentukan initial seeds. Penentuan jumlah cluster yang digunakan dalam penelitian ini sebanyak tiga cluster dengan kategori tinggi, sedang dan rendah. Hasil dari penelitian ini untuk kategori sedang meningkat dengan range 3,92% dan 14%, untuk kategori rendah meningkat 31,37% dan 74%, untuk kategori tinggi menurun 35,29% dan 60%.
Analisis Deteksi Kemiripan Dokumen Tugas Mahasiswa pada LMS Undiknas Menggunakan Metode K-Shingling dan Cosine Similarity Komang Nova Artawan; Made Sudarma; Nyoman Gunantara
Jurnal Teknologi Elektro Vol 23 No 1 (2024): (Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2024.v23i01.P08

Abstract

Aplikasi LMS (Learning Management System) pada salah satu perguruan tinggi swasta di Bali yaitu Universitas Pendidikan Nasional (Undiknas) mulai dikembangan sejak adanya kewajiban untuk melakukan pembelajaran secara daring saat pandemi COVID melanda, dan hingga saat ini penggunaan LMS Undiknas digunakan untuk menunjang implementasi dari proses pembelajaran jarak jauh agar dapat dilakukan secara digital. Salah satu hal yang perlu diperhatikan dari metode pembelajaran jarak jauh tersebut adalah terkait bagaimana memastikan bahwa mahasiswa telah paham dengan materi pembelajaran yang diberikan secara daring. Hal tersebut dapat dilakukan dengan memberikan tugas yang harus dikerjakan oleh mahasiswa. Namun, pemberian tugas melalui LMS juga dapat menjadi celah untuk mahasiswa melakukan kecurangan dengan kerap ditemukannya bahwa antar mahasiswa melakukan duplikasi jawaban tugas dari mahasiswa yang lain. Sehingga, dalam penelitian ini dilakukan upaya untuk mengatasi permasalahan tersebut dengan melakukan analisis fitur deteksi kemiripan dokumen tugas mahasiswa pada LMS Undiknas dengan metode K-Shingling dan Cosine Similarity agar dapat digunakan oleh dosen untuk mendeteksi persentase kemiripan dari dokumen pengumpulan tugas tiap mahasiswa. Berdasarkan tahap training dan tahap testing yang telah dilakukan, didapatkan kesimpulan bahwa pada rasio partisi data 70% (training) dan 30% (testing), deteksi kemiripan dokumen tugas mahasiswa dengan menggunakan preprocessing teks dan nilai parameter K = 9 pada metode KShingling diperoleh nilai akurasi sebesar 73,55% pada tahap testing yang menunjukkan performa dan tingkat keberhasilan sistem dalam melakukan deteksi kemiripan dokumen jawaban tugas mahasiswa, dan nilai akurasi pada tahap testing ini lebih tinggi 8.24% dibandingkan nilai akurasi pada tahap training. Kata Kunci— LMS Undiknas, Kemiripan Dokumen Tugas, KShingling, Cosine Similarity.
Evaluasi Pengembangan Disaster Recovery Center untuk Data Center Universitas Udayana Kheri Arionadi Shobirin; Nyoman Putra Sastra; Made Sudarma
Jurnal Teknologi Elektro Vol 20 No 1 (2021): (Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2021.v20i01.P20

Abstract

Data Center has a vital and strategic role in supporting university operations. Based on Government Regulation No.17 of 2019 article 20 section 1: Every Data Center owner must have a Disaster Recovery Center. Evaluation of Disaster Recovery Center Development for Udayana University Data Center conducted by considering aspects of natural threats, human threats, environmental threats, existing Data Center specification, virtualization, and cloud technology used to maintain the availability of Data Center services for Udayana University with the most efficient development costs. Using cost comparation for DRC development and operation for 3 years, found that implementation cost of Cloud DRC 3 times higher compare to Conventional DRC. High cloud computing cost contribute 67% of Cloud DRC cost structure.
Penentuan Target Pajak Kendaraan Bermotor Di Provinsi Bali Menggunakan ARIMA Dan Algoritma Genetik I Gusti Ngurah Rai Dharma Widhura; Made Sudarma; Ruksi Sari Hartati
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2018.v17i03.P07

Abstract

Bali Regional Income Board is a regional organization tasked with determining the amount of local tax revenue target for the next fiscal year. Currently still done manually in accordance with existing upgrading trends from previous years. So it needs to be done in way that can be measured and accurate forecasting. In recent studies, it shows that forecasting by combining conventional and artificial intelligence (hybrid) methods results in better forecasting accuracy. By that reason, the writer tries to forecast the target of revenue from Motor Vehicle Tax (PKB and BBNKB), which contribute 70% to Bali Province income by combining ARIMA method and Genetic Algorithm. The data used consisted of five groups: yearly and new Vehicles that have linear data types, and as Reverse Names, Entrance Mutations and Output Mutations that have non-linear data types. Each data group consisted of PKB and BBNKB, where it’s monthly realization data from 2011 to 2016 used to be training data and realization data for 2017 as test data. The Combined forecasting mechanism is performed using ARIMA to forecast linear data and using Genetic Algorithms for non-linear data. As a benchmark for combined forecasting using ARIMA and Genetic Algorithms, forecasting using ARIMA and Genetic Algorithms independently is used for all data types (linear and nonlinear). Testing is done by comparing data of forecasting result with that 3 different methods for year 2017 with data realization year 2017. Then the error percentage is counted using MAPE. From the test results obtained for ARIMA MAPE value of 3.63, Genetic Algorithm 4.72 and combined ARIMA and Genetic Algorithm of 1.13. Thus, the result of forecasting with combination ARIMA and Genetic Algorithm have the best result and then used to forecasting target of PKB for 2018 and so on
PENGEMBANGAN APLIKASI LAYANAN INFORMASI KAMPUS PADA JURUSAN TEKNIK ELEKTRO UNIVERSITAS UDAYANA BERBASIS MOBILE DAN WEB SERVICE Komang Isabella Anasthasia; Made Sudarma; I Made Arsa Suyadnya
Jurnal Teknologi Elektro Vol 13 No 2 (2014): (July - December) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

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

Abstract

Selama ini, Jurusan Teknik Elektro Universitas Udayana telah memanfaatkan tiga media sebagai pertukaraninformasi, yaitu: halaman website, papan pengumuman, dan TV Jurusan. Namun, penyebaran informasi kemahasiswa terkadang datang dari mulut ke mulut sehingga informasi yang disampaikan menjadi kurang berkualitas.Penelitian ini akan merancang aplikasi layanan informasi kampus berbasis mobile dengan menggunakan fitur SMSdan aplikasi Android. Informasi yang diterima akan saling terintegrasi dan ditampilkan pada TV jurusan. Hasil akhirdari penelitian membuktikan bahwa web service JSON merupakan solusi dalam pengintegrasian informasi.Perangkat mobile yang dilengkapi dengan notifikasi membuat informasi tersebut dapat dikirim dan diterima kapanpun dan di mana pun. Informasi yang diterima juga lebih berkualitas apabila dilihat dari sisi ketersediaan,keakuratan sumber, dan ketepatan waktu.
Literature Review Penerapan Teknologi Informasi dan Metode Pengukuran Pada Audit Kepuasan Pelanggan Charolina Devi Oktaviana Soleman; Made Sudarma; Nyoman Pramaita
Jurnal Teknologi Elektro Vol 20 No 2 (2021): (Juli-Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2021.v20i02.P13

Abstract

Customer loyalty is very important in the sustainability of a business, to maintain customer loyalty, companies are required to understand the level of customer satisfaction and complaints that arise in the service delivery process, manual questionnaires will prevent companies from obtaining customer satisfaction measurement results quickly and accurately. , the faster development of information technology is expected to be able to assist companies in the customer satisfaction audit process, both from the process of distributing questionnaires and processing customer satisfaction measurement data, the results of the literature study show that the application of information technology combined with methods in customer satisfaction audits can help companies in obtaining information related to the results of measuring customer satisfaction quickly and with ease of access, so that stakeholders in the company can take corrective actions to resolve complaints. customer satisfaction and increased performance improvement according to the level of customer satisfaction, from the research results obtained 95% of website-based technology is still widely used in the customer satisfaction audit process and 34% of the CSI method is the method most often applied for measuring customer satisfaction.
Co-Authors A. A. K. Oka Sudana A.A Ngurah Narendra A.A Raka Novi Aristi Adi Darmawan Ervanto Adinata Mas Pratama Aggry Saputra Aggry Saputra 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 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 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 Arya Wiratama I Kadek Dwi Gandika Supartha I Kadek Sastrawan I Kadek Yuda Setiadi I ketut Gede Darma Putra I Komang Yogi Sutrisna I Made Adi Bhaskara I Made Arsa Suyadnya I Made Artawan I Made Budi Sentana 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 Gunantara 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 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 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 Gede Manuaba Ida Bagus Gede Widnyana Putra 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 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 R. Sapto Hendri Boedi Soesatyo Reni Surmayanti Ricky Aurelius Nutanto Diaz, Ricky Aurelius Rifky Lana Rahardian Risky Aswi R, Risky Rizky Muharram Julyanto Roekhudin, Roekhudin Rukmi Sari Hartati Rukmi Sari Hartati 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