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All Journal TEKNIK INFORMATIKA JURNAL SISTEM INFORMASI BISNIS Voteteknika (Vocational Teknik Elektronika dan Informatika) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Riau Journal of Computer Science JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Penelitian Pendidikan IPA (JPPIPA) Indonesian Journal of Artificial Intelligence and Data Mining Rang Teknik Journal ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Information Technology and Computer Engineering Jambura Journal of Informatics ComTech: Computer, Mathematics and Engineering Applications Jusikom: Jurnal Sistem Informasi Ilmu Komputer bit-Tech Systematics Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Informatika Ekonomi Bisnis Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Ilmiah Manajemen Kesatuan Dinasti International Journal of Digital Business Management JUKI : Jurnal Komputer dan Informatika Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Journal of Applied Computer Science and Technology (JACOST) Journal of Computer Scine and Information Technology Bulletin of Computer Science Research Jurnal Penelitian Inovatif Jurnal Ipteks Terapan : research of applied science and education Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Sistim Informasi dan Teknologi Jurnal Administrasi Sosial dan Humaniora (JASIORA) Innovative: Journal Of Social Science Research e-Jurnal Apresiasi Ekonomi Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JR : Jurnal Responsive Teknik Informatika Jurnal Responsive Teknik Informatika

Sarjon Defit

Universitas Putra Indonesia YPTK Padang

Author-ID : 2476220

Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Sistem Pakar Menggunakan Metode Forward Chaining Untuk Mendeteksi Kerusakan Jaringan Internet (Studi Kasus : Di Layanan Internet Diskominfotik Sumatera Barat) Zaki, Ahmad; Defit, Sarjon; Sumijan, Sumijan; Fauzana, Rahmi
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9 No 3 (2023): Desember 2023
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i3.2023.227-236

Sistem informasi yang interaktif dapat membantu kinerja pegawai dalam mendukung program SPBE (Sistem Pemerintah Berbasis Elektronik. Dinas Kominfotik Sumatera Barat berperan penting dalam memberikan layanan internet kepada OPD-OPD di bawah lingkup Pemerintahan Provinsi Sumatera Barat. Pembangunan sistem jaringan internet yang sudah baik tidak dapat dijamin bahwa jaringan tersebut terbebas dari gangguan dan kerusakan. Gangguan terhadap akses internet akan berdampak terhadap produktifitas bekerja pegawai dan pelayanan kepada masyarakat. Kurangnya pemahaman PIC OPD dan pengguna dalam menangani permasalahan gangguan jaringan internet, maka dibutuhkan keahlian pakar dalam melakukan identifikasi kerusakan pada jaringan internet berdasarkan gejala-gejala yang terjadi, serta diberikan solusi perbaikan pada gangguan yang ada. Pengumpulan data dilakukan melalui wawancara dan observasi lapangan. Metode yang digunakan untuk pengolahan data pada Sistem Pakar ini yaitu metode forward chaining. Forward Chaining adalah sebuah strategi pencarian dalam system pakar yang dimulai dari sekumpulan data atau fakta, dari data-data tersebut, system akan mencari suatu kesimpulan yang menjadi solusi dari permasalahan yang dihadapi. Berdasarkan hasil pengujian Sistem Pakar menggunakan metode forward chaining untuk mendeteksi gangguan jaringan internet menghasilkan tingkat akurasi sebesar 100 % menggunakan 29 data uji. Berdasarkan hasil yang didapatkan dari Sistem Pakar dengan metode forward chaining, system tersebut dapat digunakan untuk mendeteksi kerusakan jaringan internet di Layanan Internet Diskominfotik Sumatera Barat.

Hybrid Data Mining with the Combination of K-Means Algorithm and C4.5 to Predict Student Achievement Ramadhanu, Agung; Defit, Sarjon; Kareem, Shahab Wahhab
International Journal of Artificial Intelligence Research Vol 5, No 2 (2021): December 2021
Publisher : Universitas Dharma Wacana

Getting academic achievement is the dream of every student who studies at higher education, especially undergraduate level. Undergraduate students aspire to the highest achievement (champion) at the last achievement of their studies. However, students cannot predict whether these students with the habits that have been done and the current conditions will make them excel or not. Apart from that, of course, students also want to know what factors and conditions influence the achievement the most. The objective to be achieved in this research is how to predict which number of students among them are predicted to excel (champion) at the end of the semester with a combination of the K-Means and C4.5 methods. Besides, the purpose of this study reveals how the K-Means algorithm performs data clustering of student data who will excel or not and how the C4.5 algorithm predicts students who have been grouped. Data processing in this study uses the Rapid Miner software version 9.7.002. The result of this research is that it is easier to group data in numerical form than data in polynomial form. Other results in this study were that out of 100 students, 27 students (27%) were predicted to excel (champions) and 73 (73%) did not achieve (not champions).

Factors Influencing Customer Satisfaction and Their Impact on Customer Loyalty Septiano, Renil; Defit, Sarjon; Yulasmi, Yulasmi; Limakrisna, Nandan; Lusiana, Lusiana
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1351

Workshop customers, known as unit entry by the automotive world, are one of the sources of revenue for automotive companies. Workshop unit entry is related to customer loyalty. The study aims to determine the relationship between perceived price on customer loyalty through customer satisfaction in auto repair shops customers. A quantitative approach is used as a research approach. Data were collected by questionnaire. The collected data were analyzed to determine the effect between variables, and the analysis technique was Partial Least Square (PLS). The research was conducted at Auto2000 West Sumatra. The research subjects are Auto2000 consumers who use workshop services. The object of research is a review of the influence of perceived price on customer loyalty with customer satisfaction as mediation. The sampling technique is purposive sampling. The results showed that Customer satisfaction can mediate the effect of perceived price on customer loyalty of consumers who use Auto2000 workshop services.

K-Means and K-NN Methods For Determining Student Interest Guslendra, Guslendra; Defit, Sarjon; Bastola, Ramesh
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Putra Indonesia University 'YPTK' Padang's Department of Information Systems, Faculty of Computing Science has three specializations, namely Information Technology Management, Business Information Systems, and Industrial Information Systems. In the fifth semester, the acquisition of specializations takes place. In the next semester, the selection of specialist programs will be determined. The option of the degree is adapted to students' needs and capacities. The acquisition of results generated in the previous semester can be seen. The objective of this survey is to provide students with suggestions for the collection of degrees. The study was performed using K-Means and K-Nearest Neighbor methods to obtain the classification of students and the correlation between recent cases and past cases. This analysis uses 13 characteristics, of which 12 are predictors and 1 is the option. The test results can be used as a way to suggest the student preferences based on preset attributes through the K-Means and K-NN methods.

Determination Potential Experts by Application The Apriori Algorithm and the K-Means Algorithm Sovia, Rini; Defit, Sarjon; Fatimah, Noor
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Experts are people who have special expertise who provide services based on their expertise.Â The company has experts in handling projects that will be carried out for the progress of the company.Â The importance of the quality of experts in the company can improve the quality of human resources.Â The Apriori algorithm is a data mining method that has the aim of looking for association patterns based on the project being carried out so that they can be identified by experts who are often used in handling projects.Â Furthermore, a data mining approach is needed to classify experts with the K-means algorithm used.Â This study combines theÂ AprioriÂ and K-means algorithms, by grouping experts based on the handling of the project they are working on.

Determination of Student Subjects in Higher Education Using Hybrid Data Mining Method with the K-Means Algorithm and FP Growth Rani, Larissa Navia; Defit, Sarjon; Muhammad, L. J.
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : Universitas Dharma Wacana

The large number of courses offered in an educational institution raises new problems related to the selection of specialization courses. Students experience difficulties and confusion in determining the course to be taken when compiling the study plan card. The purpose of this study was to cluster student value data. Then the values that have been grouped are seen in the pattern (pattern) of the appearance of the data based on the values they got previously so that students can later use the results of the patterning as a guideline for taking what skill courses in the next semester. The method used in this research is the K-Means and FP-Growth methods. The results of this rule can provide input to students or academic supervisors when compiling student study plan cards. Lecturers and students can analyze the right specialization subject by following the pattern given. This study produces a pattern that shows that the specialization course with the theme of business information systems is more followed by students than the other 2 themes

Indeks Kesiapan Perguruan Tinggi dalam Mengimplementasikan Smart Campus Zakir, Supratman; Defit, Sarjon; Vitriani, Vitriani
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 3: Juni 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Keberhasilan perguruan tinggi memanfaatkan Teknologi Informasi dan Komunikasi (TIK) atau sering dikenal dengan istilah smart campus sebagai upaya kompetitif dan bernilai saing pada hakekatnya terletak pada sejumlah indicator seperti technoware, infoware, orgaware dan humanware. Upaya pencapaaian tujuan penggunaan smart campus tersebut dibutuhkan skema perencanaan yang matang dan need analysis yang menyeluruh. Banyak perguruan tinggi yang gagal mengimplementasikn smart campus disebabkan beberapa hal, seperti perencanaan yang tidak baik, tenaga ahli yang tidak siap, sarana prasarana yang kurang memadai, biaya awal pengembangan yang tidak tersedia dan kebijakan yang tidak konsisten. Penelitian ini bertujuan untuk melihat kesiapan perguruan tinggi dalam mengimplemetasikan smart campus. Penelitian ini menggunakan jenis penelitian deskriptif kuantitatif. Hasil penelitian memperlihatkan bahwa pengembangan cyber campus pada komponen ICT Use yang mencakup dimensi kebutuhan dan keselarasan serta dimensi proses dan tata kelola baru memasuki tahap kurang siap. Komponen ICT Readiness yang mencakup dimensi sumber daya teknologi pada kategori hampir berhasil. Komponen ICT Capability yang mencakup dimensi komunitas memasuki kategori belum berhasil. Komponen ICT impact sudah memasuki kategori hampir berhasil. Secara keseluruhan komponen pengembangan cyber campus dikategorikan hampir berhasilAbstractThe triumph of higher education in utilizing ICT or commonly termed as smart campus as a competitive strategy depends on some indicator like technoware, infoware, orgaware and human ware. To achieve such goal is not an easy task, it needs to have a good planning and a holistic needs analysis. Many educational institutions fail to implement smart campus due to some factors for instance bad planning, unready human resources, unsporting infrastructure, lack of fund and inconsistent policy. The research aims at revealing readiness index of higher education in utilizing ICT. The research uses descriptive quantitative approach research that describes an object as it is with research stages including presurvey, leterature studies, questionnaires, data analysis and empirical findings. Data were obtained by using a research questionnaire. The finding reveals that developing cyber campus in the component ICT Use which covers need, harmony, and process dimensions and governance is categorized less-ready. Component of ICT Readiness which covers dimension of technology resources is categorized as successful, meanwhile component of ICT capability of community dimension is not successful yet. Component of ICT impact comes to category near to successful. As a whole, the components of developing cyber campus are in the success category.

Analisis Sentimen Publik Terhadap Program Penurunan Angka Prevalensi Stunting Indonesia Menggunakan Data Twitter Dengan Metode Naïve Bayes Putri, Yozi Aulia; Defit, Sarjon; Nurcahyo, Gunadi Widi
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.15180

Abstrak Penelitian ini bertujuan untuk menganalisis sentimen publik terhadap program penurunan angka prevalensi stunting dengan menggunakan data Twitter sebagai sumber informasi. Stunting adalah masalah kesehatan masyarakat yang serius di banyak negara, termasuk Indonesia. Pemerintah Indonesia telah meluncurkan berbagai program untuk mengatasi masalah ini. Penelitian ini menggunakan metode analisis sentimen Naive Bayes untuk memahami persepsi dan pendapat publik terhadap upaya-upaya tersebut. Data Twitter yang dikumpulkan meliputi twit yang berkaitan dengan “stunting dan program pengentasannya”. Dari Hasil Crawling data Twitter didapat data twit sebanyak 2.543, yang kemudian masuk pada proses cleaning data, sehingga didapat sebanyak 2.307 dataset. Penerapan Metode Naïve Bayes berhasil memprediksi sentimen masyarakat dengan membagi kelas positif, netral, dan negatif, Hingga dinilai mampu menggali knowledge bahwa dari jumlah data data 2.307 data twit yang ada diketahui ada sebanyak 975 twit atau 42% yang memberikan sentimen positif, sebanyak 741 twit atau 32% yang bernilai sentimen netral, dan sebanyak 591 twit atau 25% yang memberikan sentimen negatif. Hasil pemodelan Naïve Bayes kemudian dievaluasi hingga mendapatkan nilai accuracy sebesar 79,10%, rata-rata class precision 78,79%, class recall 78,5%, dan F1-Score 78,27%. Hingga dapat diambil kesimpulan bahwa penerapan Naïve Bayes untuk klasifikasi kelas sentimen memiliki akurasi yang baik dan stabil. Kata Kunci: Sentimen Analisis, Publik Sentimen, Stunting, Twitter, Naive Bayes

Analisis Data Mining dengan Metode K-Means Clustering Dalam Pengelompokan Penggunaan Alat Kontrasepsi Rahmad, Rahmad; Defit, Sarjon; Sovia, Rini
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.750

Family Planning (KB) is a strategic government effort to suppress population growth and improve the quality of life. The availability of various types of contraceptives can delay unwanted pregnancies, including in women facing increased pregnancy risks. Based on this, this study aims to cluster contraceptive use. The K-Means Clustering method is an unsupervised learning algorithm used to group data into several clusters based on similar characteristics. This algorithm works by minimizing the distance between the data and the cluster center (centroid). The advantages of K-Means are its simplicity and speed in processing large data. This research variable uses data from the 2024 Family Data Collection of the BKKBN Representative Office of West Sumatra Province in West Pasaman Regency. Based on the application of the K-Means Clustering method to the contraceptive use data, the grouping is obtained into three clusters: low use of MKJP contraceptives, moderate use of MKJP contraceptives, and high use of MKJP contraceptives. This study contributes in the form of a data mining-based analysis model that is able to group contraceptive use patterns in a more structured and objective manner. By applying the K-Means Clustering method, this study produces information that can be used to identify the characteristics of each user group, so that relevant agencies can design more targeted contraceptive counseling and distribution strategies.

Analisis Algoritma K-Means Clustering Dalam Pengelompokan Prestasi Belajar Siswa Menengah Atas (SMA) Dila, Rahmah; Defit, Sarjon; Arlis, Syafri
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.751

The increased use of social media among high school students has a positive and negative impact on academic achievement. This can be seen from changes in learning patterns, concentration levels, and students' motivation in participating in learning activities. This study aims to classify student learning achievement based on the level of social media use using the K-Means Clustering algorithm. K-Means Clustering is one of the main methods in data mining. which is a technique of grouping data based on the similarity of its characteristics. The parameters used in analyzing this study are Social Media Duration (X1), Active Time (X2), Main Platform (X3), Main Goal (X4), Social Media Access Time While Learning (X5), Social Media Addiction (X6), Social Media Addiction Level (X7), Number of Study Groups (X8) and Academic Average (X9). Based on the K-Means Clustering method, it has been proven to be able to group students based on the level of social media use. These results can be seen from the cluster category C0 (High) with 46 students, C1 (medium) with 80 students, and C2 (Low) with 72 students. The contribution of this research benefits students by helping them understand the relationship between social media usage habits and learning achievement, so as to encourage more effective time management.

Co-Authors Abdul Azis Said Adawiyah, Quratih Adek Putri Adi Gunawan Adi Gunawan, Adi Adyanata Lubis Afriyadi, Iqbal Agus Perdana Windarto Agustin, Riris Ahmad Zaki Ahmad Zamsuri, Ahmad Akbar, Muhamad Rafi Akbar, Syifa Chairunnissa Deliva Am, Andri Nofiar Amran Sitohang Anam, M Khairul Andema, Henky Andin, Silfia Andri Nofiar Angga Putra Juledi Anthony Anggrawan Arda Yunianta ardialis Ariandi, Vicky Arif Budiman Arif Budiman Arika Juwita Z Asri Hidayad Ayunda, Afifah Trista Bastola, Ramesh Bosker Sinaga Breinda, Engla Bufra, Fanny Septiani Daeng Saputra Perdana Dahria, Muhammad Daniel Theodorus Dayla May Cytry Dendi Ferdinal Deno Yulfa Ardian Deti Karmanita Devita, Retno Dhena Marichy Putri Dila, Rahmah Dinda Permata Sukma Dwi Utari Iswavigra Dwiki Aulia Fakhri Efendi, Akmar Efendi, Muhamad Efrizoni, Lusiana Eka Praja Wiyata Mandala Elda, Yusma eriwandi Fadlul Hamdi Faisal Roza Fajrul Islami Fanny Septiani Bufra Fatimah, Noor Fauzan Azim Fauzana, Rahmi Fauzi Erwis Febri Aldi Febri Hadi Febrina, Yerri Kurnia Firdaus, Muhammad Bambang Fitriani, Yetti Fristi Riandari Fuad El Khair Gaja, Rizqi Nusabbih Hidayatullah Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo, Gunadi Guslendra, Guslendra Hadiyanto, Tegas Halifia Hendri Handika, Yola Tri Haris Kurniawan Hartati, Yuli Hasmaynelis Fitri Haviluddin Haviluddin Hazlita, H Hendrik, Billy Hendro Budiantoro Hengki Juliansa Henky Andema Hermanto Hidayad, Asri Hidayat, Rahmadani Honestya, Gabriela Huda, Ramzil Ikhbal Salam, Riyan Indah Savitri Hidayat Indhira, Sonia INTAN NUR FITRIYANI Ira Nia Sanita Irsyad, As'Ary Sahlul Irzal Arief Wisky Ismail Virgo Jefdy Kurniawan Jeri Wandana Juansen, Monsya Jufri, Fikri Ramadhan Juledi, Angga Putra Junadhi, Junadhi Kareem, Shahab Wahhab Khairul Azmi Kurniawan, Jefdy Kurniawan, Mhd Hary Leony Lidya Lidya, Leoni Lubis, Fitri Amelia Sari Lubis, Siti Sahara Lusiana Lusiana M Syahputra M. Ibnu Pati M. Syahputra Mardayatmi, Suci Mardison Mardison Mardison Marfalino, Hari Meilinda Sari Meilinda Sari Melissa Triandini Menhard, Menhard Mhd Hary Kurniawan Miftahul Hasanah Miftahul Hasanah, Miftahul Mike Zaimy Monsya Juansen MUHAMMAD TAJUDDIN Muhammad, L. J. Mulyanda, Sandy Nadya Alinda Rahmi Nandan Limakrisna Nanik Istianingsih Nori Sahrun, Nori Novi Yanti Nurcahyo, Gunadi Nurcahyo, Gunadi Widi Nurdin, Yogi K Nurhadi Nurhidayat Nursyahrina Okfalisa, - Okmarizal, Bisma Olivia, Ladyka Febby Pandu Pratama Putra, Pandu Pratama Parinduri, Rezti Deawinda Pati, Muhammad Ibnu Pebriyanti, Defi Pratiwi, Mutiana Pulungan, Akhiruddin Purnomo, Nopi Putra, Akmal Darman Putra, Rahman Arief Putra, Surya Dwi Putri, Adek Putri, Dhena Marichy Putri, Yozi Aulia Putut Wicaksono, Putut R Rahmiyanti Radillah, Teuku Rafika Sani Rafiska, Rian Rahmad Aditiya Rahmad Rahmad Rahmadani Hidayat Rahman Arief Putra Rahmi, Nadya Alinda Ramadhan, Mukhlis Ramadhanu, Agung Ramdani Bayu Putra Rani, Larissa Navia Refina Afindania, Pipin Resnawita, R Rezki - Rezki Rusydi Rian Kurniawan Rianti, Eva Rio Andika Malik Ritna Wahyuni Rizki Mubarak Roza Marmay Roza, Yesi Betriana Rusdianto Roestam Rustam, Camila S Sumijan Said, Abdul Azis Sandrawira Anggraini Sani, Rafikasani Saputra, Dhio Sari, Imrah Sari, Laynita Selfi Melisa Septiano, Renil Setiawan, Adil Sharon Shaza Alturky Siregar, Diffri Solihin Sitanggang, Sahat Sonang Slamet Riyadi Sofika Enggari Sovia, Rini Sri Dewi Sri Dewi Sri Rahmawati Suci Mardayatmi Suhefi Oktarian Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Suri, Ghea Paulina Surmayanti Surya Dwi Putra Suryani, Vivi Susandri, Susandri Susriyanti, Susriyanti Syafri Arlis Syafrika Deni Rizki, Syafrika Deni Syaljumairi, Raemon Syofneri, Nandel Tamaza, Muhammad Abyanda Teri Ade Putra Tesa Vausia Sandiva Tukino, Tukino Veri, Jhon Veza, Okta Virgo, Ismail Vitriani, Vitriani Wahyu, Fungki Wanto, Anjar Wenni Afrodita Weri Sirait Y Yuhandri Yamin, Abdul Yamin Yemi, Leonardo Yerri Kurnia Febrina Yetti Fitriani Yogi K. Nurdin Yoni Aswan Yuda Irawan Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yulasmi Yulasmi, Yulasmi Yuli Hartati Yulihartati, Sandra Yunus, Yuhandri Yusma Elda Zakir, Supratman Zia Rahimi, Hadisha Zulvitri, Z Zuqron, M. Iqbal Zurni Mardian

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