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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
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Sistem Pakar dalam Mengidentifikasi Minat Vokasi Menggunakan Metode Certainty Factor dan Forward Chaining Jefdy Kurniawan; Sarjon Defit; Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 2
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.051 KB) | DOI: 10.37034/jsisfotek.v3i2.47

Abstract

Developing an expert system application in providing an overview of the interests of students to help decision making interests in the vocational field so that they are right on target in choosing a major. In this study, using the Certainty Factor method and the Fordward Chaining method where this expert system can help experts identify vocational interests based on the characteristics of vocational interest in students. The personality types used to determine the type of vocational interest are Tangible, Thinking, Flexible, and Entrepreneur. The results of system calculations with expert decisions are worth 80% of the 4 test data, so a good level of accuracy is obtained. The resulting expert system can help students quickly provide an overview of vocational interest in making department decisions in continuing higher education, can carry out online consultations, document files, and can be used as a consultation portal for students.
Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5 Yetti Fitriani; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (862.628 KB) | DOI: 10.37034/jsisfotek.v3i3.54

Abstract

Student learning in schools has changed since the Covid-19 pandemic. Student learning in normal conditions is carried out face-to-face and turns into online or online learning. The research was conducted to predict student learning outcomes during the COVID-19 pandemic so that the results of this study can be used as a reference in policymaking in schools. The C4.5 method was used in the study to classify the data for class XII of the Multimedia Department at SMKN 2 Padang Panjang and the classification results could predict student learning outcomes during the pandemic. Processed student value data were taken from 1 (one) subject as the research data sample. Analysis of the value of student learning outcomes using the C4.5 Method to obtain new knowledge from student learning outcomes data carried out during the COVID-19 pandemic. The data analyzed consisted of attributes of attendance, assignments, daily tests, and test scores which influenced the decision criteria for student learning outcomes in online learning. The learning outcome decision criteria consist of "Satisfactory" and "Not Satisfactory" which refer to the Minimum Completion Criteria. Tests conducted on the training data of learning outcomes show that the value of the Daily Test is the most influential attribute in decision making. Implementation of the results using the RapidMiner Studio 9.2.0 software and produces an accuracy of 83.33% of the test data testing with the rules of data analysis training results. The results of the C4.5 classification testing method in this study can be used to predict student learning outcomes. The test results with an accuracy of 83.33% can be recommended to help schools in making policies
Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour Raemon Syaljumairi; Sarjon Defit; S Sumijan; Yusma Elda
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.421 KB) | DOI: 10.37034/jsisfotek.v3i3.55

Abstract

The Current wireless technology is used to find out where the user is in the room. Utilization of WiFi strength signal from the Access Point (AP) can provide information on the user position in a room. Alternative determination of the user's position in the room using WiFi Receive Signal Strength (RSS). This research was conducted by comparing the distance between users to 2 or more APs using the euclidean distance technique. The Euclidean distance technique is used as a distance calculator where there are two points in a 3-dimensional plane or space by measuring the length of the segment connecting two points. This technique is best for representing the distance between the users and the AP. The collection of RSS data uses the Fingerprinting technique. The RSS data was collected from 20 APs detected using the wifi analyzer application, from the results of the scanning, 709 RSS data were obtained. The RSS value is used as training data. K-Nearest Neighbor (K-NN) uses the Neighborhood Classification as the predictive value of the new test data so that K-NN can classify the closest distance from the new test data to the value of the existing training data. Based on the test results obtained an accuracy rate of 95% with K is 3. Based on the results of research that has been done that using the K-NN method obtained excellent results, with the highest accuracy rate of 95% with a minimum error value of 5%.
Sistem Pendukung Keputusan bagi Penerima Bantuan Komite Sekolah Menggunakan Metode Topsis Suci Mardayatmi; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.013 KB) | DOI: 10.37034/jsisfotek.v3i3.56

Abstract

Vocational High School Number 3 Mukomuko was the school that has given assistance for the learners. It was by exempting learners from paying committee charge monthly, it called Bantuan Komite Sekolah (BKS). In order to give motivation for the learners who was unfortunate to keep staying at the school, so it can make the learners to keep going on teaching and learning process (KBM). This research used Topsis method by collecting data for the prospective scholarship learners as many as 20 learners by categorizes were parents’ revenue, the total numbers of duties, the distance of residence, the average score of report and the condition of living environment. The result of try out from 20 learners who was obtain BKS by using Topsis Method showed that there were 18 learners who were significant to obtain scholarship by validity score was 90%. It was be a sample, before Topsis Method was used and the data was reliable after using Topsis Method. The development of supporting decision application system used Topsis Method that was getting in more accurated qualification. Futhermore, this system can help the school in constructing decisions to get the result be more advantageous in determining for the next BKS recipients.
Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor Yerri Kurnia Febrina; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (429.75 KB) | DOI: 10.37034/jsisfotek.v3i4.66

Abstract

Currently the Expert system has become a field of research for computer scientists as well as agricultural scientists for applications in various information development. The Expert System can be designed to simulate one or more of the ways an agricultural expert uses his knowledge and experience in making the diagnosis and passing on the necessary recommendations regarding nutritional deficiencies. Nutrient deficiency is a lack of food for survival in plants. The nutrient content of plant parts, especially the leaves, is very relevant to be used to identify nutritional deficiencies. Provide the results of a diagnosis of nutritional deficiency to farmers to be a benchmark for improving plant nutrients and providing good nutrition for hydroponic plants. The data used are nutritional deficiency data and symptoms as well as nutritional solutions obtained from farmer data at the Payakumbuh City Agriculture Office. The method used in this expert system is the Certainty Factor (CF) method. This method provides a diagnosis in the form of certainty or uncertainty of conditions in the rules used to conclude. The results of testing this method showed as many as 12 nutritional deficiencies were detected with 41 symptoms experienced. So that it can measure the level of nutritional deficiency that occurs. Expert System in Analyzing Hydroponic Plant Nutrient Deficiency Using Certainty Factor Method can show that predictions are almost 94% accurate.
Algoritma K-Means Clustering dalam Mengklasifikasi Data Daerah Rawan Tindak Kriminalitas (Polres Kepulauan Mentawai) Yoni Aswan; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (558.183 KB) | DOI: 10.37034/jsisfotek.v3i4.73

Abstract

Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and threaten their inner and outer peace. The research location is the Mentawai Islands Police, which is an agency that can provide security and protection for the community, especially those in the Mentawai Islands Regency. The problem is that it is difficult for the Mentawai Islands Police to classify areas that are prone to crime in the most vulnerable, moderately vulnerable and not vulnerable categories. Especially considering the condition of the Mentawai, there are four large islands consisting of 10 sub-districts, where crime is increasing every year, especially those in the Mentawai Islands Regency area such as motor vehicle theft. Based on the background of the problem above, the researcher is interested in taking research in creating a system to predict the crime rate in the Mentawai Islands Regency in order to anticipate the surge in crime that will come. The method used is the K-Means Clustering Algorithm as a non-hierarchical data clustering method to partition existing data into one or more clusters or groups. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. Clustering is one of the data mining techniques used to get groups of objects that have common characteristics in large enough data. The data used is data on cases of criminal theft of motor vehicles for the last 5 years from 2016 to 2020. The results of the test show that South Sipora District is an area prone to the crime of motor vehicle theft.
Identifikasi Tingkat Kerusakan Peralatan Labor Teknik Komputer Jaringan Menggunakan Metode Decision Tree Dinda Permata Sukma; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (527.183 KB) | DOI: 10.37034/jsisfotek.v3i4.78

Abstract

The computer laboratory is a place for practical learning for students, where computers have an important role in the smooth running of the practice. The use of computer labor at any time is very vulnerable to damage. If there is damage it will disrupt the teaching and learning process. Utilization of data mining in determining the level of damage is one of them. SMKN 1 Sintuk Toboh Gadang has 3 laboratories, TKJ (Network Computer Engineering), RPL (Software Engineering) and Technician labor. Application of the Decision Tree method in identifying damage to computer laboratory equipment, especially TKJ (Computer Network Engineering) labor. The data obtained in this study are computer equipment sourced from the computer laboratory of SMKN 1 Sintuk Toboh Gadang. Based on the analysis of the computer laboratory, there are 50 computer laboratory equipment. Furthermore, if the data is processed, several variables are needed to identify the level of damage to labor equipment including the name of the tool, number of tools, inspection, duration of use, and condition. The result of testing this method is to test whether the labor equipment can still be used or repaired. The purpose of this research is to help computer labor technicians to identify computer labor equipment that can still be used or repaired so that no damage occurs during practical learning hours. Furthermore, the best method in determining the level of damage to computer laboratory equipment is the Decision Tree Algorithm method. Decision Tree Algorithm is a predictive model using a decision tree structure and makes complex decisions simpler. The results of the research method show that the condition variable has the highest Gain value, namely 0.4734353, then the variable length of use is obtained with a Gain value of 0.896038. The factors that cause damage include the condition of the tool and the duration of use.
Simulasi dalam Optimalisasi Pengadaan Barang menggunakan Metode K-Mean Clustering Indah Savitri Hidayat; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.407 KB) | DOI: 10.37034/jsisfotek.v3i4.79

Abstract

Products provided by a store have an influence on store sales. Consumers will be attracted to stores that provide products according to their wants and needs. The purpose of this research is to find out what ornamental flower products are most in demand by consumers, in demand by consumers and less desirable to consumers. Keywords: inventory of goods, K-Mean Clustering, Data Mining, cluster, optimal. Store managers can get information about goods that have been depleted of inventory stock to be updated immediately. The method used in this study is the K-Mean Clustering method which belongs to one of the branches of Data Mining. The data used in the study is data from January 2020 to December 2020 as many as 100 pieces taken from naafilah official shop, Padang. The data variables used in the entry of goods are the year, product name, price and amount sold. Furthermore, the data is processed using Rapid Miner software. The first stage of processing is to determine the value of clusters randomly, in this study researchers divided the cluster values into 3 groups. Next, the centroid value of each group will be determined. Centroid is derived from the minimum value, middle value and maximum value of the data provided. Then, the cluster process is calculated using the euclidean distance formula. Cluster calculations are done by calculating the closest distance to the data. The final result of this study is to find out the best-selling, best-selling and less-selling ornamental flowers, so that sellers can optimize the provision of ornamental flowers for the future.
EVALUATION OF THE QUALITY OF ONLINE LEARNING USING THE ROUGH SET METHOD IN THE COVID 19 ERA Ramdani Bayu Putra; Sarjon Defit; Hasmaynelis Fitri
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 15 No. 2 (2021): Vol. 15 No. 2 (2021): Jurnal Ipteks Terapan ( Research of Applied Science and
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.584 KB) | DOI: 10.22216/jit.v15i2.256

Abstract

The occurrence of the Covid 19 pandemic around the world has changed all human physical activities in all lines of life, including activities in carrying out the teaching and learning process in educational institutions. This study seeks to analyze and evaluate the quality of online learning in the Covid 19 era. Measuring the quality of online learning is carried out using the rough set method, where the aspects or attributes used to consist of learning motivation, cognitive and self-efficacy. This research was conducted on students of the Putra Indonesia University YPTK Padang during the Covid 19 pandemic. By using the rough set algorithm technique, it is expected that the pattern or combination between attributes can produce knowledge or information in predicting the quality of online learning in the Covid 19 era. The results of testing with the Rosetta application found that The combination of cognitive and self-efficacy is an attribute that directly determines the quality of online learning in the Covid 19 era
Menentukan Pola Pembelian Produk Dengan Rule Mining Algoritma Apriori Pada Ud. Pelita Kita Padang Susriyanti -; Sarjon Defit; Nanik Istianingsih
Jurnal Administrasi Sosial dan Humaniora Vol 5, No 2 (2021): Desember
Publisher : Institut Administrasi dan Kesehatan Setih Setio

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.739 KB) | DOI: 10.56957/jsr.v4i3.185

Abstract

Penelitian ini merupakan penelitian kuantitatif menggunakan data sekunder dari transaksi penjualan perusahaan menggunakan rule asosiasi Apriori. Tujuannya adalah untuk melihat pola perilaku pembelian pelanggana terhadap produk-produk UD. Pelita Kita Padang secara kombinasi. Dari hasil pengujian rule asosiasi Apriori, didapat 5 rule asosiasi yang terbentuk. Pola asosiasi yang terbentuk dalam hasil pengujian menggunakan nilai minimum support 30% dan nilai minimum confidence 70% menghasilkan 5 aturan rule asosiasi. Dan strong rules tertinggi didapatkan pada rule asosiasi J → P dengan nilai support 38% dan nilai confidence 86,4%. Artinya pelanggan yang membeli produk J (Jendela) dan P (Pintu) secara bersamaan sebanyak 38% dari semua transaksi yang ada, dengan tingkat kebenaran atau keyakinan mereka akan membeli keduanya secara bersamaan adalah 86,4%.
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