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All Journal TEKNIK INFORMATIKA JURNAL SISTEM INFORMASI BISNIS Voteteknika (Vocational Teknik Elektronika dan Informatika) Elektron Jurnal Ilmiah Jurnal Sains dan Teknologi Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Prosiding Semnastek JUITA : Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Ilmiah Rekayasa dan Manajemen 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 JITK (Jurnal Ilmu Pengetahuan dan Komputer) 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 International Journal of Informatics and Computation Dinasti International Journal of Education Management and Social Science 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 Indonesian Journal of Electrical Engineering and Computer Science JUKI : Jurnal Komputer dan Informatika Jurnal Perangkat Lunak Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Journal of Applied Computer Science and Technology (JACOST) Jurnal Manajemen Sains 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 SATIN - Sains dan Teknologi Informasi RJOCS (Riau Journal of Computer Science) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JR : Jurnal Responsive Teknik Informatika Jurnal Responsive Teknik Informatika Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Journal of Soft Computing Exploration
Sarjon Defit
Universitas Putra Indonesia YPTK Padang
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Penerapan Metode TOPSIS Untuk Pemberian Bantuan Bedah Rumah Di Nagari Lunang Selatan Fitriyani, Intan Nur; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.738

Abstract

Indonesian government seeks to improve people's welfare by holding various poverty reduction programs, one of which is providing assistance to uninhabitable houses (RTLH). Equitable development of the welfare of Indonesian society must be comprehensive and even, starting from the smallest scope, namely the village. One of the villages in Indonesia that has implemented a program to provide assistance for uninhabitable houses is Nagari Lunang Selatan which is located in Lunang sub-district, Pesisir Selatan Regency, West Sumatra Province. The implementation of the uninhabitable housing assistance program in Nagari Lunang Selatan has so far still used a manual system so it is not effective because the final results are not objective. There are 5 criteria and 10 alternatives as sample data used in this research. These criteria include the number of dependents, total expenses, total income, land ownership status, and condition of the house. For this reason, this research provides a solution by implementing a decision support system for providing assistance for uninhabitable housing using the Technique For Order of Preference by Similarity to Ideal Solution method, known as TOPSIS, the TOPSIS method is suitable for solving semi-structural problems such as the problem of providing assistance for inadequate housing. inhabit. The aim of this research is to produce a system that can facilitate decision making regarding providing assistance for uninhabitable housing. The results obtained from the test calculation process on sample data of 10 alternatives with 5 criteria provide accurate results. From this test, the results obtained for 3 alternatives as recipients of house renovation assistance
Rancang Bangun Sistem Pakar Backward Chaining Untuk Antisipasi Hama Tumbuhan Kedelai Resnawita, R; Siregar, Diffri Solihin; Adawiyah, Quratih; Defit, Sarjon
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.759

Abstract

Soybeans are an important source of protein in Indonesia. Soybean cultivation in Indonesia faces difficulties posed by climate-related elements that create an ideal environment for the proliferation of various pest species, including those that attack leaves and pods. An expert system is a computing system designed to replicate all aspects of expert capacity in decision making. The Backward Chaining method is an approach where the reasoning process begins with the goal or conclusion to be achieved. This research aims to build a system to provide anticipation in dealing with soybean plant diseases and pests. The results of this expert system research support consultations by uploading photos as a consultation medium. Administrators have the ability to manage soybean crop data in the knowledge base, including adding, editing, and deleting data. The expert system is able to display diagnoses accompanied by complete prevention and management solutions for identified symptoms
Metode Multi Attribute Utility Theory (MAUT) Untuk Penilaian Kinerja Guru Yamin, Abdul Yamin; Defit, Sarjon; Sumijan, Sumijan
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.5920

Abstract

The performance assessment of teachers is a foundation or basis for the development decisions in terms of promotion and career of teachers in a madrasah or school. Currently, teacher performance assessment at Pondok Pesantren MTI Canduang is limited to teachers who are civil servants (PNS) or have obtained certification. In an effort to improve the quality of education, it is important to evaluate the performance of all teachers, including those who are not civil servants. The conventional method of assessment using paper-based evaluation sheets is considered inaccurate and inefficient due to the large number of teachers being assessed. Furthermore, there is no appropriate method for making decisions regarding teacher reward programs. Therefore, the purpose of this research is to apply the Multi Attribute Utility Theory (MAUT) method for teacher performance assessment. This method aims to provide a basis for decision-making in recommending teachers who deserve rewards in each assessment period. Based on the test results using the MAUT method with 40 teacher data and 12 defined assessment criteria, it was found that 3 data points for Tsanawiyah level had the highest value of 0.797 and the lowest value of 0.332, while 3 data points for Aliyah level had the highest value of 0.874 and the lowest value of 0.386. Thus, the research results can help the madrasah determine the best alternatives according to predefined criteria and weights. The resulting web-based application can facilitate the assessment process by making it easier, faster, and more accurate.
Implementasi Naïve Bayes dalam M-Series 4 Mobile Legends untuk Prediksi Kemenangan Tamaza, Muhammad Abyanda; Defit, Sarjon; Sumijan, Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6707

Abstract

Mobile Legends is a game made by a developer from China called Moontoon which implements the Multiplayer Online Battle Arena (MOBA) system which is currently popular. The popularity of this game is proven by the holding of low, middle and high level tournaments. Recently a high level or international tournament called the M-Series World Championship was held in Indonesia. This game is played by two teams consisting of five players with the aim of destroying enemy targets in the form of towers. The problem in this game is winning and losing. One of the factors that determines victory or defeat is the choice of hero. The wrong hero composition during the draft pick stage can make it difficult for your team to play and lead to unexpected results. This research aims to predict the percentage level of Mobile Legends wins based on the drafted heroes. Prediction is the process of minimizing errors in systematically estimating the future based on past information. The technique used in this research is the Naïve Bayes algorithm. The Naïve Bayes algorithm is a classification method based on probability. This method consists of four stages, namely data understanding, data preparation, data analysis, and results analysis. This research dataset is provided by Youtube MPL Indonesia. The dataset consists of 880 training data and 90 test data for M-Series 4 Mobile Legends. The results of this research provide a percentage value in the form of prediction of 96.67%, precision of 95.65% and recall of 97.78%. The results of an accuracy rate of 96.67% using the Naïve Bayes algorithm show that predictions using the Naïve Bayes algorithm can be applied to predict win ratios in M-Series 4 Mobile Legends.
Penerapan Metode Fuzzy Logic Dalam Sistem Pemantauan Tanaman Berbasis Internet Of Things (Iot) Dengan Arduino sabil, Muhammad; Sarjon Defit; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6710

Abstract

Hydroponic plants in this increasingly modern era, people are increasingly aware that their vegetable needs must be met so that the body's nutritional balance can be met properly. One of the Urban Farming that is suitable in urban areas with narrow dominant land is the hydroponic system. Hydroponics comes from two Greek syllables combined, namely hydro which means water and ponos which means work, so hydroponics means working using air. One of the advantages of this agricultural system is the minimal use of land, where even small areas of land can be utilized. well. Hydroponics is agricultural cultivation without using soil, so hydroponics is an agricultural activity that is carried out using air as a medium to replace soil. Hydroponic systems are increasingly popular among farmers and agricultural service providers because they are able to produce healthier and more productive plants without using soil as a growing medium. This research aims to test the performance of an Internet of Things (IoT) based Hydroponic Monitoring System using Arduino on plants or vegetables with the method used in this research is Fuzzy logic. This method has 3 stages, namely Fuzzification, Defuzzification, Fuzzy Rule. The data set processed in this research was taken from measurements of pH and temperature on hydroponic vegetable plants in the PKK garden of Kemantan Kebalai Village. The dataset consists of 340 data. The results of this research can identify and calculate the percentage of pH and temperature measurements with an accuracy level of 90%. Therefore, this research can be a reference in measuring acid, normal and alkaline levels in hydroponic plants.
Implementasi Data Mining untuk Pemetaan Persebaran Infeksi Human Imunodeficiency Virus di Provinsi Riau Fadillah, Riszki; Sarjon Defit; Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6712

Abstract

Based on data released by the Riau Provincial Health Service until October 2022, there were 8034 people living with HIV/AIDS (PLWHA), of which 3,711 were in the AIDS stage. Human Immunodeficiency Virus is a virus that attacks the body's immune system, while Acquired ImmunoDeficiency Syndrome (AIDS) is a collection of diseases caused by the HIV virus due to damage to the immune system in humans, resulting in the body being susceptible to potential diseases. This research aims to map the spread of HIV/AIDS in Riau Province to prevent and control the spread of the HIV/AIDS virus by the relevant agencies. The method used in this research is Fuzzy C-Means to carry out clustering in districts/cities which will then be visualized using a map or with a Geography Informatics System (GIS). The Fuzzy C-Means method is a data grouping technique that uses the existence of each data point in A cluster as determined by the degree of membership. The output from Fuzzy C-Means is a series of cluster centers and several degrees of membership for each data point. The data used in this research is HIV/AIDS data in Riau Province from 1997 to 2023. Based on the results of the tests that have been carried out, the results obtained are 3 clusters, namely the safe zone has 5 districts/cities, the alert zone has 5 districts/cities, and There are 2 districts/cities in the dangerous zone. There needs to be treatment through the Health Service, the AIDS Control Commission, and related Non-Governmental Organizations (NGOs) to prevent and control HIV/AIDS in Riau Province for areas that have a high potential for the spread of HIV/AIDS. The tests that have been carried out obtain a minimum error value of 0.008251 in the 8th iteration with the performance of Fuzzy C-Means being 13.271 in the distance between clusters.
Penerapan Convolutional Neural Network pada Klasifikasi Citra Pola Kain Tenun Melayu Mukhlis Santoso; Sarjon Defit; Yuhandri
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6713

Abstract

The use of electronic computerized media is growing along with advances in hardware and software as an analytical tool with various algorithms and methods for classifying and measuring objects in various contexts. This progress aims to overcome the weaknesses that exist in conventional methods used in the identification process. The identification process can be applied to various objects, one of which is an image object. An image is a visual representation of an object formed through a combination of RGB (red, green, blue) colors. RGB color components or features have a range of values from 0 to 255 in an image. Weaving is a type of fabric that is specially made with distinctive motifs. Malay weaving motifs have a lot of diversity, this diversity makes it difficult to distinguish the motifs of these fabrics.This study aims to recognize and distinguish the pattern of Malay woven fabric. The method used in this research is Convolutional Neural Network (CNN). The CNN method has several stages, namely Convolution Layer, Pooling Layer, Rectifed Linear Unit (ReLU) Function, Fully-Connected Layer, Transfer Learning, Optimizer and Accuracy. The dataset used in this research is sourced from Tenun Putri Mas Bengkalis. The dataset used consists of 1000 images of weaving motifs which are divided into 80% training data and 20% testing data, from the existing dataset divided into three categories of weaving motifs namely pucuk rebung, elbow clouds and elbow keluang. The results in this study are considered good because they produce accuracy with a result of 95% with an epoch value of 15. From the results of good enough accuracy, it is hoped that it can help the community in recognizing Malay weaving motifs.
Penerapan jst perceptron untuk mengenali huruf hijaiyah sebagai media pembelajaran anak usia dini Dwiprihatmo, Mohammad Reza; Sarjon Defit; Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6718

Abstract

Computer vision is the transformation of data obtained or taken from a webcam into another form to determine the decisions to be taken. All forms of transformation are carried out to achieve certain goals. One of the techniques that supports the application of computer vision to a system is digital image processing, because the aim of digital image processing techniques is to transform images into digital format so that they can be processed by a computer. Computer vision and digital image processing can be implemented into a hijaiyah letter pattern recognition system on cards that have been prepared and placed on a white board which is supported by the perceptron algorithm artificial neural network method which is used as a learning technique for the system to be able to learn and recognize hijaiyah letter patterns. This research aims to enable computers to read hijaiyah letters using a camera. The methods used in this research are image processing and the perceptron algorithm. The data set processed in this research comes from 783 hijaiyah letters consisting of 29 hijaiyah letters and 30 samples per each hijaiyah letter. How it works is that each hijaiyah letter is captured using a webcam and produces a continuous image which is transformed into a digital image and processed using several techniques including grayscale images, binary images and cropping images. The results of this research are that the system is able to identify and classify hijaiyah letters with a testing rate of 99,746%. Therefore, this research can be a reference in the modern teaching and learning process and is expected to help children's interest in learning hijaiyah letters.
Glaucoma detection in retinal fundus images using residual network architecture Islami, Fajrul; Sumijan, Sumijan; Defit, Sarjon
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7621

Abstract

Glaucoma is a significant eye disease that can lead to irreversible vision loss if not detected and treated early. This research focuses on developing an automated glaucoma detection system using a combination of a convolutional neural network (CNN) with the residual network 18 (ResNet18) architecture, locality sensitive hashing (LSH), and Hamming distance calculation. The CNN model is trained to extract meaningful features from retinal images, while LSH enables efficient indexing and retrieval of similar images. Hamming distance calculations are utilized to measure the dissimilarity between binary codes obtained from LSH. A dataset of 506 retinal images, consisting of 117 glaucoma images, 19 glaucoma suspect images, and 370 healthy images. The proposed glaucoma detection system achieved an average accuracy of 99.96%, sensitivity of 99.97%, and specificity of 99.94% during training, and 82.37% accuracy, 86.78% sensitivity, and 73.55% specificity during testing. Comparative analysis demonstrated its superiority over traditional methods. Further research should focus on larger datasets and explore multi-class classification for different glaucoma stages. The proposed system has potential for early glaucoma detection, facilitating timely intervention, and preventing vision loss.
Analisa Data Profil Pelanggan Menggunakan Algoritma FP-Growth Suryani, Vivi; Defit, Sarjon; Yunus, Yuhandri
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i1.8

Abstract

The number of bouquet orders is quite varied sometimes increased and decreased. The number of hikes certainly carries the goodness but the amount of decline certainly has an impact for Wawa Florist because it can not fulfill the number of bouquet order. The purpose of this research is to know how Data Mining techniques with Fp-Growth algorithm methods and designing the grouping of customer data of Wawa Florist with the FP-Growth algorithm method to obtain better and more effective analysis results. The result of the order data of the wreaths in Wawa Florish can be obtained which area information most booked wreaths, the most ordered bouquet of flowers are: D02 (Lubuk Buaya), D04 (Lubuk Minturun), D01 (Pariaman) and D03 (Lubuk Alung ). These results are obtained based on the appearance of the itemset of the bouquet booking data. Meet minimum confidence 60%.
Co-Authors Abdul Azis Said Abulwafa Muhammad Adawiyah, Quratih Ade, Ade Puspita Sari Adek Putri Adi Gunawan Adi Gunawan, Adi Adyanata Lubis Aflili Sari Afriosa Syawitri Agus Perdana Windarto Agustin, Riris Ahmad Zaki Ahmad Zaki Ahmad Zamsuri, Ahmad AHMADI Akbar, Muhamad Rafi Akbar, Syifa Chairunnissa Deliva Ali Ikhwan Alkhairi, Putrama Alvi Dwi Wahyuni Am, Andri Nofiar Amran Sitohang Anam, M Khairul Andema, Henky Andri Nofiar Angga Putra Juledi Anisya Anisya Anthony Anggrawan Arda Yunianta ardialis Ariandi, Vicky Arif Budiman Arif Budiman Arika Juwita Z Asri Hidayad Ayunda, Afifah Trista Bastola, Ramesh Billy Hendrik Bob Subhan Riza Bosker Sinaga Boy Sandy Dwi Nugraha.H Breinda, Engla Brestina Gultom Bufra, Fanny Septiani Chairun Nas Cyntia Trimulia Daeng Saputra Perdana Dahria, Muhammad Daniel Theodorus Dayla May Cytry Defi Pebriyanti Dendi Ferdinal Deno Yulfa Ardian Deti Karmanita Devia Kartika Devita, Retno Dhena Marichy Putri Dhio Saputra Dicky Novriansyah Dila, Rahmah Dinda Permata Sukma Dinul Akhiyar Dwi Utari Iswavigra Dwiki Aulia Fakhri Dwiprihatmo, Mohammad Reza Efendi, Akmar Efendi, Muhamad Efrizoni, Lusiana Eka Praja Wiyata Mandala Elda, Yusma Elfiswandi Elfiswandi eriwandi Fadillah, Riszki Fadlul Hamdi Faisal Roza Faizal Riza Faizal Riza Fajrul Islami Fajrul Islami Fanny Septiani Bufra Fatimah, Noor Fauzan Azim Fauzana, Rahmi Fauzi Erwis Febi Nur Salisah Febri Aldi Febri Hadi Febrina, Yerri Kurnia Firdaus Firdaus Firdaus, Muhammad Bambang Fitri Safnita Fitriani, Yetti Fristi Riandari Fuad El Khair Gaja, Rizqi Nusabbih Hidayatullah Ghea Paulina Suri Gunadi W Nurcahyo Gunadi Widi N. Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Guslendra Guslendra Guslendra, Guslendra Habdi, Habdi Hadiyanto, Tegas Halifia Hendri Hamsir hamsir Handika, Yola Tri Haris Kurniawan Hartati, Yuli Hasmaynelis Fitri Haviluddin Haviluddin Hazlita, H Hendrik, Billy Hendro Budiantoro Hengki Juliansa Henky Andema Hermanto Hidayad, Asri Honestya, Gabriela Huda, Ramzil Ikhbal Salam, Riyan Indah Savitri Hidayat Indhira, Sonia INTAN NUR FITRIYANI Iqbal Afriyadi Ira Nia Sanita Irsyad, As'Ary Sahlul Irzal Arief Wisky Ismail Virgo Istianingsih, Nanik Iswandi Saputra Jefdy Kurniawan Jeri Wandana Juansen, Monsya Jufri, Fikri Ramadhan Jufriadif Na`am, Jufriadif Juledi, Angga Putra Julius Santony Junadhi, Junadhi Kareem, Shahab Wahhab Khairul Azmi Kurniawan, Jefdy Kurniawan, Mhd Hary Lengga S. Sandy Leony Lidya Lidya, Leoni Lubis, Fitri Amelia Sari Lubis, Siti Sahara Lusiana Lusiana M Syahputra M. Ibnu Pati M. Iqbal Zuqron M. Syahputra Mardayatmi, Suci Mardian, Zurni 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 Dahria Muhammad Tajuddin MUHAMMAD TAJUDDIN Muhammad, Abulwafa Muhammad, L. J. Mukhlis Santoso Mulyanda, Sandy Mutiana Pratiwi Nadya Alinda Rahmi Nandan Limakrisna Nanik Istianingsih Nori Sahrun Nori Sahrun, Nori Novi Yanti Nur Aini Nurcahyo, Gunadi Nurcahyo, Gunadi Widi Nurdin, Yogi K Nurhadi Nurhidayat Nursyahrina Okfalisa, - Okmarizal, Bisma Olivia, Ladyka Febby Pandu Pratama Putra, Pandu Pratama Pati, Muhammad Ibnu Pipin Refina Afindania Pratiwi, Mutiana Pulungan, Akhiruddin Purnomo, Nopi Putra, Akmal Darman Putra, Rahman Arief Putra, Ramdani Bayu Putra, Surya Dwi Putri, Adek Putri, Dhena Marichy Putri, Yozi Aulia Putut Wicaksono, Putut R Rahmiyanti Radillah, Teuku Rafika Sani Rafiska, Rian Rafki, Rafnelly Rahmad Aditiya Rahmad Rahmad Rahmadani Hidayat Rahman Arief Putra Rahmi Fauzana Rahmi, Nadya Alinda Rakhmad Pribowo Hariputra Ramadhan, Mukhlis Ramadhanu, Agung - Randy Permana Rani, Larissa Navia Refina Afindania, Pipin Resnawita, R Rezki - Rezki Rusydi Rezti Deawinda Parinduri Rian Kurniawan Rianti, Eva Rico Anggara Rini Sovia Rini Sovia Rio Andika Malik Ritna Wahyuni Rizki Mubarak Roza Marmay Roza, Yesi Betriana Ruri Hartika Zain Rusdianto Roestam Rusdianto Roestam Rustam, Camila S Sumijan S Sumijan Sabil, Muhammad Said, Abdul Azis Saiful Nurarif Sandrawira Anggraini Sani, Rafikasani Sari, Imrah Sari, Laynita Selfi Melisa Septiano, Renil Setiawan, Adil Sharon Shaza Alturky Silfia Andin Sintia Sintia Siregar, Diffri Solihin Siregar, Fajri Marindra Siswahyudianto Sitanggang, Sahat Sonang Slamet Riyadi Sofika Enggari Sovia, Rini Sri Dewi Sri Dewi Sri Dewi, Apriandini Sri Rahmawati Suci Mardayatmi Suhefi Oktarian Sukardi Sulastri Sulastri Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Surmayanti, Surmayanti Surya Dwi Putra Suryani, Vivi Susandri, Susandri Susriyanti, Susriyanti Syafri Arlis Syafrika Deni Rizki Syaljumairi, Raemon Syofneri, Nandel Tamaza, Muhammad Abyanda Teri Ade Putra Tesa Vausia Sandiva Tukino, Tukino 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 Yenila, Firna Yerri Kurnia Febrina Yetti Fitriani Yogi K. Nurdin Yoni Aswan Yuda Irawan Yudha Aditya Fiandra Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yul Antonisfia Yulasmi Yulasmi, Yulasmi Yuli Hartati Yulihartati, Sandra Yunus, Yuhandri Yusma Elda Zakir, Supratman Zia Rahimi, Hadisha Zulharbi Zulharbi Zulvitri, Z