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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Gramatika Jurnal Ilmiah KOMPUTASI JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Sebatik Journal of Information Technology and Computer Engineering Digital Zone: Jurnal Teknologi Informasi dan Komunikasi KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JURTEKSI INTEK: Informatika dan Teknologi Informasi Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Teknologi Informasi dan Pendidikan Jurnal Elektronika Listrik dan Teknologi Informasi Terapan bit-Tech Systematics Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Informatika Ekonomi Bisnis Journal of Robotics and Control (JRC) JSR : Jaringan Sistem Informasi Robotik Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Infortech Community Development Journal: Jurnal Pengabdian Masyarakat JUKI : Jurnal Komputer dan Informatika 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 Computer Scine and Information Technology Bulletin of Computer Science Research Insearch: Information System Research Journal Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Gramatika: Jurnal Penelitian Pendidikan Bahasa dan Sastra Indonesia Journal of Materials Exploration and Findings Jurnal Komtekinfo Jurnal Sistim Informasi dan Teknologi INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Innovative: Journal Of Social Science Research Jurnal Teknologi Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) The Indonesian Journal of Computer Science CSRID Jurnal Riset Pendidikan Multidisiplin dan Pengabdian Kepada Masyarakat
Yuhandri Yuhandri, Yuhandri
UnUniversitas Putra Indonesia YPTK Padang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Klasterisasi Tingkat Masa Studi Tepat Waktu Mahasiswa Menggunakan Algoritma K-Medoids Firzada, Fahmi; Yunus, Yuhandri
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 | DOI: 10.37034/jsisfotek.v3i3.146

Abstract

The period of study on time is one of the parameters of a student's success in completing college to obtain a bachelor's degree. A student is said to have completed his studies on time if he is able to complete his studies less than or equal to the predetermined time. Academic Provides facilities to find out the estimated time of student graduation. By providing information on which students are included in the cluster, they can complete their studies on time and which students do not complete their studies on time. In this study, the data processed were data from students who had graduated in the previous year. Then the data is processed using rapidminer software. This study applies the K-Medoids algorithm in clustering. The result of testing this method is to determine the student clusters who can complete the study period on time and the student clusters who cannot complete the study period on time. This research is expected to contribute to the campus in evaluating the tendency of students to complete their studies on time or not. The results of the evaluation of performance can produce information for study programs, lecturers and students in making policies.
Klasifikasi Kualitas Mutu Daun Gambir Ladang Rakyat Menggunakan Metode Convolutional Neural Network Winanda, Teddy; Yunus, Yuhandri; Hendrick, H
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 | DOI: 10.37034/jsisfotek.v3i3.156

Abstract

Indonesia is one of the countries which have the best Gambier quality in the world. Those are a few areas in Indonesia which have best gambier quality such as Aceh, Riau, North Sumatera, Bengkulu, South Sumatera and West Sumatra. Kabupaten 50 Kota is one of the regencies in west Sumatra that supplies gambier in Indonesia. The gambier leaf selection is mostly done by manual inspection or conventional method. The leaf color, thickness and structure are the important parameters in selecting gambier leaf quality. Farmers usually classify the quality of gambier leaves into good and bad. Computer Vision can help farmers to classify gambier leaves automatically. To realize this proposed method, gambier leaves are collected to create a dataset for training and testing processes. The gambier image leaves is captured by using DLSR camera at Kabupaten 50 Koto manually. 60 images were collected in this research which separated into 30 images with good and 30 images with bad quality. Furthermore, the gambier leaves image is processed by using digital image processing and coded by using python programming language. Both TensorFlow and Keras were implemented as frameworks in this research. To get a faster processing time, Ubuntu 18.04 Linux is selected as an operating system. Convolutional Neural Network (CNN) is the basis of image classification and object detection. In this research, the miniVGGNet architecture was used to perform the model creation. A quantity of dataset images was increased by applying data augmentation methods. The result of image augmentation for good quality gambier produced 3000 images. The same method was applied to poor quality images, the same results were obtained as many as 3000 images, with a total of 6000 images. The classification of gambier leaves produced by the Convolutional Neural Network method using miniVGGNet architecture obtained an accuracy rate of 0.979 or 98%. This method can be used to classify the quality of Gambier leaves very well.
Identifikasi Penderita COVID-19 Berdasarkan Chest X-Ray Menggunakan Algoritma Jaringan Syaraf Tiruan Backpropagation Putra, Heru Rahmat Wibawa; Yuhandri, Y
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.169

Abstract

Corona Virus Disease 2019 (COVID-19) is an infectious respiratory disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2). This disease first appeared in Wuhan, China and spread throughout the world. COVID-19 has had a major impact on public health around the world. On March 9, 2020, the World Health Organization (WHO) declared COVID-19 a pandemic. Early identification of people with COVID-19 can help limit the wider spread. One of the factors behind the rapid spread of the disease is the long clinical trial time. Rapid clinical testing is a challenge facing the spread of COVID-19. Most countries, including Indonesia, face the problem of lack of detection equipment and experts in diagnosing this disease. Chest X-Ray is one of the medical imaging techniques and also an alternative to identify the symptoms of pneumonia caused by COVID-19. This study aims to identify pneumonia caused by COVID-19 and other diseases based on Chest X-Ray. 107 Chest X-Ray images used as material for this study were obtained from the General Hospital of Ibnu Sina Padang Indonesia, which consisted of 27 images of pneumonia caused by COVID-19, 51 images with other diseases and 29 images of normal lungs. Then pre-processing is carried out as an initial stage and then feature extraction is carried out. Furthermore, the learning and identification process is carried out using the Backpropagation Artificial Neural Network (ANN) algorithm. In this study, 92 images were used as training data, and 15 images were used as test data. The results of calculations carried out using a network with a pattern of 16-100-100-100-2 obtained an accuracy value of 73%. The results of the identification prediction can be used as consideration in establishing a diagnosis of COVID-19 sufferers, but cannot be used as an absolute reference.
Sistem Pakar Menggunakan Metode Certainty Factor dalam Menganalisis Penyakit Karies Gigi pada Manusia Andrean, Fajri Ilhami; Yuhandri, Y
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.171

Abstract

Karies adalah penyakit gigi yang kerap ditemukan, yaitu suatu penyakit pada jaringan keras gigi berupa hilangnya ion – ion mineral secara terus menerus pada permukaan enamel gigi yang sebagian besar disebabkan oleh metabolisme bakteri. Tingkat kesadaran yang rendah dalam merawat gigi menyebabkan dampak buruk pada kesehatan gigi dan terhadap kesehatan tubuh. Pada saat sekarang ini umumnya masyarakat belum memiliki pengetahuan dalam menganalisis tentang penyakit karies gigi yang nantinya dapat mengakibatkan kerusakan yang parah terhadap gigi seperti matinya pulpa gigi. Penelitian ini bertujuan untuk menganalisis penyakit karies dengan menggunakan metode Certainty Factor. Dalam penelitian ini diolah data sebanyak 50 data yang diperoleh dari hasil wawancara dengan pakar pada Klinik Rahmatan Lil Alamin Padang Indonesia. Ditemukan beberapa faktor yang menyebabkan penyakit karies gigi pada manusia. Data tersebut diperoleh dari catatan medis pasien yang telah melakukan pemeriksaan di klinik. Data tersebut digunakan untuk menganalisis jenis penyakit karies berdasarkan bimbingan dari pakar tersebut. Tahapan pengolahan yang dilakukan adalah pemecahan rule, menentukan nilai bobot setiap gejala dan menghitung nilai Certainty Factor. Hasil yang didapatkan setelah dilakukan pengujian terhadap metode ini adalah terdapat 94% yang mengidap penyakit karies dengan jenis yang paling sering diderita pasien karies superfisialis. Hasil pengujian dapat menganalisis penyakit karies secara spesifik, dengan demikian sistem pakar yang digunakan telah dapat direkomendasikan untuk membantu dokter gigi menganalisis penyakit karies gigi pada manusia.
Optimalisasi dalam Penetrasi Testing Keamanan Website Menggunakan Teknik SQL Injection dan XSS Zikir Risky, Muhammad Arif; Yuhandri, Y
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.172

Abstract

SQLI (SQL Injection) and XSS are hacking techniques that are often used by hackers. This technique can find out the contents of the database by inserting a script on the website. This technique can be a threat if a website does not have security that can ward off such attacks. Hackers will look for loopholes using this technique in a login menu, searching, upload menu, input menu and URLs that have parameters ending in numbers, but not all websites that can be attacked use this technique if you don't limit the use of characters. This research was conducted to find out the gaps in a website that can be attacked with SQLI and XSS techniques and help optimize website security to avoid these attacks. Penetration testing will be carried out on a CV car rental website. Merdeka Auto Rental which is located in Padang City. This penetration testing uses SQLI and XSS techniques to find security holes in a website. The result of this test is that on the car rental website there are 12 gaps that are vulnerable to SQLI and XSS attacks, based on the results of these tests, a PHP script function is made that can remove all dangerous special characters. The script function is inserted in the PHP input, process and output files. The use of this script function does not apply to attacks other than SQLI and XSS so that if hackers use attack techniques other than that, this website is vulnerable to these attacks. After the script is inserted in the source code of the website, it can be concluded that the 12 known loopholes in the previous test without using the script function have changed status to not vuln or not vulnerable to SQLI and XSS attacks.
Sistem Pakar dalam Menganalisis Gangguan Jiwa Menggunakan Metode Certainty Factor Putra, Rafi Septiawan; Yuhandri, Y
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.177

Abstract

People with Mental Disorders (ODGJ) as a trigger for people who suffer from disorders of thought, feeling and behavior cause changes in attitudes and behavior that hinder normal human functioning. Mental disorders as a syndrome characterized by a change in a person's behavior that will be associated with symptoms such as difficulties or disorders, as well as psychological functions and behavior that are not confident in dealing with people but can also be with that person. An expert system is an intelligent computer technology that is based on solving problems using inferential knowledge and procedures. As a problem solver, expert systems will also find it easier to make decisions or policies like humans do. This study aims to produce an expert system that is used to analyze mental disorders who can make similar decisions, as well as psychiatric specialists. The data processed in this study is scientific data on mental disorders ranging from types of mental illness, early symptoms of disease and patient diagnosis data by mental health specialists, then the data is processed using the Certainty Factor method and displayed in the form of a web-based application using the PHP programming language. and MySQL databases. The results obtained from testing the expert system using the Certainty Factor method show that there is a match between the results of an expert diagnosis of depression with a certainty level of 73%. An expert system for analyzing mental disorders using the Certainty Factor method can make it easier for sufferers to understand the type of mental disorder they are experiencing.
Enlarge Medical Image using Line-Column Interpolation (LCI) Method Jufriadif Na'am; Julius Santony; Yuhandri Yuhandri; Sumijan Sumijan; Gunadi Widi Nurcahyo
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.955 KB) | DOI: 10.11591/ijece.v8i5.pp3620-3626

Abstract

Quality of medical image has an important role in constructing right medical diagnosis. This paper recommends a method to improve the quality of medical images by increasing the size of the image pixels. By increasing the size of pixels, the size of the objects contained therein is also greater, making it easier to observe. In this study medical images of Brain CT-Scan, Chest X-Ray and Panoramic X-Ray were processed using Line-Column Interpolation (LCI) Method. The results of the treatment are then compared to Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) processing results. The experiment shows that Line-Column Interpolation Method produces a larger image with details of the objects in it are not blurred and has equal visual effects. Thus, this method is expected to be a reference material in enlarging the size of the medical image for ease in clinical analysis.
An artificial neural network approach for detecting skin cancer Sugiarti Sugiarti; Yuhandri Yuhandri; Jufriadif Na'am; Dolly Indra; Julius Santony
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9547

Abstract

This study aims to present diagnose of melanoma skin cancer at an early stage. It applies feature extraction method of the first order for feature extraction based on texture in order to get high degree of accuracy with method of classification using artificial neural network (ANN). The method used is training and testing phases with classification of Multilayer Perceptron (MLP) neural network. The results showed that the accuracy of test image with 4 sets of training for image not suspected of melanoma and melanoma with the lowest accuracy of 80% and the highest accuracy of 88.88%, respectively. The 4 sets of training used consisted of 23 images. Of the 23 images used as a training consisted of 6 as not suspected of melanoma images and 17 as suspected melanoma images.
Perbandingan Algoritma K-Means Clustering dengan Fuzzy C-Means Dalam Mengukur Tingkat Kepuasan Terhadap Televisi Dakwah Surau TV Rio Andika Malik; Sarjon Defit; Yuhandri Yuhandri
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 3 No 1 (2018): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (573.499 KB) | DOI: 10.36341/rabit.v3i1.387

Abstract

Da'wah Television Surau TV is a broadcasting media that presents broadcasts around Islam. This media will quickly develop as it presents broadcasting material in meeting the spiritual needs of its viewers. To Increased media development is highly dependent on the satisfaction of the audience in all aspects of broadcast supporting. It is therefore, to measure the level of audience satisfaction as an effort to generate continuous broadcast quality improvement.This research is performing of algorithm clustering comparation with K-Means Clustering modeling and Fuzzy C-Means modeling to classify and mapping the most appropriate dataset so that it can assist analysing or measuring the level of audience satisfaction toward the da'wah television Surau TV. Comparison of clustering algorithm performance with K-Means Clustering modeling and Fuzzy C-Means modeling is based on processing speed and trace value of each RMSE parameter of clustering algorithm. The RMSE result of clustering research using algorithm with K-Means Clustering is 2.09879 and by using algorithm with Fuzzy C-Means model is 2.07911. Fuzzy C-Means modeling speed is faster in conducting the clustering process compared with K-Means Clustering modeling. It can be concluded that clustering with Fuzzy C-Means modeling is able to produce more accurate cluster compared to clustering with K-Means Clustering modeling accuracy Keywords: Clustering; K-Means; Fuzzy C-Means; Satisfaction rate survey; RMSE
IMPLEMENTASI JARINGAN SYARAF TIRUAN DALAM MEMPREDIKSI FREKUENSI RESONANSI ANTENA MIKROSTRIP Khairi Budayawan; Yuhandri Yuhandri; Gunadi Widi Nurcahyo
Jurnal Teknologi Informasi dan Pendidikan Vol 12 No 1 (2019): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/tip.v12i1.174

Abstract

The resonant frequency of an antenna is determined by the dimensional parameters and permittivity of the antenna substrate. Generally, to get the resonant frequency, a complex mathematical formula is needed to solve. For this reason, an intelligent method is offered to determine the resonant frequency more easily. In this study, an artificial neural network method with Backpropagation algorithm is used to overcome the problem. The data used were consisting of 80 training data and 15 testing data. The results have shown that the artificial neural network learning method with the backpropagation algorithm was successfully utilized to calculate the resonant frequency of microstrip antennas, where the precision of the resonant frequency obtained of 93.33% at an error of ≤ 1%, and 100% at an error of ≤ 2%.
Co-Authors - Hendrick - Khairiazaz AA Sudharmawan, AA Aal, Defrizal Abda Abda Abdul Azis Said Achmad Fauzan Syaputra Ade Dwi Dayani Afifah Cahayani Adha Aggy Pramana Gusman Agung Ramadhanu Agus Perdana Windarto Akbar Iskandar Akbari Wafridh Aldi Muharsyah Alfallah, Fadhly Alifcha Ghazian Alifia Restu Selvanda Allans Prima Aulia Andema, Henky Andre Rahmat Kurniawan Andrean, Fajri Ilhami Angga Putra Juledi Anita Sindar Anjun Dermawan Antoni Antoni Aprilian Gevindo Ardiyan, Destio Arif Budiman Arika Juwita Z Ariza Ikhlas Asyhari, Ahmad Aulia, Allans Prima Auriga, Wira Ayu Prima Siska Bambang Supperianto Billy Hendrik Borianto, B Budayawan, Khairi Budi Jaya Budi Permana Putra Chairul Imam Chairul Imam, Chairul Chandra, Mrs Montesna Dahria, Muhammad Dari, Rahmatia Wulan Darnis, Rahmi Delmayanti, Vera Dendi Ferdinal Deno Yulfa Ardian Desi Laidawati Devi Maryuni Dewi Eka Putri Dian Maharani, Dian Dikki Handoko Djasmayena, Selvia Djesmedi, Dinda Dodi Andre Putra Dolly Indra DWI JULISA UTARI Dwi Narulita Dwika Assrani Dzaki Al Fikri Effendy, Geraldo Revanska Efori Buulolo Eggy Febyanti Edwar Eka Naufaldi Novri Eka Praja Wiyata Mandala Eka Ramadhani Putra Eka Sofianti Elpina, Elpina Sari Dewi Hasibuan Eriyanto, Joko Erizke Aulya Pasel Esa Kurniawan Esa Kurniawan Eska, Juna Eva Rianti Fachrul Ilmawan Fadil Idensia Fahmi Firzada Fajri Ilhami Andrean Fauzan, Yuniko Febri Aldi Febri Hadi Feri Irawan Fernando Ramadhan Fhajri Arye Gemilang Finny Fitry Yani Firna Yenila Firzada, Fahmi Fitra, Ilham Fuad El Khair Gayatri, Satya Gemilang, Fhajri Arye Gunadi Dwi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo Gunadi Widi Nurcahyo, Gunadi Hadi Syahputra Hadrila P A Halifia Hendri Harkamsyah Andrianof Hartika Zain, Ruri Hartika Hartomi, Zupri Henra Hasanatul Iftitah Hasni, Salmi Hasri Awal Hendrick, H Hendro Zalmadani Henky Andema Hermanto Heru Rahmat Wibawa Putra Ibnu Luthfi Idir Fitriyanto Idir Idun Ariastuti Ikhlas, Muhammad Ilham Asy'ari Ilham Fitra Indah Dwi Putri Indah Permata Sari Indra Riyana Rahadjeng Irvan Okta Mazhona Iskandar Fitri, Iskandar Ismail Virgo Jaya, Budi Jefdy Kurniawan Jhon Veri Johan Danu Wijaya Jufriadif Na`am, Jufriadif Juledi, Angga Putra Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony K Kadrahman Kadrahman, Kadrahman Karseno, Doni Khairani, Maisan Dewi Puspa Khairiazaz Kurniawan, Jefdy Laidawati, Desi Larissa Navia Rani, Larissa Lc Granadi Suhaidir Lidia K Simanjuntak Liga Mayola Lova Endriani Zen Lusi Kestina M Ikhsan Setiawan M Ilham Aldyno M Mutia M, Mutia M.Iqbal, M.Iqbal Maharani Maharani, Maharani Majid Rahman Aziz Mardayulis, Mardayulis Mardison Mardison Mardison Meiditra, Irzon Mesran, Mesran Mey Yuki Lestari Mifthahul Rahmi Mohammad Guntur Montesna Muhammad Abrar Masril Muhammad Amin Muhammad Amin Muhammad Arif Zikir Risky Muhammad Ihksan Muhammad Noor Hasan Siregar Mukhlis Santoso Na'am, Jufriadif Nabilla Yasmin Nandra Sunaryo Nasma Yeni Nasution, Annio Indah Lestari Natalia Silalahi, Natalia Negoro, Wahyu Saptha Nelly Astuti Hasibuan Nissa, Ika Ima Nuning Kurniasih Nurdiyanto, Heri Olivia, Ladyka Febby Ondra Eka Putra P, Prihandoko Permana, Randy Petti Indrayati Sijabat Pohan, Yosua Ade Pratama , Abdul Hanif Pratama, Muhammad Harits Pratiwi, Fitri Prestian Ramadhan Prihandoko Prihandoko Prihandoko Prihandoko, P Pulungan, Akhiruddin Purnomo, Nopi Putra, Heru Rahmat Wibawa Putra, Rafi Septiawan Putra, Rezi Elsya Putri, Stefani R Rahmiyanti Rafi Septiawan Putra Ragil Ardiansyah Rahayu, Rita Rahmad Dian Rahmad Dian Rahmansyah, Rizky Rakhmad Kuswandhie Resnawita Retno Devita Riadi, Rahadatul ‘Aisy Riati, Itin Ridho, Ridho Afwan Rifky, Muhammad Rio Andika Malik Ririn Violina Riski Randa Hidayatullah Rita Sari Rita Sari Rivo Stephano Roby Nurbahri Romi Hardianto Romzi Rahman Ronda Deli Sianturi Rovidatul Rubiati, Nur Rusydi, Rezki S Salmiati Sabri T Rahman Sagala, Gamrina Sahat Sonang Sitanggang Sahri, Alfi Said, Abdul Azis Sajida, Mayang Salman Alfarisi Salimu Salmiati, S Samosir, Khairunnisa Saputra, Randy Sari, Fitri P. Sarjon Defit Seni Oknora Firza Septiana Vratiwi Septiana, Vina Tri Setiawan, Adil Setiawan, Adil Silfia Andini Siregar, Diffri Sisi Hendriani Siska, Ayu Prima Soeheri Soeheri Sonang, Sahat Sonia Indhira Sopi Sapriadi Soraya Rahma Hayati Sovia, Rini Sri Amalia Harahap Sri Dewi Sri Dewi Sri Rahmawati Stefani Hardiyanti Putri Stephano, Rivo Subrianto Chandra Sugiarti, Sugiarti Suginam Suhaidir, Lc Granadi Sukardi Sulastri Sulastri Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Sunaryo, Nandra Supriyanto, Boby Surya Darma Nasution Suryani, Vivi Sutiksno, Dian Utami Syafri Arlis Syafrika Deni Rizki Syafril Syafril Syahid Hakam Abdul Halim Syahputra, Afriadi Syaiffullah, Afif Syaljumairi, Raemon Syaputra, Eka B. Tajuddin, Muhammad Takyudin, Takyudin Tamin, Zulfiqar Taufik Nur Zam Zam Teddy Winanda Teguh Junaidi Teri Ade Putra Tessa Y M Sihite Toti Sri Mulyati Tri Agusti Farma Triyolla Ivandina Tukino, Tukino Uthama, Rayhan Veri, Jhon Very, Jhon Virgo, Ismail Vratiwi, Septiana Wanto, Anjar Wendi Boy Wenni Afrodita Willy Eka Septian Winanda, Teddy Winarto Winarto Wira Apriani Wira, M Wira Sanjaya Wirahmadayanti, Isna Yanti, Salma Nofri yanto, heri Yanto, Musli Yanto, Musli Yendi Putra Yendi Putra Yeni, Nasma Yolla Rahmadi Helmi Yosua Ade Pohan Yuda Irawan Yuda, Fitra Yuda Yudha Aditya Fiandra Yudha Aditya Fiandra Yundari, Yundari Yuniko Fauzan Yusma Elda Yusmaity Zalmadani, Hendro ZH, Lina Alfaridah. Zufari, Faisal Zupri Henra Hartomi