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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Advances in Applied Sciences TEKNIK INFORMATIKA Techno.Com: Jurnal Teknologi Informasi Pixel : Jurnal Ilmiah Komputer Grafis Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Fountain of Informatics Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal JTERA (Jurnal Teknologi Rekayasa) Indonesian Journal of Artificial Intelligence and Data Mining INOVTEK Polbeng - Seri Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL REKAYASA TEKNOLOGI INFORMASI JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo ILKOM Jurnal Ilmiah Voice Of Informatics MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) JURTEKSI ComTech: Computer, Mathematics and Engineering Applications CSRID (Computer Science Research and Its Development Journal) JOISIE (Journal Of Information Systems And Informatics Engineering) EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik Jurnal Sistem Informasi dan Informatika (SIMIKA) Zonasi: Jurnal Sistem Informasi Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Sains, Aplikasi, Komputasi dan Teknologi Informasi Grouper: Jurnal Ilmiah Perikanan JISA (Jurnal Informatika dan Sains) JSES : Journal of Sport and Exercise Science Aiti: Jurnal Teknologi Informasi Jurnal Sistem Informasi dan Sistem Komputer Journal of Applied Data Sciences Jurnal J-PEMAS Decode: Jurnal Pendidikan Teknologi Informasi Ikhtisar: Jurnal Pengetahuan Islam Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Formosa Journal of Science and Technology (FJST) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) J-COSCIS : Journal of Computer Science Community Service JAIA - Journal of Artificial Intelligence and Applications Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi Bulletin of Social Informatics Theory and Application Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA) The Indonesian Journal of Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) Indonesian Journal of Health Research Innovation
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Implementation of Cloud Computing Based on Infrastructure as a Service (IaaS) to Improve Transaction Quality (Case Study Shop of Central Mart Pekanbaru) Eva Yumami; Irfansyah Irfansyah; M Khairul Anam; Hamdani Hamdani
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 6 No. 1 (2023): Jurnal Teknologi dan Open Source, June 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i1.3127

Abstract

An virtually infinite number of connected information and communication technology (ICT) resources can be found using a method known as cloud computing. Customers can use these resources on-demand over a network in the form of a public IP because both infrastructure and applications are fully owned and managed by third parties.To enhance staff performance and services in the context of transactions made by parties engaged in the buying and selling industry, a computer-based system is required, particularly for cashiers who handle customer payment transactions. There are still a lot of cashier programs available today that can only be accessed via a device linked to the same network or over the local network.In order to facilitate transactions and enable remote control, this research makes use of cloud computing technology that employs Infrastructure as a Service (IaaS) offerings. IaaS is a service that "rents" out fundamental information technology resources, such as storage space, computing power, memory, operating systems, network capacity, and others, so that customers can use them to execute their applications.Azure gives developers access to tools like Visual Studio and the ability to construct applications in a variety of languages, including.NET, Java, and Node.js. Because businesses don't have to worry about the expense of server equipment, implementing cloud computing can make it simpler for them to manage their business apps and finances. The ability for store administrators to use this program remotely (online) may then be aided or made simpler by this IaaS solution.
Evaluation of An Existing System Using The System Usability Scale (SUS) as A Guideline for System Improvement M. Khairul Anam; Susanti Susanti; Nurjayadi Nurjayadi; Fransiskus Zoromi; Atalya Kurnia Sari
JURNAL TEKNIK INFORMATIKA Vol 18, No 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.40766

Abstract

The e-Polvot system at the University of Science and Technology Indonesia (USTI) is a digital platform used for student elections, replacing traditional paper-based voting to enhance efficiency and minimize election fraud. This study evaluates the system using the System Usability Scale (SUS) to assess its usability, including efficiency, effectiveness, and user satisfaction. However, SUS alone does not determine failure points but provides a usability score that reflects user perception. A survey was conducted with 88 respondents from three different academic programs, which showed that while the system generally received a "Good" usability rating, certain areas require enhancement to improve user engagement and satisfaction. Based on the findings, this study recommends enhancing the user interface, providing targeted user training, and introducing additional features to broaden the system’s application across academic units. Additionally, the study highlights the potential for expanding the system's functionality beyond student elections, supporting activities such as departmental voting and organizational decision-making processes. These improvements aim to increase user satisfaction and usability, making the system a more effective tool for various academic and institutional contexts.
Sara Detection on Social Media Using Deep Learning Algorithm Development M. Khairul Anam; Lucky Lhaura Van FC; Hamdani Hamdani; Rahmaddeni Rahmaddeni; Junadhi Junadhi; Muhammad Bambang Firdaus; Irwanda Syahputra; Yuda Irawan
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.5390

Abstract

Social media has become a key platform for disseminating information and opinions, particularly in Indonesia, where SARA (Ethnicity, Religion, Race, and Intergroup) issues can fuel social tensions. To address this, developing an automated system to detect and classify harmful content is essential. This study develops a deep learning model using Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) to detect SARA-related comments on Twitter. The method involves data collection through web scraping, followed by cleaning, manual labeling, and text preprocessing. To address data imbalance, SMOTE (Synthetic Minority Over-sampling Technique) is applied, while early stopping prevents overfitting. Model performance is evaluated using precision, recall, and F1-score. The results demonstrate that SMOTE significantly improves model performance, particularly in detecting minority-class SARA comments. CNN+SMOTE achieves a accuracy of 93%, and BiLSTM+SMOTE records a recall of 88%, effectively capturing patterns in SARA and non-SARA data. With SMOTE and early stopping, the model successfully manages class imbalance and reduces overfitting. This research supports efforts to curtail hate speech on social media, especially in the Indonesian context, where SARA-related issues often dominate public discourse.
DIGITALISASI LAYANAN PERPUSTAKAAN: PENGEMBANGAN KATALOG BUKU BERBASIS WEB PADA DINAS PERPUSTAKAAN DAN KEARSIPAN KOTA LANGSA Siregar, Ginda Maruli Andi; M. Khairul Anam; Ahmad Ihsan; Liza Fitria; Munawir; Khairul Muttaqin
Jurnal Masyarakat Berdikari dan Berkarya (Mardika) Vol 2 No 4 (2024): Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA)
Publisher : Fakultas Teknik, Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/mardika.v2i4.12511

Abstract

Pengelolaan informasi buku yang efektif dan efisien menjadi kebutuhan penting dalam pelayanan perpustakaan modern. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk membantu Dinas Perpustakaan dan Kearsipan Kota Langsa dalam meningkatkan kualitas layanan melalui implementasi Sistem Informasi Katalog Buku berbasis digital. Sistem ini dirancang untuk memudahkan pengguna dalam mencari, melihat, dan mengakses informasi buku secara cepat, serta memfasilitasi admin dalam mengelola data buku dan data admin secara terstruktur. Sistem terdiri dari dua entitas utama, yaitu user dan admin, dengan fitur yang mencakup pencarian katalog, manajemen data buku, dan pengelolaan akun admin. Hasil implementasi menunjukkan bahwa sistem ini mampu meningkatkan efisiensi pengelolaan data buku serta mempermudah akses informasi bagi masyarakat. Diharapkan sistem ini dapat terus dikembangkan dengan fitur yang lebih inovatif dan mendukung transformasi digital layanan perpustakaan.
Utilization of the e-Polvot System to Increase Student Participation in Higher Education Anam, M. Khairul; Zoromi, Fransiskus; Hamdani, Hamdani; Efendi, Yoyon; Kudadiri, Parlindungan
JTERA (Jurnal Teknologi Rekayasa) Vol 10, No 1: Juni 2025
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v10.i1.2025.165-172

Abstract

STMIK Amik Riau currently has a student organization, one of which is the Student Executive Board (BEM). Every year, BEM is chosen as the representative of the students to voice their aspirations both within and outside the campus. The election process for BEM representatives is still conducted traditionally on campus. However, not all students can participate in the election process regularly, resulting in some students being unable to vote for the candidates for the student president and vice-president. To address this issue, a system is needed to facilitate the election process. One solution is to conduct electronic elections, allowing all students to vote from anywhere using the internet. In this research, the developed system is called e-Polvot (Electronic Polling and Voting). This system can be used by anyone to conduct elections by creating their own election campaigns. Before designing the system, the research conducted a measurement of the potential users using the TRI model. The results from the TRI measurement were then used to determine whether the system should be developed or not. Subsequently, the e-Polvot system was built and implemented at STMIK Amik Riau. After the implementation, the system underwent black box testing to ensure its functionality. The testing results showed that the main features of the e-Polvot system were able to perform well.
The Application of Na ve Bayes Classifier Based Feature Selection on Analysis of Online Learning Sentiment in Online Media Putra, Ryanda Satria; Agustin, Wirta; Anam, M. Khairul; Lusiana, Lusiana; Yaakub, Saleh
Jurnal Transformatika Vol. 20 No. 1 (2022): July 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i1.5144

Abstract

There are problems that still exist in online learning including limited-reach networks, inadequate facilities and infrastructure, and others. This study discussed the analysis of sentiment which used the Na ve Bayes Classifier (NBC) method with XGBoost feature selection as a performance improvement that took data from news portals. The results of this study showed that graph data on the application of online learning forms in Indonesia had a "Negative" opinion. Performance testing of the NBC method based on XGBoost feature selection was conducted four times. The first experiment resulted in an accuracy value of 60.18% with 50/50 split data. The next experiment had an accuracy value of 56.92% with 70/30 split data. After that, the third experiment resulted in an accuracy value of 65.90% with 80/20 split data. The result of the last experiment was an accuracy value of 63.63% with 90/10 split data. After using XGBoost feature selection, it produced an accuracy of 60.18%, 67.69%, 70.45%, and 77.27%. The study also produced the highest average score at 10-Fold Cross-Validation in the second trial with a score of 65.62%.
Sentiment Analysis Optimization Using Ensemble of Multiple SVM Kernel Functions M. Khairul Anam; Lestari, Tri Putri; Efrizoni, Lusiana; Handayani, Nadya Satya; Andhika, Imam
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6708

Abstract

This research aims to optimize sentiment analysis by leveraging the strengths of multiple Support Vector Machine (SVM) kernels—Linear, RBF, Polynomial, and Sigmoid—through an ensemble learning approach. This study introduces a novel model called SVM Porlis, which integrates these kernels using both hard and soft voting strategies to improve the classification performance on imbalanced datasets. Sentiment classification in this study involves two classes: positive and negative. Tweets related to the controversy over the naturalization of Indonesian national football players were collected using the official X/Twitter API, resulting in a dataset of 2,248 entries. The dataset was notably imbalanced, with significantly more negative samples than positive samples. Data preprocessing included cleaning, labeling, tokenization, stopword removal, stemming, and feature extraction using TF-IDF. To address the class imbalance, the SMOTE technique was applied to synthetically augment the minority class. Each SVM kernel was trained and evaluated individually before being combined into an SVM Porlis model. Evaluation metrics included accuracy, precision, recall, F1-score, and confusion matrix analysis. The results demonstrate that SVM Porlis with soft voting achieved the highest performance, with 98% accuracy, precision, recall, and F1-score, surpassing the performance of individual kernels and other ensemble approaches such as SVM + Chi-Square and SVM + PSO. These findings highlight the effectiveness of combining multiple kernels to capture both linear and non-linear patterns, offering a robust and adaptive solution for sentiment analysis in real-world, imbalanced data scenarios.
Analisis Pilkada Medan pada Sosial Media Menggunakan Analisis Sentimen dan Social Network Analyisis Anam, M. Khairul; Firdaus, Muhammad Bambang; Fitri, Triyani Arita; Lusiana; Agustin, Wirta; Agustin
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3027

Abstract

The simultaneous regional head elections were over, but during the campaign until it was decided to become regional head there were many comments, both pro and contra. The city of Medan is one of the regions that will hold the 2020 ELECTION during the pandemic. The Medan City Election has decided that the pair Bobby Nasution and Aulia Rachman have won. This victory certainly gets a variety of comments on social media, especially Twitter. This study conducts sentiment analysis to see the sentiment that occurs, namely seeing negative, positive, or neutral comments. This sentiment analysis uses two methods to see the resulting accuracy, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC). This study also looks at the interactions that occur using Social Network Analysis (SNA). In addition to sentiment analysis and SNA, this study also looks at the existence of BOT accounts used in the #PilkadaMedan. The results obtained from the sentiment analysis show that NBC has the highest accuracy, which is 81, 72% with a data proportion of 90:10. Then on SNA, the @YanHarahap account got the highest nodes, namely 911 nodes. Then from 10326 tweets, 11% were suspected of being BOT by the DroneEmprit Academic system.
OPTIMALISASI KINERJA KLASIFIKASI TEKS BERDASARKAN ANALISIS BERBASIS ASPEK DAN MODEL HYBRID DEEP LEARING Salsabila Rabbani; Agustin; Susandri; Rahmiati; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4034

Abstract

The conflict between Palestine and Israel has generated strong debates and reactions on social media, including in Indonesia. Public perception of various aspects is certainly important to identify issues in the Palestinian-Israeli conflict. However, the process of manually classifying aspects of the Palestinian-Israeli conflict requires human resources and considerable time. This research aims to explore the views of Indonesians on the Palestinian-Israeli conflict through sentiment analysis based on aspects of Territory, Religion, Politics, and History. Using deep learning technology, specifically a combination model of Convolutional Neural Networks with Long Short-Term Memory (CNN-LSTM), this research analyzes opinion and views data collected from X social media platform (Twitter). This research shows the results of the dataset obtained that the Political aspect dominates more than other aspects. The model evaluation results obtained an accuracy value of 96%, which indicates that the model's ability to classify X users' sentiments towards the Palestinian-Israeli conflict achieved a high level of success.
Klasifikasi Emosi Terhadap Konflik Israel-Palestina Menggunakan Algoritma Gated Recurrent Unit Saputra, Eko Ikhwan; Fatdha, T.Sy. Eiva; Agustin; Junadhi; M. Khairul Anam
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4106

Abstract

The Israel-Palestine conflict intensified following the October 7, 2023, attack by Hamas on Israel, triggering various emotional reactions on social media. Emotion classification is crucial for understanding public sentiment related to this conflict. This study utilizes 9,917 tweets from platform X (Twitter) to classify emotions such as joy, sadness, anger, fear, disgust, and surprise. The deep learning algorithm used is Gated Recurrent Unit (GRU), developed with three different training and testing data splits: 70:30, 80:20, and 90:10. For text representation, Global Vector (GloVe) word embedding is employed. Given the imbalanced dataset, this study applies the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. The research results indicate that the GRU model with a 90:10 data split without using SMOTE achieves the highest accuracy of 75%, followed by the models with 70:30 and 80:20 splits, which each have an accuracy of 73%.
Co-Authors -, Tashid Abrar Hadi Ade Riyanda Putra Agus Tri Nurhuda Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Ahmad Ihsan Ahmad Zamsuri Ahmad Zamsuri, Ahmad Aisum Aliyah Sari Akram, Rizalul Al Amin Fadillah Sani Alkadri Masnur Ambiyar, Ambiyar Andesa, Khusaeri Andhika, Imam Andi Supriadi Chan, Andi Supriadi Anwar, Reksi Aprillian Kartino Arba, Muhammad Hendra Arda Yunianta Arda Yunianta Arief Hidayat Arita Fitri, Triyani Arsyah, Ulya Ilhami Atalya Kurnia Sari Atmaja, Teuku Hadi Wibowo Bambang Kurniawan Br.Situmorang, Elisabet Sinta Romaito Budiman, Edy Budiman, Edy Bunga Nanti Pikir Bunga Nanti Pikir Chatarina Umbul Wahyuni Cut, Banta Damar Sanggara Habibie Darma, Adi Surya Daryanto, Diki Dea Safitri Dedy Irfan Devi Yuliana Dewi Sari Wahyuni Dewi, Nina Nurmalia Didik Sudyana Didik Sudyana Diki Daryanto Diky Daryanto Dona Wahyuning Laily Eddy Kurniawan Pradana Efrizoni, Lusiana Elangga Sony Widiharsono Elva, Yesri Emerlada, Esi Tri Erlin Erlin Erlinda, Susi Ersan Fadrial, Yogi Esi Tri Emerlada Fadli Suandi Fahrul Yamani Faisol Mas’ud Fajar Arifandi Fajrizal Fatdha, T.Sy. Eiva Faza Alameka Fernando Elda Pati Fika Felanda Ardelia Firdaus, Muhammad Bambang Fransiskus Zoromi Fransiskus Zoromi Fransiskus Zoromi Fransiskus Zoromi, Fransiskus Fryonanda, Harfebi Fuquh Rahmat Shaleh Gendhy Dwi Harlyan Gubtha Mahendra Putra Gunadi Gunanti Mahasri Gunawan, Chichi Rizka Habibi Ulayya Hadi Asnal, Hadi Hairah, Ummul Halim, Muhammad Yusuf Hamdani Hamdani - Hamdani . Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Handayani, Nadya Satya Hanif Aulia Happy Yugo Prasetiya Haris Kurniawan, Haris Hartomi, Zupri Henra Hasan J. Alyamani Haviluddin Haviluddin Hazira, Nadila Helda Yeni Helda Yenni, Helda Hendra Saputra Hendrawan, Riki hendri, nofri Herianto Herianto Herwin Herwin Ika Purnamasari Ike Yunia Pasa Ikhsan Ikhsan Indah Mukhlis Tamara Indra Prayogo Indra Prayogo Indri Febrianti Irfan Putra Pratama Irfansyah Irfansyah Irfansyah Irfansyah Irsyad, Akhmad Irwanda Syahputra Irwanda Syahputra Irzal Arief Wisky Istianah Istianah Jamaris, Muhamad Jamaris, Muhammad Jasmarizal Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Kadek Mirnawati Karfindo, Karfindo Karpen Kartina Diah K. W. Kharisma Rahayu Khusaeri Andesa Khusaeri Andesa Kresnapati, I Nyoman Bagus Aji Kudadiri, Parlindungan Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah Lathifah, Lathifah Latifah Lia Oktavia Ika Putri Lilis Cahaya Septiana Liza Fitria Lucky Lhaura Van FC Lucky Lhaura Van FC, Lucky Lhaura Lusiana Lusiana Efrizoni Lusiana Lusiana M Syauqi Hafizh Machdalena Mahamad, Abd Kadir Mahendra, Muhammad Ihza Mahessya, Raja Ayu Mardainis Mardainis Mardainis Martilinda Panjaitan Mega Susanti Mega Susanti Melda Royani Michal Dennis Michel Kasaf Mi`rajul Rifqi Mohamad, Nur Ikhwan Bin Muhaimin, Abdi Muhamad Jamaris Muhamad Sadar Muhamad Sadar, Muhamad Muhammad Bambang F Muhammad Bambang Firdaus Muhammad Bambang Firdaus Muhammad Budi Saputra muhammad Fuad Muhammad Nur Ihwan Muhammad Wisdan Pratama Putra Munawir Munawir Munawir N.A, Randi Nadila Rahmadhani Nadya Alinda Rahmi Nanda, Novianda Nanda Nariza Wanti Wulan Sari Nasrul Sani Neci Nirwanda Nisa, Aida Nora Lizarti Novi Yona Sidratul Munti Nu'man, Nu'man Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurkholifah Dwi Rahayu Nurul fadillah, Nurul Nurul Indriani Nurwijayanti Pandu Pratama Putra, Pandu Pratama Paradila, Dinda Parlindungan Kudadiri Permana, Randy Pradipta , Rahman Pranata, Angga Pratiwi, Mutiana Purwanto Putra, Ryanda Satria Rahmaddeni Rahmaddeni Rahmaddeni Rahmaddeni Rahmi, Nadya Alinda Rahmiati Rahmiati Rahmiati Rebecca La Volla Nyoto Refni Wahyuni Reksi Anwar Rini Yanti Rini Yanti Rini Yanti Rinno Hendika Putra Rio Andika Malik Rivaldi Dwi Andhika Rohana Yola Parastika Hutasoit Rohmat Romadhoni Rometdo Muzawi, Rometdo Ruri Hartika Zain Saiful Bukhori Salman Aldo Alfaresi Salsabila Rabbani Salsabila Rabbani Saon, Sharifah Saputra, Eko Ikhwan Sari Irma Yani Sitorus Sari, Atalya Kurnia Sarjon Defit Silvyana Dwi Putri Sofiansyah Fadli Sofiansyah Fadli Soni Sovia, Rini suaidah suaidah Sumijan Sumijan Susandri, Susandri Susanti Susanti Susanti Susanti Susanti Susanti Susanti, Mega Susanti, Susanti SUSI ERLINDA Susi Erlinda Susi Erlinda Syam, Salmaini Safitri Syamsiar, Syamsiar T. Sy. Eiva Fatdha Taruk, Medi Tashid Tashid Tashid Tatang Hidayat Tejawati, Andi Tengku Alvin Firdaus Teri Ade Putra Tjut Rizqi Maysyarah Hadi Torkis Nasution Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari, Tri Putri Triyani Arita Fitri Ulfah, Aniq Noviciate Wahyudianto, Mochamad Rizky Wahyuni, Dewi Sari Waksito, Alan Zulfikar Waskita, Ghozi Indra Wifra, Rizki Wirta Agustin Wirta Agustin Woro Hastuti Setyantini Yaakub, Saleh Yansyah Saputra Wijaya Yesaya Twin Situmorang Yogi Ersan Fadrial Yogi Yunefri, Yogi Yoyon Efendi Yuda Irawan Yudhistira, Dewangga Yumami, Eva Zainal Arifin Zeki Kurniadi zeki Kurniadi