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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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K-Means Clustering to Identity Twitter Build Operate Transfer (BOT) on Influential Accounts M. Khairul Anam; Ike Yunia Pasa; Kartina Diah Kusuma Wardhani; Lusiana Efrizoni; Muhammad Bambang Firdaus
ComTech: Computer, Mathematics and Engineering Applications Vol. 14 No. 2 (2023): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v14i2.10620

Abstract

Twitter is a popular social media with hundreds of millions of users, but some are not human. About 48 million accounts are created by Build Operate Transfer (BOT), which represents up to 15% of all accounts. BOTs are created for various purposes, one of which is to post information about news automatically. However, BOTs have also been abused, such as spreading hoaxes or influencing public perception of a topic. The research aimed to determine which Twitter accounts were identified as BOT accounts based on predefined attributes. The research used tweet data from 213 Twitter accounts. The accounts used as test data were accounts that had influence. After that, the data were clustered using k-means using the attributes of retweets + replies count, followers count, account age, friends count, status count, digits count in name, username length, name similarity, name ratio, and likes count. The results show the optimal number of clustering at k = 3 on the Sum of Squared Errors (SSE) evaluation and the Elbow method and the best quality and cluster power at k = 2 on the silhouette coefficient. It shows that the clustered accounts with the highest number of members on each attribute are places for accounts with high BOT scores from several aspects of the BOT score type.
Enhancing the Decision Tree Algorithm to Improve Performance Across Various Datasets Putra, Pandu Pratama; Anam, M Khairul; Defit, Sarjon; Yunianta, Arda
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 2 (2024): August 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i2.22280

Abstract

Background: The Village Fund is an initiative by the central government to promote equitable regional development. However, it has also led to corruption. Many Indonesians share their opinions on the Village Fund on social media platforms like X, and news coverage is extensive on portals like detik.com. Objective: This study aims to classify data from social media and news coverage to enhance understanding. Methods: The research improves the decision tree algorithm by integrating other algorithms and techniques such as XGBoost and SMOTE. Ensuring high accuracy is vital for the credibility of machine learning classifications among the public. The study uses two different datasets, necessitating varied testing approaches. For the news portal dataset, a single test with seven labels is conducted, followed by enhancement with XGBoost. The X dataset undergoes two tests with datasets of 1200 and 3078 entries, using three labels. Conclusion: The evaluation results indicate that the highest accuracy achieved with the news portal data was 82%, thanks to a combination of decision tree algorithms with various parameters and the balancing effect of SMOTE. For the Twitter dataset with 3078 entries, the highest accuracy reached 95%, attributed to the application of ensemble techniques, particularly boosting.
The Readiness Analysis of Smart School Implementation Using Technology Readiness Index to Support Smart City Implementation M. Khairul Anam; Indra Prayogo; Susandri; Yoyon Efendi; Erlin; nurjayadi
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.507

Abstract

Smart Schools have been widely applied in several schools within the scope of education and services as they are being encouraged to support Smart City. Smart Schools is a school concept utilizing information technology used in the teaching and learning process in the class and school administration. One of the schools in Pekanbaru City that will implement intelligent schools in Junior High School 17 Pekanbaru. Building smart schools themselves is adequate infrastructure such as servers, labor, and integrated systems and the readiness of schools and students to implement Smart Schools in the future. Therefore, to determine the readiness level of prospective users of the Smart Schools concept, the technology readiness index (TRI) method with four personality variables; optimism, innovativeness, discomfort, and insecurity. The purpose of this research was to find out the readiness index of prospective users in the implementation of Smart Schools and see what factors need to be improved from the readiness of prospective users. This research was expected to help Junior High School 17 prepare schools to become Smart Schools to support smart city implementation in Pekanbaru
Penerapan Metode Finite State Machine Pada Mobile Game Side Scrolling “Utan Adventure” Firdaus, Muhammad Bambang; Arba, Muhammad Hendra; Tejawati, Andi; Taruk, Medi; Irsyad, Akhmad; Anam, M Khairul
SemanTIK : Teknik Informasi Vol 10, No 1 (2024):
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v10i1.47474

Abstract

Game ialah satu dari sekian sarana untuk menghilangkan kebosanan, dengan kemajuan teknologi smartphone saat ini, banyak game dengan platform mobile berkembang cepat. Android didukung oleh terjangkaunya smartphone android dipasaran sehingga lebih mudah diakses oleh anak-anak, remaja dan orang tua. Pengembangan game side-scrolling “Utan Adventure” ini untuk membangun game yang dapat mengasah otak dan kreativitas pemain serta untuk mempromosikan budaya lokal di Kalimantan. Game side-scrolling “Utan Adventure” ini adalah game dengan genre action adventure lebih tepatnya dengan subgenre side-scrolling dirancang menggunakan unity game engine dan menggunakan metode Finite State Machine yang diterapkan pada Player, Enemy dan mekanisme level. Finite State Machine ialah suatu metode untuk perancangan sistem kontrol yang memperlihatkan prinsip kerja sistem dengan fokus pada tiga hal penting : state (keadaan), event (kejadian), dan action (aksi). Berdasarkan hasil pengujian penelitian ini terdapat pengujian gameplay, pengujian artificial intelligence, pengujian kontrol pemain, dan pengujian mekanisme level. Hasil akhir dari game ini adalah game side-scrolling berbasis platform android, dengan fitur tambahan berupa toko, upgrade, leaderboard, dan Non-Playable Character (NPC) yang dapat patroli, mencari, dan menyerang pemain di setiap level. Kata kunci; Mobile Game, Finite State Machine, Non-Playable Character
Implementation of The Open Group Architecture Framework to See the Readiness of Smart Schools in Pekanbaru Anam, M. Khairul; Hendrawan, Riki; Arita Fitri, Triyani; Agustin, Wirta; Zamsuri, Ahmad
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 14 No. 2 (2023): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v14i2.14916

Abstract

Smart Schools are a derivative of smart people in the 6 pillars of Smart City. Smart Schools is also a school concept utilizing information technology used in the teaching and learning process in the classroom and school administration. One of the schools in Pekanbaru City that will implement smart schools is Junior High School 17 Pekanbaru. Currently, the school already has several infrastructures including servers, laboratories, and administrative rooms, but it is necessary to analyze the technology architecture aimed at implementing Smart Schools. The technological architecture would be analyzed using TOGAF (The Open Group Architecture Framework) Framework version 9. The TOGAF framework is a framework for enterprise architecture which is able to develop an enterprise architecture in an organization. Enterprise architecture is an explicit explanation and current documentation of the relationship between management, business processes, and information technology. This research describes the current architectural conditions and target architectures to include the rules, standards, and lifecycle of information systems to optimize and maintain the environment of organizations that want to create and maintain by managing the IT portfolios. The results of this study are to produce an IT blueprint that is used as a school guide in implementing technology architecture to support the implementation of Smart Schools in Pekanbaru City.
Application of Naïve Bayes Algorithm for Non-Cash Food Assistance Recipients in Kampar Regency Anam, M Khairul; Rahmiati; Paradila, Dinda; Mardainis; Machdalena
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.12032

Abstract

Non- Non-Cash Food Assistance (BPNT) is a non-cash food social assistance from the government given to beneficiary families (KPM) of Rp. 200,000 per month which is given in the form of basic necessities by using an electronic card. The large number of residents who will be selected makes it difficult for village officials to make decisions on who is eligible or ineligible as recipients of non-cash food assistance every month. This research was conducted to design a decision support system for the eligibility of non-cash food assistance recipients by using the naïve bayes algorithm in order to help the Parit Baru Village apparatus every month in determining the eligibility of the next non-cash food assistance recipients, by perform Confusion Matrix calculations. From the results of the discussion carried out, it can be concluded that Naïve Bayes and the resulting rules had an accuracy rate of 95%, the Precision value was 94% and Recall was 100%. Therefore, the Naïve Bayes algorithm can be applied to the decision support system in determining the eligibility of recipients of non-cash food assistance.
Comparison of Support Vector Machine and Random Forest Algorithms for Analyzing Online Loans on Twitter social media Hamdani; N.A, Randi; M. Khairul Anam
JAIA - Journal of Artificial Intelligence and Applications Vol. 4 No. 1 (2024): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/jaia.v4i1.1087

Abstract

Online loans represent a form of financial service wherein borrowers can apply for loans through digital platforms without the need to visit physical offices. The application, approval, and disbursement processes are conducted online, leveraging technology to facilitate financial access and transactions. However, some online lending services impose high-interest rates, resulting in a significant financial burden for borrowers. Moreover, there are instances of inappropriate debt collection practices, such as contacting the borrower's friends or family, leading to discussions and comments on social media platforms like Twitter. This research aims to analyze the patterns of comments in Indonesian society regarding online lending. The study utilizes sentiment analysis and compares machine learning algorithms to assess their accuracy. The algorithms employed in this study are Support Vector Machine (SVM) and Random Forest. The results indicate that the SVM algorithm achieves an accuracy of 93.85%, while Random Forest achieves an accuracy of 91.62%.
VIRTUAL REALITY MUSEUM MULAWARMAN BERBASIS VIDEO 360° Firdaus, Muhammad Bambang; Tejawati, Andi; Budiman, Edy; Wahyudianto, Mochamad Rizky; Anam, M Khairul
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 11 No 2 (2021): September 2021
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (374.85 KB) | DOI: 10.33020/saintekom.v11i2.222

Abstract

Recent years, visitors have decreased in the Mulawarman Museum, located in Tenggarong Kutai Kartanegara. A small number of visitors to the Mulawarmen Museum could have been due to a lack of promotions. The purpose of this study is to develop and present the Mulawarman Museum as a promotional medium a Visual Video Application for the Mulawarman Tenggarong Kutai Kartanegara. A combination of VR and Android mobile technology, which is owned by most levels of society, enables application users to view the videos in 360 degrees, can serve this research purpose. The aim of the research is This research. The test results from Android devices show that the application is smooth to run and suitable for use in versions of Android 5.1 and later with a screen-like aspect ratio of 16:9 and 18:9. All of the questions in the questionnaire received agree and strongly agree between 85% and 100%.
Early Stopping on CNN-LSTM Development to Improve Classification Performance Anam, M. Khairul; Defit, Sarjon; Haviluddin, Haviluddin; Efrizoni, Lusiana; Firdaus, Muhammad Bambang
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.312

Abstract

Currently, CNN-LSTM has been widely developed through changes in its architecture and other modifications to improve the performance of this hybrid model. However, some studies pay less attention to overfitting, even though overfitting must be prevented as it can provide good accuracy initially but leads to classification errors when new data is added. Therefore, extra prevention measures are necessary to avoid overfitting. This research uses dropout with early stopping to prevent overfitting. The dataset used for testing is sourced from Twitter; this research also develops architectures using activation functions within each architecture. The developed architecture consists of CNN, MaxPooling1D, Dropout, LSTM, Dense, Dropout, Dense, and SoftMax as the output. Architecture A uses default activations such as ReLU for CNN and Tanh for LSTM. In Architecture B, all activations are replaced by Tanh, and in Architecture C, they are entirely replaced by ReLU. This research also performed hyperparameter tuning such as the number of layers, batch size, and learning rate. This study found that dropout and early stopping can increase accuracy to 85% and prevent overfitting. The best architecture entirely uses ReLU activation as it demonstrates advantages in computational efficiency, convergence speed, the ability to capture relevant patterns, and resistance to noise.
Machine Learning Algorithm Optimization using Stacking Technique for Graduation Prediction Herianto, Herianto; Kurniawan, Bambang; Hartomi, Zupri Henra; Irawan, Yuda; Anam, M Khairul
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.316

Abstract

Graduating on time is crucial for academic success, impacting time, costs, and education quality. Hang Tuah University Pekanbaru (UHTP) is currently struggling to meet its goal of achieving a 75% on-time graduation rate. This study introduces an innovative approach using machine learning techniques, particularly ensemble learning with Stacking Machine Learning Optuna SMOTE (SMLOS), to address this issue. Our primary objective is to enhance data classification accuracy to predict student graduation timelines effectively. We employ algorithms such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree (C4.5), Random Forest (RF), and Naive Bayes (NB). These were combined with meta-models, including Logistic Regression (LR), Adaboost, XGBoost, LR+Adaboost, and LR+XGBoost, to create a robust prediction model. To address class imbalance, we applied the Synthetic Minority Over-sampling Technique (SMOTE) and utilized Optuna for hyperparameter tuning. The findings reveal that SMLOS with the Adaboost meta-model achieved the highest accuracy of 95.50%, surpassing previous models' performances, which averaged around 85%. This contribution demonstrates the effectiveness of using SMOTE for class imbalance and Optuna for hyperparameter optimization. Integrating this model into UHTP's academic information system facilitates real-time monitoring and analysis of student data, offering a novel solution for promoting a Smart Campus through more accurate student performance predictions. This technique is not only beneficial for predicting student graduation but can also be applied to various machine learning tasks to improve data classification accuracy and stability.
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