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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) AKSIOMA: Jurnal Program Studi Pendidikan Matematika International Journal of Artificial Intelligence Research Jurnal CoreIT JITK (Jurnal Ilmu Pengetahuan dan Komputer) Dinamisia: Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNOLOGI DAN OPEN SOURCE Digital Zone: Jurnal Teknologi Informasi dan Komunikasi IJISTECH (International Journal Of Information System & Technology) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Zonasi: Jurnal Sistem Informasi Journal of Applied Engineering and Technological Science (JAETS) Jurnal Pengabdian Masyarakat Multidisiplin JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Jurnal Teknik Informatika (JUTIF) IJISTECH Jutsi: Jurnal Teknologi dan Sistem Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat J-COSCIS : Journal of Computer Science Community Service Edumatica: Jurnal Pendidikan Matematika Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat SATIN - Sains dan Teknologi Informasi JURNAL KARYA ILMIAH MULTIDISIPLIN Jurnal Pengabdian Masyarakat dan Riset Pendidikan INOVTEK Polbeng - Seri Informatika Edu Komputika Journal IndoAI: Journal of Artificial Intelligence and Computational Logic
Ahmad Zamsuri, Ahmad
Universitas Lancang Kuning
Aerospace Engineering Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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PRO DAN KONTRA PENGGUNAAN AI PADA DUNIA PENDIDIKAN Ahmad Zamsuri; Wenni Syafitri; Guntoro Guntoro; Idel Waldelmi; Novia Putri Bimby
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5414

Abstract

Abstract: The Community Service (PkM) activity aims to enhance the knowledge of teachers at MI AL FATTAAH regarding the utilization of Generative Artificial Intelligence (Gen-AI) in education. Currently, student assessment is still conducted conventionally, meaning the utilization of Gen-AI technology is not yet optimal. Non-involvement in this technological development could negatively impact the quality of education in the future. Through socialization and education activities, this PkM introduced the concepts, usage, and result analysis of Gen-AI in the educational context, highlighting the pros and cons of its implementation. Effectiveness assessment was conducted using pre-tests and post-tests with the Coefficient of Reproducibility (CR) and Coefficient of Scalability (CS). CR and CS results of 1 indicate that the knowledge transfer was effective and the activity was executed well. This PkM not only improved the teachers' understanding of AI but also has the potential to become a learning model for similar educational institutions.            Keywords: Gen-AI, Socialization, Utilization, Education  Abstrak: Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan meningkatkan pengetahuan guru MI AL FATTAAH mengenai pemanfaatan Generative Artificial Intelligence (Gen-AI) dalam pendidikan. Selama ini, penilaian murid masih dilakukan secara konvensional, sehingga pemanfaatan teknologi Gen-AI belum optimal. Ketidakterlibatan dalam perkembangan teknologi ini dapat berdampak negatif terhadap kualitas pendidikan di masa depan. Melalui kegiatan sosialisasi dan edukasi, PkM ini memperkenalkan konsep, penggunaan, serta analisis hasil Gen-AI dalam konteks pendidikan, dengan menyoroti aspek pro dan kontra penerapannya. Penilaian efektivitas dilakukan melalui pre-test dan post-test menggunakan koefisien Reprodusibilitas (CR) dan Skalabilitas (CS). Hasil CR dan CS sebesar 1 menunjukkan bahwa transfer pengetahuan berlangsung efektif dan kegiatan terlaksana dengan baik. PkM ini tidak hanya meningkatkan pemahaman guru terhadap AI, tetapi juga berpotensi menjadi model pembelajaran bagi lembaga pendidikan sejenis. Kata kunci: Gen-AI, Sosialisasi, Pemanfaatan, Edukasi
Geodetically-Enhanced Hybrid GRU with Adaptive Dropout and Dynamic L2 Regularization for Earthquake Parameter Prediction in Indonesia Mubarak MR, Najmuddin; Susandri, Susandri; Zamsuri, Ahmad
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5478

Abstract

Earthquake prediction remains challenging due to the nonlinear behavior and uncertainty of seismic activity. This study introduces a geodetically-enhanced hybrid GRU model integrating adaptive dropout and dynamic L2 regularization to improve robustness and accuracy in earthquake magnitude prediction. In addition to seismic sequence data, slip-rate values derived from scalar moment distribution were incorporated as a domain-informed feature to represent tectonic strain accumulation across Indonesia. The dataset consisted of BMKG records from 2010–2025 and was processed through outlier removal, normalization, temporal reshaping, and feature integration. The proposed model was evaluated against multiple deep learning baselines including CNN-1D, LSTM, standard GRU, Transformer-based models, and Neural ODE architectures. Performance assessment used RMSE, MAE, and R² metrics. The resulting hybrid GRU achieved improved predictive accuracy with an RMSE of 0.5176, MAE of 0.3973, and an R² score of 0.5997, outperforming both CNN-1D and standard GRU baselines. The integration of slip-rate features contributed to reduced prediction variance across tectonically active zones. These findings demonstrate that combining geodetic information with adaptive regularization strategies improves generalization and model stability for seismic forecasting. The approach offers potential applicability for rapid early-warning scenarios requiring low latency and reliable prediction accuracy.
TRANSFORMASI PEMBELAJARAN STATISTIKA MELALUI PENGEMBANGAN E-MODULE INTERAKTIF UNTUK PENINGKATAN LITERASI STATISTIS MAHASISWA Sari Herlina; Yaya S Kusumah; Dadang Juandi; Ahmad Zamsuri; Dola Julianti
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol. 14 No. 4 (2025)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v14i4.13308

Abstract

Di era digital, kemampuan untuk memahami dan menganalisis data statistik semakin penting. Kemahiran dalam statistik atau literasi statistis memungkinkan individu untuk memahami data yang digambarkan melalui grafik, tabel, dan ilustrasi, membantu mereka untuk membuat keputusan yang tepat berdasarkan data. Penelitian ini bertujuan untuk mengembangkan e-module menggunakan  Kvisoft Flipbook Maker untuk meningkatkan Literasi Statistis calon guru matematika. Dalam penelitian ini didesain bahan ajar berupa E-Module yang didesain menggunakan Kvisoft Flipbook Maker digunakan dalam pembelajaran Statistika Pendidikan. E-Module ini dikembangkan dengan menggunakan software Kvisoft Flipbook Maker yang menyajikan materi Statistika Pendidikan dengan visualisasi yang menarik serta kaya dengan fitur multimedia. Metode penelitian ini merupakan penelitian pengembangan dengan mengadaptasi model ADDIE. Subjek penelitiannya adalah mahasiswa calon guru matematika di Program Studi Pendidikan Matematika, Universitas Islam Riau. Jumlah subjek penelitian sebanyak 42 orang mahasiswa. Instrumen yang digunakan terdiri dari lembar validasi, tes literasi statistis, lembar observasi dan lembar wawancara. Data dikumpulkan melalui tes literasi statistis, observasi, dan respons mahasiswa melalui wawancara. Hasil penelitian menunjukkan bahwa: 1) Hasil desain E-Module menggunakan  Kvisoft Flipbook Maker telah diuji kelayakannya. Dari segi validitas, kelayakan desain ini berada dalam kategori valid, sedangkan kepraktisannya berada pada kategori praktis. Desainnya juga efektif, karena ada peningkatan literasi statistik yang mencapai 76,19%. Dengan demikian, penelitian ini menghasilkan desain E-Module digital menggunakan  Kvisoft Flipbook Maker yang efektif dan layak digunakan untuk meningkatkan Literasi Statistis mahasiswa calon guru matematika. Kesimpulan penelitian ini, E-Module dapat diaplikasikan dalam matakuliah statistika, serta e-modul dapa digunakan dilingkup yang lebih luas diberbagai program studi di Indonesia.In the digital age, the ability to understand and analyze statistical data is increasingly important. Proficiency in statistics or statistical literacy allows individuals to understand the data depicted through graphs, tables, and illustrations, helping them to make informed decisions based on data. This research aims to develop an e-module using Kvisoft Flipbook Maker to improve the Statistical Literacy of prospective mathematics teachers. In this study, teaching materials in the form of E-Modules were designed using Kvisoft Flipbook Maker to be used in learning Educational Statistics. This digital module was developed using Kvisoft Flipbook Maker software which presents educational statistics material with interesting visualizations and rich multimedia features. This research method is a development research by adapting the ADDIE model. The subject of the research is a prospective mathematics teacher student at the Mathematics Education Study Program, Universitas Islam Riau. The number of research subjects was 42 students. The instruments used consisted of validation sheets, statistical literacy tests, observation sheets and interview sheets. Data were collected through statistical literacy tests, observations, and student responses through interviews. The results of research show that 1) The design results of the Digital E-Module using Kvisoft Flipbook Maker have been tested for feasibility. In terms of validity, the feasibility of this design is in the valid category, while the practicality is in the practical category. The design is also effective, because there is an increase in statistical literacy which reaches 76.19%. Thus, this study produced a digital E-Module design using Kvisoft Flipbook Maker that is effective and suitable to be used to improve the Statistical Literacy of prospective mathematics teacher students. The conclusion  of this research is that e-modules can be applied in statistics courses, and e-modules can be used in a wider scope in various study programs in Indonesia.
Evaluation of the Effect Of Regularization on Neural Networks for Regression Prediction: A Case Study of MLLP, CNN, and FNN Models Susandri; Ahmad Zamsuri; Nurliana Nasution; Maya Ramadhani
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/m2rcsf96

Abstract

Regularization is an important technique for developing deep learning models to improve generalization and reduce overfitting. This study evaluated the effect of regularization on the performance of neural network models in regression prediction tasks using earthquake data. We compare Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Feedforward Neural Network (FNN) architectures with L2 and Dropout regularization. The experimental results show that MLP without regularization achieved the best performance (RMSE: 0.500, MAE: 0.380, R²: 0.625), although prone to overfitting. CNN performed poorly on tabular data, while FNN showed marginal improvement with deeper layers. The novelty of this study lies in a comparative evaluation of regularization strategies across multiple architectures for earthquake regression prediction, highlighting practical implications for early warning systems.
ANALISIS SENTIMEN PERUNDUNGAN TERHADAP GURU DENGAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN NAÏVE BAYES Ahmad Zamsuri; Nurliana Nasution; Susandri Susandri; Novia Putri Bimby
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4916

Abstract

Abstract: This study discusses sentiment analysis of bullying experienced by teachers on social media. The research employs the Support vector machine (SVM) and Naïve Bayes methods to classify sentiments into positive, negative, or neutral categories. The data were collected from various social media platforms and analyzed using text mining techniques. The results show that the SVM method achieved a higher accuracy rate compared to Naïve Bayes in detecting negative sentiments related to bullying toward teachers. These findings contribute to a better understanding of digital bullying patterns targeting educators and provide a foundation for developing more effective policies to address bullying cases in the educational environment. Keywords: Sentiment Analysis, Bullying, Teachers, Support Vector Machine, Naïve Bayes, Text Mining. Abstrak: Penelitian ini membahas analisis sentimen terhadap perundungan yang dialami oleh guru di media sosial. penelitian ini menggunakan metode support vector machine (svm) dan naïve bayes untuk mengklasifikasikan sentimen menjadi positif, negatif, atau netral. data yang digunakan berasal dari berbagai platform media sosial dan dianalisis menggunakan teknik text mining. hasil penelitian menunjukkan bahwa metode svm memiliki tingkat akurasi yang lebih tinggi dibandingkan dengan naïve bayes dalam mendeteksi sentimen negatif terkait perundungan terhadap guru. temuan ini dapat membantu dalam memahami pola perundungan digital terhadap tenaga pendidik serta memberikan dasar untuk kebijakan yang lebih efektif dalam menangani kasus perundungan di dunia pendidikan. Kata Kunci: Analisis Sentimen, Perundungan, Guru, Support Vector Machine, Naïve Bayes, Text Mining.
PENINGKATAN KREATIVITAS DIGITAL MELALUI PELATIHAN PEMBUATAN KARAKTER AI MENGGUNAKAN MIDJOURNEY PADA SISWA SMK NEGERI 8 PEKANBARU Fajrizal Fajrizal; Ahmad Zamsuri; Mhd Arief Hasan; Muhammad Al Fajar
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.2814

Abstract

Abstract: This program aimed to introduce and enhance students' understanding of artificial intelligence (AI), with a focus on using MidJourney in digital character creation. The training, attended by 10 students and 1 teacher, covered material from basic to advanced levels regarding AI technology and its application in creative industries. The training methodology included theory introduction, MidJourney tool demonstrations, and hands-on practice in creating digital characters. Evaluation was conducted through pre-test and post-test questionnaires, showing significant improvement in participants' understanding of AI and MidJourney. The pre-test results indicated that 70% of participants had limited foundational knowledge of AI, while the post-test results revealed a 40% increase, with participants now able to create more effective prompts for generating digital characters. Additionally, a post-training satisfaction survey showed high satisfaction levels regarding the delivery of material and the overall quality of the training. This training successfully improved the participants' technological literacy and prepared them for the challenges of the creative industry, which increasingly relies on AI technology. Overall, this activity made a positive contribution in enhancing students' skills in AI-based digital design. Keyword: training; artificial intelligence; midjourney; character design; SMK Negeri 8 pekanbaru; creative technology  Abstrak: Program ini bertujuan untuk memperkenalkan dan meningkatkan pemahaman siswa tentang kecerdasan buatan (AI) dengan fokus pada penggunaan MidJourney dalam pembuatan karakter digital. Peserta pelatihan, yang terdiri dari 10 siswa dan 1 guru pendamping, diberikan materi dari dasar hingga mahir mengenai teknologi AI dan penerapannya dalam dunia kreatif. Metode pelatihan meliputi pengenalan teori, demonstrasi penggunaan MidJourney, serta sesi praktik pembuatan karakter digital. Evaluasi dilakukan menggunakan kuesioner pre-test dan post-test yang menunjukkan peningkatan signifikan dalam pemahaman peserta terhadap AI dan MidJourney. Hasil pre-test menunjukkan bahwa 70% peserta memiliki pemahaman dasar yang terbatas tentang AI, sementara hasil post-test menunjukkan peningkatan sebesar 40% dengan peserta mampu menyusun prompt yang lebih efektif untuk menghasilkan karakter digital. Selain itu, survei kepuasan yang dilakukan setelah pelatihan juga menunjukkan tingkat kepuasan yang tinggi terhadap penyampaian materi dan kualitas pelatihan. Pelatihan ini tidak hanya berhasil meningkatkan literasi teknologi peserta, tetapi juga mempersiapkan mereka untuk menghadapi tantangan dunia kerja di industri kreatif yang semakin bergantung pada teknologi AI. Secara keseluruhan, kegiatan ini memberikan kontribusi positif dalam mengasah keterampilan peserta didik di bidang desain digital berbasis AI.. Kata kunci: pelatihan; kecerdasan buatan; midjourney; desain karakter; SMK Negeri 8 pekanbaru; teknologi kreatif 
Evaluation Of CNN-LSTM with Attention for Forest Fire Prediction in Indonesia: Challenges of  Imbalanced Data Susandri; Ahmad Zamsuri; Nurliana Nasution; Feldiansyah; Ilzi Adrolis SNR; Firman Hidayat
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 3 (2026): August
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/6dzf1988

Abstract

Forest and land fires are annual disasters in Indonesia that are influenced by the temporal and nonlinear dynamics of surface weather conditions. This study evaluated a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) architecture with an attention mechanism for predicting forest fire risk based on multivariate surface weather data from BMKG stations for the 2015–2024 period. The dataset comprised 4,931 daily observations with eight weather features and four fire risk levels. The models were evaluated using temporal cross-validation and compared with the baselines (Random Forest, XGBoost, LightGBM, SVM, and standalone LSTM). The results indicate that the CNN-LSTM-attention model achieved 71.47% accuracy and 62.36% F1-score in the initial configuration. However, optimization attempts using SMOTE substantially degraded the performance to 50.95% accuracy (F1=0.55). The critical findings are as follows: (1) SMOTE is unsuitable for time-series data as it disrupts temporal patterns; (2) simpler architectures outperform excessive complexity; (3) class weighting is preferable to oversampling for handling class imbalance; and (4) basic weather features (without extensive engineering) yield optimal results. This study concludes that deep learning approaches for forest fire prediction in tropical regions face significant challenges related to class imbalance and temporal stability, necessitating the development of more adaptive modeling strategies
Artificial Intelligence Utilization Training to Improve Teachers' Learning Preparation Competencies at Bahira Islamic School Pekanbaru: Pelatihan Pemanfaatan Kecerdasan Artifisial  untuk Meningkatkan Kompetensi Persiapan Pembelajaran Guru Sdit Bahira Islamic School Pekanbaru Susandri Susandri; Ahmad Zamsuri; Nurliana Nasution; Eddissyahputra Putra Pane; Feldiansyah Feldiansyah; Muhammad Rosyadi
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 10 No. 1 (2026): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v10i1.29554

Abstract

The rapid growth of Artificial Intelligence (AI) offers tangible opportunities for primary school teachers to create lesson preparation artifacts more efficiently and creatively while aligning with the curriculum. This community service program aimed to enhance teachers’ competencies at SDIT Bahira Islamic School Pekanbaru in utilizing Canva AI and ChatGPT to develop lesson plans and teaching media. Two face-to-face training sessions were conducted, followed by pre- and post-tests using a Guttman scale assessing cognitive, affective, and psychomotor aspects. Results indicate significant improvement: 100% of participants could provide concrete examples of Canva AI use and craft effective prompts; Canva AI was the most preferred tool (75%). Key challenges included internet infrastructure, language barriers, content validation, and local context adaptation. The program successfully improved digital literacy and teachers’ self-efficacy; sustained mentoring and policy integration are recommended
PELATIHAN DESAIN MEDIA DENGAN APLIKASI CANVA UNTUK SISWA MADRASAH ALIYAH MA'ARIF NU PEKANBARU Ahmad Zamsuri; Susandri Susandri; Eddissyah Putra Pane; Feldiansyah Feldiansyah; Fajrizal Fajrizal; Sari Herlina
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 5 No. 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3022

Abstract

Abstract: The Canva application is an application that can be used in creating banner designs. With the utilization and development of techniques in making banner designs. In this case, the use of attractive and appropriate media in the process of making training banners will have a positive impact that will have the potential to greatly improve students' ability to create banners with the Canva application. Students and students really need knowledge in making media design with the aim of providing provisions in making media design even though students at Madrasah Aliyah Ma'arif NU Pekanbaru are quite many who want trainings to improve students' soft skill knowledge. Community Service offers a solution in the form of media design making training with the Canva application for students of Madrasah Aliyah Ma'arif NU Pekanbaru. Where this program is expected to be a forum and inspiration for students to increase their knowledge in making Media Design with the canva application. Where this program is expected to be able to be a forum and inspiration for students to be able to increase their knowledge in making Media Design with the great canva application that students and students of Madrasah Aliyah Ma'arif NU Pekanbaru hope for. As a speaker, he provided socialization and at the same time assistance on how to make Media Design with an interesting and certainly very useful application for students of Madrasah Aliyah Ma'arif NU Pekanbaru. Keyword: Media Design, Canva, Students of Madrasah Aliyah Ma'arif NU Pekanbaru  Abstrak: Aplikasi canva merupakan aplikasi yang dapat digunakan dalam pembuatan desain spanduk. Dengan pemanfaatan dan pengembangkan teknik dalam pembuatan desain spanduk. Dalam hal ini, pemanfaatan media yang menarik dan tepat guna dalam proses pembuatan spanduk pelatihan akan memiliki dampak positif yang akan sangat berpotensi meningkatkan kemampuan siswa dalam membuat spanduk dengan aplikasi canva. Para siswa dan siswi sangat membutuhkan pengetahuan dalam membuat desain media dengan tujuan memberikan bekal dalam pembuatan desain media walaupun siswa di Madrasah Aliyah Ma'arif NU Pekanbaru cukup bayak yang menginkan pelatihan-pelatihan untuk meningkatkan pengetahuan softskill siswa. Pengabdian Kepada Masyarakat menawarkan solusi berupa pelatihan pembuatan desain media dengan aplikasi canva untuk siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Di mana program ini diharapkan mampu menjadi wadah dan inspirasi bagi para siswa dapat menambah pengetahuan dalam membuat Desain Media dengan aplikasi canva besar harapan siswa dan siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Sebagai pemateri memberikan sosialisasi dan sekaligus pendampingan mengenai bagaimana pembuatan Desain Media dengan aplikasi canva yang menarik dan pastinya sagat dapat bermanfaat bagi siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Kata kunci: Desain Media, Canva, Siswa Madrasah Aliyah Ma'arif NU Pekanbaru
Co-Authors Abini, Eka Yestira Nita Alkhairi, Putrama Alwan, Hiba Basim Anam, M Khairul Andi Zahran Budiman Andre Armada Aprilia Milanda Putri Arini Arita Fitri, Triyani Arpan Asparizal, Asparizal Astri Wahyuni Baehaqi Bayu Febriadi, Bayu Bimby, Novia Putri Dadang Juandi Deni Iskandar Diyah Ayu Rizqiani Dola Julianti Eddis Syahputra Pane, Eddis Syahputra Eddissyahputra Putra Pane Eko Sediyono Elvira Asril, Elvira Elvira Elvira Fadly Suandi Fajar, Muhammad Al Fajrizal Fajrizal Fajrizal, Fajrizal Febrizal Alfarasy Syam Febrizal Alfarasy Syam Febrizal As-Syam Feldiansyah Feldiansyah Feldiansyah Feldiansyah Feldiansyah Feldiansyah, Feldiansyah Firman Hidayat Fitri Juliani Gunadi Widi Nurcahyo Guntoro, Guntoro Hamdani Hamdani Hazira, Nadila Hendrawan, Riki Hiba Basim Alwan Idel Waldelmi idel waldelmi, idel Ilzi Adrolis SNR Indriati, Mefa Julianti, Dola Keumala Anggraini Khairani Djahara, Khairani Lisnawita Lisnawita Loneli Costaner Mariza Devega Maya Ramadhani Mhd. Arief Hasan, Mhd. Arief Mubarak MR, Najmuddin Muhamad Sadar, Muhamad Muhammad Al Fajar Muhammad Rosyadi Muzdalifah, Indah Novia Putri Bimby Nurfika Sari Nurliana Nasution Nurliana Nasution, Nurliana Nuroini, Indi Pandu Pratama Putra, Pandu Pratama Pardede, Akim Manaor Hara Poningsih Rahmiati Rahmiati Ramadani, Indah Ramadhani, Maya Roki Hardianto Sahrul Saputra Saputra, Eko Ikhwan Sari Herlina Sari Herlina Sari Herlina Sari Herlina Sarjon Defit Shelydia Martha Suhendra Sumijan , Sumijan Susandri Susandri Susandri, Susandri Susi Handayani Sutejo Sutejo Syahtriatna D Syahtriatna Djusar Syahtriatna Djusar Syam, Salmaini Safitri Taufiq Hidayah Tintien Koerniawati Toresa, Dafwen Triyani Arita Fitri Turnandes, Yogo Vebby Vebby Vebby Walhidayat Walhidayat Walhidayat Wenni Syafitri Wirta Agustin Yaya S Kusumah Yaya S. Kusumah Yenni, Heda Yogi Yunefri, Yogi Yogo Turnandes Yogo Turnandes Yoyon Efendi Yuhelmi Yuhelmi Yuvi Darmayunata Zamzami, Zamzami