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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
Anam, M Khairul
Universitas Samudra
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Clustering Junior Schools in Implementing Smart School Using The K-Means in Pekanbaru Nisa, Aida; Anam, M. Khairul; Yenni, Helda; Kudadiri, Parlindungan; Gunadi
Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Vol. 3 No. 3 (2024)
Publisher : Department of Informatics Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/snati.v3.i3.40

Abstract

The purpose of this research is to determine the readiness of schools in implementing the Smart School system through various stages. One of the concepts of a Smart City involves integrating information and communication technology into the learning process at every school to create Smart Schools. However, not all schools are ready to implement this technology because it requires suitable technology to support the quality of teaching and learning. Another issue is the absence of information systems that can facilitate administrative tasks and the teaching and learning process. The use of the K-Means method is beneficial for clustering schools based on their stages, characteristics, and readiness to implement the Smart School system. This helps identify schools with the highest level of readiness. This research demonstrates that the use of K-Means can identify school readiness based on the established stages related to the Smart School system. It also can pique students' interest in developing and boosting the school's reputation as the best technology-based school.
Evaluation of An Existing System Using The System Usability Scale (SUS) as A Guideline for System Improvement Anam, M. Khairul; Susanti, Susanti; Nurjayadi, Nurjayadi; Zoromi, Fransiskus; Sari, Atalya Kurnia
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.
ANALISIS TINGKAT PENGETAHUAN PENANGANAN ASI SERET MENGGUNAKAN OBAT TANAMAN KELUARGA PADA IBU MENYUSUI DI DESA MESANGGOK KECAMATAN GERUNG Muhammad Khairul Anam; Nurul Indriani; I Nyoman Bagus Aji Kresnapati
Indonesian Journal of Health Research Innovation Vol. 1 No. 4 (2024): Indonesian Journal of Health Research Innovation
Publisher : Yayasan Menawan Cerdas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64094/50904812

Abstract

Penggunaan tanaman obat keluarga (TOGA) sebagai solusi alami untuk masalah laktasi semakin diperhatikan, terutama di daerah pedesaan. Pengetahuan ibu menyusui mengenai ASI eksklusif dan pemanfaatan TOGA untuk mengatasi ASI seret sangat penting untuk keberhasilan menyusui. Penelitian ini bertujuan untuk mengevaluasi karakteristik demografis dan tingkat pengetahuan ibu menyusui tentang ASI eksklusif serta penanganan ASI seret menggunakan TOGA di Desa Mesanggok. Desain penelitian ini adalah deskriptif kuantitatif. Data dikumpulkan melalui kuesioner yang didistribusikan kepada 52 responden. Validitas data diuji menggunakan perangkat SPSS versi 27. Hasil analisis menunjukkan bahwa mayoritas responden berusia 20-30 tahun (63,46%), diikuti oleh kelompok usia 31-40 tahun (32,70%), dan usia 41-47 tahun (3,84%). Dari segi pendidikan, 9,6% responden memiliki tingkat pendidikan SD, 21,2% SMP, 51,9% SMA, dan 17,3% perguruan tinggi. Tingkat pengetahuan responden tentang ASI eksklusif dan penggunaan TOGA untuk mengatasi ASI seret tergolong baik, dengan 61,54% responden memiliki pengetahuan tinggi, 21,15% sedang, dan 17,31% rendah. Hasil ini menunjukkan bahwa sebagian besar ibu menyusui memiliki pemahaman yang baik tentang pentingnya ASI eksklusif dan manfaat TOGA dalam penanganan ASI seret. Penelitian ini menegaskan pentingnya edukasi berkelanjutan untuk meningkatkan pengetahuan ibu menyusui tentang praktik kesehatan alami yang aman dan efektif.
ACLM Model: A CNN-LSTM and Machine Learning Approach for Analyzing Tourist Satisfaction to Improve Priority Tourism Services Arsyah, Ulya Ilhami; Pratiwi, Mutiana; Fryonanda, Harfeby; Anam, M. Khairul; Munawir, Munawir
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.974

Abstract

Tourist satisfaction is a key proxy for destination service quality, yet automatic sentiment analysis of online reviews still faces class imbalance, overfitting, and limited deployability. This study proposes ACLM, a hybrid sentiment classification pipeline that learns semantic and temporal features with a CNN-LSTM backbone and evaluates three classifier heads (Softmax, Logistic Regression, XGBoost) on a three-class corpus (neutral, satisfied, dissatisfied). The objective is to deliver an accurate and operational model for decision support in tourism services. The idea combines Word2Vec embeddings, a compact CNN for local patterns, an LSTM for sequence dependencies, and a training workflow with text cleaning, SMOTE based balancing, and regularization to curb overfitting; outputs are exposed through a simple Streamlit interface. Results show that CNN-LSTM with a Softmax head attains accuracy 0.89, macro precision 0.89, macro recall 0.84, and macro F1 0.86, outperforming Logistic Regression (accuracy 0.87, macro precision 0.84, macro recall 0.82, macro F1 0.82) and XGBoost (accuracy 0.85, macro precision 0.80, macro recall 0.82, macro F1 0.80). The findings indicate that deep sequence features paired with a simple Softmax head provide the best tradeoff between accuracy and stability for three-way sentiment classification. The contribution is a reusable, end to end blueprint from preprocessing and balanced training to quantitative evaluation and an inference GUI, and the novelty lies in testing interchangeable classifier heads on a single CNN-LSTM feature extractor while explicitly addressing data imbalance and deployment constraints. The GUI is implemented using the highest accuracy model, namely CNN-LSTM with Softmax.
Implementation of Cloud Computing Based on Infrastructure as a Service (IaaS) to Improve Transaction Quality (Case Study Shop of Central Mart Pekanbaru) Yumami, Eva; Irfansyah, Irfansyah; Anam, M Khairul; 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.
Framework for Analyzing Netizen Opinions on BPJS Using Sentiment Analysis and Social Network Analysis (SNA) Anam, M Khairul; Mahendra, Muhammad Ihza; Agustin, Wirta; Rahmaddeni, Rahmaddeni; Nurjayadi, Nurjayadi
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 1 (2022): February 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.221 KB) | DOI: 10.29407/intensif.v6i1.15870

Abstract

The Social Security Administrative Body is a legal entity established to administer social security programs. News about BPJS policies is often found online and social media that has received responses from netizens as a form of public opinion on the policy. One of them is the opinion of netizens on social media Twitter. Ideas can be positive, neutral, or negative. These opinions are processed using the Support Vector Machine (SVM) method, in some SVM studies still getting unsatisfactory results, with rates below 60%. For this reason, it is necessary to have feature selection or a combination with the other methods to obtain higher accuracy. To see the actors who influence the opinion of netizens on the topic of BPJS, the Social Network Analysis (SNA) method is used. Based on the SVM Method's test results, the best accuracy results are obtained in combining the SVM Method with Adaboost, with an accuracy rate of 92%. Compared to the pure SVM method by 91%, the Combination of SVM Particle Swarm Optimization (PSO) by 87% and SVM using Feature Selection Genetic Algorithm (GA) by 86%.
Ambulance tracking system using GPS module and IoT based telegram messenger to find fastest route Akram, Rizalul; Novianda, Novianda; Atmaja, Teuku Hadi Wibowo; Anam, M. Khairul; Cut, Banta
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1322-1331

Abstract

Traffic congestion in urban areas affects ambulance trips to hospitals. This research aims to find the fastest route for ambulances to travel. The fastest route has criteria such as road shape, road width, shortest distance traveled, and fewer road users. This detection system applies internet of things (IoT) technology to each ambulance equipped with global positioning system (GPS), NodeMCU, and Wi-Fi modem that can send GPS coordinates to the cloud server, which will then mark the shortest distance from its current location to the hospital through the place where the emergency call is raised. The components used in this research are Neo6M GPS, NodeMCU ESP8266, cloud computing, and smartphone. This system can provide realtime information on all ambulance positions via android applications and Telegram messenger. The results obtained can determine the fastest path, distance, and travel time. In addition, the operation of this system takes 2-3 minutes to find the GPS signal at the beginning, then there is a 1-2 second delay from the GPS Tracking movement. Testing the route accuracy of this system and google maps by driving by motorcycle shows the results of this GPS system are more accurate in terms of distance and travel time.
Benchmarking Graphics Rendering Capabilities: Java Processing vs. P5.js Firdaus, Muhammad Bambang; Darma, Adi Surya; Arifin, Zainal; Anam, M. Khairul; Halim, Muhammad Yusuf; Yunianta, Arda
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2036

Abstract

Rendering efficiency is a critical factor in cross-platform animation development. This study benchmarks the performance of Java Processing and P5.js by measuring frame rates and frame counts across six heterogeneous computing devices for 2D and 3D animation tasks. Each benchmark was executed under standardized conditions for 60 seconds, and performance data were collected at fixed intervals. Results indicate that Java Processing consistently achieves higher rendering efficiency, with up to 313% greater frame rates and 265% higher frame counts compared to P5.js, particularly in computationally intensive 3D scenarios. These differences are attributed to Java Processing’s compiled execution and direct OpenGL integration, while P5.js performance is constrained by browser-based execution and limited GPU utilization. The findings suggest Java Processing is preferable for high-performance simulations and complex visualizations, whereas P5.js remains effective for lightweight web-based 2D applications.
MYCD: Integration of YOLO-CNN and DenseNet for Real-Time Road Damage Detection Based on Field Images Yenni, Helda; Muzawi, Rometdo; Karpen, Karpen; Anam, M. Khairul; Kasaf, Michel; Hadi, Tjut Rizqi Maysyarah; Wahyuni, Dewi Sari
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1040

Abstract

Road damage such as cracks, potholes, and uneven surfaces poses serious risks to transportation safety, logistics efficiency, and maintenance budgeting in Indonesia. Manual inspection is time consuming, labor intensive, and prone to error, motivating the use of reliable computer vision solutions. This study proposes MYCD, a hybrid and mobile ready architecture that combines the fast detection ability of YOLO with the dense feature reuse of DenseNet, enhanced by the Convolutional Block Attention Module (CBAM) for spatial and channel focus and Spatial Pyramid Pooling (SPP) for multi scale context understanding. The system detects and classifies the severity of road damage into minor, moderate, and severe categories using images captured by standard cameras. MYCD was trained and validated on 1,120 field images using an 80/20 split to simulate realistic deployment. Validation achieved 64 percent accuracy, with the highest per class precision of 0.72 for minor damage and mAP@0.5 = 0.677. The confusion matrix showed that most errors occurred in the moderate category because of visual similarity with minor and severe damage. Unlike earlier studies that extended YOLO with heavy backbones such as ResNet or EfficientNet, MYCD focuses on feature propagation (DenseNet), attention precision (CBAM), and multi scale fusion (SPP) optimized for real time operation on standard hardware. Efficiency profiling confirmed its deployability. After compression, the model size is 46.8 MB and it requires 3.7 GFLOPs per inference at 640×640 resolution. On a mid-range Android device (Snapdragon 778G, 8 GB RAM), MYCD runs at 19 frames per second with 1.2 GB peak memory. Compared with YOLOv8 WD (68 MB; 5.2 GFLOPs), MYCD reduces computation by 31 percent while maintaining similar accuracy. Overall, MYCD achieves a practical balance of speed, accuracy, and efficiency, providing a deployable and reproducible framework for real time road damage detection in resource limited settings.
Robust Predictive Model for Heart Disease Diagnosis Using Advanced Machine Learning Techniques Sovia, Rini; Anam, M. Khairul; Wisky, Irzal Arief; Permana, Randy; Rahmi, Nadya Alinda; Zain, Ruri Hartika
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1092

Abstract

This study presents a hybrid ensemble learning framework designed to enhance the predictive accuracy, robustness, and generalizability of heart disease classification models. The framework integrates three base classifiers: Decision Tree (DT), Gaussian Naive Bayes (GNB), and K Nearest Neighbor (KNN), which are combined using a stacking ensemble method with Logistic Regression (LR) as the meta learner. Each classifier contributes a distinct analytical perspective: DT models nonlinear relationships, GNB provides probabilistic reasoning, and KNN captures similarity-based patterns. Logistic Regression aggregates their outputs to produce a unified predictive decision. To mitigate class imbalance commonly observed in clinical datasets, the Synthetic Minority Oversampling Technique (SMOTE) is applied to generate synthetic samples of the minority class, improving the model’s ability to recognize underrepresented cases. Hyperparameter optimization is performed using the Optuna framework, which applies the algorithm to efficiently explore parameter configurations. The proposed model was evaluated on a publicly available heart disease dataset and achieved an accuracy of 99.61%, precision of 99.62%, recall of 99.59%, F1 score of 99.60%, and specificity of 99.58%, corresponding to a false positive rate of only 0.42 percent. These results demonstrate the framework’s strong ability to accurately identify heart disease cases while minimizing misclassification. The integration of SMOTE, stacking, and Optuna optimization contributes to its superior performance and robustness. Consequently, this approach shows strong potential for integration into clinical decision support systems to assist healthcare professionals in reliable and timely diagnosis.
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