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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 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 Sisfo: Jurnal Ilmiah Sistem Informasi 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 Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Masyarakat Madani Indonesia 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 Journal of Informatics and Information Security Advance Sustainable Science, Engineering and Technology (ASSET) Indonesian Journal of Health Research Innovation
Anam, M Khairul
Universitas Samudra
Religion Aerospace Engineering Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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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.
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.
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.
The Role of Machine Learning in Modern Football Analytics: A Systematic Review of Approaches and Their Implications Waskita, Ghozi Indra; Kurniawan, Haris; Yudhistira, Dewangga; Mohamad, Nur Ikhwan Bin; Anam, M. Khairul
JSES : Journal of Sport and Exercise Science Vol. 8 No. 2 (2025): September
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jses.v8n2.p178-186

Abstract

Purpose: Football has increasingly become a multidisciplinary field that integrates not only physical and tactical elements but also technological advancements to enhance decision-making. One of the prominent developments in this domain is the application of machine learning (ML) techniques to analyze match-related data, assess player performance, and optimize team strategies. This study aims to conduct a systematic literature review of contemporary research that employs machine learning algorithms within the context of football. Materials and Methods: A total of 50 scientific articles were initially retrieved from various reputable databases. Following a rigorous screening and eligibility assessment, 30 articles were selected for detailed analysis. Result: These studies employ diverse machine learning approaches, including Support Vector Machines (SVMs), Random Forests, XGBoost, Deep Learning, and clustering methods, for a wide range of purposes, such as match outcome prediction, player performance evaluation, injury detection, and playing position classification. The findings of this review underscore the potential of machine learning to contribute significantly to data-driven decision-making in football, providing valuable insights for coaches, performance analysts, and club management. Conclusion: Furthermore, this study identifies key challenges that remain, including data quality, data availability, and the interpretability of complex models. This review will serve as a critical reference for researchers and practitioners advancing intelligent technologies in sports, with particular emphasis on football.
Development of Knowledge Management System to Improve the Performance of the New Student Admission System for Higher Education Anam, M. Khairul; Fitri, Triyani Arita; Zoromi, Fransiskus; Junadhi, Junadhi; Nu'man, Nu'man
JISA(Jurnal Informatika dan Sains) Vol 5, No 2 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i2.1443

Abstract

The New Student Admission System (PMB) is the main door or core business of the University and requires a good management system. Every Academic Year STMIK Amik Riau forms a committee to carry out this PMB activity. The PBM committee consists of several parts, namely the promotion section, the registration section and the selection section.  Each section carries out knowledge sharing or knowledge transfer in carrying out its duties. This knowledge sharing is only limited to informal or formal communication through meetings so that the knowledge sharing process has not been carried out optimally. The purpose of this study was (1) to measure the readiness of human resources in the application of knowledge sharing in terms of the dimensions of knowledge, culture, technology and dimensions and (2) to develop knowledge sharing features in the PMB system to support decision making quickly to increase the business value of the institution. The stages used in this KMS were The 10-Step Knowledge Management Roadmap while the evaluation of the application of KMS used the SECI model. The results obtained in this study are a system that helps new PMB officers learn the STMIK Amik Riau PMB system. so that the new PMB officer does not ask the old officer again.
Penerapan Na ̈ıve Bayes Classifier, K-Nearest Neighbor (KNN) dan Decision Tree untuk Menganalisis Sentimen pada Interaksi Netizen dan Pemeritah M. Khairul Anam; Bunga Nanti Pikir; Muhammad Bambang Firdaus; Susi Erlinda; Agustin Agustin
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i1.1092

Abstract

Pemerintah Pekanbaru saat ini sudah menerapkan teknologi dalam sistem pemerintahan, penerapannya saat ini masih mendapat keluhan dari masyarakat seperti layanan publik command center yang hanya sebagian masyarakat mengetahuinya dan penerapan cctv yang ada di Alat Pemberi Isyarat Lalu Lintas (APILL) yang belum berfungsi dengan baik. Penerapan teknologi lainnya oleh Pemerintah Pekanbaru dapat kita lihat dari keberadaan portal-portal web situs resmi Pemerintah. Sedangkan untuk melihat beragam komentar netizen dari twitter. Twitter menjadi tempat untuk mendapatkan data yang diungkapkan masyarakat melalui tweets yang diposting ke timeline. Analisa sentimen dilakukan untuk melihat pendapat atau kecenderungan opini netizen terhadap pemerintah Pekanbaru yang mengandung sentimen positif, negatif, dan netral. Data yang digunakan adalah tweet dengan jumlah dataset sebanyak 150 tweets. Data tersebut kemudian di analisa agar menjadi informasi. Analisa dilakukan menggunakan metode data mining yaitu Naïve Bayes Classifier, K-Nearest Neighbor (KNN), dan Decision tree. Penggunaan ketiga pendekatan ini berupaya untuk mengkategorikan hasil komentar netizen terkait penggunaan teknologi yang telah melalui proses analisis sentimen dan membandingkan keakuratan ketiga cara tersebut. Hasil akurasi yang didapatkan cukup beragam yaitu dari metode Naïve Bayes akurasi 100%, metode KKN akurasi 98,25%, dan metode decision tree akurasi 62,28%.
The Application of Usability Testing to Analyze the Quality of Android-Based Acupressure Smart Chair Applications M. Khairul anam; Esi Tri Emerlada; Susi Erlinda; Tashid Tashid; Torkis Nasution
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2312

Abstract

A smart chair is a reflection smart chair that utilizes waste tires as an alternative to acupuncture. Smart chairs are designed for people who are phobic about acupuncture needles by replacing these needles with waste tires. Acupuncture smart chairs also make it easier for users without having to go to the acupuncture practice place. This smart chair is equipped with an application that is directly connected to android. The smart chair application is an android-based remote control where users can control the application remotely. However, this application has not been tested so it is not yet known how effective and efficient the use of the application is. Therefore, researchers would conduct testing by using the usability testing method. The usability testing method is a method carried out to measure the ease of the application that has been made. The analysis in this method used five evaluation components, namely learnability, efficiency, memorability, errors, and satisfaction. This research would make instruments based on usability testing and then distribute instruments to samples by using sampling techniques. The results of this study showed a variable learnability value was 65% while the efficiency variable got a value of 74%. In terms of memorability, its value was 59%, then the Errors variable value was 74%, and the last variable, namely satisfaction, reached a value of 74%.
DESIGN THINKING APPROACH FOR OPTIMIZING TRANSACTION IN ANDROID-BASED CAMPUS CANTEENS M. Khairul Anam; Parlindungan Kudadiri; Hamdani Hamdani; Triyani Arita Fitri; Fransiskus Zoromi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3357

Abstract

Android is extensively used by some startups for food ordering applications, such as go food, grab food, Shopee food applications. However, the application cannot be used in a small scope such as the canteen on campus. At STMIK Amik Riau, the existing canteens still use manual methods in ordering and payment, therefore to facilitate canteen transactions, innovation was carried out, namely by using the e-canteen application. This application was created to make it easier to order menus, find out what menus are on that day and to prevent purchases without making payments. The e-canteen application had several features such as the name of the canteen, selection of available menus, menu prices, and payment processing. The making of e-canteen used a design Thinking approach. Design Thinking is a creative approach that collects ideas directly from application users. Design thinking has several stages, such as: empathize, define, ideate, prototype and test. The testing process showed how the target users interacted with the prototype that had been created. The results obtained from this study demonstrated that the e-canteen application significantly facilitated canteen services by simplifying the ordering and payment processes. Specifically, users were able to place orders more efficiently and complete payments seamlessly, which improved overall user satisfaction and operational efficiency within the campus canteen.
Co-Authors -, Tashid Abrar Hadi Ade Riyanda Putra Adi Surya Darma Agustin Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Agusviyanda Ahmad Ihsan Ahmad Tantoni Ahmad Zamsuri Ahmad Zamsuri, Ahmad Aisum Aliyah Sari Akram, Rizalul Al Amin Fadillah Sani Alfa Saleh Alfisyahrin Alfisyahrin Alkadri Masnur Ambiyar, Ambiyar Andesa, Khusaeri 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 Ayu Mahessya, Raja 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 Daryanto, Diki Dea Safitri Dedy Irfan Devi Yuliana Dewi Sari Wahyuni Dewi Sari Wahyuni Didik Sudyana Didik Sudyana Diki Daryanto Diky Daryanto Eddy Kurniawan Pradana Efrizoni, Lusiana Emerlada, Esi Tri Erlin Erlin Erlinda, Susi Ersan Fadrial, Yogi Esi Tri Emerlada Fadli Suandi Fahrul Yamani 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 Gendhy Dwi Harlyan Gubtha Mahendra Putra Gunadi Gunawan, Chichi Rizka Habibi Ulayya Hadi Asnal, Hadi Hairah, Ummul Hamdani Hamdani Hamdani - Hamdani . Hamdani Hamdani Hamdani Hamdani Hamdani Hamdani Hanif Aulia Happy Yugo Prasetiya Haris Kurniawan, Haris Hasan J. Alyamani Haviluddin Haviluddin Hazira, Nadila Helda Yeni Helda Yenni Helda Yenni, Helda Hendra Saputra Hendrawan, Riki hendri, nofri Herianto Herianto Herwin Herwin Herwin Herwin, Herwin Ike Yunia Pasa Ikhsan Ikhsan Imam Andhika Indah Mukhlis Tamara Indra Prayogo Indra Prayogo Indri Febrianti Irfan Putra Pratama Irfansyah Irfansyah Irsyad, Akhmad Irwanda Syahputra Irwanda Syahputra Irzal Arif Wisky Istianah Istianah Jamaris, Muhamad Jamaris, Muhammad Jasmarizal Jetno Harja Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Kadek Mirnawati Karfindo, Karfindo Karpen 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 Liza Fitria Lucky Lhaura Van FC Lucky Lhaura Van FC, Lucky Lhaura Lusiana Lusiana Efrizoni Lusiana Efrizoni Lusiana Lusiana M Syauqi Hafizh M. Ikhsan Wibowo Machdalena Mahamad, Abd Kadir Mahendra, Muhammad Ihza 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 Bambang Firdaus Muhammad Budi Saputra muhammad Fuad Muhammad Ikhsan Wibowo Muhammad Nur Ihwan Muhammad Wisdan Pratama Putra Muhammad Yusuf Halim Munawir Munawir Munawir Munawir Munawir Mutiana Pratiwi N.A, Randi Nadila Rahmadhani Nadya Alinda Rahmi Nadya Satya Handayani Nanda, Novianda Nanda Nariza Wanti Wulan Sari Nasrul Sani Neci Nirwanda Nisa, Aida Nora Lizarti Novi Yona Sidratul Munti Novia Arista Nu'man, Nu'man Nurhuda, Agus Tri Nurjayadi Nurjayadi Nurjayadi Nurjayadi Nurul Fadillah Nurul fadillah, Nurul Nurul Indriani Nurwijayanti Pandu Pratama Putra, Pandu Pratama Paradila, Dinda Parlindungan Kudadiri Permana, Randy Pradipta , Rahman Pranata, Angga 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 Ruri Hartika Zain Saiful Bukhori Saiyaratul Mawaddah 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 Taufik Taufik Tejawati, Andi Tengku Alvin Firdaus Teri Ade Putra Tjut Rizqi Maysyarah Hadi TM Rezaka Alfitra Torkis Nasution Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari Tri Putri Lestari, Tri Putri Triyani Arita Fitri Ulfah, Aniq Noviciate Wahyudianto, Mochamad Rizky Waksito, Alan Zulfikar Waskita, Ghozi Indra Wifra, Rizki Wirta Agustin Wirta Agustin Yaakub, Saleh Yansyah Saputra Wijaya Yenni, Heda Yesaya Twin Situmorang Yesri Elva Yogi Ersan Fadrial Yogi Yunefri, Yogi Yoyon Efendi Yuda Irawan Yudhistira, Dewangga Yumami, Eva Zainal Arifin Zeki Kurniadi zeki Kurniadi Zupri Henra Hartomi