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All Journal Riau Journal of Computer Science Al Ishlah Jurnal Pendidikan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Komunikasi : Jurnal Komunikasi ILKOM Jurnal Ilmiah INTECOMS: Journal of Information Technology and Computer Science JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Sistem Informasi dan Aplikasi JOURNAL OF SCIENCE AND SOCIAL RESEARCH Informatika : Jurnal Informatika, Manajemen dan Komputer JOISIE (Journal Of Information Systems And Informatics Engineering) Journal of Technopreneurship and Information System (JTIS) Infotekmesin Jurnal Teknologi Informasi dan Multimedia Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Community Engagement and Emergence Journal (CEEJ) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Jurnal Ilmu Komputer Journal of Applied Data Sciences Jurnal Pengabdian kepada Masyarakat Jurnal J-PEMAS Jurnal Ipteks Terapan : research of applied science and education pendidikan, science, teknologi, dan ekonomi Jurnal Rekam Medis (Medical Record Journal) Jurnal Teknik Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Telecommunication Control and Intelligent System Journal of Software Engineering and Information System (SEIS) SATIN - Sains dan Teknologi Informasi RJOCS (Riau Journal of Computer Science) Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Jurnal 7 Samudra Politeknik Pelayaran Surabaya Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) The Indonesian Journal of Computer Science Jurnal Pengabdian Masyarakat Terapan Komunikasi : Jurnal Komunikasi
Yuda Irawan
Universitas Hang Tuah Pekanbaru
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Optimasi Algoritma C5.0 untuk Peningkatan Akurasi dalam Klasifikasi Ulasan Masyarakat Terhadap Layanan BPJS Kesehatan Mohd Rinaldi Amartha; Refni Wahyuni; Yuda Irawan
JEKIN - Jurnal Teknik Informatika Vol. 5 No. 1 (2025)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v5i1.995

Abstract

Penelitian ini bertujuan untuk meningkatkan akurasi klasifikasi sentimen ulasan masyarakat terhadap layanan BPJS Kesehatan dengan mengoptimalkan algoritma C5.0 menggunakan teknik SMOTE dan XGBoost. Pengujian dilakukan dengan beberapa kombinasi, termasuk C5.0, C5.0 dengan XGBoost, C5.0 dengan SMOTE, dan kombinasi ketiganya. Hasil menunjukkan bahwa algoritma C5.0 dasar mencapai akurasi sebesar 67.18%, kombinasi C5.0 dengan XGBoost mencapai 73.55%, C5.0 dengan SMOTE memiliki akurasi 67.00%, sementara kombinasi ketiganya (C5.0, SMOTE, dan XGBoost) memberikan akurasi tertinggi sebesar 80.87%, mengungguli metode lain. Analisis sentimen mengindikasikan bahwa mayoritas ulasan cenderung negatif, menyoroti ketidakpuasan konsumen terhadap layanan BPJS Kesehatan. Peningkatan akurasi yang signifikan dengan penerapan SMOTE dan XGBoost menunjukkan bahwa penanganan ketidakseimbangan kelas dan penguatan model melalui Boosting dapat memperbaiki kelemahan algoritma C5.0. Hal ini memperjelas pentingnya strategi ensemble dalam klasifikasi teks yang kompleks. Temuan ini menunjukkan bahwa penggunaan SMOTE dan XGBoost secara signifikan dapat meningkatkan performa model, membantu dalam memahami persepsi publik secara lebih akurat.
Model Prediksi Risiko Kebakaran Hutan Menggunakan Algoritma Random Forest dengan Seleksi Fitur Lasso Regression Refni Wahyuni; Muhardi; Yulanda; Yuda Irawan
JEKIN - Jurnal Teknik Informatika Vol. 5 No. 1 (2025)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v5i1.998

Abstract

Kebakaran hutan di Indonesia telah menyebabkan kerusakan lingkungan, polusi udara, serta dampak serius pada kesehatan dan ekonomi. Penelitian ini mengembangkan model prediksi risiko kebakaran hutan menggunakan algoritma Random Forest dengan seleksi fitur melalui Lasso Regression, berdasarkan data meteorologi dari BMKG (2011-2024). Variabel utama yang digunakan meliputi temperatur rata-rata, kelembapan, curah hujan, dan kecepatan angin. Hasil evaluasi model menunjukkan akurasi 100%, dengan precision, recall, dan F1-score masing-masing 1.00 untuk semua kelas risiko kebakaran. Confusion matrix dan kurva ROC mengonfirmasi kemampuan model dalam mengklasifikasikan setiap instance tanpa kesalahan. Analisis fitur menyoroti temperatur rata-rata, kelembapan, dan curah hujan sebagai faktor utama. Model ini berpotensi menjadi komponen penting dalam sistem peringatan dini kebakaran hutan di indonesia. Penelitian ini merekomendasikan integrasi data tambahan dan implementasi real-time untuk meningkatkan akurasi dan aplikabilitas model di masa mendatang.
Analisa Prioritas Bandwidth Menggunakan Metode HTB (Hierarchical Token Bucket) Studi Kasus : SMK Taruna Mandiri Pekanbaru Yuda Irawan; Herianto; Siti Aisyah; Refni Wahyuni
SATIN - Sains dan Teknologi Informasi Vol 8 No 1 (2022): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v8i1.814

Abstract

Banyaknya kebutuhan dunia pendidikan yang mengharuskan pihak pengembang aplikasi dalam mengembangkan berbagai terobosan teknologi untuk mendukung stabilitas dalam berinteraksi. Harga Bandwitdh yang cukup tinggi menyebabkan pihak sekolah melakukan pembatasan jumlah Bandwitdh yang diberikan oleh operator. Semakin meningkatnya kebutuhan akan internet hal ini menjadi permasaalahan bagi pengguna. Permasalahannya adalah semakin banyak yang membuka situs di internet tentu akan mengurangi kuota atau paket data. Untuk menyelesaikan permasalahan ini maka dilakukan proses tahapan analisa prioritas bandwidth menggunakan metode HTB (Hierarchical Token Bucket). Metode ini mempunyai kelebihan dalam pembatasan trafik pada tiap level maupun klasifikasi, sehingga bandwidth yang dipakai level yang tinggi dapat digunakan atau dipinjam oleh level yang lebih rendah. Berdasarkan hasil analisa dan pengujian yang telah dilakukan Penulis, maka dapat disimpulkan bahwa Metode antrian Hierarchical Token Bucket dinilai lebih efektif membagi bandwidth secara adil dan merata kepada masing-masing client yang membutuhkan bandwidth, terlihat dari grafik perhitungan nilai QoS yang telah dilakukan. Dari hasil perhitungan dalam pengujian metode HTB melalui download berkas, nilai rata-rata yang diperoleh berdasarkan standar kategori TIPHON untuk indeks parameter. Throughtput indeks parameter delay bernilai 4 dengan indeks parameter jitter indeks parameter packet loss.
YOLOv12 Model Optimization for Monitoring Occupational Health and Safety in Hospital Archive Rooms Jepisah, Doni; Octaria, Haryani; Muhamadiah, Muhamadiah; Irawan, Yuda
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.v6i4.936

Abstract

The application of artificial intelligence technology in occupational safety monitoring systems within healthcare facilities has become an urgent necessity, particularly to support compliance with Occupational Safety and Health (OSH) standards in hospitals. This study aims to develop an automated detection model based on YOLOv12 to identify visual OSH elements in hospital archive rooms, such as APAR, evacuation signs, windows, and Personal Protective Equipment (PPE) including masks, gloves, and shoes. The initial dataset consisted of 2,866 documented images, which were expanded through augmentation to 6,886 images to increase data diversity and prevent overfitting. The YOLOv12 model was trained over 100 epochs using SGD as the optimization technique. The dataset was divided into three subsets training, validation, and testing in a proportional manner. Model evaluation employed metrics such as precision, recall, mAP@0.5, and mAP@0.5–0.95, supported by visualizations including the confusion matrix, F1-confidence curve, and precision-recall curve. One of the key advantages of YOLOv12 lies in its architectural efficiency and enhanced generalization capability, enabled by the integration of R-ELAN, Area Attention Mechanism, and FlashAttention. These components allow for broader receptive field processing with reduced computational complexity. Furthermore, the removal of positional encoding and adjustment of the MLP ratio make the model lighter and faster without compromising accuracy. Compared to previous versions (YOLOv8–YOLOv11), YOLOv12 demonstrates more stable and accurate performance in detecting complex OSH objects in indoor environments. The system was also implemented in a real-time user interface using Streamlit, automatically displaying personnel PPE completeness and room safety compliance status. In conclusion, the optimized YOLOv12 model has proven effective for real-time visual detection in OSH contexts. Future studies are recommended to incorporate data balancing approaches, spatial segmentation, and IoT sensor integration to expand the system’s coverage and resilience across diverse workplace conditions.
Optimization of Machine Learning Models for Risk Prediction of DHF Spread to Support Management Strategies in Urban Areas Devis, Yesica; Muhamadiah, Muhamadiah; Yulanda, Yulanda; Irawan, Yuda; Wahyuni, Refni
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.v6i4.898

Abstract

Dengue fever is an endemic disease that poses a serious threat to public health in tropical regions such as Indonesia. Efforts to control this disease require a data-based approach that is able to accurately predict the level of risk so that interventions can be targeted. This study aims to develop a predictive model of DHF risk using ensemble stacking method optimized with Optuna algorithm and integrated into an interactive dashboard based on Streamlit. The dataset used includes environmental, climate, and socio-demographic indicators from 2015 to 2024 with a total of 1,440 data entries. The preprocessing process includes normalization with Standard Scaler, feature selection using LASSO, and label data balancing with the SMOTE method. Model validation was performed using 10-Fold Cross Validation to ensure model generalization to new data. The stacking model is built with three basic algorithms, namely SVM, KNN, and Random Forest, which are combined using Logistic Regression as a meta-learner. The evaluation results show that the model is able to achieve an average accuracy of 97.57%, with high precision, recall, and f1-score values in all three prediction classes (low, medium, high). The ROC-AUC for each class also showed near-perfect performance. The implementation of the model in the Streamlit dashboard allows non-technical users such as health center or health office staff to perform regional risk prediction and obtain data-driven intervention recommendations automatically. This research not only contributes to the development of predictive technology, but also strengthens evidence-based health promotion practices in urban areas. Further research is recommended to integrate IoT-based real-time data and expand the scope of application areas.
IMPLEMENTASI SISTEM INFORMASI AKADEMIK DI PKBM AR ROYYAN UNTUK MENINGKATKAN EFISIENSI ADMINISTRASI DAN MONITORING Yuda Irawan; Refni Wahyuni; Abdi Muhaimin; M. Khairul Anam
Jurnal Masyarakat Berdikari dan Berkarya (Mardika) Vol 3 No 2 (2025): Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA)
Publisher : Fakultas Teknik, Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/mardika.v3i2.12965

Abstract

PKBM Ar Royyan menghadapi tantangan dalam pengelolaan data akademik seiring dengan peningkatan jumlah siswa dan kompleksitas administrasi. Pengelolaan data yang masih dilakukan secara manual menyebabkan inefisiensi, risiko kehilangan data, serta keterbatasan sumber daya manusia. Oleh karena itu, adopsi sistem informasi akademik digital menjadi sangat penting untuk mengatasi masalah ini. Tujuan dari kegiatan pengabdian masyarakat ini adalah meningkatkan efisiensi pengelolaan data akademik dan administrasi di PKBM Ar Royyan melalui implementasi Sistem Informasi Akademik (SIAKAD). Selain itu, kegiatan ini bertujuan menjamin keamanan dan keberlanjutan data, serta meningkatkan kapasitas teknologi informasi di sekolah melalui pelatihan penggunaan sistem digital. Hasil kegiatan menunjukkan bahwa penerapan SIAKAD secara signifikan berhasil meningkatkan efisiensi pengelolaan data dan mempercepat proses administratif. Meskipun terdapat tantangan infrastruktur dan keterampilan teknologi, masalah tersebut berhasil diatasi melalui pelatihan dan dukungan teknis. Implementasi ini juga mendorong transparansi dan memberikan contoh bagi sekolah lain di wilayah tersebut dalam memanfaatkan teknologi untuk meningkatkan kualitas pendidikan. Secara keseluruhan, kegiatan ini membangun fondasi bagi pengembangan teknologi pendidikan yang berkelanjutan di masa depan.
Sistem Komunikasi Mikrokontroler dan PLC Berbasis Komunikasi Serial Host Link dan Protokol C-Command RS232 Ruwahida, Dewi Rizani Ruwahida; Rachman, Isa; Widodo, Hendro Agus; Adhitya, Ryan Yudha; Irawan, Yuda
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1924

Abstract

The communication between microcontrollers and PLC has become an important technology development that needs to be enhanced. One of the reasons for the communication between these two devices is to facilitate the input process of data or information from sensors, which are responsible for detecting or measuring specific parameters. Not all sensors can be directly read by PLC, as some sensors have their own communication protocols or specific libraries that are not directly supported by PLC. Microcontrollers are often used as intermediaries between sensors and PLC. Microcontrollers can read sensor data and then convert it into a format that can be understood by PLC. Microcontrollers can perform flat processing tasks such as conversion and status evaluation to provide more relevant data, and then send this data to the PLC through a compatible communication protocol. In this study, the communication protocol used is the Host Link serial communication using the C-mode Command method. The communication testing conducted using 10 different data samples resulted in accurate values with an error percentage of 0%.
Multimodal Deep Learning and IoT Sensor Fusion for Real-Time Beef Freshness Detection Kurniawan, Bambang; Wahyuni, Refni; Yulanda, Yulanda; Irawan, Yuda; Habib Yuhandri, Muhammad
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.v6i4.977

Abstract

Beef freshness quality is one of the important indicators in ensuring food safety and suitability. However, conventional methods such as manual visual inspection and laboratory testing cannot be widely applied in real-time and mass scale. To overcome these challenges, this study proposes a meat freshness detection system based on a multimodal approach that combines visual imagery and gas sensor data in a single IoT-based framework. This system is designed by utilizing the YOLOv11 architecture that has been optimized using the Adam optimizer. The dataset consisted of 540 original beef images, expanded into 1,296 images after augmentation. The model is trained on these augmented images and is able to achieve detection performance with a mAP@0.5 value of 99.4% and mAP@0.5:0.95 of 95.7%. As a further improvement, the cropped image features from the YOLOv11 model are processed through a combination of the ViT model and CNN to classify the level of meat freshness into three classes: Fresh, Medium, and Rotten with an accuracy of 99%. On the other hand, chemical data was obtained from the MQ136 and MQ137 gas sensors to detect H₂S and NH₃ levels which are indicators of meat spoilage. Data from visual and chemical data were then combined through a multimodal fusion method and classified using the Random Forest algorithm, producing a final prediction of Fit for Consumption, Need to Check, and Not Fit for Consumption. This multimodal model achieved a classification accuracy of 98% with a ROC-AUC score approaching 1.00 across all classes. While the proposed system achieved very high accuracy, further validation across diverse real-world environments is recommended to establish its generalizability.
Aplikasi Pengarsipan Surat Masuk dan Surat Keluar Berbasis Web pada SMP Negeri 32 Pekanbaru Yulisman, Yulisman; Wahyuni, Refni; Irawan, Yuda
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 3 No. 4 (2020): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Archiving incoming and outgoing mail is very important in an organization, especially for institutions such as SMP Negeri 32 Pekanbaru. The filing of letters at SMP Negeri 32 Pekanbaru is still done by writing incoming and outgoing letters on the agenda book and storing letters in filing cabinets, making it difficult to find old letter archives and often losing letters. The purpose of this research is to find the right solution so that the archiving of incoming and outgoing mail at SMP Negeri 32 Pekanbaru is more effective and efficient by making an application for archiving incoming and outgoing mail. The method used in this research is the system development model method, namely the Waterfall Model. The application design and analysis model uses the UML (Unified Modeling Language) model which is an object-oriented language or OOP (Object Oriented Programming). Application development and development uses a static programming language, namely PHP (Hypertext Pre-processor) and MySQL as application database. The results of the research on the making of incoming and outgoing mail archiving applications are very helpful and easier for SMP Negeri 32 Pekanbaru in filing incoming and outgoing mail, especially the Administration (School Administration) section because letter archiving is already stored in the database. The conclusion is that the application is very easy and helpful in archiving incoming mail and this letter is evident from the user's assessment of the application with a value of 92% more effective and efficient.
Penyuluhan Cyberbullying dan Etika Digital bagi Siswa Sekolah Dasar di SDIT Ar Royyan Pekanbaru Riau berbasis Teknologi Interaktif Wahyuni, Refni; Irawan, Yuda
Jurnal Pengabdian Masyarakat Terapan Vol 2 No 3 (2025): JUPITER Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.2.3.92

Abstract

Penggunaan teknologi digital yang semakin meluas di kalangan siswa sekolah dasar memberikan peluang besar dalam proses pembelajaran, namun juga menghadirkan risiko serius berupa cyberbullying dan perilaku bermedia yang tidak etis. Permasalahan yang ditemukan di SDIT Ar Royyan Pekanbaru menunjukkan bahwa banyak siswa terlibat dalam tindakan seperti ejekan di media sosial, komentar kasar, penggunaan bahasa tidak sopan saat bermain game daring, hingga tindakan lain seperti penyebaran pesan bernada merendahkan dan pelecehan verbal digital. Minimnya literasi digital, rendahnya etika berinternet, serta kurangnya edukasi formal mengenai keamanan digital menjadikan siswa rentan menjadi pelaku maupun korban perundungan siber. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman siswa mengenai bahaya cyberbullying dan menanamkan etika digital melalui pendekatan edukatif dan interaktif berbasis teknologi. Metode kegiatan meliputi presentasi visual, video edukatif, diskusi kelompok, kuis digital, serta roleplay yang menggambarkan kasus nyata seperti flaming, harassment, trolling, impersonation, dan outing. Kegiatan diikuti oleh 30 siswa kelas IV dan V, diawali dengan pre-test yang menunjukkan hanya 45% siswa mampu mengidentifikasi bentuk-bentuk cyberbullying beserta dampaknya. Setelah penyuluhan, hasil post-test meningkat signifikan menjadi 87%. Selain peningkatan kognitif, observasi lapangan menunjukkan perubahan sikap positif, seperti meningkatnya kehati-hatian siswa dalam berkomentar, menurunnya penggunaan bahasa kasar saat bermain daring, serta tumbuhnya empati terhadap korban cyberbullying. Guru pendamping juga melaporkan bahwa siswa mulai lebih terbuka dalam membicarakan pengalaman digital mereka dan meminta bimbingan dalam menggunakan media sosial dengan bijak. Kegiatan ini membuktikan bahwa pendekatan edukatif berbasis teknologi, dipadukan dengan metode partisipatif seperti roleplay dan gamifikasi, sangat efektif dalam meningkatkan literasi digital, kesadaran etika bermedia, dan kemampuan siswa dalam mengenali serta mencegah berbagai bentuk cyberbullying.
Co-Authors -, Herianto A.A. Ketut Agung Cahyawan W Abdullah Mitrin Achmad Deddy Kurniawan Achmad Nizar Hidayanto Adhitya, Ryan Yudha Aditya Rickyta Adyanata Lubis Afresi Yunita Agnita Utami Agus Alamsyah Ahmad Fauzan Azim Akbar, Amri Akhmad Zulkifli Aldiga Rienarti Abidin Anam, M Khairul Andre Wahyu Novrianto Anisa, Lia Anita Febriani Aprilia, Ulfa Areta Sonya Rahajeng Arfianto, Afif Zuhri Arnawilis Arnawilis Arnawilis Bakhrizal Bambang Kurniawan Bayu Saputra Budy Mustika Debi Setiawan, Debi Desi Rahmawati Devis, Yesica Dhea Arina Ramadhini Dhini Septhya Diandra, Roni Edriyansyah Eka Sabna Elisawati, Elisawati Fachry Abda El Rahman Fatmawati, Kiki Fitri, Imelda Fonda, Hendry Gilang Citra Lenardo Habib Yuhandri, Muhammad Hadi Asnal, Hadi Hafizh Sallam Hamdani Hamdani Hamid, Abdurrahman Hartomi, Zupri Henra Hasnor Khotimah Hayami, Regiolina Hendro Agus Widodo, Hendro Agus heri, Herianto Herianto Herianto Herianto Herianto - Herianto Herianto Herianto Herianto Hidayati Kurnia Fitri Hohashi, Naohiro Irawan, Rina Irwanda Syahputra Jamaris, Muhamad Jenli Susilo Jenni Oinike Br Sitorus Jepisah, Doni Jeri Trio Sentana Junadhi Junadhi Junadhi Junadhi Junadhi, Junadhi Khairunisa Khairunisa Khairunisa, Khairunisa Kharisma Rahayu Kurniawan, Bambang Leonita, Emy Lia Anisa Lubis, Mustopa Husein Lucky Lhaura Van FC, Lucky Lhaura Mardainis Mardeni Mardeni Mardeni, Mardeni Matthijs B Punt Maulita Yulia Sari Mbunwe Muncho Josephine Mbunwe Muncho Josephine Melyanti, Rika Mitrin, Abdullah Mohd Rinaldi Amartha Muhaimin, Abdi Muhamadiah, Muhamadiah Muhammad Bambang Firdaus Muhardi Muhardi - Muhardi Muhardi Muhardi Muhardi Mulya Rispani Mutiara Sari, Ria Naima Belarbi Naima Belarbi Nella Sari Nico Chandra Nopriadi Noratama Putri, Ramalia Nurhadi Nurhazimah Rafiah Octaria, Haryani Oktavia Dewi Ordila, Rian Perkasa, Reza Prihandoko, P Purnomo, Nopi Purwanti, Siti Putra Rahmaddeni Rahmaddeni Rahmaddeni Rahmaddeni Rahmalisa, Uci Rahman, Rudi Refni Wahyuni renaldi, reno Renaldi, Reno Reza Perkasa Rian Ordila Rian Ordila Riananda, Dimas Pristovani Richi Andrianto Rickyta, Aditya Rofiqoh, Ummi Rometdo Muzawi, Rometdo Roni Diandra Rudi Rahman Ruwahida, Dewi Rizani Ruwahida Sabna, Eka Sakroni Indra Gunawan Salsabila Rabbani Saputra, Haris Tri Sarjon Defit Sentana, Jeri Trio Siti Aisyah Siti Aisyah Siti Purwanti Sugiati Suherman Sohor Suherman Suherman Suriandi Suriandi Susanti, Susanti Susi Oustria Simamora Susilo, Jenli Syamsul Arifin Uci Rahmalisa Ulfa Aprilia Utami, Urfi Vindi Fitria Winda Herrianti Manullang Winda Sari Wulan Sari Yesica Devis Yuhandri, Y Yulanda Yulanda Yulanda Yulanda, Yulanda YULISMAN Yulisman, Yulisman Yunior Fernando Zufari, Faisal Zufi Pratama Noviardi Zupri Henra Hartomi