Article Per Year (5 Year)
p-Index From 2021 - 2026
15.317
P-Index
This Author published in this journals
All Journal Jurnal Media Infotama Telematika : Jurnal Informatika dan Teknologi Informasi Rekursif: Jurnal Informatika Jurnal Pseudocode Jurnal Informatika Upgris Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL PENDIDIKAN TAMBUSAI Jurnal Ilmiah Pendidikan dan Pembelajaran Jurnal Sistem Cerdas JSAI (Journal Scientific and Applied Informatics) Journal of Technopreneurship and Information System (JTIS) Jurnal Pengabdian Masyarakat Bumi Raflesia Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Applied Computer Science and Technology (JACOST) Jurnal Abdimas Serawai Decode: Jurnal Pendidikan Teknologi Informasi EXPLORER Jurnal Multidisiplin Dehasen (MUDE) International Journal of Education and Social Science (IJESS) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sistem Informasi Dan E-Bisnis Jurnal Ilmu Komputer Dan Informatika Jurnal Media Computer Science JIMAKUKERTA JURNAL BESEMAH Mestaka: Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan dan Pengabdian Masyarakat JPNM : Jurnal Pustaka Nusantara Multidisiplin Cendikia Pendidikan Jurnal Informatika: Jurnal Pengembangan IT GEMBIRA (Pengabdian Kepada Masyarakat) RESLAJ: Religion Education Social Laa Roiba Journal JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Jurnal Pengabdian Masyarakat Ilmu Komputer International Journal of Information Technology and Business Jurnal TAM (Technology Acceptance Model) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) JCOSIS (Journal Computer Science and Information Systems) Jurnal Komputer, Informasi dan Teknologi
Wijaya, Ardi
Program Studi Teknik Informatika, Fakultas Teknik Universitas Muhammadiyah Bengkulu, Bengkulu, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 124 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 124 Documents
Search

 6   7   8   9   10 
Pendeteksian Penyakit pada Daun Cabai dengan Menggunakan Metode Deep Learning Rosalina Rosalina; Ardi Wijaya
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.2857

Abstract

Chili is one of the most essential horticultural plants in Indonesia. In addition to the lack of supply of plants, the price of chili on the market has increased dramatically. The shortage is affected by unpredictable climate changes, which have to result in many chili plants suffering from crop failure. It was because the disease infects chili plants so that harvests are decreased. This work would incorporate Deep Learning for image processing in Disease Detection Systems. This disease detection method will be used to help users, in particular chili farmers, identify whether or not the leaves of their chili plants are contaminated with the disease. This system would take a picture of chili leaf using a Raspberry Pi camera and implement image processing on the chili leaf image to collect valuable information on the image to find out whether or not the chili leaf is contaminated with the disease. The purpose of this research is to make a desktop application for a disease detection system that has the ability to detect whether or not a chili leaf is infected by several diseases, display the condition of the chili leaves, display the type of disease that infects the chili leaves (if any), and provide a percentage probability of the system in detecting the image of the chili leaves correctly (whether it is healthy chili leaves or sick chili leaves). The system reaches 100 percent accuracy with good brightness and distance less than 1 meter, while the system reaches 68.8 percent accuracy with poor brightness and distance greater than or equal to 100 percent. Keywords— chili leaf; deep learning; disease detection; raspberry pi
Perbandingan Metode KNN dan Naïve Bayes dalam Deteksi Tingkat Stres Berdasarkan Ekspresi Wajah Alamsyah, Malik Fajar; Wijaya, Ardi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8513

Abstract

Stress is a feeling in which a person feels under pressure, overwhelmed, and has difficulty in dealing with a problem. Stress can be caused by various factors, such as academic pressure, work, personal problems, or social environment. If not addressed immediately, stress can have adverse effects on an individual's health, such as causing high blood pressure, heart disease, sleep disturbances, and a decreased immune system, which makes a person more vulnerable to various diseases. Therefore, monitoring stress levels is very important to prevent more serious negative impacts. Generally, stress detection is done through consultation with a psychologist, but this method has a subjective nature and requires a lot of time and money. Therefore, this research develops a computer vision-based stress detection system using OpenCV and Dlib, with K-Nearest Neighbors and Naïve Bayes algorithms. The data of 500 samples is divided into 80% training data and 20% test data. Features were extracted, and stress was classified into three levels: low, medium and high. Evaluation using k-fold cross-validation (n_split=10, random_state=42) based on accuracy, precision, recall, and F1-score. The results showed that K-Nearest Neighbors with k=5 excelled with 74% accuracy, 73% precision, 73% recall, and 73% F1-score. Meanwhile, Naïve Bayes only achieved 52% accuracy, 51% precision, 48% recall, and 41% F1-score. This shows that KNN is more effective in stress level classification. However, the accuracy of the model is still limited due to the small amount of training data. Parameter optimization and dataset addition are required to improve the overall system performance.
PELATIHAN CANVA SEBAGAI MATERI PEMBELAJARAN UNTUK SISWA SMP N 01 BENGKULU TENGAH Ardi Wijaya; Pandu Sujaba; Vicky Victori; Novan Gilang Ramadhan; Muhammad Kurrata A’yunin; Kusuma Putra Al Pharisie
JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Vol. 5 No. 1 (2025): April
Publisher : Lembaga Penelitian Pengabdian Masyarakat Penerbitan dan Percetakan Indonesian Scholar Khiar Wafi (LPPMPP IKHAFI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jpmtt.v5i1.565

Abstract

SMP negeri 01 kota Bengkulu Tengah dengan Nomor Pokok Nasional (NPSN) 10700229 beralamat di jalan raya pasar pedati km 10.5, Kelurahan Pasar Pedati, Kecamatan Pondok Kelapa, Bengkulu Tengah. SMP Negeri 01 Bengkulu Tengah terletak tidak jauh dari pusat kota. Penelitian ini bertujuan untuk mengkaji penggunaan aplikasi Canva sebagai media pembelajaran kreatif di SMP 01 Bengkulu Tengah. Canva adalah aplikasi berbasis desain grafis yang menawarkan berbagai fitur untuk membuat presentasi, infografis, dan materi pembelajaran interaktif. Penerapan aplikasi ini di lingkungan SMP bertujuan untuk meningkatkan keterampilan digital siswa, memperkaya pengalaman belajar, serta mendorong kreativitas dan kolaborasi. Metode penelitian yang digunakan adalah pendekatan kualitatif dengan pengumpulan data melalui observasi, wawancara, dan studi dokumen. Hasil penelitian menunjukkan bahwa siswa mampu memanfaatkan Canva untuk membuat desain yang menarik, seperti poster dan presentasi, yang relevan dengan materi pelajaran. Selain itu, guru menyatakan bahwa penggunaan Canva mempermudah penyampaian materi dan meningkatkan antusiasme siswa dalam belajar. Kesimpulannya, aplikasi Canva memiliki potensi besar untuk diintegrasikan dalam proses pembelajaran sebagai media yang efektif dan inovatif. metode yang di gunakan ini iyalah sebagai mana mempresentasikan materi canva untuk menjelaskan cara dalam penggunaan canva, Hasil dari, Kegiatan PKM ini berhasil dilaksanakan dengan lancar dan mendapatkan respons positif dari siswa dan pihak sekolah. Dengan pelatihan ini, diharapkan siswa memiliki kemampuan baru yang dapat digunakan untuk mendukung pembelajaran mereka
IMPLEMENTATION OF BILATERAL FILTERING FOR AESTHETIC ENHANCEMENT OF FACIAL IMAGES Wijaya, Ardi; Febriani, Lovi; Muntahanah, Muntahanah; Veronika, Nuri David Maria
Jurnal TAM (Technology Acceptance Model) Vol 16, No 1 (2025): Jurnal TAM (Technology Acceptance Model)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jurnaltam.v16i1.1803

Abstract

Digital image is a representation of an image in the form of pixels arranged in a matrix. The image processing process includes acquisition, analysis, and manipulation to produce the desired output. In photography and social media, digital images play an important role in attracting attention. However, photos often experience problems such as noise and uneven lighting, which can reduce image quality. Therefore, image enhancement is needed to overcome these problems. The Bilateral Filtering method is one of the techniques that is very effective in reducing noise by considering the special distance and intensity differences between pixels, so that it can maintain the clarity of important elements in the image. This study aims to implement this technique in improving the aesthetics of facial images and evaluate its effectiveness in producing more attractive and high-quality images. from 50 datasets taken. The results of the study showed that Bilateral Filtering was able to improve the clarity of facial images without eliminating important details. The evaluation was carried out using image quality parameters such as PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index), which showed an increase in quality after the application of this method. In terms of user satisfaction, the results of the questionnaire showed that the satisfaction level reached 86.38%, which based on Table 5 is included in the "very good" category. Thus, the Bilateral Filtering method not only successfully improves the image quality without losing important details on the face. Objectively, but also provides high satisfaction for users in terms of aesthetics and visual comfort.
Combination of Deep Neural Network and YuNet for Python-Based Human Lifespan Prediction Apridiansyah, Yovi; Ardiansyah, Adidi Muhammad; Wijaya, Ardi
Telematika Vol 22 No 1 (2025): Edisi Februari 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i1.14510

Abstract

Purpose: In this research on face detection, many methods face challenges in the accuracy of age prediction due to the complexity of facial features that are influenced by factors such as lighting, expression, and image quality. Therefore, this research focuses on developing more accurate and efficient methods by utilizing Deep Neural Network (DNN) and YuNet. The purpose of this study is to develop a face recognition model in detecting and determining human age automatically using Python with the DNN method to study facial patterns in determining human age precisely and integrate the YuNet library as a lightweight face detection framework that is efficient in the identification process.Design/methodology/approach: In this study, a system was created for predicting human age using the Deep Neural Network method which functions to predict age based on facial patterns in images and the Yunet method as a facial image detector. The stages of this research start from taking pictures, installing python libraries, namely opencv, face detection process, and age detection process.Findings/result: The results of the study show that the DNN and YuNet methods have tested as many as 50 samples in the form of photos of human faces taken at a distance of half a meter, so by using the DNN and YuNet methods, researchers have succeeded in obtaining the age of the human face through the image processing process which can then obtain an accuracy level or Precission of 80% and the accuracy level of success between the prediction value and the actual value given by the system is 80%.Originality/value/state of the art: In this study, the system uses Python tools where in the face detection process using the YuNet method, this method is used because YuNet can directly detect facial features in the image and is lightweight in operation. In terms of DNN prediction, it functions as a method that can predict age based on the results of facial image detection. In this study, a dataset was also used for 50 facial samples that were tested for accuracy using the confussion matrix by looking for precission, recal, and accuracy values. 
Analysis of MP3 Bitrate on the Accuracy of Academic Audio Transcription Using Whisper large-v3 Selta Jaya Putra; Wijaya, Ardi; Alam, RG. Guntur
Jurnal Sistem Cerdas Vol. 8 No. 2 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i2.528

Abstract

In the digital era, automatic transcription is a crucial solution for converting audio content into text, especially in the context of academic documentation. The main challenge in this process is transcription accuracy, which can be affected by the quality of the audio file, including its bitrate and file size. This study aims to analyze the impact of MP3 bitrate and file size on transcription accuracy using the Whisper large-v3 model. Five academic audio files were converted into five different bitrate levels, ranging from 64 kbps to 320 kbps, and then transcribed automatically using the Whisper model. Evaluation was conducted by calculating the Word Error Rate (WER) as an indicator of transcription accuracy. In addition, processing time and file size were recorded to analyze transcription efficiency. The results show that increasing bitrate does not always lead to higher accuracy. Bitrates of 128–192 kbps provided the best balance between transcription accuracy, processing efficiency, and file size. This study makes a significant contribution to the development of automatic transcription systems based on ASR models, particularly for audio documentation needs in educational institutions. These findings serve as a technical reference for developing efficient and accurate audio documentation systems in academic environments.
Deteksi Keaslian Uang Kertas dengan Pengolahan Citra Cigital Mengunakan Metode Canny Bagaskoro, Siswo; Veronika, Nuri David Maria; Darmi, Yulia; Wijaya, Ardi
Jurnal Pendidikan Tambusai Vol. 9 No. 3 (2025): Desember
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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

Abstract

Uang adalah alat bantu tukar atau standar dari pengukur nilai (kesatuan hitungan) yang sah, dikeluarkan oleh pemerintah suatu negara berupa kertas, emas, perak atau logam-logam lain yang dicetak dengan bentuk dan gambar tertentu. Deteksi adalah suatu proses untuk memeriksa atau melakukan pemeriksaan terhadap sesuatu dengan menggunakan cara dan teknik tertentu. Seiring dengan kemajuan teknologi informasi, kriminalitas yang memanfaatkan teknologi juga berkembang. Pengolahan citra digital saat ini telah berkembang kegunaannya untuk melakukan sistem pengenalan terhadap kemungkinan gangguan kriminalitas, terutama untuk pengenalan objek yang unik, pada uang kertas rupiah. Proses deteksi dimulai dengan akuisisi citra uang kertas yang kemudian diproses melalui beberapa tahap pengolahan citra, termasuk konversi ke skala abu-abu, perbaikan kualitas citra, membuat suatu objek, dilasi operasi untuk memperbesar lapisan segmen objek dengan menambahkan lapisan di sekeliling objek, erosi unruk megikis objek, ekstraksi ciri dan pendeteksian tepi menggunakan algoritma Canny. Hasil dari metode Canny kemudian digunakan untuk membandingkan fitur-fitur citra uang kertas dengan basis data citra uang asli yang telah diverifikasi. Sistem ini diuji dengan berbagai denominasi uang kertas dan kondisi pencahayaan yang berbeda untuk mengevaluasi keandalan dan ketepatannya. Hasil uji coba menunjukkan bahwa metode ini berhasil mendeteksi keaslian uang kertas dengan tingkat akurasi yang tinggi mencapai 85.71%, dengan tingkat kesalahan yang minimal dibandingkan dengan teknik deteksi lainnya. Kesimpulannya, pengolahan citra digital dengan metode Canny adalah alat yang efektif dan efisien untuk meningkatkan keamanan finansial melalui deteksi keaslian uang kertas.
Analisis Performa, Overload dan Kerentanan Pada Website Basarnas Bengkulu Untuk Optimalisasi Kinerja Cheka, Julyane Kevin; Toyib, Rozali; Wijaya, Ardi; Muntahanah
Jurnal PROCESSOR Vol 20 No 2 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.2.2507

Abstract

The Bengkulu Basarnas website plays a crucial role in providing information related to search and rescue activities to the public. However, with the increasing number of visitors and the need for fast and accurate information, the site faces several challenges related to performance, overload, and vulnerabilities such as slow page load times, a website that tends to be unresponsive, and indications of defacement, which are certainly detrimental. Therefore, research was conducted with the aim of analyzing and providing recommendations for optimizing website performance. Implementing the Software Testing Life Cycle (STLC) method, a method used for software testing, and assisted by tools such as PageSpeed Insights, Apache Jmeter, and Acunetix, enabled the research to be conducted comprehensively and efficiently. The results obtained an average performance score of 81.87, which is included in the good range but still needs improvement. On overload, the research results were obtained, namely scenario 1 with 5 users (105 samples) there was 0.00% error, scenario 2 with 15 users (315 samples) there was 0.32% error, and scenario 3 with 45 users (945 samples) there was 1.90% which overall shows that website performance is still quite good at low loads but decreases at high loads. And on vulnerabilities, the research results were in the Low severity vulnerabilities category, which means there are minor vulnerabilities and are still relatively safe but still need to be followed up for prevention efforts. Based on these findings, it is recommended to pay attention to server infrastructure, optimize content or images, and improve and pay attention to system security in order to minimize vulnerabilities to prevent threats and attacks that can disrupt website performance.
Penerapan Qr Code Geolocation Pada Presensi Dosen Fakultas Teknik Universitas Muhammadiyah Bengkulu Rajes Andika Putra; Yovi Apridiansyah; Ardi Wijaya; RG. Guntur Alam
JCOSIS (Journal Computer Science and Information Systems) Vol. 1 No. 1 (2024): Mei
Publisher : Institute for Research and Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61567/jcosis.v1i1.177

Abstract

Tujuan : Proses presensi merupakan suatu hal yang sering dilakukan setiap orang yang bekerja baik di pemerintahan maupun swasta. Pada dasarnya proses presensi menggunakan presensi manual ada juga yang telah menggunakan finger print sehingga memudahkan dalam melakukan presensi Metode/Design/Pendekatan: Di Fakultas Teknik UM Bengkulu juga sudah menggunakan system presensi dosen menggunkan finger print, akan tetapi di masa pandemic covid-19 ini seluruh kegiatan belajar mengajar banyak yang melaksanakan secara daring, sehingga dalam penelitian ini menerapkan sistem absen dengan Qr Code dan geolocation untuk mengetahui lokasi dari dosen yang melakukan absen. Qr Code yang berarti kode yang bisa menyampaikan informasi secara cepat yang bertujuan untuk mengevaluasi kinerja dosen dalam kedisiplinan kerja Hasil/Temuan: Dari penelitian ini juga menghasilkan sistem aplikasi presensi dengan menerapan QR Code Geolocation Pada Presensi Dosen Fakultas Teknik Universitas Muhammadiyah Bengkulu, Dapat memberikan informasi hasil evaluasi kinerja dosen dengan menerapan QR Code Geolocation Pada Presensi Dosen Fakultas Teknik Universitas Muhammadiyah Bengkulu, evaluasi tersebut berupa cetak riwayat yang ada pada system, serta Meningkatkan disiplin dosen dalam kegiatan belajar dan bertanggung jawab dalam bekerja dengan adanya sistem presensi geolocation ini. Kebaharuan/Originalitas/Nilai: Dengan penelitian ini maka dapat memberikan informasi presensi dengan tingkat keberhasilan sistem berdasarkan tingkat evaluasi mencapai tingkat keberhasilan 85%. Keywords: QR, geolocatioan, presensi
Implementasi Algoritma A-Star Untuk Menentukan Jalur Evakuasi Bencana Banjir (Kelurahan Semarang Kec. Sungai Serut) Kota Bengkulu Elly Hertita; Yulia Darmi; Ardi Wijaya; Surya Ade Saputera
JUKOMIKA (Jurnal Ilmu Komputer dan Informatika) Vol. 7 No. 1 (2024): Juni 2024
Publisher : LPPMPP Yayasan Sejahtera Bersama Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54650/jukomika.v7i1.551

Abstract

Kota Bengkulu merupakan salah satu daerah yang sering terjadi banjir akibat meluapnya Air Bengkulu (Sungai Bungkulu). Hampir setiap tahun, Kota Bengkulu mengalami dua hingga tiga kali banjir yang menggenangi sekitar 400 hektar wilayahnya. Kelurahan Semarang, Kec. Sungai Serut merupakan salah satu daerah yang sering terjadi bencana banjir di Provinsi Bengkulu. Hal ini disebabkan tidak adanya penyerapan air akibat pengerukan sungai (untuk batu bara) yang terus menerus dan karena letaknya yang relatif rendah di atas permukaan laut saat hujan. Air menggenang dan banjir terjadi karena kurangnya drainase. Banjir ini lebih sering terjadi bukan hanya karena faktor ketinggian, tapi juga karena meluapnya air sungai ke wilayah kelurahan Semarang kec. Sungai Serut Kota Bengkulu. Oleh karena itu diperlukan jalur evakuasi sehingga semakin cepat evakuasi dilakukan, semakin besar kemungkinan jumlah orang yang dapat diselamatkan dari bencana tersebut. Algoritma A* adalah satu metode yang cukup sering digunakan untuk mencari rute terpendek dari suatu titik menuju titik lainnya. Algoritma A* juga dapat digunakan untuk menentukan rute terpendek untuk jalur evakuasi bencana banjir. Penelitian ini bertujuan untuk Menentukan Jalur Evakuasi Bencana Banjir di Kelurahan Semarang Kec. Sungai Serut Kota Bengkulu menggunakan Algoritma A (a-star) dan membantu daerah Kelurahan Semarang kec. Sungai Serut Kota Bengkulu dengan mudah dan cepat dalam pencarian rute terpendek tempat evakuasi bencana banjir. Dari penelitian ini dapat disimpulkan bahwa penelitian ini dapat memberikan informasi jalur terpendek tempat evakuasi bencana banjir menggunakan metode Algoritma A (a-star) untuk menentukan rute terpendek dalam evakuasi bencana banjir dan dapat mencari rute terdekat dari suatu lokasi menuju lokasi lainnya yang dimana terdapat lokasi yang dapat dilewati dan lokasi tidak dapat di lewati dan melakukan pencarian. Dari hasil pengujian, diperoleh jawaban sangat menarik 47 %, menarik 45 %, dan tidak menarik 8%.
Co-Authors A.R. Walad Mahfuzhi Abdul Syukur Abdullah, Dedy Ade Ferdiansyani Ade Saputra Adedio, Rangga Affandi Mussa, Anitya Putri Afrizal Afrizal Agus Setiawan Agustio, Faidillah Ahmad Novianto Aji Setiyadi Alam, RG.Guntur Alamsyah, Malik Fajar Aldi Gustomi Alfarrizi, Jhodie Ali Sutan Pane Andilala Andre Mefriansyah Anes Meyzera Anggara, Muhammad Andre Angtyas Candra Pratama Anisa Fhadila Anita Septiani Putri Anita Septiani Putri Aprianti, Zalia Apridiansyah, Yovi Ardiansyah, Adidi Muhammad Ardoni, Yoan Ari Purjiawan Arif Setiawan Aripun Arjun Putra Nandika Army Martia Harjuna Arya Gilang Ramadhan Avida, Meny Bagaskoro, Siswo Bryan Febriansyah Cecep Saputra Chahima Gustina Chandra Kusuma Johan2 Cheka, Julyane Kevin Daffa Putra Sadhevi Dandi Sunardi Darnita, Yulia Darsah Wendanado David Maria Vironika, Nuri Dede Erawan Dedy Abdullah Dedy Abdullah Deki Rahmat Della Rahma Della Dendi Pranata, Dendi Pranata Dendy Pratama Dian Ariestanto Diana Diana Diana Diana M.Kom Dimas Andrean Saputra Dinda Putri Dita, Willia Cahaya Doli Juliadi Dwita Deslianti Dwy Mutia Dita Dwy Mutia Dita Eka Sahputra Elly Hertita Elly Hertita fadila, selvana Fadli, Rengga Fadlikal Ilham Aditma, Afredo Febitri, Nora Febriani, Lovi Feni, Rita Fernando, Jerry Franata, Heru Gading Cempaka Gugi Walus Riman Gunawan Gunawan Gunawan Gunawan Gunawan Guntur Alam Gustomi, Aldi Habiel Fachrozzy Hariani, Merti Sri Harry Witriyono Harry Witriyono Hendri Wibowo, Sastya Hennie Lestyaningsih Heru Franata Heru Franata hidayah, agung kharisma Iffah Zafira Jannati Ilpiklus Andika Putra Ilpiklus Andika Putra Imelia Okta Rama Yanti Indra Setiawan Irsyad Ahmad Fauzan Janati, Iffah zafira Jeri Fernando Winata Jerry Ario Zhonata Jerry Fernando Jestika Safitri Juhardi , Ujang Juhardi, Ujang Julfi Siswanto Juliza, Sita Khairullah khairullah Kharisma , Agung Khoiriah nur aisyah Kirman Kirman Kirman, Kirman Kontesa, Ronaldo Kornengsih, Resnita Kurniawan, Edo Kusuma Putra Al Pharisie Lestri Yanti Liza nurpatmala M Rafli Yudhatama M Sapta Pirdaus M Yusuf Ramadhan M. Dhaffa Ghiffari M. Dhaffa Giffari M. Gilang Ramadhan M. Gilang Ramadhan M. Husni Rifqo M. Khairul Razikin M. Sapta Firdaus M. Sapta Firdaus Marhalim marhalim, marhalim Maskuri Sutomo Maulana, M Fiqri Mawarni, Shindy Meny Avida Merti Sri Hariani Metrisza Yona Saputra Meyzera, Anes Mohammad Abkar Nur Rohman Mohammad Candra wiliam Muhamad Abdul Fajri Muhammad Aksyah Muhammad Andre Anggara Muhammad Febriansyah Muhammad Hikmal Febrian Muhammad Husni Hidayat Muhammad Husni Rifqo Muhammad Husni Rifqo Muhammad Imanullah Muhammad Kurrata A’yunin Muhammad Miatsyah Muhammad Naufal Al Fadhil Muhammad Naufal Al Fadhil Muhammad Rafi Aldan Pratama Muhammad Rifqo Muhammad Teguh Satrio Mulyadi, Maheran Muntahanah Muntahanah Muntahanah, Muntahanah Mutiara Hikmah Nadia Berliana Nagita Efprillia Nhadya Vita Loca Nirina Nurhazelin Noris Feter Novan Gilang Ramadhan Nur'aini Nur'aini Nur'aini, Nur'aini Nurhayati Nurhayati Nuri David Maria Veronica Nuri David Maria Veronika Nuri David Maria Veronika Nurwijayanti Nyko Condro Dinoto M.N Pahriza Pahriza Pahrizal Pahrizal Pahrizal Pahrizal Pahrizal, Pahrizal Pandu Sujaba Pasha Osama F Fatona Pindo Putra Pratama Pitria Hasanah Pratama, Rindi Yudha Prayoga Putra Puji Rahayu Putra, Erwin Dwika Putra, Muhammad Ardiansah Putra, OJi Herwanda Putra, Riky Ade Putri Rahma Della Putri, Dinda Raffles, Richard Rahmat, Deki Rajes Andika Putra Ramzi, Reja Muhamad Randi Randi Afri Nandes Randi Trio Ardiansyah Rasyid, Muhammad Soelaiman Regi Febian Guteres Rekhi Thiara Renaldi Renaldi Reyno Januarian Syatria Ria Parina Ridho Akbar Ridho Ikhlasul Rifqo, Muhammad Husni rindy, rindy balincha Rohman, Mohammad Abkar Nur Ronaldo Kontesa Rosalina Rosalina Rozali Toyib Rozali Toyib Safitri Safitri Safitri Safitri Safitri, Aisyah Sandhy Fernandez Seftianto Selta Jaya Putra Sherenia Anisah Putri Sherenia Anisah Putri Soneta Sulaini Sonita , Anisya Sonita, Anisya Sulaini, Soneta Supriatin Supriatin Supriatin Supriatin, Supriatin Surya Ade Saputera Susilo Dwi Prabowo Tauhid, Muhammad Ikhsan Teguh Wibowo Thio Ragil Alfares Toyib, Rozali Ujang Juhard ujang juhardi Umasih Umasih Venny Arisi Veronika, Nuri David Maria Vicky Victori Vivin Tamara Waluyo Willia Cahaya Dita Wisnu Gusti Gusti Gusti Witriyono, Harry Yawahar, Jon Yoan Ardoni Yoga Muhamad Aryanto Yoga Saputra Yogi Bakti Husada Yovi Apridiansyah Yovi Apridiansyah Yovi Apridiyansyah Yovi Apridiyansyah Yuda, Azildjian Arma Yudha, Bima Satria Yulia Darmi Yulia Darnita yuliadarnita yuliadarnita Yuza Reswan Zalia Aprianti