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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Dinamik Jurnal Ilmu Komputer dan Informasi Jurnal Masyarakat Informatika Jurnal Sains dan Teknologi Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Journal of ICT Research and Applications Teknika: Jurnal Sains dan Teknologi Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi dan Sistem Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Manajemen Informatika Jurnal Kridatama Sains dan Teknologi Infotekmesin Jurnal Mnemonic Abdimasku : Jurnal Pengabdian Masyarakat Variabel Journal of Intelligent Computing and Health Informatics (JICHI) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Journal of Soft Computing Exploration Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Scientific Journal of Informatics LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Advance Sustainable Science, Engineering and Technology (ASSET)
Eko Hari Rachmawanto
Teknik Informatika S1, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Improved imperceptible engagement-based 2D sigmoid logistic maps, Hill cipher, and Kronecker XOR product Lestiawan, Heru; Sani, Ramadhan Rakhmat; Abdussalam, Abdussalam; Rachmawanto, Eko Hari; Purwanto, Purwanto; Sari, Christy Atika; Doheir, Mohamed
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8331

Abstract

Image encryption is a crucial facet of secure data transmission and storage, and this study explores the efficacy of combining sigmoid logistic maps (SLM), Hill cipher, and Kronecker's product method in enhancing image encryption processes. The evaluation, conducted on diverse images such as Lena, Rice, Peppers, Cameraman, and Baboon, unveils noteworthy findings. The Lena image emerges as the most successfully encrypted, as evidenced by the lowest mean squared error (MSE) at 92.81 and the highest peak signal-to-noise ratio (PSNR) at 19.43, reflecting superior fidelity and quality preservation. Additionally, the encryption of 64×64 pixels images consistently demonstrate robustness, with a high number of pixels change rate (NPCR) and unified average change intensity (UACI) values, particularly notable for the Cameraman image. Even for 128×128 pixels images, commendable encryption performance persists across the tested images. The amalgamation of SLM, Hill cipher, and Kronecker's product emerges as an effective strategy for balancing security and perceptual quality in image encryption, with the Lena image consistently outperforming others based on comprehensive metrics. This research provides valuable insights for future studies in the dynamic domain of image encryption, emphasizing the potential of advanced cryptographic techniques in ensuring secure multimedia communication.
Hybrid image encryption using quantum bit-plane scrambling and discrete wavelet transform Rachmawanto, Eko Hari; Susanto, Ajib; Hermanto, Didik; Sari, Christy Atika; Setiarso, Ichwan; Sarker, Md Kamruzzaman
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8887

Abstract

Digital image security is increasingly vulnerable to sophisticated attacks, underscoring the urgent need for robust encryption techniques. Traditional encryption methods often fall short in defending against advanced threats, highlighting the importance of innovative solutions to protect digital images. This study tackles these challenges by incorporating quantum computing into image encryption, employing techniques such as bit-plane scrambling, pixel permutation, and bit permutation. These strategies enhance security by introducing complex, non-linear transformations that make decryption attempts significantly more difficult without the correct cryptographic keys. A key configuration based on r=44, μ=2024 is employed to achieve this. The integration of quantum bit-plane scrambling and quantum pixel permutation results in a highly secure encryption method. Experimental results show substantial improvements in entropy levels, along with strong unified average changing intensity (UACI) and number of pixels change rate(NPCR) values across various images. Notably, the "Peppers" image achieved the best performance, with UACI values of 33.5572 and NPCR values of 99.8301. The method proves highly effective, as repeated tests with incorrect keys failed to decrypt the plain image accurately. Future research could explore the addition of a discrete quantum wavelet transform to further enhance the security and efficiency of quantum-based image encryption methods.
Comparison of Shallot Price Prediction In Pati City With LSTM, GRU and Linear Regression Asyari, Fajar Husain; Proborini, Ellen; Safitri, Melina Dwi; Rachmawanto, Eko Hari
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 2 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i2.11373

Abstract

Shallots are superior vegetable plant and contribute quite significantly to the development of the national economy. The price of shallots fluctuates almost every year. At certain times the price of shallots soars due to high demand while the supply in the market is insufficient. Therefore, an analysis is needed to see what phenomena significantly affect the increase in the price of shallots. The methods used in the study were LSTM, GRU and LR. The results of the analysis show that the LSTM algorithm gets a MAE value of 0.011072172783, MAPE 3.93678% and RMSE 0.03139695060, this error is the lowest compared to GRU getting MAE value is 0.01185741, MAPE 4.2282357% and RMSE 0.03122299395 and LR with MAE 0.0134737280395416, MAPE 5.45081% and RMSE is 0.0313332635305961, so LSTM is a suitable algorithm for predicting shallot data in Pati district.
DIGITAL SIGNATURE PADA CITRA MENGGUNAKAN RSA DAN VIGENERE CIPHER BERBASIS MD5 Handoko, Lekso Budi; Umam, Chaerul; Setiadi, De Rosal Ignatius Moses; Rachmawanto, Eko Hari
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 1 (2019): JURNAL SIMETRIS VOLUME 10 NO 1 TAHUN 2019
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v10i1.2212

Abstract

Salah satu teknik yang populer untuk mengamankan data dengan tingkat keamanan yang tinggi yaitu kriptografi. Berbagai penelitian telah dilakukan dengan menggabungkan kunci simteris dan kunci asimteris untuk mendapatkan keamanan ganda. Dalam makalah ini, tanda tangan digital diterapkan melalui Rivest Shamir Adleman (RSA) sebagai algoritma kunci asimteris yang akan digabung dengan algoritma kunci simteris Vigenere Cipher. RSA yang tahan terhadap serangan karena menggunakan proses eksponensial dan kuadrat besar dapat menutupi kelemahan Vigenere Cipher, sedangkan Vigenere Cipher dapat mencegah kemunculan huruf yang sama dalam cipher yang mempunyai pola tertentu. Vigenere cipher mudah diimplementasikan dan menggunakan operasi substitusi. Untuk mengkompresi nilai numerik yang dihasilkan secara acak, digunakan fungsi hash yaitu Message Digest 5 (MD5). percobaan dalam makalah ini telah memberikan kontribusi dalam peningkatan kualitas enkripsi dimana citra digital dioperasikan dengan MD5 yang kemudian hasilnya akan diubah menjadi RSA. Fungsi hash awal yaitu 32 karakter diubah menjadi 16 karakter yang akan menjadi inputan untuk proses RSA dan Vigenere Cipher. Pada citra berwarna yang digunakan sebagai media operasi, akan dilakukan pengecekan apakah citra tersebut sudah melalui proses digital signature
Identifikasi Citra Jenis Rempah-Rempah Menggunakan Arsitektur RestNet50 Sari, Christy Atika; Pradana, Luthfiyana Hamidah Sherly; Rachmawanto, Eko Hari
LogicLink Vol. 2 No. 1, Juni 2025
Publisher : Universitas Islam Negeri K.H. Abdurrahman Wahid Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28918/logiclink.v2i1.10713

Abstract

Indonesia has various types of spices used in culinary and traditional medicine. However, changes in lifestyle and modernization have made it increasingly difficult for the younger generation to recognize spices directly. Conventional identification still relies on manual observation which is prone to errors. Therefore, an artificial intelligence-based solution is needed to improve the accuracy of spice classification. This study applies the Convolutional Neural Network (CNN) method with the ResNet50 architecture, which is part of Deep Learning, to classify digital images of spices. This model utilizes Computer Vision to recognize visual patterns, Transfer learning to improve training efficiency, and Data Augmentation Techniques such as rotation, flipping, and scaling to improve model robustness. Evaluation using Confusion Matrix was carried out with various dataset division scenarios, including ratios of 90:10, 80:20, 70:30, 60:40, and 50:50. The experimental results showed that the model with a ratio of 90:10 provided the best accuracy, reaching 98.04%, with high precision, recall, and F1-score. In conclusion, the CNN method with ResNet50 has proven effective in identifying spices based on digital images. Further development can be done by adding variations of datasets and exploring other Deep Learning architectures to improve model performance.
Aplikasi Klaim Asuransi Kendaraan Bermotor untuk Mempermudah Pelanggan dengan Memanfaatkan Geolocation Positioning Guna Merekomendasikan Bengkel Terdekat Muhammad Mahdi; Eko Hari Rachmawanto; Adiyah Mahiruna; Dila Ananda Oktafiani; Wahyu Dwy Permana; Fazlur Rahman Hafidz; Ardika Alaudin Arsa
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1405

Abstract

Mobile phones can be used to communicate with each other quickly, whenever and wherever. With the rise of smartphones, users began to switch to using the internet as a medium of communication. Apart from being a communication device, today`s smartphone also has features and facilities that can be utilized to facilitate the work, such as cameras, GPS, and various sensors. Looking at this, business people are eager to create mobile apps to expand their business dimensions and to ease and provide better services to their customer. No exception is a vehicle insurance service company that intends to create a mobile application to provide services to its customers whenever and wherever they are. The application must enable the customer to file an insurance claim. Customers can also track the progress of the stages of claim work. At the time of the claim submission process, the customer may choose a partner workshop to work on the claim process. Because this app is mobile, it should also have a feature to search partner workshop located near the customer's location. So with the creation of mobile smartphone-based applications allow users to make claims and monitor / track claim progress on anywhere in real-time. The workshop search feature will use geolocation positioning method using GPS device on the smartphone to get the customer`s current location and search for a partner workshop within a certain radius.
Monk Skin Tone Classification: RMSprop vs Adam Optimizer in MobileNetV2 Aryaputra, Firman Naufal; Sari, Christy Atika; Rachmawanto, Eko Hari
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 3 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i3.8886

Abstract

The lack of accurate and accessible skin tone classification systems poses significant challenges in personalized fashion recommendations and inclusive technology development. This study aims to develop a skin tone classification system utilizing the Monk Skin Tone (MST) scale through the implementation of Convolutional Neural Network with MobileNetV2 architecture enhanced by transfer learning techniques. The MST scale encompasses ten distinct categories providing comprehensive representation of human skin color diversity. The methodology leverages efficient MobileNetV2 architecture suitable for web deployment, transfer learning to enhance accuracy despite limited training data, and strategic dataset balancing. A dataset of 1,729 facial photographs representing the complete MST spectrum was utilized. Preprocessing involved scaling images to 224×224 pixels, normalization, and augmentation through various transformations to address class imbalance challenges. The dataset was partitioned using a 70:15:15 ratio for training, validation, and testing respectively. The system was implemented as a web platform called SkinToneAI that enables users to upload facial images for skin tone analysis and receive personalized clothing color recommendations. Evaluation demonstrated classification accuracy of 97.83% on the test dataset with a loss value of 0.1166 when using Adam optimizer, while RMSprop optimizer achieved better performance with 98.26% accuracy and 0.0548 loss value. The implemented web application successfully translates technical capabilities into practical fashion assistance. The system provides users with customized apparel color suggestions based on their identified skin tone category, effectively connecting advanced AI technology with everyday fashion needs.
Lung Segmentation in X-ray Images of Tuberculosis Patients Using U-Net with CLAHE Preprocessing Mabina, Ibnu Farid; Sari, Christy Atika; Rachmawanto, Eko Hari
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9869

Abstract

Tuberculosis (TB) is an infectious disease that commonly affects the lungs and remains one of the leading causes of death from infectious diseases. Early detection is essential to prevent further spread and organ damage. Chest X-ray images are one of the main methods for diagnosing TB, but image quality is often affected by low contrast and noise. This study proposes the application of Contrast Limited Adaptive Histogram Equalization (CLAHE) method to improve X-ray image quality, combined with U-Net deep learning architecture for lung segmentation in X-ray images of tuberculosis patients. U-Net was chosen due to its excellent capability in medical image segmentation, thanks to its architectural structure that has encoder-decoder with skip connections, which allows the model to retain detailed information on high-resolution images, even on complex and noisy data. Experimental results using the Shenzhen and Montgomery datasets show that the U-Net model with CLAHE achieves Pixel Accuracy 97.96%, Recall 94.93%, Specificity 98.97%, Dice Coefficient 95.87%, and Jaccard Index (IoU) 92.07%.
A Banana Disease Detection Using MobileNetV2 Model Based on Adam Optimizer Aryanta, Muhammad Syifa; Sari, Christy Atika; Rachmawanto, Eko Hari
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9870

Abstract

The main objective of this study is to develop a deep learning-based disease detection system for banana plants using the MobileNetV2 architecture through a comprehensive comparison with VGG16. This study utilizes a dataset of 3,653 images categorized into 12 classes, including Aphids, Bacterial Soft Rot, Bract Mosaic Virus, Cordana, Insect Pest, Moko, Panama, Fusarium Wilt, Black Sigatoka, Yellow Sigatoka, Pestalotiopsis, and healthy specimens. The methodological framework includes architecture comparison, data balancing, preprocessing techniques, and performance evaluation. The dataset was divided with a distribution ratio of 75% for training, 15% for validation, and 10% for testing. Comparative analysis shows excellent performance of MobileNetV2 with an accuracy of 96.21% compared to 90.15% for VGG16, while maintaining a significantly smaller model size of 10.0 MB compared to 57.8 MB for VGG16. Statistical validation through the McNemar test confirms significant superiority with a p-value of 0.008. The findings of this study contribute positively to the development of agricultural technology, particularly in the development of automated systems for disease detection in banana plants.
Real-Time Braille Letter Detection System Using YOLOv8 Himawan, Reyshano Adhyarta; Rachmawanto, Eko Hari; Sari, Christy Atika
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10060

Abstract

The purpose of this research is to create a system capable of detecting and recognizing Braille letters in real-time using the YOLOv8 algorithm for object detection, integrated with image processing technology and a user interface based on Tkinter. This system is developed to support visually impaired individuals in reading Braille text through the use of a webcam that captures and identifies Braille letters from images. The identification process is carried out by comparing the obtained images with a precompiled database of Braille letters. This research utilizes a dataset consisting of images of Braille code from letters A to Z, collected through public and private methods, with a total of 6013 images that comprehensively represent Braille letters. The model training is done using YOLOv8 to recognize Braille letter objects, with model performance evaluation using the Mean Average Precision (mAP) metric.The results of the tests show a very satisfactory model performance, with a mAP50 score of 0.98 and a mAP50-95 score of 0.789, as well as a high accuracy rate for almost all Braille letters tested. In addition, the system is equipped with a Tkinter-based graphical user interface (GUI) that allows users to operate the Braille letter detection process interactively and easily. This research proves that the YOLOv8-based object detection approach has significant potential for Braille letter recognition applications, which is expected to enhance accessibility and the independence of visually impaired individuals in reading text effectively.
Co-Authors Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abu Salam Adhitya Nugraha Adiyah Mahiruna Agustina, Feri Ahmad Salafuddin Ajib Susanto Akbar Aji Nugroho Akbar, Ilham Januar Al-Ghiffary, Maulana Malik Ibrahim Ali, Rabei Raad Alifia Salwa Salsabila Alvin Faiz Kurniawan Anak Agung Gede Sugianthara Andi Danang Krismawan Anidya Nur Latifa Annisa Sulistyaningsih Antonio Ciputra Antonius Erick Handoyo Aqsel, Aryasatya Muhammad Ardika Alaudin Arsa Arfian, Aldi Azmi Ariska, Ratih Aristides Bima Wintaka Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Asyari, Fajar Husain Aulia, Lathifatul Auni, Amelia Gizzela Sheehan Azzahra, Fidela Bijanto Bijanto Briliantino Abhista Prabandanu Cahaya Jatmoko Cahyo, Nur Ryan Dwi Candra Irawan Candra Irawan Candra Irawan Castaka Agus Sugianto Chaerul Umam Chaerul Umam Christy Atika Sari Cinantya Paramita Ciputra, Antonio D.R.I.M. Setiadi Danar Bayu Adi Saputra Danu Hartanto Daurat Sinaga De Rosal Ignatius Moses Setiadi Deddy Award Widya Laksana Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Destriana, Rachmat Didik Hermanto Dila Ananda Oktafiani Doheir, Mohamed Doheir, Mohamed Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Egia Rosi Subhiyakto Egia Rosi Subhiyakto Elkaf Rahmawan Pramudya Ellen Proborini Erna Daniati Erna Zuni Astuti Ery Mintorini Faisal, Edi Farrel Athaillah Putra Fazlur Rahman Hafidz Fida Maisa Hana Fidela Azzahra Florentina Esti Nilawati Florentina Esti Nilawati Florentina Esti Nilawati Folasade Olubusola Isinkaye Giovani Ardiansyah Gumelar, Rizky Syah Guruh Fajar Shidik Hadi, Heru Pramono Haryanto, Christanto Antonius Haryanto, Christanto Antonius Hasbi, Hanif Maulana Herman Yuliansyah, Herman Heru Agus Santoso Heru Lestiawan Hidayat, Muhammad Taufiq Hidayati, Ulfa Himawan, Reyshano Adhyarta Hussain Md Mehedul Islam Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ihya Ulumuddin, Dimas Irawan Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Iqtait, Musab Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiawan, Deden Istiqomah, Annisa Ayu Ivan Stepheng Kamila, Izza Putri Kas Raygaputra Ilaga Krismawan, Andi Danang Kumala, Raffa Adhi Kunio Kondo Kurniawan, The, Obed Danny Kusuma, Edi Jaya L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Lalang Erawan Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Lungido, Joshua Mabina, Ibnu Farid Mahadika Pradipta Himawan Mahiruna, Adiyah Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mehta Pradnyatama Meitantya, Mutiara Dolla Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Mahdi Mulyono, Ibnu Utomo Wahyu Munis Zulhusni Musfiqur Rahman Sazal Muslih Muslih Muslih Muslih Nabila, Qotrunnada Nanna Suryana Herman Naufal, Muhammad Khanif NGATIMIN, NGATIMIN Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yacoob Nova Rijati Novi Hendriyanto, Novi Nugroho, Dicky Anggriawan Nugroho, Widhi Bagus Nur Ryan Dwi Cahyo Nuri Nuri Oktaridha, Harwinanda Oktayaessofa, Eqania Oleiwi, Ahmed Kareem Parti Astuti, Yani Parti Astuti, Yani parti astuti, yani Parti Astuti1, Yani Parti Astuti1, Yani Pradana, Luthfiyana Hamidah Sherly Pradana, Rizky Putra Praskatama, Vincentius Pratama, Zudha Pratiwi, Saniya Rahma Proborini, Ellen Pulung Nurtantio Andono Purwanto Purwanto Putra, Ifan Perdana Putri, Ni Kadek Devi Adnyaswari Rabei Raad Ali Rabei Raad Ali Rabei Raad Ali Rabei Raad Ali Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Reza Arista Pratama Ruri Suko Basuki Safitri, Melina Dwi Saifullah, Zidan Salsabila, Alifia Salwa Sania, Wulida Rizki Santoso, Bagus Raffi Saputra, Danar Bayu Adi Saputro, Fakhri Rasyid Sarker, Md Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Setiawan, Tan Valencio Yobert Geraldo Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sofyan, Ega Adiasa Solichul Huda, Solichul Sudibyo, Usman Sudibyo, Usman Sudibyo, Usman Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Sutrisno, Hendra Syabilla, Mutiara Tan Samuel Permana Tan Samuel Permana Titien Suhartini Sukamto Tri Esti Rahayuningtyas Umah Nur, Raisul Umam, Choerul Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Wahyu Dwy Permana Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Winarsih, Nurul Anisa Sri Winaryanti, Hida Sekar Yaacob, Noorayisahbe Bt Mohd Yaacob, Noorayisahbe Mohd Yani Parti Astuti Zulhusni, Munis