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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 JUTI: Jurnal Ilmiah Teknologi Informasi Prosiding SNATIF Journal of ICT Research and Applications Teknika: Jurnal Sains dan Teknologi Jurnal Informatika dan Teknik Elektro Terapan 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 SISFOTENIKA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer English Language and Literature International Conference (ELLiC) Proceedings Infotekmesin Jurnal Mnemonic Abdimasku : Jurnal Pengabdian Masyarakat SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Journal of Soft Computing Exploration Advance Sustainable Science, Engineering and Technology (ASSET) Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Seminar Nasional Teknologi dan Multidisiplin Ilmu 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) INOVTEK Polbeng - Seri Informatika
Christy Atika Sari
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Arts Humanities 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 Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Other

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Bounding Box and Thresholding in Optical Character Recognition for Car License Plate Recognition Sania, Wulida Rizki; Sari, Christy Atika; Rachmawanto, Eko Hari; Doheir, Mohamed
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12944

Abstract

License plate recognition plays a central role in a variety of application contexts, including traffic management, automated parking, and law enforcement. Among the various approaches available, the Optical Character Recognition (OCR) technique has proven its effectiveness in recognizing characters in license plate images. This study describes an approach for detecting and recognizing vehicle license plates by utilizing the OCR method with Bounding Box, Thresholding, and template matching. In addition, this study uses MATLAB R2022a software as the main tool in developing and implementing the method. The goal is to recognize vehicle license plates from images, describe their characteristics, and generate relevant information. This approach involves a series of image processing steps starting with the pre-processing stage, followed by the process of binarization and license plate segmentation. After successfully isolating the license plate area, isolating the character using a bounding box is performed using image separation techniques. The OCR method is used to recognize license plate characters through comparison using the correlation method. Through a series of experiments on several image datasets, this approach succeeded in showing that out of 20 sampled license plate images, the results obtained were a reading accuracy of 93.55% of 100%, recognizing 13 out of 20 license plate images accurately when tested. Thus, the findings of this research are expected to contribute to the recognition of vehicle license plates that are accurate and efficient, by utilizing image processing techniques and OCR methods implemented using MATLAB R2022a software.
Ambon Banana Maturity Classification Based On Convolutional Neural Network (CNN) Nisa, Yuha Aulia; Sari, Christy Atika; Rachmawanto, Eko Hari; Mohd Yaacob, Noorayisahbe
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12961

Abstract

The banana (Musa paradical), is an excellent fruit produced nationally and high in vitamins. In Indonesia, banana production is at a higher level than other fruit products. However, one of them is the issue with bananas' post-harvest, which arises when they are produced in huge quantities on a large scale or by an industry that sorts bananas. So far, the determination of the maturity level of bananas is done by relying on visual analysis limited to the color of the skin by the human eye. However, this identification approach has several drawbacks. First, this method requires significant effort in the banana sorting process. In addition, the perception of the fruit's maturity level can vary, because humans can experience fatigue and lack of consistency in judgment. In addition, human judgment is also influenced by subjective factors that can affect the final result. Considering this problem, developed a system to classify the ripeness level of Ambon bananas. This system utilizes image enhancement features to increase contrast, which is implemented using a Convolutional Neural Network (CNN). The classification process is carried out through image processing using MATLAB R2022a software, which forms the basis of a classification system with 4 classes which include 486 images of unripe Ambon bananas, 235 images of half-ripe Ambon bananas, 309 images of perfectly ripe Ambon bananas, 184 images of rotten Ambon bananas. The dataset analyzed in this study totaled 1214 data divided into 1093 training data and 121 test data. The CNN method is used in this data classification, and the results show an accuracy rate of 95.87%.
Imperceptible and Robust Encryption: Salsa20 Stream Cipher for Colour Image Data Arfian, Aldi Azmi; Sari, Christy Atika; Rachmawanto, Eko Hari; Isinkaye, Folasade Olubusola
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13049

Abstract

Data security has become crucial, especially in today's era, therefore we need to protect our personal data to avoid unwanted incidents. The primary objective of this research is to empirically demonstrate the viability of our proposed methodology for encrypting color images using the Salsa20 algorithm, renowned for its stream cipher characteristics, which inherently afford it a swift processing speed. The encryption method we use is to take each pixel from the original image and convert it into bytes based on the RGB value in it, then encrypt it using a keyword that has been converted using a hash function. In this study, we carried out several evaluations to evaluate the performance of the encrypted and decrypted images to test the method we propose, including histogram analysis and compare patterns, visual image testing, and key space analysis. Through this experiment, it has been proven that Salsa20 is effective in maintaining confidentiality and image integrity. Histogram analysis reveals differences in pixel distribution patterns between the original and encrypted images. Visual testing shows that the encrypted image maintains good optical quality. Keyspace analysis ensures the security of encryption keys. The performance evaluation resulted in an NPCR above 99%, UACI had been reached 69.28%, MSE was closes to 0, and the highest PSNR was around 61.89dB, this shows that encrypted images recovered with high accuracy.
Text and Image Encryption Using Symmetric Cryptography Ron Rivest Cipher 2 (RC2) Pratiwi, Saniya Rahma; Sari, Christy Atika; Rachmawanto, Eko Hari
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13054

Abstract

In the current context, ensuring the secure transmission of data over the internet has become a critical concern, with information technology playing a fundamental role. As society advances into the digital information age, the importance of network security issues continues to increase. Therefore, the need for cryptographic technology has emerged to overcome these challenges. Cryptography includes symmetric and asymmetric cryptography. An example of symmetric cryptography is the RC2 algorithm. RC2 is a symmetric encryption algorithm that uses a single key to encrypt and decrypt data. The ciphertext is then concealed within an image using the Stepic technique. The RC2 encryption method also utilizes symmetric encryption, ensuring the security of the encryption process while maintaining efficient encryption and decryption speeds. The result of this research is that the average percentage of MSE is 0.00%, and for PSNR and AVA are 70.85% and 34.93%. However, the AVA value is quite unstable because the average value is below 40%. Meanwhile, image encryption results in the longer the text that needs to be hidden in the image, the higher the UACI percentage. This is inversely proportional to the NPCR, the longer the text that needs to be hidden in the image, the lower the NPCR percentage. The average results obtained for UACI and NPCR values are 41.46% dan 98.13%.
Comparison Of Machine Learning Algorithms On Stunting Detection For 'Centing' Mobile Application To Prevent Stunting Sabilillah, Ferris Tita; Sari, Christy Atika; Abiyyi, Ryandhika Bintang; Susanto, Ajib
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13967

Abstract

Stunting is a growth disorder caused by chronic undernutrition, with long-term impacts on child health and development. In Indonesia, the prevalence of stunting reached 31.8% in children under five years old in 2018, indicating an urgent need for effective interventions. In an effort to address this issue, we developed a mobile application called Centing (Cegah Stunting) that utilizes machine learning for early detection and prevention of stunting. In this study, we compare the performance of four machine learning algorithms Logistic Regression, Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel, Convolutional Neural Network (CNN), and Multilayer Perceptron (MLP) in detecting children's nutritional status based on a dataset from Kaggle with 121 thousand data and four main features: age, gender, height, and nutritional status. The experimental results show that SVM with RBF kernel and CNN achieved the highest accuracy of 98%, while Logistic Regression and MLP achieved 76% and 97% accuracy respectively. SVM with RBF kernel was chosen as the best model due to its high accuracy and efficiency in computation time. These findings suggest that the Centing application, with the implementation of SVM RBF, has significant potential in early detection and prevention of stunting, and makes an important contribution to improving child health in Indonesia.
KOMPARASI WATERMARKING DENGAN LIFTING WAVELET TRANSFORM DAN DISCTERE WAVELET TRANSFORM Ningrum, Amanda Prawita; Praskatama, Vincentius; Sari, Christy Atika; Rachmawanto, Eko Hari
Jurnal Mnemonic Vol 7 No 1 (2024): Mnemonic Vol. 7 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i1.7779

Abstract

Privasi dan security merupakan hal yang sangat penting untuk dijaga pada era teknologi seperti sekarang. Cara untuk menjaga privasi dapat dilakukan dengan menggunakan pengamanan pada data. Data perlu dijaga karena didalam data tersebut terdapat informasi pribadi dan sangat bahaya apabila sampai disalahgunakan oleh pihak yang tidak bertanggung jawab. Watermarking merupakan proses yang dilakukan untuk melakukan pengamanan data dengan cara menyisipkan citra watermark ke dalam citra host atau utama. Tujuan dilakukannya watermarking yaitu untuk melakukan pengamanan pada citra. Pada penelitian ini akan dilakukan proses watermarking dengan menggunakan algoritma Lifting Wavelet Transform (LWT) dan Disctere Wavelet Transform (DWT). Tujuan dilakukannya penelitian ini yaitu untuk melakukan komparasi dari proses watermarking yang dimana nantinya dapat dilihat proses watermarking mana yang lebih baik untuk digunakan. Data yang digunakan pada penelitian ini yaitu citra host menggunakan citra Lena dan Baboon yang memiliki ukuran 512*512 pixel dan citra watermark dengan ukuran 64*64 pixel. Hasil yang didapatkan dari penelitian ini yaitu setelah dilakukan proses pengujian, dengan menggunakan citra lena, pada algoritma LWT mendapatkan nilai PSNR sebesar 47.5513 dB dan pada algoritma DWT mendapatkan PSNR sebesar 42.2207 dB
Improved Javanese script recognition using custom model of convolution neural network Susanto, Ajib; Mulyono, Ibnu Utomo Wahyu; Sari, Christy Atika; Rachmawanto, Eko Hari; Setiadi, De Rosal Ignatius Moses; Sarker, Md Kamruzzaman
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6629-6636

Abstract

Handwriting recognition in Javanese script is not widely developed with deep learning (DL). Previous DL and machine learning (ML) research is generally limited to basic characters (Carakan) only. This study proposes a deep learning model using a custom-built convolutional neural network to improve recognition accuracy performance and reduce computational costs. The main features of handwritten objects are textures, edges, lines, and shapes, so convolution layers are not designed in large numbers. This research maximizes optimization of other layers such as pooling, activation function, fully connected layer, optimizer, and parameter settings such as dropout and learning rate. There are eleven main layers used in the proposed custom convolutional neural network (CNN) model, namely four convolution layers+activation function, four pooling layers, two fully connected layers, and a softmax classifier. Based on the test results on the Javanese script handwritten image dataset with 120 classes consisting of 20 basic character classes and 100 compound character classes, the resulting accuracy is 97.29%.
The Involvement of Local Binary Pattern to Improve the Accuracy of Multi Support Vector-Based Javanese Handwriting Character Recognition Sari, Christy Atika; Sari, Wellia Shinta; Shelomita, Viki Ari; Kusuma, Mohammad Roni; Puspa, Silfi Andriana; Gusta, Muhammad Bima
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8450

Abstract

Indonesia is a country that is rich in cultural diversity. An example of one such variety is the Javanese language. The letters that are usually used in Javanese are non-Latin letters or are usually known as Javanese script. However, along with advances in technology, the Javanese language is increasingly being forgotten. In the past, the Javanese script was used as a subject in schools, aiming for Indonesian students to continue to gain knowledge about the Javanese script. The initial step in the introduction of the Javanese script starts with the preprocessing process by changing the image of the Javanese script from the RGB image to a grayscale image which is then performed feature extraction, where the feature extraction used in this script recognition is texture extraction with the Local Binary Pattern (LBP) algorithm. The results of this processing are obtained information that can be used as a parameter in the Multi Support Vector Machine (SVM) classification to predict Javanese script images. In this study using the LBP method with the Multi SVM Algorithm as a classification algorithm produces a high accuracy of 90% in the recognition of Javanese script, better than using only Multi SVM with an accuracy of 80%.
Crypto-Stegano Color Image Based on Rivest Cipher 4 (RC4) and Least Significant Bit (LSB) Rachmawanto, Eko Hari; Hasbi, Hanif Maulana; Sari, Christy Atika; Irawan, Candra; Inzaghi, Reza Bayu Ahmad; Akbar, Ilham Januar
Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i2.8497

Abstract

Rivest Cipher 4 (RC4) has the main factors that make this algorithm widely used, namely its speed and simplicity, so it is known to be easy for efficient implementation. The nature of the key in the RC4 algorithm is symmetrical and performs a plain per digit or byte per byte encryption process with binary operations (usually XOR) with a semirandom number. To improve the visual image after the encryption process, in this article we use the Least Significant Bit (LSB). In this study, the quality of the stego image and the original image has been calculated using MSE, PSNR and Entropy. Experiments were carried out by images with a size of 128x128 pixels to 2048x2048 pixels. Experiments using imperceptibility prove that the stego image quality is very good. This is evidenced by the image quality which has an average PSNR value above 53 dB, while the lowest PSNR value is 48 dB with a minimum dimension of 128x128 pixels.
Completing Sudoku Games Using the Depth First Search Algorithm Alfany, Fauzan Maulana; Sari, Christy Atika; Jatmoko, Cahaya; Laksana, Deddy Award Widya; Irawan, Candra; Huda, Solichul
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (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.v9i1.10017

Abstract

Sudoku is a digital game that is included in the type of logic-based puzzle game where the goal is to fill in the puzzle with random numbers. Therefore, in this research it is proposed to use Artificial Intelligence which contains the Depth First Search Algorithm to track the number of possible solutions that lead to only one so that it becomes efficient. This game has different levels of difficulty such as easy, medium and difficult. The time and complexity of execution will vary depending on the difficulty so it is proposed to use Android Studio software. The experimental results prove that there is an increase in playing the Sudoku game quickly and accurately by applying the Depth First Search Algorithm method. This is proven by the ability to complete this game using the Depth First Search Algorithm using the Android Studio programming language. The average time at the easy level is 11:04 minutes, at the normal level is 10:52 minutes, at the hard level is 25:46 minutes, and at the extreme level is 38 minutes.
Co-Authors AA Sudharmawan, AA Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abiyyi, Ryandhika Bintang Agustina, Feri Ahmad Salafuddin Ajib Susanto Akbar, Fadhilah Aditya Akbar, Ilham Januar Alfany, Fauzan Maulana Ali, Rabei Raad Alifia Salwa Salsabila Alvian Ideastari, Nukat Alvin Faiz Kurniawan Anak Agung Gede Sugianthara Andi Danang Krismawan Anggraeny, Tiara Annisa Sulistyaningsih Anny Yuniarti Antonius Erick Handoyo Ardy, Rizky Damara Ardyani, Salma Shafira Fatya Arfian, Aldi Azmi Ariska, Ratih Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Auni, Amelia Gizzela Sheehan Azzahra, Fidela Bambang Sugiarto Briliantino Abhista Prabandanu Budi Harjo Cahaya Jatmoko Cahyo, Nur Ryan Dwi Candra Irawan Candra Irawan Chaerul Umam Chaerul Umam Cinantya Paramita D.R.I.M. Setiadi Danang Krismawan, Andi Danang Wahyu Utomo Danar Bayu Adi Saputra Danu Hartanto Daurat Sinaga Daurat Sinaga De Rosal Ignatius Moses Setiadi Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Didik Hermanto Doheir, Mohamed Doheir, Mohamed Doheir, Mohamed A S Dwi Puji Prabowo Edi Faisal Egia Rosi Subhiyakto Egia Rosi Subhiyakto Eko Hari Rachmanto Eko Hari Rachmawanto Eko Septyasari Elkaf Rahmawan Pramudya Ericsson Dhimas Niagara Erika Devi Udayanti Erlin Dolphina Erna Daniati Erna Zuni Astuti Ery Mintorini Etika Kartikadarma Farrel Athaillah Putra Fidela Azzahra Florentina Esti Nilawati Florentina Esti Nilawati Florentina Esti Nilawati Folasade Olubusola Isinkaye Folasade Olubusola Isinkaye Giovani Ardiansyah Gumelar, Rizky Syah Guruh Fajar Shidik Gusta, Muhammad Bima Hadi, Heru Pramono Haqikal, Hafidz Hartono, Matthew Raymond Haryanto, Christanto Antonius Haryanto, Christanto Antonius Hasbi, Hanif Maulana Hayu Wikan Kinasih Heru Lestiawan Heru Lestiawan Himawan, Reyshano Adhyarta Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ifan Rizqa Ihya Ulumuddin, Dimas Irawan Ikhsanuddin, Rohmatulloh Muhamad Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiqomah, Annisa Ayu Ivan Stepheng Kamila, Izza Putri Kas Raygaputra Ilaga Krismawan, Andi Danang Kumala, Raffa Adhi Kurniawan, Nicholas Alfandhy Kusuma, Edi Jaya Kusuma, Mohammad Roni Kusumawati, Yupie L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Latifa, Anidya Nur Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Mabina, Ibnu Farid Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Meitantya, Mutiara Dolla Mohamed Doheir Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Rikzam Kamal Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Munis Zulhusni Musfiqur Rahman Sazal Muslih Muslih Nabila, Qotrunnada Neni Kurniawati Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yacoob Nova Rijati Nugroho, Widhi Bagus Nur Ryan Dwi Cahyo Oktaridha, Harwinanda Oktayaessofa, Eqania Ozagastra Caluella Prambudi Parti Astuti, Yani Parti Astuti, Yani parti astuti, yani Parti Astuti1, Yani Parti Astuti1, Yani Permana langgeng wicaksono ellwid putra Pradana, Luthfiyana Hamidah Sherly Pradana, Rizky Putra Pradnyatama, Mehta Praskatama, Vincentius Pratama, Zudha Pratiwi, Saniya Rahma Prayogi, Arditya Pulung Nurtantio Andono Purwanto Purwanto Puspa, Silfi Andriana Putri Mega Arum Wijayanti Rabei Raad Ali Rahmalan, Hidayah Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Robert Setyawan Sabilillah, Ferris Tita Saifullah, Zidan Salma Shafira Fatya Ardyani Salsabila, Alifia Salwa Sania, Wulida Rizki Santoso, Bagus Raffi Saputra, Danar Bayu Adi Sari, Wellia Shinta Sari Shinta Sarker, Md Kamruzzaman Sarker, Md. Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Shelomita, Viki Ari Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sofyan, Ega Adiasa Solichul Huda, Solichul Sudibyo, Usman Sudibyo, Usman Sudibyo, Usman Sugianto, Castaka Agus Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Sutrisno, Hendra Syabilla, Mutiara Syafira, Zahra Ghina Tan Samuel Permana Tan Samuel Permana Tiara Anggraeny Titien Suhartini Sukamto Umah Nur, Raisul Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wintaka, Aristides Bima Yaacob, Noorayisahbe Mohd Yani Parti Astuti Yupie Kusumawati Zaenal Arifin Zulhusni, Munis