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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
Teknik Informatika S1, Fakultas Ilmu Komputer, 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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Milkfish Freshness Classification Using Convolutional Neural Networks Based on Resnet50 Architecture Maulana Malik Ibrahim Al-Ghiffary; Christy Atika Sari; Eko Hari Rachmawanto; Noorayisahbe Mohd Yacoob; Nur Ryan Dwi Cahyo; Rabei Raad Ali
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17017

Abstract

Milkfish (Chanos chanos) had become the main commodity in three major cities in Indonesia, contributed at least 77 thousand tons of aquaculture production in 2021. The quality of fish is determined based on the level of freshness carried out in the sorting process, the sorting process is generally done by evaluating physical characteristics of the fish. However, this method is still considered less efficient and economical because the ability to classify the freshness level of fish can vary for each individual. In this study, by utilizing deep learning, a classification method for milkfish freshness level classification with ResNet50 architecture is proposed, the proposed method is purposed to overcome the previously stated problems, thus creating an efficient and economical system. By creating an efficient system, milkfish sorting process can be carried out quicker and more accurately. Using personal dataset divided into four different classes, the proposed method produces excellent result
A Combination of Vigenere Cipher and Advanced Encryption Standard for Image Security Ivan Stepheng; Christy Atika Sari; Eko Hari Rachmawanto; Folasade Olubusola Isinkaye
Advance Sustainable Science Engineering and Technology Vol 5, No 3 (2023): August-October
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i3.17150

Abstract

In an era where digital information security is paramount, this research addresses the pressing need for robust encryption methods. We propose a novel approach that combines the Vigenere Cipher and the Advanced Encryption Standard (AES) for secure digital image transmission. Our study recognizes the research gap in secure image transmission methods and aims to bridge it with a powerful encryption solution. We implement this hybrid encryption approach using the Vigenere Cipher in C++ and the AES algorithm in MATLAB. Our experiments validate the effectiveness of our program in concealing and restoring digital images during transmission. This hybrid encryption technique has promising applications in healthcare, military, and confidential business operations, bolstering image security in real-life scenarios. By enhancing image security, our research can contributed to safeguarding sensitive information in the digital age
PENGARUH LINEAR BINARY PATTERN (LBP) DALAM PENGENALAN CITRA AKSARA JAWA BERBASIS OPTICAL CHARACTER RECOGNITION (OCR) Christy Atika Sari; Wellia Shinta Sari; Putri Mega Arum Wijayanti
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol 2 No 1 (2022): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/semnastekmu.v2i1.149

Abstract

Salah satu peninggalan budaya Indonesia dari tanah jawa yaitu Aksara Jawa. Aksara Jawa telah digunakan oleh masyarakat sejak jaman dulu untuk menulis sastra dan menulis sehari-hari. Karena memiliki bentuk yang rumit aksara jawa menjadi jarang dikenali. Oleh karena itu pada penelitian ini akan dijadikan salah satu upaya untuk belajar sekaligus melestarikan budaya khususnya Aksara Jawa yakni melakukan suatu transliterasi Aksara Jawa. Metode yang digunakan pada penelitian ini adalah dengan menggunakan Optical Character Recognition (OCR) berbasis Template matching dan ekstraksi fitur Linear Binary Pattern (LBP). OCR akan dapat membantu dalam proses pengkonversian gambar yang berisi tulisan Aksara Jawa yang nantinya akan dilakukan proses transliterasi. Cara kerja Template Matching adalah dengan mencocokkan tiap bagian pada citra dengan citra template yang telah ditentukan. LBP akan membantu dalam pengenalan huruf aksara yang memiliki objek terpisah. Berdasarkan dari pengujian diperoleh rata-rata akurasi sebesar 89,4%. Nilai akurasi tertinggi sebesar 100% dan nilai akurasi terendah sebesar 50%. Tingkat keberhasilan dalam proses transliterasi bergantung pada kejelasan objek huruf Aksara Jawa pada citra uji.
CONVOLUTIONAL NEURAL NETWORK DALAM SISTEM DETEKSI HELM PADA PENGENDARA MOTOR Ajib Susanto; Yupie Kusumawati; Ericsson Dhimas Niagara; Christy Atika Sari
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol 2 No 1 (2022): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/semnastekmu.v2i1.158

Abstract

Di tahun ini sudah terjadi perubahan atau revolusi dalam sistem industri yaitu revolusi industri 4.0, di mana industri sudah mengimplementasikan sebuah mesin-mesin yang serba cepat dan praktis untuk membantu dalam hal produktivitas. Dengan semakin pesatnya teknologi, banyak alat-alat yang di ciptakan untuk perkembangan teknologi di dunia. Pemanfaatan teknologi di gunakan untuk sebagai penggerak di pesatnya sistem berbasis AI ini dapat di manfaatkan untuk di berbagai bidang, salah satunya adalah penerapan sistem deep learning dan salah satu teknik yang terkenal dan sudah banyak digunakan untuk klasifikasi citra adalah menggunakan metode Jaringan Syaraf Tiruan (JST) yang mampu mengenali wajah manusia dan suatu gambar citra lalu mengklasifikasinya atau bisa di sebut image classification dan image recognition. Untuk perancangan sistem deteksi helm pada penelitian ini akan menggunakan algoritma CNN(Convolutional Neural Network). Convolutional Neural Network dan untuk model arsitektur yang di gunakan adalah MobileNetV2 dengan akurasi 80%, yang dapat di kategorikan baik dalam sebuah akurasi.
GABUNGAN ADVANCED ENCRYPTION STANDARD DAN VIGENERE CIPHER UNTUK PENGAMANAN DOKUMEN DIGITAL Eko Hari Rachmawanto; Christy Atika Sari
Jurnal Informatika Polinema Vol. 8 No. 4 (2022): Vol 8 No 4 (2022)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v8i4.996

Abstract

Penggunaannya yang kian massif dan banyakya data dan informasi yang tersebar di internet yang mungkin saja terdapat data yang bersifat rahasia, menjadikan data tersebut rawan untuk disalahgunakan dari tindakan illegal oleh pihak yang tidak bertanggung jawab. Faktor keamanan menjadi hal yang sangat penting agar data tersebut tetap aman dan terjamin keasliannya. Maka dibutuhkan metode agar data tetap aman dan asli. Kriptografi adalah metode untuk mengamankan data digital dengan cara mengubah dan mengacak data asli (plainteks) menjadi bentuk yang tidak dikenali (cipherteks). Maka dari itu dipilihlah menggunakan kombinasi algoritma vigenere dan AES dalam mengamankan data agar tetap asli. Vigenere digunakan sebagai pembangkit kunci karena aman, cepat dan tidak banyak menghabiskan sumber daya, menghasilkan ciphertext yang bervariasi. AES dipilih sebagai algoritma yang akan mengenkripsi file dokumen karena menggunakan sistem cycle atau putaran, yang bervariasi terhadap panjang kunci. Sehingga ketika variasi panjang kunci yang berbeda, AES akan mengenkripsi file dokumen dengan jumlah putaran yang disesuaikan. Dengan adanya program kombinasi algoritma Vigenere dan AES ini diharapkan dapat membantu dalam menyembunyikan dan mengamankan data agar data tetap terjamin keasliannya. Berdasarkan hasil eksperimen pada proses enkripsi dan dekripsi, dihasilkan nilai Avalanche effect yang cukup baik. Nilai Aevalache Effect diperngaruhi oleh pajnag kunci yang digunakan. Pada Analisa kebutuhan waktu enkripsi dekripsi, diketahui bahwa proses dekripsi pesan membutuhkan waktu yang lebih lama disbanding proses enkripsi.
Optimasi Keamanan Watermarking pada Daubechies Transform Berbasis Arnold Cat Map Abdussalam Abdussalam; Eko Hari Rachmawanto; Noor Ageng Setiyanto; De Rosal Ignatius Moses Setiadi; Christy Atika Sari
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i1.911

Abstract

Digital image security using Transform Domain algorithms such as Discrete Wavelet Transform (DWT) has been widely used. To improve the security of the DWT algorithm needs to randomize the pixel coefficient, namely Arnold Cat Map (ACM). Computing ACM as one of the chaos functions is known to be fast and fits with Transform Domain. DWT has been implemented in the Daubechies filter which is the development of the Haar filer. In this paper, we proposed the message insertion model using a combination of DWT and ACM on a 512x512 piskel grayscale image and a 64x64 pixel message on the LL subband. The experiments were performed on 2 different images to determine the ability produced by the combined algroithm. The ability test for message insertion process is done through Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and comparation between original image histogram and image insertion histogram. While in the process of message extraction, algorithmic capability test is done by calculating Normalized Cross Correlation (NCC) and its correlation. The highest MSE result is 2.9502 and the highest PSNR is 43.4323 dB, while the NCC value is 237.3584 with correlation 0.7181.
Klasifikasi Jeruk Nipis Terhadap Tingkat Kematangan Buah Berdasarkan Fitur Warna Menggunakan K-Nearest Neighbor Cinantya Paramita; Eko Hari Rachmawanto; Christy Atika Sari; De Rosal Ignatius Moses Setiadi
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i1.1267

Abstract

In the process of classification of lime fruit previously done manually using the human eye is a very difficult thing to do. This is proven by being inconsistent and subjective, causing a low level of accuracy. Sometimes there are also differences of opinion from the human eye to one another. Therefore, to increase the level of accuracy and reduce the subjectivity of the human eye, this study proposes the K-Nearest Neighbor algorithm to classify the maturity level of lime based on the skin color of the lime. In this study, the K values used were 1, 3, 5, 7 and 9 to test the search for Euclidean distance and cityblock distance distances on images with pixel sizes of 512x512, 256x256 and 128x128. In the prerosesing stage, the extraction feature process uses mean RGB. The research that has been done proves that with Euclidean distance distance k = 3 and k = 7 has a percentage value of 92% and the cityblock distance distance k = 1 and k = 3 has a percentage value of 88%. Based on the level of accuracy possessed, the color feature k = 3 shows the best k value in the classification of the maturity level of the lime fruit.
KLASIFIKASI BUNGA MAWAR MENGGUNAKAN KNN DAN EKSTRAKSI FITUR GLCM DAN HSV Sari, Wellia Shinta; Sari, Christy Atika
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 5 No 2 (2022): Jurnal SKANIKA Juli 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2033.71 KB) | DOI: 10.36080/skanika.v5i2.2951

Abstract

Bunga mawar biasanya di produksi sebagai bahan kecantikan maupun parfum. Bunga mawar dapat dibudidayakan untuk bunga potong dan bunga hias. Peneltian ini bertujuan untuk mengklasifikasikan bunga mawar kedalam 5 kategori yaitu bunga mawar doube delight, bunga mawar megawati, bunga awar musk, bunga mawar putri dan bunga mawar thalita yang di dominasi dengan warna merah. Diketahui beberapa jenis mawar mempunyai tampilan kelopak bunga maupun warna yang sama. Kesamaan bentuk dan warna membuat proses klasifikasi berdasarkan mata manusia saja menjadi lebih sulit, sehingga membutuhkan teknik pengolahan citra. Beberapa penelitian bunga mawar hanya menggunakan satu ekstraksi fitur saja sehingga kurang akurat. Dalam penelitian ini telah digunakan algoritma KNN dan ekstraksi fitur GLCM-HSV. Nilai fitur yang digunakan berupa ekstraksi tekstur GLCM dan warna HSV yang nantinya akan dijadikan sebagai parameter perhitungan klasifikasi menggunakan K-NN berdasarkan Euclidean Distance. Data yang digunakan sebanyak 100 data latih dan 25 data uji. Hasil akurasi klasifikasi tertinggi terletak pada K=3 yaitu 96%.
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%.
Co-Authors AA Sudharmawan, AA Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abiyyi, Ryandhika Bintang 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 Anidya Nur Latifa Annisa Sulistyaningsih Anny Yuniarti Antonius Erick Handoyo Arditya Prayogi Ardyani, Salma Shafira Fatya Arfian, Aldi Azmi Ariska, Ratih Aristides Bima Wintaka 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 Castaka Agus Sugianto 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 Feri Agustina 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 Himawan, Reyshano Adhyarta Hussain Md Mehedul Islam 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 Iqtait, Musab 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 Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Mabina, Ibnu Farid Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mehta Pradnyatama Meitantya, Mutiara Dolla Mohamed Doheir 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 Naufal, Muhammad Khanif 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 Praskatama, Vincentius Pratama, Zudha Pratiwi, Saniya Rahma Pulung Nurtantio Andono Purwanto Purwanto Puspa, Silfi Andriana Putri Mega Arum Wijayanti Rabei Raad Ali Rabei Raad Ali Rahmalan, Hidayah Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Rizky Damara Ardy 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 Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Sutrisno, Hendra Syabilla, Mutiara 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 Wellia Shinta Sari Yaacob, Noorayisahbe Mohd Yani Parti Astuti Yupie Kusumawati Zaenal Arifin Zahra Ghina Syafira Zulhusni, Munis