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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

Author-ID : 353930

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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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

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

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

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.

EKSTRAKSI FITUR WARNA DAN GLCM PADA ALGORITMA KNN UNTUK KLASIFIKASI KEMATANGAN RAMBUTAN Heru Pramono Hadi; Eko Hari Rachmawanto
Jurnal Informatika Polinema Vol. 8 No. 3 (2022): Vol 8 No 3 (2022)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v8i3.949

Nephelium lappaceum adalah nama latin buah yang lebih dikenal dengan rambutan. Rambutan ternyata mengandung banyak vitamin (vitamin c, magnesium, serat makanan, dll) yang dapat menyembuhkan beberapa penyakit seperti diabetes, hipertensi, dll. Namun karena rendahnya pengetahuan dikalangan masyarakat membuat penjual rambutan mengalami kerugian, karena mereka cenderung menyamaratakan mutu buah. Rendahnya penerapan klasifikasi dikarenakan proses klasifikasi yang dilakukan secara manual dengan menggunakan indra penglihatan. Hal ini menyebabkan akurasi yang rendah, karena indra penglihatan tidak mampu dijadikan tolak ukur tingkat kematangan buah. Maka penelitian ini menerapkan teknologi pengolah citra digital yang menggunakan metode ekstraksi fitur warna RGB, ekstraksi fitur tekstur GLCM dan menerapkan algoritma K-Nearest Neighbor untuk proses klasifikasi. Penelitian ini menghasilkan 4 tingkat kematangan buah yaitu mentah, setengah matang, matang dan busuk. Akurasi tertinggi dihasilkan oleh K=1 sebesar 98,75% dan akuasi terendah dihasilkan oleh K=7 dan 9 sebesar 92,5%. Berdasarkan hasil ekperimen, dapat disimpulkan bahwa semakin besar nilai K maka semakin rendah tingkat akurasi yang dihasilkan, karena pada proses klasifikasi tetangga(data latih dan data uji) yang dibandingkan tergantung pada nilai K

Time Optimization of Watermark Image Quality Using Run Length Encoding Compression Mahiruna, Adiyah; Rachmawanto, Eko Hari; Istiawan, Deden
Journal of Intelligent Computing & Health Informatics Vol 4, No 2 (2023): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v4i2.12058

Internet technology continues to have a significant impact on digital media, such as text, images, audio, and video. One effect is the ease of exchange, distribution, and duplication of digital data; on the other hand, this ease raises the problem of digital data being protected by copyright or digital data confidentiality. Watermarking is a way to protect digital data rights. Extensive research on watermarking has been conducted, including a hybrid DWT-DCT-SVD approach. Several studies have found weaknesses in the message insertion process; for example, the time required to insert a watermark image is relatively long, particularly for large images. To address the problem of long message insertion times, this study applies a compression process to the original image before the watermark image insertion process. The original image to be inserted into the watermark image is compressed using the run-length encoding (RLE) algorithm. The results of RLE compression demonstrate that image file size is reduced significantly, which optimizes the watermarking process. The experimental results demonstrate that watermarked images with RLE compression preprocessing exhibit better imperceptibility and comparable or improved PSNR values. Specifically, the image "Elaine" showed a PSNR improvement from 28.7541 to 31.4502 with RLE compression. These findings demonstrate that combining DWT-DCT-SVD with RLE compression not only reduces watermarking time but also maintains or enhances image quality, providing a robust solution for digital copyright protection.

Optimizing Medical Image Security Using Combined DWT-DCT-SVD Watermarking and RLE Compression Strategies Mahiruna, Adiyah; Ngatimin, Ngatimin; Aulia, Lathifatul; Oleiwi, Ahmed Kareem; Rachmawanto, Eko Hari
Journal of Intelligent Computing & Health Informatics Vol 5, No 1 (2024): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v5i1.14256

Medical images, including MRI, CT, ultrasound, X-rays, and ECG, are crucial for diagnostics; however, they present significant data security challenges. This study introduces a novel watermarking technique that utilizes discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD) to enhance the security, confidentiality, and integrity of medical images. In addition, Run Length Encoding (RLE) is implemented for efficient compression, which significantly reduces data memory requirements. The proposed method demonstrated a notable improvement in the peak signal-to-Noise Ratio (PSNR), increasing by up to 5 dB compared to existing techniques, and achieved a file size reduction of 15-30%. These advances ensure that high-quality images consume less storage space while maintaining diagnostic integrity. The improved PSNR values indicate that the watermark remains imperceptible, making the proposed method highly effective for clinical applications. Compared to existing methods, the proposed method offers enhanced robustness against digital attacks and better image quality preservation. These findings support the secure and efficient handling of medical image data, thereby promoting their use in clinical environments.

ANALISA FITUR EKSTRAKSI CIRI DAN WARNA DALAM PROSES KLASIFIKASI KEMATANGAN BUAH RAMBUTAN BERBASIS K-NEAREST NEIGHBOR Hadi, Heru Pramono; Rachmawanto, Eko Hari
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 5 No 2 (2022): Jurnal SKANIKA Juli 2022
Publisher : Universitas Budi Luhur

Klasifikasi citra buah rambutan leci, lengkeng, pulasan dan rambutan yang merupakan buah dalam stau spesies telah dilakukan. Klasifikasi buah rambutan menggunakan KNN saja atau fitur ekstraksi saja sudah pernah dilakukan. Dalam penelitian ini, proses klasifikasi kematangan buah rambutan dilakukan dengan K-NN berbasis fitur ekstraksi ciri dan warna dengan tujuan untuk meningkatkan akurasi klasifikasi citra. Terpilih ekstraksi ciri GLCM dan ekstraksi ciri warna HSV, dimana masing-maisng mempunyai keunggulan masing-masing. Berdasarkan 100 dataset citra dalam 4 kelas yaitu mentah, setengah matang, matang dan busuk, telah dilakukan percobaan bervariasi menggunakan sudut GLCM dari 00, 450, 900, 1350dan nilai K=1,3,5,7,9,11,13. Akurasi terbaik yang dihasilkan yaitu 97,5% pada K=1 dan 00. Sedangkan yang terendah pada K=13 dan 1350 dengan hasil 62,5%.

CONVOLUTIONAL NEURAL NETWORK (CNN) UNTUK KLASIFIKASI CITRA PENYAKIT DIABETES RETINOPATHY Muslih, Muslih; Rachmawanto, Eko Hari
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 5 No 2 (2022): Jurnal SKANIKA Juli 2022
Publisher : Universitas Budi Luhur

Diabetic Retinopathy (DR) merupakan suatu komplikasi yang terjadi karena adanya kerusakan pada pembuluh darah retina. DR melalui citra retina mata sudah pernah diteliti menggunakan proses peningkatan kualitas citra maupun teknik filtering. Citra DR, memiliki garis tebal dan tipis pada citra fundus dimana tebal tipisnya digunakan untuk menentukan apakah citra fundus tersebut terkategori sebagai citra DR. Biasanya, teknik filtering diperlukan dalam mempertajam garis pada citra fundus. Pada penelitian ini, optimasi dalam klasifikasi citra retina mata yang terdiagnosa retinopati telah dilakukan menggunakan algoritma Convolutional Neural Network (CNN) dengan tujuan pengenalan pembuluh darah pada retina mata terdiagnosa DR. Urgensi dari penelitian ini yaitu melakukan uji performa CNN dalam proses klasifikasi citra DR pada jumlah data yang cukup besar tanpa menggunakan preprosesing apapun sehingga dapat disimpulkan bahwa CNN saja sudah mampu mengklasfikasi objek dengan baik. Citra berasal dari Kaggle database dengan total 88702 citra yang di sortir menjadi 88000 data. Hasil klasifikasi citra benar yaitu 82445 dengan prosentse 93,68% sedangkan citra salah klasifikasi yaitu 5555 citra dengan prosentase kegagalan yaitu 6,32%.

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

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

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 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

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