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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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Coffee Beans Classification Using Convolutional Neural Networks Based On Extraction Value Analysis In Grayscale Color Space Santoso, Bagus Raffi; Sari, Christy Atika; Rachmawanto, Eko Hari
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8916

Abstract

Coffee is a vital agricultural commodity, and precise classification of coffee beans is crucial for quality assessment and agricultural practices. In this study, we propose a methodology utilizing Convolutional Neural Networks (CNN) based on ResNet-101 architecture for coffee bean classification. The novelty of our approach lies in the integration of comprehensive feature extraction from grayscale coffee bean images, including mean, standard deviation, skewness, energy, entropy, and smoothness, with the transfer learning capabilities of CNN. Through this integration, we achieved exceptional classification performance, with the CNN model attaining accuracy, recall, precision, and F1-score metrics of 99.44% and 100% on the training data, and 100% on the testing data. These results underscore the robustness and generalization capability of our methodology in accurately classifying coffee bean types. While the dataset used in this study is experimental, the comprehensive feature extraction and the effectiveness of the CNN architecture suggest the potential for accurate classification of coffee bean types beyond the experimental data, provided the new data shares similar characteristics to the collected samples. For future research, we recommend exploring the integration of two transfer learning techniques within CNN architectures to further enhance coffee bean classification systems. Specifically, leveraging pre-trained CNN models as a foundation for feature extraction, while simultaneously fine-tuning specific layers to adapt to the nuances of coffee bean classification tasks, could offer improved model performance and scalability.
An Ensemble Learning Layer for Wayang Recognition using CNN-based ResNet-50 and LSTM Irawan, Candra; Rachmawanto, Eko Hari; Hadi, Heru Pramono
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.2053

Abstract

Wayang is commonly used to tell epic stories of Mahabharata and Ramayana, as well as local legends and myths. There are various types of wayang, such as wayang kulit (made of buffalo or goat leather), wayang golek (made of wood), and wayang klithik (combination of leather and wood). Although it indicates cultural richness, such diversity also makes it difficult for the general public to identify the character of wayang they are seeing because each type has unique characteristics and details. Recognizing   wayang characters is a challenging task due to their intricate designs and subtle variations. This research addresses this problem by leveraging machine learning technology, specifically CNN-based classification methods, to accurately identify wayang characters. This study proposed a novel method that integrates ResNet-50 transfer learning with LSTM, enhancing the model's ability to capture both spatial and sequential features of wayang images. The proposed model achieved an impressive accuracy of 97.92%, with precision, recall, and F1-scores all reaching 100%. Despite the extended training time of 188 minutes and 21 seconds, the results demonstrate the model's superior performance. This advancement can significantly aid in the preservation and educational dissemination of Indonesian cultural heritage. Future research can focus on optimizing the training process to reduce the time while maintaining or even improving the accuracy, potentially expanding the model's application scope and effectiveness.
Enhancing Medical Image Security Using Hyperchaotic Lorenz and Josephus Traversing Encryption Rachmawanto, Eko Hari; Pramudya, Elkaf Rahmawan; Pratama, Zudha
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.9815

Abstract

Purpose: The present work focuses on developing a methodology to encrypt medical images using combined Hyperchaotic Lorenz systems with Josephus Traversing. This, therefore, forms the basis of the present paper to establish the efficacy of the proposed method against glioma, meningioma, and pituitary kinds of brain tumor images at 256 × 256 and 512 × 512 pixels image sizes. Methods: In this regard, a state-of-the-art encryption technique based on the Hyperchaotic Lorenz systems for Josephus Traversing has been proposed against the medical images of glioma, meningioma, and pituitary tumor datasets obtained from the repository via medical imaging. Result: The different distortion of test outcomes has the MSE value lying between 69.01 and 172.1, while fidelity preservation-PSNR lies between 12.971 and 18.321 dB for different tumor types and sizes of images. The UACI is between 3.625 and 11.34, while the NPCR is always greater than 99% to show very high tamper resistance. This approach is very new in integrating chaos and traversal algorithms for encrypting medical images. Hence, it has a great promising enhancement of security and protection of patient privacy. Novelty: This research contributes a comprehensive investigation based on different metrics that allows exploring not only the efficiency but also strength against decryption techniques for a proposed encryption method. More investigations could be done for further research work in order to enhance the encryption speed, which would improve robustness against advanced decryption techniques in medical image security for digital health applications.
The AirNav Semarang Employee Presence System Using Face Recognition Based on Haar Cascade Fidela Azzahra; Christy Atika Sari; Eko Hari Rachmawanto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.672

Abstract

The presence of employees is a key factor in supporting the needs of the workplace. At present, the employee presence system at PT. AirNav Indonesia Semarang Branch still uses fingerprint and RFID-based employee ID cards for authentication. This RFID-based system can increase employee fraud by allowing employees to misuse each other's ID cards. To avoid such fraud, a system needs to be built and it will be using face recognition technology as the primary authentication method, with the Haar Cascade Algorithm. This algorithm has the advantage of being computationally fast, as it only relies on the number of pixels within a rectangle, not every pixel of an image. In addition to fast computation, this algorithm also has the advantage of identifying objects that are relatively far away. With the implementation of the Haar Cascade algorithm, the results indicate the capability of face recognition in detecting the faces of registered employees within the system based on facial angles with an accuracy rate of 60%, expressions with an accuracy rate of 100%, as well as obstructive parameters such as glasses and masks with an accuracy rate of 33.33%. The ability to detect objects from various camera angles, recognize faces with different expressions, and identify objects obstructed by parameters can serve as reasons why this algorithm needs to be implemented
Implementation of DenseNet121 Architecture for Waste Type Classification Munis Zulhusni; Christy Atika Sari; Eko Hari Rachmawanto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.673

Abstract

The growing waste management problem in many parts of the world requires innovative solutions to ensure efficiency in sorting and recycling. One of the main challenges is accurate waste classification, which is often hampered by the variability in visual characteristics between waste types. As a solution, this research develops an image-based litter classification model using Deep Learning DenseNet architecture. The model is designed to address the need for automated waste sorting by classifying waste into ten different categories, using diverse training datasets. The results of this study showed that the model achieved an overall accuracy rate of 93%, with an excellent ability to identify and classify specific materials such as batteries, biological materials, and brown glass. Despite some challenges in metal and plastic classification, these results confirm the great potential of using Deep Learning technology in waste management systems to improve sorting processes and increase recycling efficiency
Classification of Movie Recommendation on Netflix Using Random Forest Algorithm Alifia Salwa Salsabila; Christy Atika Sari; Eko Hari Rachmawanto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.676

Abstract

Netflix is one of the most popular streaming platforms in this world. So many movies and shows with various genres and production countries are available on this platform. Netflix has their own recommendation systems for the subscribers according to their data and algorithm. This research aims to compare two methods of data classifications using Decision Tree and Random Forest algorithm and make a recommendation system based on Netflix dataset. This paper use feature importance to selecting relevant feature and how n_estimators affect the classification. In this research, Random Forest with 50 trees estimator with 96.84% accuracy before feature selection and 96.92% accuracy after feature selection has the best accuracy compared to the Decision Tree classification. Besides, Decision Tree has only 95.64% accuracy before feature selection and increases to 96.07% accuracy after feature selection. Trees estimator also affect the accuracy of Random Forest classification. After comparing the results, Random Forest with 50 trees estimators using feature selection provides best accuracy and it will be used to predict some similar movies and shows recommendation
Classification of Corn Leaf Disease Using Convolutional Neural Network Ratih Ariska; Christy Atika Sari; Eko Hari Rachmawanto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i4.772

Abstract

Corn is a crop that plays a major role in food supply worldwide. Known as a cereal crop with high economic value, corn is one of the most important raw materials in the agricultural industry in many parts of the world. Leaf blight is characterized by small spots that gradually enlarge and turn brown. It is a decay of foliage caused by the fungus or species Rhizoctonia solani. Leaf spot is caused by the fungus Hel-minthoporium maydis, while stem rot is caused by Fusarium granearum. From these problems, a machine learning-based solution is given to classify corn leaf diseases using the Convolutional Neural Network (CNN) algorithm. CNN are used to classify corn leaf diseases. The selection of CNN is based on its ability to extract local attributes from image data and combine them for a more detailed and abstract representation, which is better. Classification was performed using 2145 datasets for leaf blight and 1574 datasets for leaf spot. The accuracy results obtained from this study reached 99% with the last training accuracy value of 99.06% and the last validation accuracy result of 98.50%. For future research may use more modern architectures such as classification using EfficientNet B3 architecture with transfer learning or MobileNet to improve accuracy results.
Jasmine Flower Classification with CNN Architectures: A Comparative Study of NasNetMobile, VGG16, and Xception in Agricultural Technology Danar Bayu Adi Saputra; Christy Atika Sari; Eko Hari Rachmawanto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 4 (2024): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i4.790

Abstract

Jasmine flowers have many benefits and uses such as for traditional medicine, tea, perfume, cosmetics, decoration, and others. in the selection of fresh jasmine flowers for making tea is very important, currently the classification of jasmine flowers for making tea is mostly still using manual methods. Often influenced by individual preferences, opinions, or biases. this causes a lack of objectivity and uncertainty in the classification of jasmine flowers. The manual method is very weak due to human visual limitations and fatigue levels which can result in less than the optimal jasmine flower classification. Therefore, in the research that has been done, a transfer learning system was applied that can classify fresh jasmine flowers with rotten jasmine flowers. This study aims to compare three different Convolutional Neural Network architectures: NasNetMobile, VGG16, and Xception. The results on the three architectures can show maximum results, namely 99.21% for NasNetMobile, 98.69% for VGG16 and 97.91% for Xception. This study provides insight into the classification of good and bad jasmine flowers to encourage further exploration in the field of agriculture.
Array Sorting Algorithm vs Traditional Sorting Algorithm: Memory and Time Efficiency Analysis: Array Sorting Algorithm vs Algoritma Pengurutan Tradisional: Analisis Efisiensi Memori dan Waktu Pujiono, Imam Prayogo; Rachmawanto, Eko Hari; Winarsih, Nurul Anisa Sri
Jurnal Manajemen Informatika JAMIKA Vol 15 No 1 (2025): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v15i1.13230

Abstract

The development of information technology has changed various aspects of life, including the way we store and sort data. Data that used to be stored in filing cabinets is now stored in digital form on computers. However, digital data that is not well organised can make it difficult to search and verify. Therefore, data sorting has become very important, and various sorting algorithms have been developed to fulfil this need, such as the Array Sorting Algorithm (ASA), which is claimed to have efficient time complexity and is very competitive when compared to the time complexity of traditional algorithms. This research examines the memory efficiency and computation time between ASA and five traditional sorting algorithms (Bubble Sort, Shell Sort, Merge Sort, Quick Sort, and Heap Sort) using the Java programming language. The research was conducted by utilising random numerical datasets on three different scales (100, 1,000, and 10,000 data) to test the performance of the six algorithms in various scenarios. ASA, which utilises a two-dimensional array structure to manage element frequencies, showed impressive performance in terms of computation time, especially on datasets containing 1,000 and 10,000 data, compared to traditional algorithms that focus more on comparison and recursion methods. The test results confirm that on datasets of 1,000 and 10,000 data, ASA excels in terms of computational speed but loses in terms of memory usage. Therefore, if memory usage is not a major consideration, then ASA is a very suitable sorting algorithm for sorting data of 100 - 10,000. These findings provide important insights for the selection of efficient sorting algorithms based on memory efficiency and computation time on multiple data sizes, which is particularly useful when developing applications using the Java programming language.
Implementasi E-Arsip Untuk Penyimpanan Dokumen Digital Pada PT BPD Jateng (Bank Jateng) Nilawati, Florentina Esti; Rizal, Mohammad; Rachmawanto, Eko Hari; Setiadi, De Rosal Ignatius Moses; Sari, Christy Atika
Techno.Com Vol. 18 No. 4 (2019): November 2019
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1058.177 KB) | DOI: 10.33633/tc.v18i4.2508

Abstract

Bank Pembangunan Daerah Jawa Tengah merupakan Bank milik Pemerintah Provinsi Jawa Tengah bersama-sama dengan Pemerintah Kota/Kabupaten Se-Jawa Tengah. Seiring dengan kemajuan teknologi pengarsipan di Bank Pembangunan Daerah Jawa Tengah memerlukan digitalisasi dalam hal pengarsipan data. Pengarsipan data adalah proses memindahkan data yang tidak aktif lagi digunakan ke perangkat penyimpanan terpisah untuk jangka panjang. Data arsip terdiri dari data lama, serta data yang harus dipertahankan untuk kepatuhan terhadap peraturan. Arsip data diindeks dan memiliki kemampuan pencarian sehingga file dan bagian file dapat dengan mudah ditemukan dan diambil. Backup data digunakan sebagai mekanisme pemulihan data yang bisa digunakan untuk mengembalikan data jika rusak atau hancur. Sebaliknya, arsip data melindungi informasi lama yang tidak diperlukan untuk operasi sehari-hari namun mungkin harus diakses sesekali. Arsip data berfungsi untuk mengurangi konsumsi penyimpanan primer dan biaya terkait, daripada bertindak sebagai mekanisme pemulihan data. Beberapa arsip data memperlakukan data sebagai read-only untuk melindunginya dari modifikasi, sedangkan data lain produk pengarsipan memperlakukan data sebagai read / write. Dengan dibangunnya e-Arsip pada PT. Bank Pembangunan Daerah Jawa Tengah (Bank Jateng) diharapkan di kemudian hari untuk proses pencarian dan penyimpanan data dapat dilakukan dengan mudah, sehingga dapat menghemat waktu dan tenaga pada proses pencarian arsip.
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