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All Journal International Journal of Electrical and Computer Engineering International Journal of Applied Power Engineering (IJAPE) Jurnal Sosial Ekonomi Pertanian Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Telematika Al Ishlah Jurnal Pendidikan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Informatika IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Komputasi Kinerja: Jurnal Ekonomi dan Manajemen JKTP: Jurnal Kajian Teknologi Pendidikan Jurnal SOLMA JURNAL SINEKTIK LIABILITIES (JURNAL PENDIDIKAN AKUNTANSI) Jurnal Elektronika dan Telekomunikasi Jurnal Sisfokom (Sistem Informasi dan Komputer) community: Pengawas Dinamika Sosial Jurnal Nasional Komputasi dan Teknologi Informasi JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Mantik Jurnal Infortech Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Science and Engineering (JCSE) Jurnal Graha Pengabdian Jurnal Teknologi Informatika dan Komputer Jurnal Sistem Informasi Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Ekonomi dan Bisnis Reputasi: Jurnal Rekayasa Perangkat Lunak IMTechno: Journal of Industrial Management and Technology Conten : Computer and Network Technology Journal of Electrical Vocational Teacher Education Jurnal Neuroanestesi Indonesia PELS (Procedia of Engineering and Life Science) Jurnal Media dan Teknologi Pendidikan Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Ilmu Ekonomi Mulawarman (JIEM) JURNAL PENGABDIAN PENDIDIKAN MASYARAKAT (JPPM) Info Abdi Cendekia Finger : Jurnal Ilmiah Teknologi Pendidikan SATIN - Sains dan Teknologi Informasi Jurnal Komputer Antartika Bulletin of Informatics and Data Science Informatics and Software Engineering (ISE) INOVASI: Jurnal Ekonomi, Keuangan, dan Manajemen Vocational: Journal of Educational Technology Journal Of Biology Education Research (JBER) Jurnal Informatika

Agus Junaidi

Universitas Bina Sarana Informatika

Author-ID : 2543263

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences Transportation Other

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Convolutional Neural Networks for Classification of Lung Cancer Based on Histopathological Images Agustiani, Sarifah; Pribadi, Denny; Junaidi, Agus; Wildah, Siti Khotimatul; Mustopa, Ali; Arifin, Yoseph Tajul
Telematika Vol 16, No 2: August (2023)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v16i2.2356

Lung cancer is one of the deadliest types of cancer characterized by the uncontrolled growth of cancer cells in the lung tissue due to the accumulation of carcinogens. Lung cancer ranks second in the most cases with 2.206 million new cases and ranks first in deaths. This lung cancer often does not cause symptoms in the early stages, because it only appears after the tumor is large enough or the cancer has spread to surrounding tissues or organs, so it is necessary to have early detests to prevent severity and determine follow-up treatment. This study aims to classify lung cancers using digital pathology images with data of 15000 images obtained from the LC25000 dataset containing 5,000 images for each class. The method used in this classification process uses convolutional neural networks (CNN) which is one of the implementations of Deep Learning used for digital image processing. Using this method, the doctor can diagnose and find out the type of lung cancer quickly without spending much time. Thus, the faster the prediction results received by the doctor / health expert, the faster the next action or handler will be, this study produces a fairly accurate accuracy value even though it uses a shallow CNN architecture because it only consists of 5 layers with 3 convolution layers and 2 fully connected layers, with the resulting accuracy value of 98.53%.

KAI Commuter Employee Development Application Using The Waterfall Method Ramadan, Angga Riski; Junaidi, Agus; Azis, Mochammad Abdul
Informatics and Software Engineering Vol. 1 No. 2 (2023): December 2023
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v1i2.93

The KAI Commuter Employee Development application is a solution to support employee development in the PT environment. Indonesian Commuter Train. The development method used in this project is the Waterfall Method, which is a sequential approach consisting of clear phases, including planning, analysis, design, development, testing, and implementation. This application aims to increase effectiveness and efficiency in the management and development of employees in the company. With features such as performance tracking, training, employee evaluation, and creating personal development plans, this application provides a powerful tool for management to monitor and improve the potential of their employees. The development process using the Waterfall Method allows developers to carefully detail requirements before starting the stage implementation. This ensures the application can meet predefined requirements well throughout the development cycle. In addition, this model allows for more structured progress monitoring and enables more efficient project management. By adopting the KAI Commuter Employee Development application and implementing the Waterfall Method, companies can develop their employees, increase productivity, and optimize resources for their humans.

PEMBERDAYAAN MASYARAKAT PETERNAK LEMBU DESA BANYUMAS KECAMATAN STABAT KABUPATEN LANGKAT DALAM MENGOLAH PAKAN TERNAK DARI LIMBAH PANEN PERKEBUNAN TEBU PTPN II SUMATERA UTARA Sari, Sri Adelila; Junaidi, Agus; Rahmah, Siti; Miswanda, Dikki; Saputra, Muhammad Fadhlan; Khairahmi, Khairahmi
Jurnal Graha Pengabdian Vol 5, No 1 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um078v5i12023p19-26

Abstrak: Masyarakat Desa Banyumas Kec. Stabat Kab. Langkat Sumatera Utara mayoritas berprofesi sebagai peternak lembu dan biasanya mengandalkan rumput sebagai sumber utama pakan ternak lembunya. Namun, ketersediaan rumput pakan semakin sedikit dengan bertambahnya areal pemukiman. Desa Banyumas berbatasan langsung dengan areal perkebunan tebu milik PTPN II Sumatera Utara. Setiap musim panen, dihasilkan limbah pucuk tebu sebanyak 560 ton perharinya. Limbah pucuk tebu ini berpotensi sebagai sumber pakan hijauan pengganti rumput. Namun, masyarakat peternak Desa Banyumas belum memiliki pengetahuan tentang pemanfaatan limbah pucuk tebu sebagai pakan ternak, selain itu masyarakat belum memiliki teknologi tepat guna (TTG) alat pencacah limbah pucuk tebu. Tahapan pelaksanaan kegiatan ini yaitu (1) Pendidikan: sosialisasi pemanfaatan limbah pucuk tebu sebagai pakan ternak, (2) Penyediaan alat TTG pencacah pucuk tebu, dan (3) Pelatihan pembuatan pakan ternak dari limbah pucuk tebu. Limbah pucuk tebu diolah menjadi produk silase melalui proses fermentasi. Sebelum dilakukan fermentasi, pucuk tebu terlebih dahulu dicacah menggunakan TTG alat pencacah pucuk tebu. Pada setiap tahap kegiatan ini, masyarakat peternak sangat antusias dan turut aktif. Pengetahuan masyarakat peternak juga telah meningkat yang semula belum mengenal produk pakan dalam bentuk silase kini mampu membuat silase secara mandiri. Abstract: Banyumas Village society, Stabat Districts, Langkat Regency, North Sumatra Province majority work as cattle breeders and usually rely on grass as the main source of their cattle feed. However, the availability of forage grass decreases with increasing residential area. Banyumas village is directly adjacent to the sugar cane plantation area belonging to PTPN II North Sumatra. Every harvest season, 560 tons of sugarcane shoots are produced per day. This sugarcane shoot waste has the potential as a source of forage substitute for grass. However, the farming community of Banyumas Village does not yet have knowledge about the use of sugarcane shoots waste as animal feed, besides that the community does not yet have appropriate technology for chopping sugarcane shoots waste. The implementation stages of this activity are (1) Education: socialization of the utilization of sugarcane shoots waste as animal feed, (2) Provision of sugarcane shoots chopper TTG equipment, and (3) Training on making animal feed from sugarcane shoots waste. Sugarcane shoot waste is processed into silage products through a fermentation process. Prior to fermentation, the shoots of sugar cane were first chopped using a TTG tool for chopping sugar cane shoots. At each stage of this activity, the farming community is very enthusiastic and actively participates. The knowledge of the farming community has also increased, those who were previously unfamiliar with feed products in the form of silage are now able to make silage independently.

Enhancing Electrical Power Engineering Education in North Sumatra: Evaluating the Effectiveness and Practicality of Consortium Collaborations Between Academia and Industry Junaidi, Agus; Afandi, Marwan; Pangaribuan, Wanapri; K, Abd Hamid; Rahmaniar, Rahmaniar
AL-ISHLAH: Jurnal Pendidikan Vol 16, No 3 (2024): AL-ISHLAH: JURNAL PENDIDIKAN
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v16i3.5446

Simulation technology tools are becoming important learning tools in higher education, facilitating the development of practical and cognitive skills in a safe and widely accessible environment. Simulation technology is applied in practicing and developing practical learning skills in a safe environment, without real risks. Computers as media and are used to improve learning outcomes and facilitate students in innovative learning. The importance of using simulation media in learning electricity engineering because inviting students to learn and interact with simulations can improve critical thinking skills, problem solving, and decision making. The simulation media was developed using the ADDIE model to achieve learning effectiveness targets by observing the parameters of alignment between simulation content and learning outcomes, interactivity that allows students to be actively involved in the learning process, the quality of feedback provided by simulations to help students understand in improving learning outcomes in the field of electricity engineering. The results of testing 21 respondents showed an increase in student involvement and motivation in the pretest results of 65.5 and post-test 83.38 in the experimental class, indicating that there was an increase in learning outcomes from media users. Practicality test 80% in the practical category shows the implication of using the media provides convenience.

Transformasi Digital untuk Mewujudkan Ruang Publik Yang Lebih Cerdas Haryani, Haryani; Agustiani, Sarifah; Junaidi, Agus; Wahyudin, Wahyudin
Jurnal Abdimas Ekonomi dan Bisnis Vol. 4 No. 2 (2024): Jurnal Abdimas Ekonomi dan Bisnis
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abdiekbis.v4i2.7289

The purpose of this activity is to provide solutions to problems in RPTRA in the form of RPTRA management information systems and provide information technology training in the form of RPTRA website management. The problem in the management of RPTRA so far is that there has been no integrated data, both data on guest visits, activity agendas, and events carried out by RPTRA and external parties that use the Annur RPTRA land. The main problems related to digital infrastructure at RPTRA Annur are the availability of access to digital information such as the use of devices for digital learning for children, access to information and online registration of activities, communication and coordination between RPTRA managers and the community. The expected result in Community Service at RPTRA Annur is to make a product in the form of an RPTRA website profile that contains an agenda of activities and events, and a guest visit book that uses land at RPTRA. In addition, with this digital transformation activity, RPTRA managers also gain increased knowledge in using the Canva application for the learning process carried out.

Digital Simulation of Short Circuit Current Calculation Using Graphical User Interface for Learning Media Electric Power System Analysis Rahmaniar, Rahmaniar; Junaidi, Agus; Tarigan, Adi Sastra P; Butar Butar, Abdul Hakim
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : STMIK Dharma Wacana

The research examines the design of a simulation program for short circuit calculations. A short circuit is an abnormal event called a disturbance in the electric power system. The classification of short circuit consists of three-phase fault, single-phase fault to ground, two-phase fault and two-phase fault to ground. Calculation of short circuit faults in electric power systems is very important for the study of reliability and safety of power systems. The method used in the design of the Graphical User Interface (GUI) based simulation program is the experimental method, which is to identify the magnitude of the short circuit current value based on the theorem of Fortescue's theorem related to symmetrical components. Furthermore, a GUI program script is built for short circuit calculations. The GUI success test was carried out by comparing the results of the short circuit analysis with the short circuit calculation program using Matlab and validation by experts. From the results of testing and validation by experts, it can be seen that the program built can complete the calculation of short circuit faults validly. The GUI SCC program can be applied to electric power system analysis learning, with a media validity level of 0.85, which is good for use in learning. In addition, this study also built a simulation for the calculation of class intervals and the practicality of the media using the Simulink Matlab media, the results of the program design were declared by experts to be valid with an average score of 0.8625

Implementation Project-Based Learning Model On Electrical Motor Installation Mustaqim, Bima; Sibuea, Abdul Muin; Siagian, Sahat; Junaidi, Agus; Amin, Muhammad; Baharuddin, Baharuddin; Ampera, Dina
JKTP: Jurnal Kajian Teknologi Pendidikan Vol 7, No 3 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um038v7i32024p108

The learning process in vocational high schools is a determining factor in producing graduates of vocational high schools who are in accordance with their competencies. The learning process will determine whether the learning objectives will be achieved. This study aims to develop a project-based learning device on the installation of electric motors. The method used is User Centered Design with data processed from teachers and students. The results of the implementation of project-based teaching materials for teachers are Good and students are Fairly Good. The project-based learning device is practical enough to make it easier for students to understand the learning of installing electric motors with guidance from teachers. These findings confirm the great usefulness of this model in facilitating a comprehensive understanding of the Installation of Electric Motors. Through its significant role in this subject, this model has developed into a versatile reference model. This model is not only easy to apply in various academic domains, but also effectively enriches students' learning experiences in various subjects. As a result, this model becomes a very valuable tool in supporting a deeper and more holistic learning and teaching process. Abstrak Proses pembelajaran di sekolah menengah kejuruan merupakan faktor penentu untuk dapat melahirkan lulusan pendidikan menengah kejuruan yang sesuai dengan kompetensinya. Proses pembelajaran akan menentukan apakah tujuan pembelajaran akan tercapai. Penelitian ini bertujuan untuk mengembangkan perangkat pembelajaran berbasis proyek tentang pemasangan motor listrik. Metode yang digunakan adalah User Centered Design dengan data yang diolah bersumber dari guru dan siswa. Hasil implementasi bahan ajar berbasis proyek untuk guru adalah Baik dan siswa adalah Cukup Baik. Perangkat pembelajaran berbasis proyek cukup praktis untuk memudahkan siswa memahami pembelajaran pemasangan motor listrik dengan bimbingan dari guru. Temuan ini menegaskan kegunaan besar model ini dalam memfasilitasi pemahaman yang komprehensif tentang Pemasangan Motor Listrik. Melalui perannya yang signifikan dalam subjek ini, model ini telah berkembang menjadi model referensi yang serba guna. Model ini tidak hanya mudah diterapkan di berbagai domain akademik, tetapi juga secara efektif memperkaya pengalaman belajar siswa di berbagai mata pelajaran. Sebagai hasilnya, model ini menjadi alat yang sangat berharga dalam mendukung proses pembelajaran dan pengajaran yang lebih mendalam dan holistik.

Deep Neural Network Classifier for Analysis of the Debrecen Diabetic Retinopathy Dataset Agustyaningrum, Cucu Ika; Haryani, Haryani; Junaidi, Agus; Fadilah, Iwan
Jurnal Elektronika dan Telekomunikasi Vol 24, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.640

Diabetic retinopathy (DR) is a serious complication that can occur in individuals who have diabetes. This disease affects the blood vessels in the retina, a part of the eye that is important for vision. Early detection of DR is key to preventing further complications and saving the patient’s vision. The goal of Diabetic Retinopathy Debrecen Data Set Analysis is to get the best, most accurate results for medical professionals to receive appropriate Diabetic Retinopathy Debrecen prediction results through the stages of data collection, evaluation, and classification. Data is collected from existing secondary sources, then assessed using a deep neural network algorithm with various variations. The classification algorithm in this research uses the Python programming language to measure accuracy, F1-Score, precision, recall, and ROC AUC. The test results show that the accuracy of the deep neural network algorithm is 79.94%, the F1 score reaches 79.16%, the precision is 79.58%, the recall is 79.60%, and the AUC is 79.56%. Thus, based on this research, the deep neural network data mining technique with variations of the four hidden layer encoder-decoder, sigmoid activation function, Adam optimizer, learning rate 0.001, and dropout 0.2 is proven to be effective. When compared with other variations such as decoder-encoder, 3-8 hidden layers, learning rate 0.1 and 0.01, the average difference in values between this variation and the others is 0.07% accuracy, 2.03% F1 score, 0.25% precision, 0.80% recall, and 0.90% AUC. Therefore, the deep neural network algorithm with the variation used shows significant dominance compared to other variations.Diabetic retinopathy (DR) is a serious complication that can occur in individuals who have diabetes. This disease affects the blood vessels in the retina, a part of the eye that is important for vision. Early detection of DR is key to preventing further complications and saving the patient’s vision. The goal of Diabetic Retinopathy Debrecen Data Set Analysis is to get the best, most accurate results for medical professionals to receive appropriate Diabetic Retinopathy Debrecen prediction results through the stages of data collection, evaluation, and classification. Data is collected from existing secondary sources, then assessed using a deep neural network algorithm with various variations. The classification algorithm in this research uses the Python programming language to measure accuracy, F1-Score, precision, recall, and ROC AUC. The test results show that the accuracy of the deep neural network algorithm is 79.94%, the F1 score reaches 79.16%, the precision is 79.58%, the recall is 79.60%, and the AUC is 79.56%. Thus, based on this research, the deep neural network data mining technique with variations of the four hidden layer encoder-decoder, sigmoid activation function, Adam optimizer, learning rate 0.001, and dropout 0.2 is proven to be effective. When compared with other variations such as decoder-encoder, 3-8 hidden layers, learning rate 0.1 and 0.01, the average difference in values between this variation and the others is 0.07% accuracy, 2.03% F1 score, 0.25% precision, 0.80% recall, and 0.90% AUC. Therefore, the deep neural network algorithm with the variation used shows significant dominance compared to other variations.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.640

Convergence in The Agricultural Economic Industry in Indonesia: A Dynamic Fitriadi, Fitriadi; Junaidi, Agus; Darma, Dio Caisar
JSEP (Journal of Social and Agricultural Economics) Vol. 17 No. 2 (2024): JURNAL SOSIAL EKONOMI PERTANIAN (J-SEP)
Publisher : University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

In addition to labor, investment, consumption, government spending, and exports, this work attempts to include elements of health, education, and technology which are seen as important in strengthening the agricultural sector. The paper aimed to assess the relationship between labor, investment, consumption, government spending, and exports on agricultural GDP based on two formats. First, modeling without health, education, and technology. Second, modeling includes health, education, and technology. A series of data series were observed in simultaneous and partial regression modeling. The case study is Indonesia, where testing was conducted during 2010â€“2022. The empirical findings conclude two points: (1) involving health, education, and technology, results are better on agricultural GDP growth than without including all three; and (2) although initially health, education, and technology were very essential, only health has positive implications for GDP growth. Without these three variables, in the short term, labor, investment, consumption, government spending, and exports also play a role in the development of the agricultural economy in Indonesia. Thus, labor, consumption, and exports remain to be increased for the future of agricultural GDP by optimizing human capital through health, education, and technology.

Co-Authors -, Rahmaniar AA Sudharmawan, AA Abdul Muin Sibuea Afandi, Marwan Agus Junaidi agusniati, Agusniati Agustiani, Sarifah ahmad yani Ahmad Yani Ahmad Yani Aji Miftahus Salim Alfonsus Sinamo Ali Mustopa, Ali Alif Rahman AMRI, MOHAMAD SYAIFUL Andi Saryoko Angga Eko Pratama Anggita, Nur Anisa Anis Suryatri AS, Usman Asyiri, Syekh Mohammad Auliabahri, Ananda Putri Ayu Wahyuni Azis, Mochammad Abdul Baharuddin Baharuddin Bakti Dwi Waluyo Butar Butar, Abdul Hakim Candra Sumirat Catra Indra Cahyadi Cucu Ika Agustyaningrum Delani, Desta Denny Haryanto Sinaga Derlina . Devi Angelina Simaremare Dewi Kartika Dewi Kartika Diah Puspitasari Dikki Miswanda DINA AMPERA Dio Caisar Darma Dodi Suryanto, Eka Donna Setiawati Efendi Napitupulu Emiliana, Meutia Raissa Fachry Abda El Rahman Fadilah, Iwan Faez Syahroni Fahmi, Jaman Fany Visella Fawzim, Ahmad febryan_wiraputra febryan Firdaus Idam Fitrayuda Rivaldy Fitriadi Fitriadi Frisma Handayanna Frisma Handayanna Gustin Setyaningsih Halawa, Ratakan Berkat Halimatun, Futria Hardiyan Hardiyan Harun Sitompul Haryani Haryani Haryani Henry Januar Saputra, Henry Januar Hutabarat, Hot Marindo Ikha Listyarini Indra Cahyadi, Catra Indra Permana Putra intan Jananto Watori Jesica Yolanda Br. Sibarani K, Abd Hamid K, Abdul Hamid Kamil, Anton Abdul Basah Keristiana Sinaga, Enny Khairahmi, Khairahmi Khairul Khairul, Khairul Khairunnisa Zakaria Lesmana, Dicky Lubis, Ali Hamzah Mansur Mariati Mariati Maruloh Maulana, Syukran Meutia Raissa Emiliana Mochammad Abdul Azis Muhammad Amin Muhammad Junaidi Munthe, Erayana Mustaqim, Bima Mustopa, Ali Ningrum, Eri Widya Nur Hafid, Ardika Nur ‘Azah Opetu, Demitila Okola Pangaribuan, Wanapri Panjaitan, Albert Popon Handayani Popon Handayani Pratama, Adryansyah Anugrah Pribadi, Denny Priyagus, Priyagus Putri, Rizky Rachma R Mursid RACHMAT HIDAYAT Rachmat Hidayat Rahmaniar Rahmaniar, Rahmaniar Ramadan, Angga Riski Ramadhan, Khoiru Iqbal Ratna Tanjung Riska Aryanti Rizki Wahyudi Rizky Rachma Putri Rizky Syahputra Rudianto Rudianto Ryan Juska Pratama S.M Santi Winarsih Saddam Saddam, Saddam Sahat Siagian Samsidar Tanjung Samsiyatun Samsiyatun Samudi Sandra Jamu Kuryanti Saprijal, Saprijal Saputra, Agus Saputra, Muhammad Fadhlan Sari, Debby Kaumala Setyaningsih, Indah Sinaga, Irma Aprilda Siti Khoiriyah Siti Khotimatul Wildah Siti Marlina Siti Nur Khasanah Sobari, Irwan Agus Sopiyan Dalis Sri Adelila Sari Sriadhi Sriadhi Sriadhi, Sriadhi St Wulan Aprianti Sulistiyah Suwarman, S Suwarno Suwarno SYAHPUTRA, MUHAMMAD RIZKI Syekh Mohammad Asyiri Tambunan, Arsita Devi Tarigan, Adi Sastra P Tatang Bisri Teguh Febri Sudarma, Teguh Febri Usman AS Wahyudin Wahyudin Wahyudin Wahyudin Yahaya, Wan Ahmad Jaafar Wan Yosefa Hutajulu, Olnes Yoseph Tajul Arifin Yunita yunita yunita Yusra Jamali Zakaria, Khairunnisa Zubir, Moondra

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