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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Sains dan Teknologi TELKOMNIKA (Telecommunication Computing Electronics and Control) CESS (Journal of Computer Engineering, System and Science) Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) SISFOTENIKA JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Mantik Penusa JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Jurnal Pengembangan Riset dan Observasi Teknik Informatika JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Building of Informatics, Technology and Science Jurnal Mantik Aisyah Journal of Informatics and Electrical Engineering INTI Nusa Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science JUSTIN (Jurnal Sistem dan Teknologi Informasi) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer SAGA: Journal of Technology and Information Systems Journal International Journal of Teaching and Learning (INJOTEL) INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) Journal of Blockchain, Nfts and Metaverse Technology

Agung Triayudi

Universita Nasional

Author-ID : 405605

Aerospace Engineering Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 259 Documents Claim Missing Document

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File Integrity Monitoring as a Method for Detecting and Preventing Web Defacement Attacks Kurniawan, Candra; Triayudi, Agung
JOIN (Jurnal Online Informatika) Vol 9 No 2 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i2.1326

The cybersecurity landscape in Indonesia recorded an increase in cyberattacks in 2022. One of the types of attacks observed was web defacement attacks targeting government websites. In 2022, there were a total of 2,348 web defacement attacks in Indonesia, with the majority occurring in the governmental sector. In proactive efforts to monitor and prevent web defacement attacks, this study implemented the open-source tool Wazuh and activated the file integrity monitoring module to detect file changes in the system. Testing was conducted with two types of attacks: brute force attacks to gain system access and web defacement attacks involving script insertion to trigger alerts from the file integrity monitoring. The results of the testing show that the implementation of Wazuh and the file integrity monitoring module can real-time detect malicious activities and file additions, so that it can be used to mitigate cyberattacks.

Jakarta Air Quality Classification Based On Air Pollutant Standard Index Using C4.5 And Naïve Bayes Algorithms Ramadhan, Duta Pramudya; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 2 No. 4 (2024): November 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i4.395

Increasing air pollution in DKI Jakarta has become an increasingly pressing environmental issue, which has a direct impact on public health and environmental sustainability. Therefore, it is very important to have a system that manages data-based air pollution levels. The purpose of this research is to classify air quality in DKI Jakarta through Air Pollutant Standard Index (ISPU) data. This data consists of parameters such as dust particles (PM10, PM2.5), sulfur dioxide (SO2), carbon monoxide (CO), surface ozone (O3), and nitrogen dioxide (NO2), as well as two classification algorithms used, namely C4.5 and Naïve Bayes. This research also seeks to compare the effectiveness of the two algorithms based on ISPU data collected in 15 Jakarta areas. The approach used in this research is to divide the data using three ratio scenarios, namely 70% : 30%, 80% : 20%, and 90%: 10%. In addition, performance assessment is carried out using accuracy, precision, recall and f1 score metrics. The experimental results showed better performance of C4.5, with an average accuracy of 95%, precision of 99%, recall of 94% and f1-score of 97%. In contrast, Naïve Bayes recorded an average accuracy of 81%, precision of 93%, recall of 73% and f1-score of 82%. These findings corroborate the validity of the C4. 5 algorithm is more effective in air quality classification based on ISPU, thus making it a reliable resource for air quality monitoring and management in DKI Jakarta, as well as supporting decision-making in air pollution control policies.

Analysis of Interrelationships between Weather Parameters in North Jakarta and Central Jakarta Based on Predictions Using LSTM and GRU Kurniawan, Faizal; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 2 No. 4 (2024): November 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i4.398

This study analyzes the interrelationships between weather parameters, including average temperature (Tavg), relative humidity (RH_avg), rainfall (RR), and average wind speed (ff_avg) in North Jakarta and Central Jakarta, and compares the performance of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models in predicting these parameters. Data was collected from Tanjung Priok Maritime Meteorological Station in North Jakarta and Kemayoran Meteorological Station in Central Jakarta from December 2021 to December 2024. The results show that GRU performs better in North Jakarta, with RMSE of 9,02, MSE of 81,28, and MAE of 4,21 at 75 epochs, while LSTM yields RMSE of 10,02, MSE of 100,34, and MAE of 4,62 at 50 epochs. Conversely, LSTM outperforms GRU in Central Jakarta, with RMSE of 8,96, MSE of 80,22, and MAE of 4,65 at 100 epochs, while GRU produces RMSE of 9,53, MSE of 90,78, and MAE of 4,85 at 75 epochs. GRU is more effective in capturing extreme fluctuations, while LSTM excels in predicting interrelationships between parameters. This study provides insights into selecting the appropriate weather prediction model based on the priority of prediction accuracy or the ability to capture extreme fluctuations

IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK MEMPREDIKSI PENJUALAN RITEL PADA PT CHELATAMA PERKASA MENGGUNAKAN REGRESI LINEAR Fathiya Zahra, Hawra; Triayudi, Agung
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13427

Data historis dari penjualan perusahaan ritel dapat dilakukan analisis lebih lanjut untuk membantu pengambilan keputusan dengan pengolahan data yang tepat. PT Chelatama Perkasa telah melakukan pengolahan data penjualan untuk memprediksi penjualan berdasarkan total pemasukan. Penelitian ini akan membahas implementasi business intelligence melalui Microsoft Power BI untuk memprediksi penjualan menggunakan regresi linear. Tujuan dari penelitian ini adalah untuk memberikan hasil prediksi dari pengolahan data historis dengan mengembangkan model regresi linear, dan memberikan informasi lebih baik terkait prediksi data penjualan yang disajikan dengan visualisasi data melalui rancangan dashboard. Variabel yang digunakan untuk analisis prediksi adalah jumlah jual (Y), dan jumlah modal (X). Kedua variabel yang digunakan memiliki kinerja yang baik untuk memodelkan regresi linear dengan koefisien determinasi sebesar 98%. Hasil yang diperoleh dari regresi linear tersebut adalah Y= 0 + 0,9905X. Pada evaluasi kinerja model dalam memprediksi data menggunakan Mean Squared Error diperoleh hasil sebesar 0,018801753, dan Root Mean Square Error sebesar 0,137119486. Pada dashboard menyajikan visualisasi data yang memberikan informasi berkaitan dengan hasil prediksi. Dari visualisasi data tersebut menunjukkan total prediksi jumlah jual sebesar Rp 3.882.000.000. Jenis kategori alumunium memiliki prediksi tertinggi pada barang ACP Exoboand Silver. Dan aksesoris menjadi kategori dengan penjualan terbanyak.

PENERAPAN MEMBACA TULISAN DI DALAM GAMBAR MENGGUNAKAN METODE OCR BERBASIS WEBSITE (STUDI KASUS: e-KTP) Rizal Toha, Muhammad; Triayudi, Agung
JST (Jurnal Sains dan Teknologi) Vol. 11 No. 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Penanganan yang membutuhkan data pribadi masih banyak dilakukan secara manual. Tidak jarang masyarakat memfotokopi e-KTP untuk memenuhi berbagai persyaratan administrasi. Dilihat dari tujuan pembuatan e-KTP, penggunaan e-KTP saat ini tentu kurang tepat. Optical Character Recognition (OCR) adalah proses yang memungkinkan sistem tanpa campur tangan manusia mengidentifikasi skrip atau abjad yang tertulis dalam komunikasi verbal pengguna. Identifikasi karakter optik telah berkembang pada individu dari aplikasi pengetahuan yang berkembang pesat di bidang deteksi pola dan kecerdasan buatan. Maka dari itu, penelitian ini bertujuan untuk merancang perangkat lunak pembacaan e-KTP dengan metode optical character recognition (OCR) berbasis web. Jenis penelitian merupakan jenis kuantitatif dengan pendekatan yang digunakan pengambilan data langsung ke relawan penelitian. Sistem yang akan dibuat untuk membaca tulisan dalam gambar menggunakan metode Optical Character Recognition. data yang dibahas dalam penelitian ini yaitu jumlah kartu sebanyak 20 e-KTP, jumlah attribute sebanyak 14 attribute, dan jumlah data sebanyat 280 data. Teknik yang digunakan dalam menganalisis data yaitu analisis deskriptif kualitatif dan kuantitatif. Dari hasil penelitian yang telah dilakukan dalam pendeteksian atribut pada e-KTP menghasilkan akurasi sebesar 100 persen, hasil pengujian 1 dari beberapa atribut yang ditemukan tidak nihil sebesar 98,09 persen dan hasil pengujian 2 yang mendeteksi kategori e-KTP yang masih bagus dan yang kurang bagus sebesar 67,61 persen.

Analisis Perbandingan Metode Dempster Shafer dan Certainty Factor pada Sistem Pakar Untuk Mendeteksi Penyakit Jantung Koroner Muhammad Rafi Fadhilah; Agung Triayudi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1624

This research aims to develop an expert system for detecting coronary heart disease by comparing the Demster-Shafer and Certainty Factor methods in providing accurate solutions. Coronary heart disease (CHD) is a disease that often threatens human health. To overcome this problem, the development of expert systems has become an important approach in diagnosing CHD accurately and efficiently. The problems faced include the level of complexity in diagnosing CHD and the need for solutions that can provide a high level of confidence. The method used involves collecting data from various sources and analysis using both methods to determine a diagnosis. The research results show that both methods are able to provide satisfactory results, however, a comparison between the two provides additional insight in understanding the reliability and accuracy of the expert system being developed. A thorough analysis shows that the Demster-Shafer method provides a higher degree of accuracy in some cases, while Certainty Factor tends to provide faster results. However, this research also reveals that optimal results can be achieved by combining the two methods. Thus, this research makes an important contribution to the development of an expert system for coronary heart disease detection and provides a foundation for further development in this domain. In conclusion, the integration of the Demster-Shafer and Certainty Factor methods shows the potential to improve the performance and reliability of expert systems in supporting CHD diagnosis effectively. The calculation results of both methods show that the Dempster-Shafer Method produces a certainty level of 99.8%, while the Certainty Factor Method provides a confidence level of 92%.

Penerapan Algoritma K-Means Data Mining untuk Clustering Kinerja Karyawan Koperasi Jhiro Faran; Agung Triayudi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1728

Employees are people who are the main element in every organization/company. An employee is someone who can carry out work and provide the results of their work to the employer or agency where the employee works, where the results of their work are in accordance with the profession or work based on their expertise. The role of employees in cooperatives is the same as the role of employees in general in every other organization/company. Giving rewards to employees is a form of company appreciation for its employees. Reward or recognition is a form of gratitude from the company for the dedication and performance of employees, namely those who have good quality work and have met the criteria for employees with good performance. The problem faced is that currently there is no process that has been carried out to group employee performance. Grouping employee performance is a fairly important problem and must be resolved immediately by the company. The solution to this problem can be solved by paying attention to patterns based on processes or data that occurred in the past. Data mining is the right way to solve this problem. Data mining is a process of processing data and extracting data to get information back from a collection of data. Clustering is a process of grouping data contained in a dataset. Grouping data in a dataset using clustering is done based on the similarity values or characteristics of each data. The K-Means algorithm is part of clustering data mining, where the K-Means algorithm can be used to form new groups of data. The results obtained from the research are that the formation of new groups/clusters is based on a total of 15 data, so there are 2 (two) clusters where in cluster 1 there is 7 data and cluster 2 there is 8 data

Penerapan Metode Dempster Shafer dalam Mendiagnosa Penyakit Pneumonia Muhammad Rafi Fadhilah; Agung Triayudi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1734

The aim of this research is to apply the Dempster Shafer Method in diagnosing pneumonia. This research aims to apply the Dempster Shafer Method in diagnosing pneumonia. The main problem faced in the diagnosis of this disease is the complexity and uncertainty in the interpretation of symptoms and medical test results. Dempster Shafer's method, a method in belief theory that allows combining information from multiple sources with different levels of certainty, was proposed as a solution to overcome this uncertainty. In this study, symptom data and medical test results from patients suspected of suffering from pneumonia were collected. Then, the Dempster Shafer Method is applied to combine information from various sources, such as blood test results, lung X-rays, and the patient's medical history. This method makes it possible to establish the level of confidence in the resulting diagnosis. The research results show that the application of the Dempster Shafer Method in diagnosing pneumonia provides more accurate results compared to traditional approaches. By considering the uncertainty and complexity in diagnosis, the Dempster Shafer Method is able to provide more reliable estimates and help doctors make more appropriate decisions in treating pneumonia cases. Application of the Dempster Shafer Method also produces a framework that can be adapted to diagnose other diseases that require managing uncertainty. Additionally, this approach can help increase efficiency in the diagnosis process, leading to a reduction in diagnostic errors and an improvement in the overall quality of patient care. Thus, this research makes an important contribution to the development of more sophisticated and reliable diagnostic methods in the medical field. The results of analysis using the Dempster-Shafer method show that the maximum value for each combination of symptoms that is important in diagnosing pneumonia is 0.9811, which is equivalent to 98.11%. Based on this interpretation, it is estimated that the patient has a high chance of suffering from severe pneumonia.

The Implementation of E-Commerce for Frozen Food Products in Providing Recommendations Using Item-Based Collaborative Filtering Method Simanungkalit, Racquel Terranova; Triayudi, Agung; Benrahman
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 2 (2024): August 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i2.262

The development of information technology, especially the internet, has significantly impacted facilitating human access to information, including the trend of society opting for frozen food as a fast food option. Meanwhile, the phenomenon of social media depicts the tendency of society to choose convenient and fast food. On the other hand, the rapid development of sales and product promotion systems through the internet is taking place, utilizing web-based technology. Recent studies also indicate that the development of web-based sales information systems for frozen food can enhance efficiency and service quality. Collaborative filtering methods in recommendation systems are also becoming increasingly popular in helping users obtain better recommendations. All of this indicates that information technology has had a positive impact on making purchasing and information management more efficient and convenient for society

Analysis of K-NN Algorithm and Linear Regression to Predict House Prices in Jabodetabek Nadia Putri Ariyanti; Agung Triayudi; Ratih Titi Komala Sari
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.265

Jabodetabek is now the region with the highest average level of citizen satisfaction, so many people migrate to this region in the hope of getting better living conditions, this will make people who want to buy a house question whether the house they want to buy is good value or not. The purpose of this study is to evaluate the effectiveness of multiple linear regression and K-Nearest Neighbors (KNN) algorithm on a dataset of house prices in Jabodetabek. Better results are obtained by using the Multiple Linear Regression model which has lower Mean Absolute Error (MAE) and Mean Squared Error (MSE) values and a fairly good R-squared of around 48.72%. However, the very high MAE and MSE values of the KNN model indicate inaccuracy and significant prediction variance. Although KNN has a relatively high R-squared value, more research is needed to see if the model can adequately explain data fluctuations. Based on the performance evaluation, multiple linear regression is ultimately a better choice

Co-Authors ., Hervian AAN SETIAWAN Abdul Azis Abdul Aziz Hasibuan Abdulah, Muhamad Biyan Aceng Supriyadi Achmad Syaifudin Rodhi Achmad Syirod Ade Muhammad Nur Fauzi Adi Firman Ari Saputra Adi Yulianto Aditya lutfi Irawan Afid Rozaqi Afiyan Nur Chafidin Afrasim Yusta Afriany, Joli Agung Rahmad Fadjar Agus Iskandar Agus Iskandar Agus Iskandar Ahmad Arief Fadila Ahmad Avivanto Ahmad Rizki Firdaus Aji Juliana Akhmad Primulyana Albaar Rubhasy Albaar Rubhasy Aldi Andres Ardiansah Aldya Bagas Prahastyo Alfian Muhharam Ali Rahman Alisa Fitriyani Alisya Mutia Mantika Alvian Nur Efendi Ananda Sustantiara Andarweni, Dhea Andreas Gerhard Simorangkir Andrianingsih Andrianingsih Andriansyah Utomo Anggita Putri Maharani Anhar Hawari Anharudin Anharudin apiek maniek Ardinsah Ardinsah Ardiyanto Wantudi Arie Gunawan Ariel Cahyono Arika Zuraidah Aris Gunaryati Artamevia, Zahrach Arya Dimas Setiadi Arya Sastranegara Astri Pertiwi Atikah Suhaimah Baldhan Difa Ben Rahman Benrahman Bernardito Jordan Cahya, Nilam Candra Kurniawan Chafidin, Afiyan Nur Chuy Mandala Putra Cintya Damayanti Dandi Putra Daud Iswandii Della Diniyati Deny Hidayatullah Dewi Janetta Az Zahra Dhea Andarweni Dhieka Avrilia Lantana Dian Yunita Sihombing Dicke Rifki Fajrin Dimas Aryanto Wijaya Diniyati, Della Diranisha, Virly Djamaludin, Muhammad Ariel Dwi Auditira Dwi Ifan Ramadhan Dwi Juliastuti Dwika Assrani Dwina Pri Indini Dwiyatno, Saleh Dzahabi Yunas, Rio Al E, Endah Tri Efendi, Alvian Nur Eka Febriyanto Riski Eka Permana Putra Endah Tri Eshti Handayani Endah Tri Esti Handayani Endah Tri Esti Handayani Eri Mardiani Eri Mardiani Eri Mardiani Fachid, Syakirah Fadhil Muhammad Supriyanto Fadillah, Rizkah Faiq Husain Pratama Faizal Kurniawan Fajar Setiawan Hidayat Fajhar Muhammad Fajrin, Dicke Rifki Faran, Jhiro Fardila Inastiana Fatha Alsidqi Husaini Fathiya Zahra, Hawra Ferina Gunawan Fifto Nugroho Fikar Wahyu Tyas Tono Fikri Fajar Asshiddiqi Fikrianzi Nindyo Kusumo Fildzah Fildzah Firzatullah, Raden Muhamad Flipo Hariski Frankly Sept Genius Zendrato Gatot Soepriyono Genius Zendrato, Frankly Sept Ghulam Prasetyo Utomo Hadi Ansyah Hakam, Muhammad Aulia Haris Triono Sigit Hasibuan, Abdul Aziz Hervian . Heryanto, Yayan Hidayat, Fajar Setiawan Hilman, Hilman Fikri Wijaya Hoga Saragih Ibnu Nur Khawarizmi Ikbal Danu Setiawan Iksal Iksal Iksal Iksal Imam Rizqi Imanuel Sinuraya Inastiana, Fardila indrawan indrawan ingsih, Andrian Ira Diana Sholihati Ira Diana Sholihati Ira Diana Solihati Ira Diana Solihati Iskandar Fitri Ismi Naili Qurrotul Aini Ismia Iwandini Jhiro Faran Juliana, Aji Jumpa Dorisman Rajagukguk Junior, Reza Phahlevi Kabeleke Melanesia L Kartika Salma Nadhiva Karyaningsih, Dentik Kiai Agus Priyaharto Mulia I Kodim Suparman Kusumaningtyas, Grasiella Yustika Rezka Talita Latif Arif Anggoro lia kamelia Lili Dwi Yulianto Listrina Turnip Ma'arif, Ridwan Ahmad Made Yoga Mahardika Mardiani, Eri Mauludani Muhammad Melati Indah Petiwi Melisa Theresia Mesran, Mesran Moh Dani Ariawan Muhamad Biyan Abdulah, Muhammad Andhika Maulana Muhammad Ariel Djamaludin Muhammad Aulia Hakam Muhammad Fadli Muhammad Faisal Abdillah Muhammad Faizal Muhammad Farhan Adistyra Muhammad Ilyas Sahputra Muhammad Jordy Muhammad Prabowo Chaniago Muhammad Rafi Fadhilah Muhammad Rizki Wardhana Muhammad Rizki Zidan Muhammad Rizky Hamdan Mutiara Mala Khairunnisa Nabilah Ananda Pratiwi Nadia Putri Ariyanti Nanda Fathi Rizky Nesha Putri Pratama Nifea Kusumawardhani Nofrisa, Dini Novi Dian Nathasia Novi Dian Nathasia Nur Hayati Nur Hayati Nur Hayati Nur Iskandar Zulkarnaen Nurfatanah Nurfatanah Nurfazriah Attamami Nurhadiyan, Thoha Oktaviani Oktaviani Oktaviani oktaviani Oky Triadi Sampurno Panjaitan, Fricia Oktaviani Penny Hendriyati Putra Dama Ramadhan Raffi Dima Sampurno Rafi Syahputra Rahmat Aji Santoso Raihan Abdi Negoro Rais Rabtsani, Muhamad Raka Alvianda Rama Setiawan Ramadhan, Duta Pramudya Ratih Mardianti Ratih Titi Komala Sari Ratih Titi Komalasari Repi, Viktor Vekky Ronald Resha Anjariansyah Reynaldo, Yohanes Reza Phahlevi Junior Riad Sahara Rian Aditia Rian Rasyidhi Rian Tineges Rian, Rian Hidayat Ricky Andri Widayat Riefand Fadhlurrohman Rifki Nur Apriyono Rima Tamara Aldisa Rima Tamara Aldisa Rima Tamara Aldisa Rio Al Dzahabi Yunas Ripin, Muhamad Riska Setiawati Riska Susilawati Rivaldi Okta Pratama Rizal Bagus Pambudi Rizal Toha, Muhammad Rizki Kurnia Rizky Setiawan Rodhi, Achmad Syaifudin Rosaima Situmorang Rosalina, Vidila Rudi Adityawan Sahputra, Muhammad Ilyas Sampurno, Raffi Dima Saragih, Nova Sari Ningsih Sawindri, Sawindri sawindri Seanand Sonia Shabrilianti Setiawan, Ikbal Danu Setiawati, Riska Setiono, Aji Shafira Shalehanny Shintia Mutiarani Sholihati, Ira Diana Simanjuntak, Handayani Simanungkalit, Racquel Terranova Singgih Yulianto Bastian Siti Nurhalizah Soepriyono, Gatot Solihati, Ira Diana Suginam Sugitha, I Kadek Agga Suhaimah, Atikah Suherman Suherman Sultana Namira Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati, Sumiati Suparman, Kodim Susilawati . Susilawati, Riska Sussolaikah, Kelik Syabana, Ulwi Syafrida Hafni Sahir Syavira Cahyaningsih Syirod, Achmad Thoha Nurhadiyan Titih Aji Kurniawan Titik Abdul Rahman Tiyas Asih Qurnia Putri Tobby Wiratama Putra Tyas Tono, Fikar Wahyu Untoroseto, Dedi Utami, Yulianti Pratiwi Vendy Blessing Gulo Vidila Rosalina Vivimaryati Vivimaryati Vivimaryati, Vivimaryati Wahid Al Jufri Wahyu Oktri Widyarto Wardhana, Muhammad Rizki Wibowo, Adhitya Eka WINARSIH Winarsih Winarsih Winarsih Winarsih Winarsih Winda Antika Putri Wiratama Putra, Tobby Wulan Kartika Murti Wulan Widhari Wulandari, Faras Tira Yana Tania Haryanto Yandi Makmur Yani Sugiyani Yanto Murnihati Waruwu Yohanes Reynaldo Yulianti Pratiwi Utami Yunan Fauzi Wijaya Zahrach Artamevia Zuraidah, Arika

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