Article Per Year (5 Year)
p-Index From 2021 - 2026
22.28
P-Index
This Author published in this journals
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
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
Claim Missing Document
Check
Articles

Found 21 Documents
Search
Journal : Journal of Computer System and Informatics (JoSYC)

 1   2   3 
Sistem Pendukung Keputusan dalam Mendiagnosa Gejala TBC dengan Metode WASPAS dan CPI Akhmad Primulyana; Agung Triayudi; Arie Gunawan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3068

Abstract

Mycobacterium bacteria is the cause of tuberculosis, an infectious disease that attacks the respiratory tract in humans and can easily spread through the air. In 2012, WHO data showed that tuberculosis is an infectious disease that causes the second largest health problem in the world. Tuberculosis is a disease that can attack other parts of the body as well as the lungs. The sooner a person finds out he has tuberculosis and gets tested, the more likely he will recover faster. There are many detection methods, but many are time consuming. A decision support system is needed using the WASPAS method and the CPI method which are capable of diagnosing tuberculosis. To overcome this problem. By forming a decision tree represented by rules, this decision support system implements Rank Order Centroids, one of the classification techniques in machine learning used in the data mining process. This study produces a system that is expected to make it easier for the general public to obtain timely and accurate information for diagnosing tuberculosis. A decision support system for diagnosing tuberculosis was developed as a result of this study. After being tested with 100 patient data, 50 as training data and 50 as testing data, the Confusion Matrix produces an accuracy value of 90%.
Perbandingan Metode Fuzzy Tsukamoto dengan Fuzzy Mamdani Untuk Mendeteksi Tingkat Kecanduan Media Sosial Pada Remaja Ariel Cahyono; Agung Triayudi; Rima Tamara Aldisa
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3069

Abstract

The level of social media use in Indonesia has increased every year. This is caused by several factors, one of which is the tendency to play social media so that you forget the time to do other activities such as studying. A system is needed that is able to detect whether someone is addicted to social media or not. The Tsukamoto fuzzy method is a method that can solve a problem by using a system on a computer in search of a truth and usually requires some expertise. While the fuzzy mamdani method has a function in finding a solution in solving the problem of social media addiction in today's youth. This comparison is done by the author to find the best answer from one of the methods used. This research was created in order to be able to detect the level of social media addiction in adolescents in the form of a web to inform adolescents to avoid the negative symptoms of social media addiction such as timelessness, lazy learning and being unable to stop oneself from controlling social media use. Then after testing with 25 adolescent data, the results obtained were 10 adolescents experiencing social media addiction problems and 15 adolescents not. It can be seen that the Tsukamoto method has a very addictive score of 0 to 20 for 10 teenagers and 15 teenagers with a non-addiction score of 80 to 100. Meanwhile, it is known that the Mamdani method has a very addictive score of 0 to 10 for 10 teenagers and 15 teenagers with a non-addicted score of 40 to 50.
Penerapan Sistem Pendukung Keputusan dalam Penentuan Alat Bantu Media Pembelajaran Fisika Terbaik Menggunakan Metode PSI Dwina Pri Indini; Mesran Mesran; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3466

Abstract

Technology in the Revolutionary Era 4.0 and Society 5.0 made changes in the manual learning system to digital. Along with the development of technology that makes technology and humans very difficult to separate. There are many ways to acquire learning knowledge, one of which is to use learning media tools that are already available on mobile phones. There are so many physics learning media tools available that make students confused in determining the best media to use. In determining physics learning media tools when learning online there are several criteria for Storage Capacity, Application Features, Number of Materials, Number of Language Choices, Number of Users and Rating Reviews. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Preference Selection Index (PSI) method which is very helpful in generating the best weight and preference values ​​from alternative data and criteria so that the final result is that the best physics learning media tool is in Alternative F4 with a value of 0.79563, namely the PhyWiz application.
Sistem Pendukung Keputusan Menentukan Aplikasi Chat Terbaik Menggunakan Metode OCRA Dengan Pembobotan ROC Ardinsah Ardinsah; Mesran Mesran; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3467

Abstract

In this study, a study was conducted to determine the Best Chat Application, the more we enter the digital era, the more applications and communication media or sending messages that appear. So researchers want to do research to determine which chat application is the best that people can use and unfortunately it is suitable for use today, then a system is applied that can help to decide, namely a Decision Support System (DSS) which can simplify the process of selecting the Best Chat Application by implementing 5 criteria i.e. Security, Number of Downloads, Reviews, Features, Storage. So we need a system that can make decisions by using SPK that applies the ROC and Operational Comprtitiveness Rating Analysis(OCRA) methods in getting the weighting value for each criterion and preference value from the best alternative, namely alternative A¬1 with the name Whatsapp Application with a preference value of 128,3123
Penerapan Artificial Intelligence Untuk Klasifikasi Penyakit Kulit Dengan Metode Convolutional Neural Network Berbasis Web Dimas Aryanto Wijaya; Agung Triayudi; Arie Gunawan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3519

Abstract

Skin is one of the human organs that functions to regulate body temperature in humans, as well as to protect all organs in the human body. There are many factors that affect skin health conditions that cause skin diseases. A system was developed to help people detect skin diseases. This system is Artificial Intelligence with Convolutional Neural Network method so that it will produce a very significant image. The network will be trained to find angles, edges, shapes, and also features. The results of system performance in this study using adam optimizer with a learning rate of 0.0001 get the highest value of data accuracy reaching a value of 97%. So that the identification of skin diseases is quite good.
Komparasi Metode Weighted Product (WP) Dan Simple Additive Weighting (SAW) Pada Sistem Pendukung Keputusan Dalam Menentukan Pembangunan Infrastruktur Kelurahan Flipo Hariski; Agung Triayudi; Gatot Soepriyono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3520

Abstract

The goverment gives urban villages more power includes urban village development. In accordance with local village goverment policies, there are specific criteria for allocating funds for village infrastructure development. The aim is to make the development of urban village infrastructure more equitable and targeted. Priorities for urban village infrastructure development must be decided. Decisions on urban infrastructure development are still made by voting and voting and often more significant developments have to be postponed due to losing votes. To prioritizes urban infrastructure development, urban village officials can use decision support system. Prioritization of urban village infrastructure development is determined using Simple Additive Weight (SAW) and Product weightn(WP) methodologies. Each proposal will be assessed according to the criteria chosen by the Kelurahan to determine development priorities. It is expected that the decision support system will be easier, more accurate, and faster in determining development priorities in Rangkapan jaya urban village. Comparison of SAW and WP methods using 10 alternative data, shows that both methods get accurate data and are suitable when applied as ranking of infrastructure development.
Face Mask Recognition Menggunakan Model CNN (Convolutional Neural Network) Berbasis Python dan OpenCV Chuy Mandala Putra; Agung Triayudi; Sari Ningsih
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3532

Abstract

During the COVID-19 pandemic, masks are one of the main measuring tools in carrying out health protocols, masks are also a top priority when carrying out activities outside the home or office. Because masks are quite effective in filtering out disease particles that allow users not to get infected. Therefore, many places have made masks an important requirement in maintaining health protocols during the COVID-19 pandemic. Previously there was a system that had been created to assist the government in implementing the mandatory wearing of masks, but there were still deficiencies. Therefore the authors created a system to detect mask wearing by updating previous researchers using the convolutional neural network (CNN) algorithm. For making this system the author uses the PYTHON and OPENCV programming languages. which will produce four parts in this detection, namely Mask, No Mask, Covered Mouth Chin and Covered Nose Mouth.
Perbandingan Algoritma Klasifikasi Data Mining Pada Prediksi Penyakit Diabetes Yunan Fauzi Wijaya; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4614

Abstract

Diabetes is a chronic disease that attacks humans. One of the causes of diabetes in humans is that sugar intake is too high which the body cannot balance due to absorption or activities carried out. Diabetes is often considered a common disease among people, but the impacts caused by this disease are very detrimental to humans. Based on this, it is necessary for everyone to know whether they suffer from diabetes or not. Therefore, this problem must be resolved appropriately, where it is necessary to predict whether someone will have diabetes or not. The prediction process is carried out to determine whether someone has diabetes or not by knowing the patterns or possible symptoms that cause someone to suffer from diabetes. In this research, the pattern formation process is based on data stored in the past collected in a dataset. A dataset is a collection of past data that occurred in fact and was then collected over a certain period of time on a large scale. Data mining is a method used to process data based on collections of past data, whether in datasets or others. In data mining, the data processing process is carried out using various techniques, one of which is the solution technique in data mining is classification. In this research, the Naïve Bayes algorithm, the K-Nearest Neighbor (K-NN) algorithm and the C4.5 algorithm will be used. In the data mining classification process, there are 3 (three) algorithms used, namely Naïve Bayes, K-Nearest Neighbor and C4.5. From the results of the tests that have been carried out, the accuracy performance results for the Naïve Bayes algorithm are 75%, accuracy for the K-Nearest Neighbor algorithm by 80.60% and the C4.5 algorithm by 91.80%. In this case, it indicates that the C4.5 algorithm has better performance compared to other algorithms. Therefore, the pattern results produced by the C4.5 algorithm are used to make predictions about diabetes.
Penerapan Data Mining Pada Prediksi Harga Emas dengan Menggunakan Algoritma Regresi Linear Berganda dan ARIMA Yunan Fauzi Wijaya; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4615

Abstract

The development of life has developed very rapidly at this time, one thing that has quite an important influence is the business processes carried out. Investment is a business that is carried out by all levels and also members of society easily and flexibly. Currently, the investment that is very popular with the public is gold. Gold itself is one of the most sought after precious metals at the moment, apart from being used to beautify oneself, gold can also be used as an investment asset. Based on several factors above, many people invest in gold. Investments made in Gold are not investments that have a short period of time but investments that are made over a fairly long period of time. Investing in Gold is done by buying Gold at a cheap price at the moment and then selling it again when the Gold price has risen. However, in the process that occurs, problems often occur, where the problems that occur are related to the price of gold. Where this problem can be solved by making a prediction. Data mining is used in predictions because the prediction process is carried out using data mining based on data processing. Data mining itself is a technique that is widely used today to assist in the problem solving process. In this research, the solution process was carried out using the Multiple Linear Regression algorithm and also ARIMA. In this research, the research process will be carried out by comparing the Multiple Linear Regression algorithm. Comparison of algorithms aims to obtain the most optimal results from implementing the algorithm. In solving using the Multiple Linear Regression algorithm and ARIMA, these two algorithms can help solve prediction problems by producing optimal results. From the process carried out, the Multiple Linear Regression algorithm has an RMSE value of 4902782.346, while the ARIMA algorithm gets a value of 5876287.332. This indicates that the results of the Multiple Linear Regression algorithm are better than the ARIMA algorithm.
Penerapan Data Mining Dengan Menggunakan Algoritma Clustering K-Means Untuk Pembagian Jurusan Pada Sekolah Menengah Atas Setiawan, Ikbal Danu; Triayudi, Agung
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4970

Abstract

Senior High School is the last level that must be taken before continuing education at a higher level such as a Diploma or Bachelor's degree. Where in general high schools have class majors for students who will move up to class XI from class Improving the quality of education carried out in the class majoring process means that students will be more focused in accordance with the field of interest of the major that the student/I should take. The process that occurs in determining majors is only based on the wishes expressed by the students without taking into account the academic grades of the subjects that the students have passed or completed in class X. This problem is not a small problem that should be ignored, it This is an important problem that must be resolved immediately because if the problem is not resolved immediately it will have lasting impacts later. The process of determining the division of majors for students can be seen based on the patterns or values of previous students. Data mining is a process used to complete processing of large data. The data that is processed is a collection of data that becomes Big Data from past data that is stored in a storage container and can then be reused by processing it. Clustering is an appropriate way to solve problems. Where in clustering grouping is carried out based on the distance to each data object. The K-Means algorithm is part of Clustering Data Mining, where this algorithm can be used to carry out new groupings based on how clusters are formed. From the results obtained, there are 2 (two) new formation clusters. In cluster 1 there are 9 (nine) students and in cluster 2 there are 6 (six) students.
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