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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) Sinkron : Jurnal dan Penelitian Teknik 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 Journal of Information Systems and Informatics 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 Equivalent: Jurnal Ilmiah Sosial Teknik SAGA: Journal of Technology and Information Systems
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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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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.
Sistem Pendukung Keputusan Penilaian Calon Supervisor Pada PT.Petnesia Resindo Dengan Metode Simple Additive Weighting (Saw) Triayudi, Agung; Syabana, Ulwi
Jurnal Sistem Informasi Vol 3 (2016)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (518.906 KB) | DOI: 10.30656/jsii.v3i0.131

Abstract

Sebagai elemen dalam perusahaan  yang sangat  penting  adalah Sumber Daya Manusia (SDM). Pengelolaan Sumber Daya Manusia dari suatu perusahaan sangat mempengaruhi banyak aspek penentu keberhasilan kinerja dari perusahaan tersebut. Jika kinerja perusahaan dapat terorganisir, maka segala aspek yang ada di dalam perusahaan tersebut dapat berjalan dengan baik. Sebab sumber daya manusia (SDM) merupakan faktor yang berperan penting dalam penentuan keberhasilan sumber daya manusia yaitu karyawan. Sebagai salah satu upaya dalam meningkatkan kualitas karyawan, PT. Petnesia Resindo (PNR) membuat suatu program yang bertujuan membantu dalam peningkatan potensi karyawan agar Sumber Daya Manusia (SDM) yang terdapat di perusahaan tersebut dapat dioptimalkan sesuai dengan yang di harapkan oleh  PT. Petnesia Resindo (PNR). Masalah yang terdapat pada PT. Petnesia Resindo (PNR) tersebut, karena belum adanya aplikasi sistem penilaian calon supervisor yang menggunakan pengukuran bedasarkan aspek dan kriteria-kriteria yang diinginkan serta di capai oleh perusahaan tersebut. Untuk memecahkan masalah di PT. Petnesia Resindo (PNR) dibutuhkan suatu aplikasi sistem pendukung keputusan penilaian calon supervisor yang dapat mengetahui potensi pada setiap karyawan yang ada di perusahaan tersebut secara real dan objektif dengan menggunakan metode Simple Additive Weighting (SAW).
ANALISIS RECENCY FREQUENCY MONETARY DAN K-MEANS CLUSTERING PADA KLINIK GIGI UNTUK MENENTUKAN SEGMENTASI PASIEN Setiono, Aji; Triayudi, Agung; Esti Handayani, Endah Tri
Jurnal Sistem Informasi Vol 10 No 1 (2023)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v10i1.5999

Abstract

Dengan semakin berkembangnya persaingan bisnis, agar mendapatkan pasien lebih banyak dan kepuasan pelayanan terhadap pasien, maka perusahaan harus mempunyai strategi. Palapa Dentists belum mengadopsi strategi CRM (Customer Relationship Management) masih memperlakukan semua pasien dengan pendekatan yang sama. Berdasarkan permasalahan tersebut maka diperlukan data mining menggunakan teknik cluster untuk mengetahui karakteristik setiap pasien. Penelitian ini menggunakan metode RFM (Recency Frequency Monetary) dan K-Means Clustering dengan tujuan menentukan segmentasi pasien dan memilih kelompok pasien mana yang paling menguntungkan bagi perusahaan. Penentuan jumlah cluster menggunakan elbow method yang menghasilkan jumlah cluster terbaik adalah 2. Silhouette score menghasilkan jumlah 2 cluster dengan score 0.6014345457538962. Sedangkan hasil davies-bouldin score menunjukan cluster optimal dengan 3 cluster tapi skornya 0.7500785223208264 masih jauh dari 0. Cluster 1 memiliki 17.413 anggota dan cluster 2 memiliki 2.068 anggota. Cluster 1 memiliki nilai rata-rata recency 641,63, frequency 3,21, dan monetary Rp. 2.424.251,98. Sedangkan cluster 2 memiliki nilai rata-rata recency 286,87, frequency 19,32, dan monetary Rp. 20.087.467,49. Dapat disimpulkan cluster 2 adalah kelompok pasien yang lebih menguntungkan dibandingkan cluster 1. Kata kunci: Customer Relationship Management, Segmentasi, RFM, K-Means Clustering, Cluster
Penerapan Algoritma Hash Based dalam Penemuan Aturan Asosiasi Penjualan Tanaman Hias Triayudi, Agung; Sumiati, Sumiati
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2626

Abstract

Technology is very influential in the world of increasingly fierce business competition so that business people must find strategies to increase sales results in the midst of business competition. Ornamental plant sellers must be smart in managing stock and making strategies in selling ornamental plants. Transaction data can be processed into information needed to increase sales results, one of which can be used as an analysis of the rules of the buyer transaction association in purchasing ornamental plants so that it can be processed and can support decision making on ornamental plant supplies and can assist officers in recommending other ornamental plants to buyers in a cross selling strategy. Knowing the ornamental plants that are often purchased will be a top priority that must be provided so that there is no stock shortage. In this case, data mining is needed to manage sales transaction data for ornamental plants at the Sindy Flower Shop using a Hash Based algorithm. Hash Based Algorithm that can optimally determine the frequent itemset of candidate itemset. In its application in determining the rules for selling associations of ornamental plants by applying a Hash Based algorithm to obtain frequent itemsets for the 3-itemset Dahlia, Empasen and Melati which are a combination of 3-itemset ornamental plants which are prioritized in sales with a support value of 25% and confidence of 60%
Evaluating Text Quality of GPT Engine Davinci-003 and GPT Engine Davinci Generation Using BLEU Score Heryanto, Yayan; Triayudi, Agung
SAGA: Journal of Technology and Information System Vol. 1 No. 4 (2023): November 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v1i4.213

Abstract

The improvement of text generation based on language models has witnessed significant progress in the field of natural language processing with the use of Transformer-based language models, such as GPT (Generative Pre-trained Transformer). In this study, we conduct an evaluation of text quality using the BLEU (Bilingual Evaluation Understudy) score for two prominent GPT engines: Davinci-003 and Davinci. We generated questions and answers related to Python from internet sources as input data. The BLEU score comparison revealed that Davinci-003 achieved a higher score of 0.035, while Davinci attained a score of 0.021. Additionally, for the response times, with Davinci demonstrating an average response time of 4.20 seconds, while Davinci-003 exhibited a slightly longer average response time of 6.59 seconds. The decision of whether to use Davinci-003 or Davinci for chatbot development should be made based on the specific project requirements. If prioritizing text quality is paramount, Davinci-003 emerges as the superior choice due to its higher BLEU score. However, if faster response times are of greater importance, Davinci may be the more suitable option. Ultimately, the selection should align with the unique needs and objectives of the chatbot development project.
Application of Sentiment Analysis in the Reshot Method to Improve User Experience of the Hijra Bank Application Ma'arif, Ridwan Ahmad; Triayudi, Agung
SAGA: Journal of Technology and Information System 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/saga.v2i1.240

Abstract

The first stage in simplifying User Experience (UX) using the RESHOT method is Refine the Challenge. This stage is carried out so that design practitioners know the problems or needs of application users through product research. However, the product research methods that can be carried out at this stage are very diverse and require time. This research aims to explain a product research method that can be used by design practitioners easily and quickly, namely the sentiment analysis method with the Naïve Bayes algorithm. Naive Bayes is a classification method based on simple probability. The results of this analysis will be used as a reference for improving UX using the RESHOT method on the Hijra Bank application. The results of product research using sentiment analysis obtained 2711 opinions originating from tweets on Twitter and user reviews of the Hijra Bank application on Google Play. Of the 2711 opinions, 149 had negative sentiment, with the most frequently mentioned opinions being "Customer" and "Data" with an analysis accuracy of 92%. The results of this analysis are converted into a hypothesis, which will later become a reference in designing interfaces using the RESHOT method.
Implementation of Naïve Bayes and K-NN Algorithms in Diagnosing Stunting in Children Wulan Widhari; Agung Triayudi; Ratih Titi Komala Sari
SAGA: Journal of Technology and Information System 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/saga.v2i1.242

Abstract

Indonesia faces a huge potential risk of stunting, as revealed in the Indonesian Nutrition Status Analysis according to 2022 data, the stunting rate reached 24.22% in 514 districts / cities throughout Indonesia. To prevent stunting in children, early detection can be done. This research was conducted to compare the performance of two algorithms Naive Bayes and K-NN to predict stunting cases in children, to get a better picture of how classification algorithms predict stunting cases with a better level of accuracy and responsiveness, comparison experiments of several algorithms are needed using specific datasets to develop an optimal classification model. Based on the results of performance testing on the K-Nearest Neighbor and Naive Bayes methods in testing the performance of accuracy, precision, recall, and f1-score, the results of performance testing on the naïve bayes method obtained performance values on 30% testing data are accuracy of 71%, precision 71%, recall 76%, and f1-score 73%. The performance results of the K-NN method using the euclidean distance measurement obtained the best performance value, namely accuracy of 97%, precision of 98%, recall of 96%, f1-score of 97% at a value of k = 3. Based on the performance results of the comparison of the Naive Bayes and K-NN methods, it shows that the best classification method on the stunting dataset is the K-NN method because it gets better performance than the Naive Bayes method.
Combination of AES (Advanced Encryption Standard) and SHA256 Algorithms for Data Security in Bill Payment Applications Rais Rabtsani, Muhamad; Triayudi, Agung; Soepriyono, Gatot
SAGA: Journal of Technology and Information System 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/saga.v2i1.250

Abstract

In the era of information technology development, digital payments and e-payments are becoming a dominant trend, supported by the crucial role of payment gateways such as Midtrans. Midtrans uses APIs to facilitate various online transactions, including debit cards. In this research, two cryptographic algorithms will be combined, namely Advance Encryption Standard (AES) with 256 bits and Secure Hash Algorithm (SHA) with 256 bits. The importance of data security in e-payments is recognized, with the application of cryptographic algorithms to protect sensitive transaction information. Yayasan Antero Prosesi Edukasi (YAPE) as an educational marketing consultant faced the challenge of time-consuming and inefficient manual payments. In an effort towards efficiency and security, YAPE plans to develop an online payment application with Midtrans Payment Gateway and the use of AES-256 and SHA-256 cryptographic algorithms. This step is expected to help the foundation keep up with technological developments, provide ease of payment, and achieve computerized efficiency. The results showed that the use of a combination of AES 256 bit and SHA256 encryption significantly increased security, making hacking attempts ineffective because encrypted data could not be accessed, with quite complicated calculation stages.
Inventory Management System for MSMEs Setiawan, Aan; Triayudi, Agung; Agus Iskandar
SAGA: Journal of Technology and Information System 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/saga.v2i1.251

Abstract

This inquire about points to create a web-based stock framework that centers on reasonableness, user-friendliness, and usefulness custom-made to desires of Miniaturized scale, Little, and Medium Ventures (MSMEs). Through in-depth analysis of MSMEs' specific inventory management requirements, the system not only provides a comprehensive solution for stock management but also integrates the Apriori algorithm for associative analysis of inventory data. The system's development adopts an Agile approach, allowing flexible adaptation to changing needs throughout the development process. Key features include efficient stock management, intuitive Point of Sales (POS) transaction recording, and customizable inventory reporting. The implementation of this system is expected to enhance MSMEs' efficiency in inventory management, provide insightful data to support more informed decision-making, and positively contribute to strengthening competitiveness and growth in the dynamic and competitive business environment.
Implementation of K-Nearest Neighbour (KNN) Algorithm and Random Forest Algorithm in Identifying Diabetes Diranisha, Virly; Agung Triayudi; Ratih Titi Komalasari
SAGA: Journal of Technology and Information System Vol. 2 No. 2 (2024): May 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v2i2.253

Abstract

Diabetes, one of the noncommunicable diseases (NCDs), is currently a major health threat worldwide. So far, diabetes symptoms have only been diagnosed by people according to known physical characteristics without the support of factual evidence or other medical considerations. With the advancement of technology, it is possible to use algorithms to solve various kinds of problems. One of artificial intelligence (AI), machine learning, concentrates on creating systems that can learn from data. This research uses the K-Nearest Neighbor (KNN) and Random Forest algorithms that can be utilised as testing algorithms to identify diabetes. Classification is done based on training data that has been provided in the dataset. The purpose of this research is to determine the best classification in identifying diabetes with the K-Nearest Neighbor (KNN) algorithm and the Random Forest algorithm and is expected to provide more understanding of the implementation of machine learning models. comparing the two algorithms between the KNN algorithm and the Random Forest algorithm. By dividing the testing data and training data using a ratio of 20%: 80% randomised data 300 times. The results of the accuracy evaluation obtained from the Confusion Matrix show that the Random Forest Algorithm has the best accuracy value of 77%, Precision 89%, Recall 78% and F1-Score 83% with an estimator of 100 trees. While the KNN algorithm obtained accuracy of 73%, Precision 87%, Recall 73% and F1-Score 79% of the value of K = 7. Based on the comparison results of the two algorithms, it shows that the accuracy value obtained is greater than the Random Forest algorithm even though the value obtained is not much different.
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 Adian Fatchur Rochim Aditya lutfi Irawan Afid Rozaqi Afiyan Nur Chafidin Afrasim Yusta Afriany, Joli 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 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 Arya Dimas Setiadi Arya Sastranegara Astri Pertiwi Atikah Suhaimah 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 Diaz Samba Prayogi Dicke Rifki Fajrin Dimas Aryanto Wijaya Dini Nofrisa 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 Esti Handayani Eri Mardiani Eri Mardiani Fachid, Syakirah Fadhil Muhammad Supriyanto Fadjar, Agung Rahmad Faiq Husain Pratama Faizal Kurniawan Fajar Setiawan Hidayat 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 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 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 Nanda Fathi Rizky Nesha Putri Pratama Nifea Kusumawardhani Nova Saragih 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 Komalasari Repi, Viktor Vekky Ronald Resha Anjariansyah Reynaldo, Yohanes Reza Phahlevi Junior Riad Sahara Rian Aditia Rian Rasyidhi Rian Tineges Ricky Andri Widayat 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 Rizkah Fadillah Rizki Kurnia Rizky Setiawan Rodhi, Achmad Syaifudin Rosaima Situmorang Rosalina, Vidila Rudi Adityawan Sahputra, Muhammad Ilyas Sampurno, Raffi Dima Sari Ningsih Sawindri, Sawindri sawindri Seanand Sonia Shabrilianti Seno Hardijanto Purnomo Setiawan, Ikbal Danu Setiawati, Riska Setiono, Aji Shafira Shalehanny Shintia Mutiarani Sholihati, Ira Diana Simanjuntak, Handayani 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 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 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