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All Journal International Journal of Electrical and Computer Engineering International Journal of Public Health Science (IJPHS) Hemera Zoa IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Natural Science: Journal of Science and Technology Journal of English Language Teaching E-JUPEKhu Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Jurnal Pendidikan Humaniora TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi Lingua Cultura IJOG : Indonesian Journal on Geoscience Jurnal Ilmu dan Industri Peternakan Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Jurnal Online Mahasiswa (JOM) Bidang Ilmu Ekonomi Biotropika JURNAL PENELITIAN SAINTIKA Jurnal Riset Kimia Seminar Nasional Informatika (SEMNASIF) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) Journal on English as a Foreign Language (JEFL) Jurnal Pendidikan Kimia FKIP Universitas Halu Oleo Economic Education Analysis Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Farmasi Galenika (Galenika Journal of Pharmacy) JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL MANAJEMEN DAN PELAYANAN FARMASI (Journal of Management and Pharmacy Practice) SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS Jurnal Pendidikan Kimia (JPKim) JITK (Jurnal Ilmu Pengetahuan dan Komputer) METASASTRA: Jurnal Penelitian Sastra Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi Mesin FENOMENA Jurnal Informasi Kesehatan Indonesia (JIKI) Jurnal Agrotek Tropika Beta: Jurnal Tadris Matematika SEIKO : Journal of Management & Business English Language and Literature International Conference (ELLiC) Proceedings NUSANTARA : Jurnal Ilmu Pengetahuan Sosial Fisitek : Jurnal Ilmu Fisika dan Teknologi Surya Abdimas Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Ilmiah Ecosystem Jurnal Hilirisasi IPTEKS (JHI) Jurnal Riset Manajemen Bisnis dan Publik JTP - Jurnal Teknologi Pendidikan Jurnal Literasiologi Techno-Fish Seminar Nasional Lahan Suboptimal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Al-Ta'lim Journal of English Language Teaching and Linguistics INTEK: Jurnal Penelitian PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Journal of Community Based Environmental Engineering and Management Menara Ilmu DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pengabdian Dharma Laksana Hydrogen: Jurnal Kependidikan Kimia Atrium Pendidikan Biologi Building of Informatics, Technology and Science KREATIF : Jurnal Ilmiah Prodi Manajemen Universitas Pamulang Jurnal GeoEkonomi English Language Teaching Educational Journal Indonesian Journal of Clinical Pathology and Medical Laboratory (IJCPML) PERSPEKTIF Jurnal Perspektif: Jurnal Kajian Sosiologi dan Pendidikan Jurnal Paradigma Jurnal Ilmiah Pendidikan Matematika Al Qalasadi Jurnal Riset Teknologi Industri JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) JIIP (Jurnal Ilmiah Ilmu Pendidikan) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Hukum Adigama Journal of Data Science and Its Applications Jurnal Ecogen Jurnal Kajian Manajemen dan Wirausaha Indonesian Journal on Geoscience International Journal of Southeast Asia Indonesian Journal on Geoscience Indian Journal of Forensic Medicine & Toxicology Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Charity : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Wahana Pendidikan Jurnal Pengabdian Polinema Kepada Masyarakat Jurnal Pengabdian kepada Masyarakat Kreator Operations Management and Information System Studies Marketing Management Studies MATHunesa: Jurnal Ilmiah Matematika Jurnal Kesehatan dan Olahraga Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabmas Masyarakat Sehat Jurnal MathEducation Nusantara Kronologi The Indonesian Journal of Gastroenterology, Hepatology and Digestive Endoscopy International Journal of Educational Research Excellence (IJERE) eProceedings of Engineering Jurnal INFOTEL
ZK Abdurahman Baizal
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences 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 Nursing Physics Public Health Social Sciences Veterinary Other

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LONG SHORT TERM MEMORY APPROACH FOR SHORELINE CHANGE PREDICTION ON ERETAN BEACH Iryanto Iryanto; Ari Satrio; Ahmad Lubis Ghozali; Eka Ismantohadi; ZK Abdurahman Baizal; Putu Harry Gunawan
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 2 (2024): JITK Issue February 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i2.4139

Abstract

Eretan Beach is one of the beaches in Indramayu and has a reasonably severe abrasion rate from year to year. The Eretan coastline always experiences significant changes due to erosion every year. Therefore, it is necessary to study changes in the coastline at Eretan beach. This study obtained coastline data from the Google Earth engine using CoastSat, a python-based open-source toolkit, from 1992 – 2022. The open-source geographic information system software used to process the data is the Quantum Geographic Information System. This study aims to analyze the Long Short-term Memory (LSTM) algorithm in predicting shoreline changes at Eretan Beach. The eight optimizer functions in the LSTM are used with nine different scenarios to analyze the algorithm's performance. The results of this study show that RMSProp has the best performance compared to other optimizers. The RMSE and MAPE values on the RMSProp are 35.06258 and 2.2923 on the training data and 9.2457 and 1.06786 on the test data. In addition, from the predictions for the next ten years at transect point 251, it was found that there would be an increase in the coastline.
Diet and Physical Exercise Recommendation System Using a Combination of K-Means and Random Forest Muhammad Ilham Hafizha; Z. K. A. Baizal
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.959

Abstract

Public health has become a significant focus in this modern era due to the increasing number of people suffering from various diseases. Unhealthy diets and lack of physical activity are often associated with multiple health problems, one of which is obesity. Several studies have been conducted to develop food recommendation systems for individuals with obesity, using K-Means and Random Forest algorithms to provide food recommendations based on user-specific aspects. However, these studies do not provide supporting information, such as physical activity recommendations to address fitness issues or lack of physical activity. This study develops a diet and physical exercise recommendation system for individuals with obesity using a combination of K-Means and Random Forest. The system categorizes and classifies foods and physical exercises and provides customized recommendations based on user data analysis. The accuracy of the system was evaluated using the MAPE metric, with the highest accuracy for dietary food recommendations being 99.03% for the non-vegan lunch diet meal recommendation and the lowest being 70.74% for the vegan morning meal diet recommendation. The MAPE for physical exercise recommendations was consistently at 26.35%, indicating a stable accuracy of 73.65%. The test results show that the system recommends diet and physical exercise accurately.
NEWS RECOMMENDER SYSTEM USING HYBRID CONTENT-BASED FILTERING AND COLLABORATIVE FILTERING Nurjayanto, Bagus Wicaksono; Baizal, Z. K. A.
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 1 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i1.4256

Abstract

The development of online news services has offered users numerous choices, resulting in information overload. This makes it challenging for users to locate desired news within a spesific timeframe. to adress this, recommender systems have developed to help users discover and select news article.
Improved Collaborative Filtering Recommender System Based on Missing Values Imputation on E-Commerce P, Kadek Abi Satria A V; Baizal, Z K A
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): March 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.756 KB) | DOI: 10.47065/bits.v3i4.1214

Abstract

One of the important aspects in e-commerce is how to recommend a product to users accurately. To achieve this goal, many e-commerce starts to build and research about recommender system. Many methods can be used to build a recommender system, one of them is using the collaborative filtering technique. This technique often experiences data sparsity problem that can impact to the recommender system prediction accuracy. To solve this problem, we apply improved collaborative filtering. This method predicts the missing values in the user item rating matrix. First, we do an initial selection to determine potential users who have the same characteristics with the active user. After that, we calculate the average distance between the active user and the other selected user. Next, we calculate missing values prediction. Missing values predictions is only done for items that have never been rated by other’s selected user but has been rated by the active user. We used Amazon electronic product with high sparsity level in this research to simulate the actual condition of e-commerce. We used MAE and RMSE to measure prediction accuracy. The methods we apply succeeds to improve the prediction accuracy compare to the conventional collaborative filtering method. The average MAE for method that we apply is 0.78 and RMSE 1.07
Movie Recommendation System Using Knowledge-Based Filtering and K-Means Clustering Wibowo, Kurnia Drajat; Baizal, Z K A
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): March 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (400.826 KB) | DOI: 10.47065/bits.v3i4.1236

Abstract

The movie recommender system has an important role in providing movie recommendations for users, but new users have difficulty choosing movies that are given by the recommender system because of the cold start problem. This study aims to overcome the cold start problem using a knowledge-based recommender system, i.e association rule mining using an apriori algorithm. The apriori algorithm aims to extract correlations between product itemsets, but the problem in the apriori algorithm is the large number of association rules that make the complex computation. To overcome this problem, we combine the apriori algorithm and k-means to produce more accurate recommendations, because the items are grouped before the recommendation process using the k-means algorithm. In this study, we use a dataset of movies and ratings from the Kaggle website. This study uses a minimum value of 0.5 confidence, and a minimum value of 4 lifts. To produce the best itemset in the form of antecedents and consequents of the Beauty and the Beast item with The Passion of Joan of Arc which has a value of 0.107981 support, 0.779661 confidence, 4.151695 lift
Healthy Food Recommender System for Obesity Using Ontology and Semantic Web Rule Language Aditya, Naufal; Baizal, Z. K. A.; Dharayani, Ramanti
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3005

Abstract

Today's lifestyle and eating patterns tend to be irregular due to busyness. People prefer eating foods that are fast and easy to obtain, but often lack knowledge of the nutritional content in them. These eating patterns lead to unbalanced nutrition and can cause various health problems and diseases, such as overweight and obesity. Due to a lack of information, people often turn to drugs instead of learning about healthy diets, making it difficult for them to determine what menu to choose or what type of food to consume. While there have been many studies to recommend healthy food based on user preferences, there is currently no recommender system that includes serving size and budget for each daily food recommendation that is implemented in a chatbot framework. This study proposes using ontology and the Semantic Web Rule Language (SWRL) to store knowledge in the ontology and then process it using SWRL to produce food recommendations based on user preferences. From a sample of user data which obtained 170 recommended meal menus. System performance is pretty good. Based on the validation results from nutritionists, the precision value was 0.852941, the recall was 1, and F-score of 0.920634 So that a healthy food recommendation system can be used to help the user follows a diet that meets his nutritional needs and is within his budget needed
Content-Based Music Recommender System Using Deep Neural Network Baizal, Z. K. A.; Andiety, Rich
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5762

Abstract

Music is one of the most popular forms of entertainment. Along with the development of information technology, music streaming platforms such as Spotify, Apple Music, and Deezer are increasingly popular among users. However, with thousands of songs available on these music streaming platforms, users often have difficulty finding songs that suit their tastes. Therefore, we design a music recommender system that can assist users in finding songs that are more in line with user preferences. In this research, we propose the development of a content-based music recommender system using a combination of Content-Based Filtering and Deep Neural Network (DNN) methods. The DNN used is Convolutional Neural Network (CNN) which serves to increase the percentage of accuracy to provide results that match user needs. This research aims to develop a music recommender system that can provide personalized recommendations to users according to the preferences of users. This research provides an accuracy result of 73.5%. From these results, it has been proven that the resulting music recommendations can be an alternative to the existing Collaborative Filtering-based recommender system.
Item-Based Collaborative Filtering Bandung Café Recommender System Using Recurrent Neural Network Baizal, Z. K. A.; Sitorus, Angela Tiara Maharani
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5772

Abstract

The aim of this study is to develop a dependable Cafe Recommender System for the Bandung area by employing a fusion of Item-Based Collaborative Filtering (IBCF) and Recurrent Neural Network (RNN) methodologies. The motivation behind this study stems from the growing need for more accurate and relevant café recommendations in Bandung, a city renowned for its diverse selection of cafes. Previous research has primarily focused on using either collaborative filtering or natural language processing approaches independently, leading to frequent limitations in understanding the entire context of user preferences and judgments. To address these shortcomings, we utilize the IBCF technique to analyze user rating data, identifying similarities amongst cafes to generate personalized recommendations. Concurrently, we employ the Recurrent Neural Network (RNN) method to examine and understand user reviews, facilitating a more advanced and contextually sensitive suggestion procedure. Our hypothesis posits that the amalgamation of IBCF (Item-Based Collaborative Filtering) and RNN (Recurrent Neural Network) will enhance the precision and pertinence of recommendations in the Bandung region. The assessment of the recommendations is conducted using measures such as Precision, Recall, and F1-score. The model demonstrates a precision of 89.04%, a recall of 88.75%, and an F1-score of 88.62%, which suggests that it is a suitable alternative to commonly used strategies for recommending cafes.
Ontology-Based Food Menu Recommender System for Patients with Coronary Heart Disease Najla Nur Adila; Baizal, Z. K. A.
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12858

Abstract

Coronary heart disease is one of the leading causes of death. Knowledge of dietary patterns and proper food selection is an effort to address the risk and support coronary heart disease's healing process. Therefore, this study developed a food menu recommender system as a reference for patients with coronary heart disease. The recommender system is crucial in creating a proper dietary pattern for managing personalized meal plans. The system calculates the required nutritional needs of users. Ontology is used to represent knowledge about nutrition data and food intake. The ontology base with Semantic Web Rule Language (SWRL) enables the system to identify the most suitable foods for patients with coronary heart disease. We use SWRL rules to generate recommendation conclusions based on the existing ontology. Using this language enhances the descriptive logic capabilities, as the rules can overcome the limitations of the ontology language. Therefore, the system is built to find food menu options that match the required nutrition for patients. The nutritionist knowledge will be used to measure the system's performance compared to the recommendations made by nutritionists. From the user data sample, 150 recommended food menu data were obtained. The validation performance results obtained a precision 0.893, recall 1, and F_Score 94.3%.
Ontology-based Nutrition Recommender System for Stunting Patients Ramadhani, Nur Laili; Baizal, Z. K. A.
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12888

Abstract

Stunting is a growth disorder that occurs in early childhood. This condition occurs because the child has a chronic nutritional problem which triggers the child to have a height below normal. The indicator used as a standard for whether a child is stunted or not is height for age. If a child has a z-score value less than -2 standard deviations, then the child is said to suffer from stunting. Poor nutritional intake is one of the factors causing children to suffer from stunting. Most Indonesian people think that the genetics of both parents causes children to be shorter than their age, but genetics is a minimal factor that causes stunting. In 2020, Indonesia ranks second in the prevalence of stunting in Southeast Asia, according to the Asian Development Bank (ADB) report. Based on the results of the Indonesian Nutritional Status Survey (SSGI) in 2021, the stunting prevalence rate in Indonesia 2021 is 24.4%, but in 2022, the stunting prevalence rate will drop to 21.6%. One way to treat stunting in children is by providing daily nutritional intake according to the child's condition. In this study, we used the Telegram chatbot with an ontology and the rules Semantic Web Rule Language as a knowledge base. The accuracy performance of our system is 93.3% which shows that our system can provide nutritional recommendations for stunting patients.
Co-Authors Abdul Muqit Abdullah Helmy Ade Kosasih Ade Romadhon Ade Sukma Adisti Rastosari Aditya, Naufal Adri Nur Fajari Afriani Sandra Agung Toto Wibowo Agus Alim Abdullah Ahmad Lubis Ghozali Akbar, Yoan Amri Alam Rahmatulloh Albi Fitransyah Ali, Muhammad Haidir Allismawita Allismawita amnah amnah An Fauzia Rozani Syafei Ana Fitriana Poerana Andiety, Rich Andini, Andini Andjioe, Oscar Rynandi Angelina Sagita Sastrawan Anindya, Widya Dara Aniq A Rahmawati Aniq A. Rahmawati Anisa Herdiani Annisa Cahya Anggraeni Annisa Cahya Anggraeni Antonius Randy Arjun Ardi Ardi Ari Satrio Arie Lasaprima Arifa Nur Hasanah Aryadi Pramarta Ayunda Farah Istiqamah Budiarti, L Endang Burhanuddin Bahar Cahya, Anindya Cahyani, Hilda Canda Ayu Arum Pertiwi Christhofer Laurent Juliant Cut Sri Maulina D. Novia Daffa Barin Tizard Riyadi Damayanti, Elok Dana Sulistyo Kusumo Danang Triantoro Murdiansyah Darmawan, Faiha Adzra Dede Tarwidi Dedi Romli Triputra Dendy Andra Deni Novia Dessy Abdullah Devi Pratami Devina Vanesa Dhiva Rezzy Pratama Diah Mahmuda Diah Pudi Langgeni Djoko Wahyono Donni Richasdy Dreyfus, Shoshana Dwi H Widyantoro Dwi Maya Sari Dwinda Tamara Edy Tandililing Eka Ismantohadi Elly Roza Elsa Rachel Dementieva Erbina Selvia Br Perangin-Angin Erliansyah Nasution Erni Masdupi Erwin B. Setiawan Erwin Budi Setiawan Esa Alfitrassalam Evitayani Evitayani Fadillah, Ichsan Alam Fatimah Nurhayani Fatimatus Zahroh Favian Dewanta Ferawati Ferawati Fernandy Marbun Ferry Lismanto Syaiful Firmansyah Firmansyah Fitriani Mangerangi Gentra Aditya Putra Ruswanda Gesit Tabrani Ghazi Ahmad Fadhlullah Gholib Gholib Grace Yohana Grace Yohana Gusti Ayu Marheni Gustina Lubis Hafid Ahmad Adyatma Hakim, Lukman Nur Hamlan andi Hary Yuswadi Hasanuddin Hasanuddin Hasanusi, Mohammad Helmi Arifin Hendra Naldi Hendri Andi Mesta Humaizi, Humaizi Humaizi, Humaizi Ichwanul Muslim Karo Karo Ida Ayu Putu Sri Widnyani Igga Febrian Virgiani Ika Arum Puspita Ilham Mujaddid Al Masyriq Imam Sunarno, Imam Ina Rofi’atun Nasihati Indira Adnani Indri Juliyarsi Inggrid Resmi Benita Intan Dwi Novieta, Intan Dwi Irfan Darmawan Irhas Jaya Iryanto Iryanto Iut Tri Utami Izzatul Ummah Jaka E. Sembodo Jamhari Jamhari Jamsari Jamsari Jaya, Irhas Jayana Citra Agung Pramu Putra Joni Dwi Pribadi Kalsum Kalsum Kemas M Lhaksmana Kemas M. Lhaksmana Kemas Muslim Lhaksmana Khaeruddin Yusuf Khaidarmansyah Khairiah, Khairiah Khamim, Khamim Khasrad . Khatimah, Ummu Husnul Khoirunnisaa’ Khoirunnisaa’ Khusnul Diana Kun Mustain Kusnadi, Kusnadi Lie Othman Lilis Suryani Lisa Rahmi Litasari Widyastuti, Litasari Liviandra, Monica Loiz, Andhika Lubis, Putri Handayani Lutfi Ambarwati M. Duskri M. Naufal Mu'afa M. Qadrian M. Rayhan Hakim M. Tahir Sapsuha Mahmud Imrona Mala Nurilmala Mansyur Arif Marayasa, I Nyoman Marendra Septianta Mayasari Mayasari Mella Ismelina F. Rahayu Miranti Andhita Scantya Mirna Fitrani Misna Ariani Mizanul Kirom Moch Arif Bijaksana Moh Naufal Mizan Saputro Moh Z Mubarok Moh. Mahsus Mudayatiningsih, Sri Muhamad Faishal Irawan Muhamad Hafidh Nofal Muhammad Adlim Muhammad Agus Muljanto Muhammad Alwi Nugraha Muhammad Attalariq Muhammad Bilal Rafif Azaki Muhammad Ilham Hafizha Muhammad Ilham Hafizha Muhammad Ridha Anshari Muhammad Zaid Dzulfikar Mustakim, ' Mustofa, Mutmainnah Mutmainnah Mustofa Najla Nur Adila Naufal Akbar Hartono Ni Nyoman Sumiasih Ni Wayan Armini Niken Titi Pratitis Ningsih Purba Ningsih, Ayu Oktavia Nirmala Ayu Aryanti Nisa, Intan Khairu Nofal, Muhamad Hafidh Nora. AN, Desri Nungki Selviandro Nur Azlina Nur Jamilah Nur Rahmawati Nur Ulfa Maulidevi Nuraini Lubis Nurjayanto, Bagus Wicaksono Nurul Ikhsan Okky Brillian Hibrianto Okky Brillian Hibrianto P, Kadek Abi Satria A V Pahrurrobi Pahrurrobi Paskalis Aditya Putra Prabowo, Ruh Devita Widhiana Prasetia, Reza Putra, A. D. A. Putu Harry Gunawan Qisti R Arvianti Rachmi Helfianur Radhiva Hibatullah, Muhammad Rafiuddin, Rafiuddin Rahmat Firdaus Rahmi Wati Rais Rais Ramadhan, Sageri Fikri Ramadhani, Nur Laili Ramanti Dharayani Randika Dwi Maulana Rasyid Ranestari Sastriani Rasbawati, Rasbawati Rayhan M Auliarahman Reinaldo Kenneth Darmawan Rena Feri Wijayanti Restu Aditya Rachman Reza Rendian Septiawan Rezano, Tomi Richo Fedhia Saldhi Rika Afriani Rina Dahlyanti Rinaldi Jasmi Rinita Amelia Risa Tiuria Risfaheri - Riska Padilah Riski Hernando Rita Rismala Rizaldy Arigi Rizky Andrian Rizqi Bayu Aji Robi Amizar Roby Dwi Hartanto Rohmat Gunawan Romy Adzani Adiputra Roseno, Rizky Haffiyan Rr. Amanda Pasca Rini, Rr. Amanda Pasca Rusli, Ridho Kurniawan S. Syamsurizal Sa'diatul Fuadiyah Sahlya Handayati Salam N. Aritonang Sanusi Ibrahim Sarini Vita Dewi Sedyo Mukti, Putri Ayu Sepri Reski Setiyoko, Didik Tri Shaufiah . Sigit Budisantoso Silvia Atika Anggrayni Simon He Siti Rohani Sitorus, Angela Tiara Maharani Solly Aryza Sri Andayani Sri Melia Suci Aprianti Sukanta Sumaryati Syukur Suyitman Suyitman Syaifuddin Ahrom Syaifuddin Ahrom Syaiful Akmal Syamsul Hadi Tebay, Selvi Teguh Surya Apri Handoyo Theriana Ayu Waskitaning Tyas Thoriq Akhdan, Muh Titi Sumanti Tongku Nizwan Siregar Ufra Neshia Umar Ali Ahmad Urnemi - Urnemi Urnemi Utomo, Muhajir Veritia, Veritia Vici E.H.S. Susilowati Wibowo, Kurnia Drajat Winardhi, Sonny Winardhi, Sonny Wiratama, Arga Kusuma Wiwik Handayani Wizna Wizna Wulandari, Dinda Atikah Yani Riyani Yanuar Firdaus Yanuar Firdaus A Yanuar Firdaus A.W. Yesi Chwenta Sari Yoan Amri Akbar Yolani Utami Yudha E. Pratama Yudha Endra Pratama Yuherman Yuherman Yulia Murni Yulia Yellita Yuliant Sibaroni Yulianti Fitri Kurnia Yuliawati Yuliawati Yulisna Gita Hapsari Yundari, Yundari Yusabri Yusran Khery, Yusran Yusri Dianne Jurnalis Yusza Reditya Murti Zidni Mubarok Zoni Hidayat