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All Journal International Journal of Electrical and Computer Engineering International Journal of Public Health Science (IJPHS) Hemera Zoa Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Natural Science: Journal of Science and Technology Journal of English Language Teaching E-JUPEKhu Jurnal Pendidikan dan Pembelajaran Jurnal Pendidikan Humaniora Perfecting a Video Game with Game Metrics 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) Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL MANAJEMEN DAN PELAYANAN FARMASI (Journal of Management and Pharmacy Practice) SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS MEDIAN 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 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 (JP) 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 (J-ABDIMAS) AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis Jurnal Pengabmas Masyarakat Sehat Jurnal MathEducation Nusantara Kronologi Fiat Iustitia : Jurnal Hukum Prosiding SNPBS (Seminar Nasional Pendidikan Biologi dan Saintek) 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
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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

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Lodging Recommendations Using the SparkML Engine ALS and Surprise SVD Ramadhan, Sageri Fikri; Baizal, Z K Abdurahman; Rismala, Rita
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v%vi%i.2257

Abstract

Recommendation system is a process or tool used to provide predictions for users to choose something based on an existing domain. This system has become a primary need for today's modern digital industry such as in the entertainment, shopping, and service sectors. In this research, we focus on how to develop a recommendation system for accommodation services. We use the Alternating Least Square and Singular Value Decomposition methods to predict and recommend lodging to users
Conversational Recommender System for Impromptu Tourists to Recommend Tourist Routes Using Haversine Formula Liviandra, Monica; Baizal, Z K Abdurahman; Dharayani, Ramanti
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3229

Abstract

In this paper, we use two terms to describe tourists, i.e. planned tourists and impromptu tourists. Planned tourists are tourists who intentionally travel. Meanwhile, impromptu tourists are those who accidentally become tourists because they are in a new area for an activity. Previously, tourists who were going to travel usually relied on the services of travel agents to get recommendations for tourist attractions, different from impromptu tourists this was not done before. Impromptu tourists sometimes do not have much time to carry out tourism activities so that impromptu tourists only visit the closest tourist attractions from their location. Lack of experience in a new area and only relying on information on the internet makes it difficult for tourists to find tourist attractions based on their preferences. One solution to this problem is that a system is needed that can recommend tourist attractions in terms of distance by considering tourist preferences. In this study, we developed a conversational recommender system (CRS) to obtain user preferences. For the method we use the Haversine Formula to calculate the distance. The results of this study are a web application that recommends tourist attractions and routes to several tourist attractions, which can be done at one time. Based on the evaluation of the time complexity in the route search, linear complexity is obtained which shows good performance with optimal conditions.
Conversational Recommender Systems Based on Criticism for Tourist Attractions using TF-IDF Rayhan M Auliarahman; Z K Abdurahman Baizal; Nurul Ikhsan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3245

Abstract

Tourist attractions are one of the attractions of tourist interest. There are many types of tourist attractions in an area, but this becomes a problem in itself because tourists will find it hard to find or determine a tourist attractions that suit their tastes. Many researches on recommendation systems based on criticism have been carried out with the aim of obtaining user preferences. However, only a few studies have conducted a critique-based recommendation system using the Conversational Recommender System (CRS). With this research, we will discuss a recommendation system based on criticism using natural language or CRS for tourist attractions in Bandung. In this study, we add assistance from the system to help users choose preferences or what can be called System-suggested Critiques (SC), users more easily determine preferences for the system. We use the Term Frequency-Inverse Document Frequency (TF-IDF) to determine critiques submitted to users. Based on the results of an evaluation involving 88 respondents who were asked to fill out a questionnaire after trying the system built, it was found that users were quite satisfied with the system we built. And obtained 62.06% system accuracy which proves that the system performance is quite satisfactory.
Tourist Places Recommender System Using Cosine Similarity and Singular Value Decomposition Methods Theriana Ayu Waskitaning Tyas; Z K Abdurahman Baizal; Ramanti Dharayani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3151

Abstract

Tourism in the city of Bandung has various potentials in the field of culture, regional specialties, buildings, and other tourist attractions. On the Tripadvisor page there are many reviews from users who have visited tourist attractions in the city of Bandung. In this case, user reviews are an important element for analysis. The analysis process is carried out using rule-based sentiment analysis. In conducting the review analysis, we use vaderSentiment to weight the positive and negative values. Positive values are subtracted from negative values to get a compound value and converted to a rating value. The rating value obtained is then processed using the Cosine Similarity and Singular Value Decomposition methods to obtain recommendations for tourist attractions in the city of Bandung. For this method, we use the Root Mean Square Error method as a measure of the level of accuracy between the predicted values. The results of the measurement of the level of accuracy produce a value of 3,489 in the Cosine Similarity method, while the Singular Value Decomposition method gets a value of 1,231. The value in the Singular Value Decomposition method is smaller than the Cosine Similarity method with a difference of 2,258 values
Group Recommender System Using Hybrid Method Esa Alfitrassalam; Ade Romadhon; Z K Abdurahman Baizal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3220

Abstract

In our daily activities, we make a lot of decisions either individually or in groups. The recommender systems is a solution for making decisions. One of the most common recommender systems is the recommendation for tourist destinations, where a number of tourist attractions are given as tourist attractions that are recommended to be visited by someone. There are still few recommended tourist attractions that provide recommendations for a group, while there are several tourist attractions that are more suitable if visited by several people at the same time. In this study, a recommender system for tourist attractions in Bandung-Raya Regency is proposed which is given to user groups. The recommended method used is Hybrid Collaborative Filtering and Knowledge-Based Filtering. In the process of selecting groups that are candidates to be recommended to users, Borda calculations are carried out with votes so that users can determine whether they like or dislike and match or not match the recommender generated by the system. The results of the evaluation of experiments conducted by taking surveys of users showed an average value. the average of the indicators of user satisfaction with the results of group recommender is 4.4 on the scale (1-5)
Conversational Recommender Systems Based on Mobile Chatbot for Culinary Ghazi Ahmad Fadhlullah; Z K Abdurahman Baizal; Nurul Ikhsan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3242

Abstract

Culinary places are one of the tourists attractions in a place that makes many new culinary places appear. Various types of new foods and drinks are present along with the addition of culinary places. However, this can be a problem when tourists visit a new destination and look for a culinary place that suits their tastes. In the previous research on the recommendation system for culinary places, users only gave their preferences at the beginning of the recommendation process and ignored the operating hours of the recommended culinary places. Therefore, we developed a recommendation system for culinary places by utilizing the context of time from users. We use the Conversational Recommender System on the chatbot platform with the Personalized PageRank algorithm to generate recommendations. In addition, we also use the explanation facility to get an explanation of the recommended items. We use questionnaires and the accuracy of recommendation results to measure user satisfaction and system performance. The evaluation results with a questionnaire involving 81 respondents concluded that users are pretty satisfied with the system built. However, testing with accuracy yields a value of 40%, proving that the system performance is low
Question Answering Chatbot using Ontology for History of the Sumedang Larang Kingdom using Cosine Similarity as Similarity Measure Rinaldi Jasmi; Z K A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4530

Abstract

Information can also be a means of learning for humans. Including information about history because history can be a means of learning for the younger generation to appreciate the nation's culture and build national identity. In the past, the Sumedang Larang kingdom was one of the many kingdoms in West Java, Indonesia, that could be used as much information as a lesson. Technological developments make more and more information available for study. We need the proper means to find the information we need. This study aims to build a Question Answering (QA) system to create a means for the younger generation to be more familiar with the history of the kingdom in the past. The QA system offers an information retrieval system that is easy to access and can immediately provide the answers we need. This QA system was built using ontology as a knowledge base and cosine similarity to determine the similarity between user questions and the dataset. The QA system that has been built is tested by providing a set of questions so that the system's performance can be measured, and the results of system testing get a precision value of 70% and a recall value of 90%.
Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot Erbina Selvia Br Perangin-Angin; Z. K. A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4574

Abstract

Technological developments affect many aspects, one of which is historical education. History lessons can shape students' personalities and encourage an interest in historical knowledge. There are many stories from Indonesian history, one of which is the Sumedang Larang Kingdom. The Sumedang Larang Kingdom is one of the Islamic kingdoms in Pasundan. However, not many people know about this kingdom. The millennial generation is technologically advanced, so they can take advantage of technological advances to quickly introduce the history of Sumedang Larang. One of them utilizes the telegram bot using the Application Programming Interface (API), which can connect the system to the telegram platform. In addition, this technology can be used as a history learning attraction using the question answering system (QA). Our research aims to build a QA system that can introduce the history of Sumedang Larang to the millennial generation. Because this system uses ontology knowledge with concepts related to the Sumedang Larang domain, it can focus on the history of Sumedang Larang. Applying the support vector machine (SVM) algorithm to process classification text can make it easier to search for text categories. The test results show the performance of the SVM method with a test size parameter of 0.5, such as 74% and 78%. The performance test results are accuracy scores in the subject category and object classification.
Food and Beverage Recommendation in EatAja Application Using the Alternating Least Square Method Recommender System Elsa Rachel Dementieva; Z K A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4549

Abstract

EatAja is a startup in Indonesia that provides a mobile application-based food and beverage ordering solution for restaurants. The EatAja application uses transaction data to recommend food and beverage menus to customers. Previous studies have developed recommender systems using the Apriori and Collaborative Filtering methods. However, there are shortcomings in the recommendation system using both methods, i.e., the lack of personalization factors and low scalability. The learning method with matrix factorization can overcome the problem. In this study, we improve the food and beverage product recommender system in the EatAja application using the Alternating Least Square (ALS) matrix factorization method on Apache Spark. We will compare the results of the recommender system using the ALS method with the Collaborative Filtering method. The comparison uses the Mean Absolute Error (MAE) evaluation method. The results showed that the MAE value decreased by 0.07 with the ALS Matrix factorization method.
News Recommender System Based on User Log History Using Rapid Automatic Keyword Extraction Inggrid Resmi Benita; Z K A Baizal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4554

Abstract

There are many ways to find information; one of them is reading online news. However, searching for news online becomes more difficult because we should visit multiple platforms to find information. Sometimes, the recommended news doesn't match the user's interests. In many prior works, news recommendations are based on trending. Thus, the recommended news may not necessarily match the user's interests. To overcome this, we built a web-based news recommender system to make it easier for users to find news. We use the Rapid Automatic Keyword Extraction (RAKE) method in the recommendation process because this method can recommend news based on user preferences by utilizing user history logs. RAKE converts the title and content of the news into vector representation using Count vectorizer and applies the Cosine Similarity function to compare similarities between news. The test results show that the average performance of our proposed system is 90.8%, this accuracy outperforms earlier systems in terms of performance by the purpose of the recommender system, i.e., diversity, novelty, and relevance.
Co-Authors Abdul Muqit Abdullah Helmy Ade Kosasih Ade Romadhon Ade Sukma Adisti Rastosari Adri Nur Fajari Afriani Sandra Agung Toto Wibowo Agus Alim Abdullah Ahmad Lubis Ghozali Alam Rahmatulloh Albi Fitransyah Ali Rahmat Allismawita Allismawita amnah amnah An Fauzia Rozani Syafei Ana Fitriana Poerana 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 Budiman Ginting Burhanuddin Bahar Cahya, Anindya Canda Ayu Arum Pertiwi Christhofer Laurent Juliant Cut Sri Maulina D. Novia Daffa Barin Tizard Riyadi Dahlan Dahlan Damayanti, Elok Dana Sulistyo Kusumo Danang Triantoro Murdiansyah Dede Tarwidi Dedi Romli Triputra Dendy Andra Deni Novia Dessy Abdullah Devi Pratami Devina Vanesa Dhiva Rezzy Pratama Diah Pudi Langgeni Dinda Atikah Wulandari 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 Faiha Adzra Darmawan 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 Hamlan andi Hary Yuswadi Hasanuddin Hasanuddin Hasanusi, Mohammad Helmi Arifin Hendra Naldi Hendri Andi Mesta Hilda Cahyani Humaizi, Humaizi Humaizi, Humaizi Ichwanul Muslim Karo Karo Igga Febrian Virgiani Ika Arum Puspita Ikhsan, Nurul Ilham Mujaddid Al Masyriq Imam Sunarno, Imam Ina Rofi’atun Nasihati Indah Chairani Saragih Indira Adnani Indri Juliyarsi Inggrid Resmi Benita Intan Dwi Novieta, Intan Dwi Irfan Darmawan Irhas Jaya Irwan Irwan Iryanto Iryanto Iut Tri Utami Izzatul Ummah, Izzatul Jaka E. Sembodo Jamhari Jamhari Jamsari Jamsari Jaya, Irhas Jayana Citra Agung Pramu Putra Joni Dwi Pribadi Kadek Abi Satria A V P Kalsum Kalsum Kemas M Lhaksmana Kemas M. Lhaksmana Kemas Muslim Lhaksamana Kemas Muslim Lhaksmana Khaeruddin Yusuf Khaeruman Khaeruman, Khaeruman Khaidarmansyah Khairiah, Khairiah Khamim, Khamim Khasrad . Khoirunnisaa’ Khoirunnisaa’ Khusnul Diana Kun Mustain Kurnia Drajat Wibowo Kusnadi, Kusnadi Lie Othman Lilis Suryani Lisa Rahmi Litasari Widyastuti, Litasari Liviandra, Monica Lutfi Ambarwati M. Duskri M. Naufal Mu'afa M. Qadrian M. Rayhan Hakim M. Tahir Sapsuha Mahmud Imrona Mahmuda, Diah Mala Nurilmala Manik, Tumiar K.B. 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 Moch. Arif Bijaksana Moh Naufal Mizan Saputro Moh Z Mubarok Moh. Mahsus Mudayatiningsih, Sri Muh Thoriq Akhdan Muhamad Faishal Irawan Muhamad Hafidh Nofal Muhammad Adlim Muhammad Alwi Nugraha Muhammad Attalariq Muhammad Bilal Rafif Azaki Muhammad Haidir Ali Muhammad Radhiva Hibatullah Muhammad Ridha Anshari Muhammad Zaid Dzulfikar Mundjanah Mundjanah Mustakim, ' Mustofa, Mutmainnah Mutmainnah Mustofa Najla Nur Adila Naufal Aditya Naufal Akbar Hartono Ni Nyoman Sumiasih Ni Wayan Armini Niken Titi Pratitis Ningsih Purba Ningsih, Ayu Oktavia Nirmala Ayu Aryanti Nisa, Intan Khairu Nora. AN, Desri Nungki Selviandro Nur Azlina Nur Jamilah Nur Laili Ramadhani Nur Rahmawati Nur Ulfa Maulidevi Nuraini Lubis Nurul Ikhsan Nurul Ikhsan Okky Brillian Hibrianto Okky Brillian Hibrianto Pahrurrobi Pahrurrobi Paskalis Aditya Putra Prasetia, Reza Priyo Cahyono, Priyo Putri Handayani Lubis Putri Handayani Lubis Putu Harry Gunawan Qisti R Arvianti Rachmi Helfianur Rafi Rizkya Aryanta Rafiuddin, Rafiuddin Rahmat Firdaus Rahmi Wati Rais Rais Ramadhan, Sageri Fikri Ramanti Dharayani 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 Ridho Kurniawan Rusli 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 Rr. Amanda Pasca Rini, Rr. Amanda Pasca S. Syamsurizal Sa'diatul Fuadiyah Sahlya Handayati Salam N. Aritonang Sanusi Ibrahim Sarini Vita Dewi Sepri Reski Setiyoko, Didik Tri Shaufiah . Sigit Budisantoso Silvia Atika Anggrayni Simon He Siti Rohani Sri Andayani Sri Melia Suci Aprianti Sukanta Sumaryati Syukur Sunarmi Sunarmi Suyitman Suyitman Syaifuddin Ahrom Syaifuddin Ahrom Syaiful Akmal Syamsul Hadi Tebay, Selvi Teguh Surya Apri Handoyo Theriana Ayu Waskitaning Tyas Titi Sumanti Tongku Nizwan Siregar Ufra Neshia Umar Ali Ahmad Urnemi - Urnemi Urnemi Utomo, Muhajir Veritia, Veritia Vici E.H.S. Susilowati Widi Sayyd Fadhil Muhammad Winardhi, Sonny Winardhi, Sonny Wizna Wizna Yani Riyani Yanuar Firdaus Yanuar Firdaus A.W. Yanuar Firdaus Arie Wibowo Yesi Chwenta Sari Yoan Amri Akbar Yofita Sandra, S.Pd., M.Pd., Zico Farlin, Dr. Budiwirman, M.Pd., 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