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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Edutech Techno.Com: Jurnal Teknologi Informasi Syntax Jurnal Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JDM (Jurnal Dinamika Manajemen) Jurnal Teknik Elektro Jurnal Informatika Jurnal Penelitian Ekonomi dan Bisnis Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Educational Science and Technology Scientific Journal of Informatics POSITIF ANDHARUPA CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris JOIN (Jurnal Online Informatika) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer International Journal of Artificial Intelligence Research Creative Information Technology Journal SISFOTENIKA Jurnal Administrasi Publik : Public Administration Journal Emerging Science Journal JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal Jurnal Teknoinfo Technomedia Journal ILKOM Jurnal Ilmiah Journal of Education Technology Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal SENSITEK ADI Journal on Recent Innovation (AJRI) Journal of Innovation and Future Technology (IFTECH) ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Computer Science and Information Technologies Journal of Innovation in Educational and Cultural Research ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Engineering, Science and Information Technology Jurnal Manajemen Retail Indonesia (JMARI) ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) MAVIB Journal : Jurnal Multimedia Audio Visual and Broadcasting Automotive Experiences International journal of education and learning Jurnal Dinamika Informatika (JDI) International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Media Riset Akuntansi Auditing & Informasi Universal Raharja Community (URNITY Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi SATIN - Sains dan Teknologi Informasi Jurnal Sistem Informasi International Transactions on Education Technology (ITEE) Nusantara Journal of Computers and its Applications Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Jurnal ilmiah teknologi informasi Asia Journal of Computer Science and Technology Application Journal of Digital Market and Digital Currency International Journal Research on Metaverse Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
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Camera Trap Approaches Using Artificial Intelligence and Citizen Science Untung Rahardja
International Transactions on Artificial Intelligence Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i1.202

Abstract

For the purpose of tracking several animal species, camera trapping is developing into a more reliable and popular technology. The idea of "citizen science"—incorporating members of the public into the research process—has been gaining momentum concurrently . As a result, millions of individuals have made contributions to research in numerous sectors. Despite early acknowledgment of camera traps' significance for public engagement, they were previously unsuited for citizen science. Academics are seeking assistance in categorizing film as a result of camera trap technological advancements that have made cameras more user-friendly, as well as the massive amounts of data that they now collect. Because of this, there are many camera trap efforts that now involve public participation, indicating that camera trap research is now a viable choice for citizen science. In order to categorize films, researchers are also applying artificial intelligence (AI). Although it has already been established that this rapidly developing field is useful, accuracy varies, Furthermore, AI does not provide the social and engagement advantages that citizen scientific endeavors provide. More attempts at fusing citizen science and AI are being suggested as a strategy to boost classification efficiency and accuracy while maintaining public interaction.
AI-Based Strategies to Improve Resource Efficiency in Urban Infrastructure Ninda Lutfiani; Nuke Puji Lestari Santoso; Ridhuan Ahsanitaqwim; Untung Rahardja; Achani Rahmania Az Zahra
International Transactions on Artificial Intelligence Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i2.545

Abstract

Rapid urbanization has significantly increased urban populations, leading to higher consumption of resources such as energy, water, and fuel. Resource efficiency is crucial to managing urban growth in an environmentally friendly and economical manner. This research aims to explore the role of artificial intelligence (AI) in improving resource efficiency in urban infrastructure. By leveraging AI technology, this study seeks to find innovative solutions that can optimize resource use, enhance energy management, and improve monitoring and control of infrastructure systems. The findings indicate that the implementation of AI can increase energy efficiency by 15%, reduce transportation travel times by 15%, and improve water management efficiency by 15%. These results demonstrate that AI can be an effective tool in supporting the sustainability of urban infrastructure, reducing operational costs, and mitigating environmental impacts. This research provides practical guidance for city managers and policymakers in designing and implementing smarter and more efficient technological solutions.
Using Highchart to Implement Business Intelligence on Attendance Assessment System based on YII Framework Untung Rahardja
International Transactions on Education Technology (ITEE) Vol. 1 No. 1 (2022): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v1i1.176

Abstract

Today's students keep track of their attendance, and advisors can easily access that data. However, there are three (three) challenges that the advisor must overcome, one of which is submitting information in the form of a table that must be compared with great care and correctness.To facilitate the registration and measurement of advisor attendance for student advice An information form chart will be submitted by PenA (Attendance Assessment) using Highchart. Nim, Advisor, and Time of guidance are the information categories presented in the PenA (Attendance Assessment) chart. A comparison of the time guidance information in the chart may be used to assess how willingly the student is following the instructions.enA (Attendance Assessment) uses a Yii Framework-based website because it makes developing web apps easier and has a sufficient level of security.There are five (5) gains and one (1) deficit on PenA in this study (Attendance Assessment). It has been anticipated that PenA (Attendance Assessment) will improve the caliber of students' attendance in the University of Raharja's supervision procedure.
Social Media Analysis as a Marketing Strategy in Online Marketing Business Rahardja, Untung
Startupreneur Business Digital (SABDA Journal) Vol. 1 No. 2 (2022): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.367 KB) | DOI: 10.33050/sabda.v1i2.120

Abstract

Information technology in the last few years has experienced fairly rapid development. During this period, a a platform that allows people around the world to connect with each other called social media. Today, Facebook, Twitter and Instagram are social media that is experiencing the fastest development. The three social media has begun to be widely used to promote a product and be used as a one of the marketing strategies by several business people. The purpose of this journal is to: to explore the use of social media especially Facebook, Twitter and Instagram in online business marketing strategy. Research is expected to be input for business people who want to use social media as one of the media promotion of services and products. This study aims to find out how the use of social media as a business strategy by some business people online based.
The Adoption of Blockchain Technology the Business Using Structural Equation Modelling Aini, Qurotul; Manongga, Danny; Sediyono, Eko; Joko Prasetyo, Sri Yulianto; Rahardja, Untung; Santoso, Nuke Puji Lestari
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 1 (2024): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.82107

Abstract

There are many aspects of readiness that must be considered when implementing technological breakthroughs, the business sector is still relatively slow in adopting blockchain technology. However, considering that blockchain technology is still in its early stages of development and has many potential applications, it is necessary to conduct empirical studies on the factors influencing its application in the industry. The problem of this study is to develop an appropriate framework based on how well its features match the needs of the business sector. This research method uses data collection using online questionnaires to obtain information from 86 respondents. The current study also utilizes the Smart PLS 4 model to produce a structural hypothetical model. The results of this study find a significant influence on Revolutionary Innovation by enriching the literature on the relationship between Blockchain, Big Data and the Business Sector, which is expanded by adding new variables. The novelty of this research identifies potential utilization, analyzes internal and external factors, and identifies how blockchain disrupts the business sector. The purpose of this study is to assess how blockchain technology is currently used in the business sector for data provision as a theoretical information technology innovation
Deciphering Digital Social Dynamics: A Comparative Study of Logistic Regression and Random Forest in Predicting E-Commerce Customer Behavior Sunarya, Po Abas; Rahardja, Untung; Chen, Shih Chih; Lic, Yung-Ming; Hardini, Marviola
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.155

Abstract

This study compares Logistic Regression and Random Forest in predicting e-commerce customer churn. Utilizing the E-commerce Customer dataset, it navigates the complexities of customer interactions and behaviors, offering a rich context for analysis. The methodology focuses on meticulous data preprocessing to ensure data integrity, setting the stage for applying and evaluating Logistic Regression and Random Forest. Both models were assessed using accuracy, precision, recall, F1-Score, and AUC-ROC. Logistic Regression showed an accuracy of 90%, precision of 91% for class 0 and 82% for class 1, recall of 98% for class 0 and 50% for class 1, F1-Score of 94% for class 0 and 62% for class 1, and AUC-ROC of 0.88. Random Forest, with its ability to handle complex patterns, demonstrated higher overall performance with an accuracy of 95%, precision of 95% for class 0 and 93% for class 1, recall of 99% for class 0 and 74% for class 1, F1-Score of 97% for class 0 and 82% for class 1, and an AUC-ROC of 0.97. This comparative analysis offers insights into each model's strengths and suitability for predicting customer churn. The findings contribute to a deeper understanding of machine learning applications in e-commerce, guiding stakeholders in enhancing customer retention strategies. This research provides a foundation for further exploration into the digital social dynamics that shape customer behavior in the evolving digital marketplace.
Predictive and Analytics using Data Mining and Machine Learning for Customer Churn Prediction Lukita, Chandra; Bakti, Lalu Darmawan; Rusilowati, Umi; Sutarman, Asep; Rahardja, Untung
Journal of Applied Data Sciences Vol 4, No 4: DECEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i4.131

Abstract

This research aims to predict and analyze customer churn using Data Mining and Machine Learning methods. The background of this research is based on the importance of understanding the factors that influence customer decisions to churn, as well as improving the effectiveness of customer retention strategies in a business context. The method used in this research involves the use of a customer bank dataset that includes information about customers who left in the past month, services registered by customers, customer account information, and demographic info about customers. The factors most influential to churn were identified through heatmap analysis, including MonthlyCharges, PaperlessBilling, SeniorCitizen, PaymentMethod, MultipleLines, and PhoneService. This research compares the performance of several machine learning algorithms, including Random Forest, Logistic Regression, Adaboost, and Extreme Gradient Boosting (XGBoost), to predict customer churn. Accuracy metrics and confusion matrix results are used to evaluate the performance of these algorithms. The results showed that XGBoost proved to be the best algorithm in predicting customer churn with high accuracy. The factors that have been correctly identified do not provide missed precision, showing a significant influence on customer churn decisions. The novelty and uniqueness of this research lies in focusing on the factors that have the most influence on customer churn and comparing the performance of machine learning algorithms. This research provides more specific and relevant insights for companies in developing effective customer retention strategies. However, this research has some limitations. One of them is the use of a dataset limited to a customer bank, so the generalizability of the findings of this research may be limited to that business context. In addition, other factors that are not the focus of this research may also contribute to the prediction of customer churn.
Improving Recommender Systems using Hybrid Techniques of Collaborative Filtering and Content-Based Filtering Widayanti, Riya; Chakim, Mochamad Heru Riza; Lukita, Chandra; Rahardja, Untung; Lutfiani, Ninda
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.115

Abstract

This innovative study introduces a novel enhancement to recommendation systems through a synergistic integration of Collaborative Filtering (CF) and Content-Based Filtering (CBF) techniques, termed the hybrid CF-CBF approach. By seamlessly amalgamating the strengths of CF's user interaction insights and CBF's content analysis prowess, this approach pioneers a more refined and personalized recommendation paradigm. The research encompassed meticulous phases, including comprehensive data acquisition, efficient storage management, meticulous data refinement, and the skillful application of CF and CBF methodologies. The findings markedly highlight the prowess of the hybrid approach in generating recommendations that exhibit enhanced diversity and precision, surpassing the outcomes obtained from either technique in isolation. Remarkably, the hybrid CF-CBF approach effectively addresses the inherent shortcomings of individual methods, such as CF's vulnerability to the "cold start" problem and CBF's limitation in fostering recommendation diversity. By fostering a harmonious synergy, this novel approach transcends these limitations and provides a holistic solution. Furthermore, the interplay of CF and CBF augments the recommender system's cognitive grasp of user preferences, subsequently enriching the quality of recommendations provided. In conclusion, this research stands as a pioneering contribution to the evolution of recommendation systems by championing the hybrid CF-CBF approach. By ingeniously fusing two distinct techniques, the study engenders a breakthrough in personalized recommendations, thereby propelling the advancement of more sophisticated and effective recommendation systems.
Skema Catatan Kesehatan menggunakan Teknologi Blockchain dalam Pendidikan Rahardja, Untung
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 1 No 1 (2022): September
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.839 KB) | DOI: 10.33050/mentari.v1i1.134

Abstract

Salah satu permasalahan serius yang dihadapi bangsa Indonesia adalah masalah medis khususnya masalah medis anak usia sekolah. Rekam medis data siswa merupakan suatu hal yang sangat penting serta memberikan manfaat yang dirasakan baik dari pasien, dokter dan petugas medis lainnya dalam hal pengambilan keputusan klinis. Melihat kepentingan hadirnya rekam medis, di Indonesia pun telah menerapkan inovasi penggunaan teknologi dalam penerapan rekam medis digital. Namun, hingga saat ini masih terdapat permasalahan yang terjadi dalam penerapan teknologi rekam medis yang ada bersifat sentralisasi sehingga masih sulit mendapatkan kepercayaan dari pasien. Oleh karena itu, dalam hal ini penelitian akan memiliki menyajikan keterbaruan berupa implementasi teknologi Blockchain pada objek penelitian penyimpanan database rekam medis tanpa keterlibatan pihak ketiga (Desentralisasi). sehingga sebagai solusi, pada penelitian ini akan menghadirkan skema sistem arsitektur teknologi Blockchain dengan keunggulan yang diberikan adanya transparansi dan sifat yang desentralisasi untuk tujuan meningkatkan kepercayaan pasien terhadap rekam medis dengan database bersifat desentralisasi dan transparan. Dalam menuju keberhasilan penelitian, metode yang digunakan adalah mind mapping yang akan memcahkan detail permasalahan dan solusi yang dihadirkan. Hasil dari penelitian yang didapatkan, sistem dapat meminimalisir penyalahgunaan data, serta rancangan skema yang dihadirkan tidak akan bergantung pada platform Blockchain yang menjadikan skema memiliki potensi penerapan lebih luas pada elektronik medis lainnya untuk meningkatkan keketatan perlindungan data sistem.
Enhancing Machine Learning with Low-Cost P M2.5 Air Quality Sensor Calibration using Image Processing Rahardja, Untung; Aini, Qurotul; Manongga, Danny; Sembiring, Irwan; Ayu Sanjaya, Yulia Putri; Rahardja.,M.T.I.,MM, Dr. Ir. Untung
APTISI Transactions on Management (ATM) Vol 7 No 3 (2023): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v7i3.2062

Abstract

Low-cost particulate matter sensors, due to their increased mobility compared to reference monitors, are transforming air quality monitoring. Calibrating these sensors requires training data from reference monitors, which is traditionally done through conventional procedures or by using machine learning techniques. The latter outperforms traditional methods, but still requires deployment of a reference monitor and significant amounts of training data from the target sensor. In this study, we present a cutting-edge machine learning-based transfer learning technique for rapid sensor calibration with Co-deployment with reference monitors is kept to a minimum. This approach integrates data from a small number of sensors, including the target sensor, reducing the dependence on a reference monitor. Our studies reveal that In recent research, a transfer learning method using a meta-agnostic model has been proposed, and the results proved to be much more effective than the previous method. In trials, calibration errors were successfully reduced by up to 32\% and 15\% compared to the best raw and baseline observations. This shows the great potential of transfer learning methods to increase the effectiveness of learning in the long term. These results highlight the potential of this innovative transfer learning technique for rapidly and accurately calibrating low-cost particulate matter sensors using machine learning.
Co-Authors AA Sudharmawan, AA Abas Sunarya Abas Sunarya, Po Abdul Hamid Arribathi Abdul Hayat Abdul Rahman, Abdul Wahab Achani Rahmania Az Zahra Achmad Nizar Hidayanto Adam Faturahman Ade Iriani Adi Setiawan Aditiya Lityanian Al Nasir Adiyarta, Krisna Aghnia Sabila Ainun Rahmawati Alexander Williams Alfiah Khoirunisa Alfiah Khoirunisa Alfiah Khoirunisa Alfiah Khoirunisa Alfiah Khoirunisa Alfian Dimas Ahsanul Rizki Ahmad Alwiyah Alwiyah Amelia, Sindy Amsyar, Izwan Ana Nurmaliana Anderson, James Andhika Dwi Putra Andriyani, Fitri Andriyansah . Anggun Aditya Ningrum Anggun Oktariyani Anggy Fatillah Anggy Giri Prawiyogi Ani Wulandari Anil Ram Anjani, Sheila Aulia Ankur Singh Bist Anoesyirwan Moeins Anoesyirwan Moeins Anwar, Aang Solahudin Apriliasari, Dwi Aptman, Ethan Ari Asmawati Arini Dwi Lestari Arini Dwi Lestari Aristo, Nabila Cynthia Arko Djajadi Ary Budi Warsito Asep Saefullah Asep Sutarman Asif Khan Asif Khan Astuti, Eka Dian Athapol Ruangkanjanases Augury El Rayeb Aulia Edliyanti Avionita, Sella Ayi Rakhmat Ramdani Ayu Martha Wardani Ayu Sanjaya, Yulia Putri Ayu Wanda Azz, Istajib Kulla Himmy Baedowi, Hikmal Bayu Pramono Bennet, Daniel Bhupesh Rawat Bist, Ankur Singh Budiarto, Mukti budiarty, frizca Bunga Pertiwi Candra, Ariya Panndhitthana Chairun Nas Chalifatullah, Siti Chen, Shih Chih Christianto, Dennies Dwi Chung-Hao Hsu Chung-Wen Hung Citra Destianty Cristhopher, Ethan Daelami Ahmad Danny Manongga Darmawan, Muhammad Diky Darmawan, Muhammad Diky Davies, Mary Deddy Pratama Desi Sartika Desrianti, Dewi Immaniar Desy Apriani Devi, Lakshmi Dewi Immaniar Dewi Mariana Apriani Dewi, Yustin Novita Dhita Rukmianti Diah Aryani, Diah Dian Maharani Damanik Dian Mustika Putri Dina Fitria Murad Dina Fitria Murad Dini Intan Pratiwi Dini Intan Pratiwi Dini Nurul Suvianti Duwi Juliansah, Muhamad Alfi Dwi Andayani, Dwi Dwi Anjani Dwi Apriliasari Dwi Apriliasari Dwi Maya Suhainingsih Edward Boris P Manurung Edward Boris P Manurung Edward Guustaaf Efa Ayu Nabila Efendy, Rifan Eko Prasetiyani Eko Prasetiyani Eko Sediyono Elinda, Bella Dhea Elinda, Bella Dhea Elmanda, Vonda Endah Nirmala Dewi Erick Alfons Lisangan Erick Febriyanto Erika Erika Erni Astuti Erviani, Maya Ima Euis Sitinur Aisyah Evi Maria Faisal Rizki Azhari Farida Agustin, Farida Faturahman, Adam Fauziah, Zaleha Febiani, Dyah Ayu Febiansyah, Hidayat Femi Allamiah Femi Allamiah Fernanda Setyobudi Armansyah, Fernanda Setyobudi Firman Hanafi Fitra Putri Oganda Fitri Faradilla Fitri Faradilla Fitri Lisnawati Fresandy, Gilang Fuad, Azharul Giandari Maulani Girinzio, Iqbal Desam Goh, Thomas Sumarsan Guustaaf, Edward Hakiki, Salman Handayani, Indri Handayani, Indri Hani Dewi Ariessanti Hani Dewi Ariessanti Harahap, Eka Purnama Harahap, Eka Purnama Harries Madiistriyatno Harries Madiistriyatno, Harries Henderi . Hendriyati, Penny Hendry Heriyanto Heriyanto Hidayati * Hidayati Hidayati Hikam, Ihsan Nuril Hindriyanto Dwi Purnomo Hua, Chua Toh Ignatius Joko Dewanto, Ignatius Joko Ilham, Muhammad Ghifari Imam Prayogi Indri Handayani Indri Handayani Indri Handayani Indri Handayani Indri Handayani Indri Handayani, Indri Ira Geraldina Irwan Nurdin Irwan Sembiring Isabella Yaumil Annisa Iwan Setyawan Jazi Eko Istiyanto Jetty Susanti Joko Siswanto Joko Siswanto Julianingsih, Dwi Juniar, Hega Lutfilah Kamal, ⁠Abdullah Arif Kamil, Muhammad Farhan Kanivia, Aan Kareem, Yasir Mustafa Kenita Zelina Khairunisa, Alfiah Khanna Tiara Khanna Tiara, Khanna Khasanah, Kartika Trissanti Kho, Ardi Khoirunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Komara, Maulana Arif Kristoko Dwi Hartomo Lalita Tri Adila Lalu Darmawan Bakti, Lalu Darmawan Latifah, Haznah Lestari Santoso, Nuke Puji Lic, Yung-Ming Lidya Wijayanti Lilik Agustin Lilis Setiani Lim, Clara Pasha Lusyani Sunarya Lutfiyah, Konita M. Ramdani Made Bunga Thalia Maharani, Herliana Wahyu Maimunah Maimunah Manik, Ita Sari Perbina Mardiana Mardiana Mardiana Mardiana Mardiansyah, Aditya Marviola Hardini Maulana, Imam Ryan Maulana, Sabda Md Asri Ngadi Melani Rapina Tangkaw Mertayasa, I Komang Meta Amalya Dewi Meylda Sarah Parwati Meytasari, Rista Mia Novalia Millah, Shofiyul Moch Sandi Alpansuri Mochamad Heru Riza Chakim Mochamad Sandi Alpansuri Mochamad Sukrisno Mardiyanto Mohammed Iftequar Ali Much Alvin Aldiya Muhamad Hendri Muhamad Yusup Muhammad Diky Darmawan Muhammad Iman Nur Hakim Muhammad Iqbal Muhammad Iqbal Muhammad Salamuddin Mukti Budiarto Muktiyanto, Ali Mulyati Mulyati Mulyati Mustofa Kamil, Mustofa Mustofa, Kenny Ilyas Nadia Nur Azizah Natalia, Elisa Ananda Natalia, Ester Ananda Natasya, Ersa Aura Neng Enay Nesti Anggraini Santoso Nevizond, Reza Filander Nia Haryani niko alnabawi Ninda Lutfiani Noval Jindan Nuke Puji Lestari Santoso Nur Azizah Nur Azizah NURAENI, RANI Nurani, Dita Lintang Nurmala, Risma Nurul Komaeni Ornlatcha Sivarak P. O. H. Putra Pahad, Baiq Aneji Pangestu, Anggit Panji Parker, Jonathan Po Abas Sunarya Pramono, Bayu Prasetyo, Ilham Bagus Pratiwi, Sarah Prihastiwi, Wahyu Yustika Purnama Harahap, Eka Purnama, Ika Yuni Putra, Nanda Dwi Putri, Dian Mustika Qory Oktisa Aulia Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Rahardja.,M.T.I.,MM, Dr. Ir. Untung Rahma Rinie Raihan Raihan, Raihan Rakhmansyah, Mohamad Ramadan, Ahmad Ramadhan, Tarisya Ramzi Zainum Ikhsan Rawat, Bhupesh Ray Indra Taufik Wijaya Renowati Hardjosubroto Reny Ardyanti Resti Rahmawati Retantyo Retantyo Retantyo Wardoyo RH. Fitri Faradilla Ridhuan Ahsanitaqwim Riya Widayanti Riza Chakim, Mochamad Heru Rizki Afri Liani Firmansyah Rizky, Agung Rochmawati Rochmawati Romzi Syauqi Naufal Rosalinda, Iis Ariska Rosyifa Rosyifa Ruey-Hsing Chang Rusilowati, Umi Sabda Maulana Salamuddin, Muhammad Sanjaya, Yulia Putri Ayu Santika Dewi Santoso, Nesti Anggraini Santoso, Nuke Puji Lestari Sarah Riwanda Shofroh Sari, Herva Emilda Sari, Meri Mayang SATRIYAS ILYAS Saulina Panjaitan, Aropria Sella Avionita Septian, Rafly Ananda Dwi Septiani, Nanda Shakinah Badar Shakinah Badar Shih-Chih Chen Shih-Chih Chen Shih-Wen Chien Shofiyul Millah Shylvia Ratna Dewi Shylvia Ratna Dewi Sihotang, Sondang Visiana Silvia, Pita Siti Chalifatullah Siti Maesaroh Siti Maesaroh Siti Mawadah Siti Nurindah Sari Siti Ria Zuliana Spits Warnar, Harco Leslie Hendric Sri Darmayanti SRI RAHAYU Sri Watini Sri Yulianto Joko Prasetyo Suciani, Ayu Sudaryono Sudaryono Sudaryono Sudaryono Sugeng Widada Sulastrini, Lily Ratna Sulistio Sulistio Sulthan Taqi Sampoerna Sunar Abdul Wahid Sunardjo, Richard Andre Sunarjo, Richard Andre Supriyati, Ruli Suryari Purnama Suryo Guritno1 Susan Oktaviani Sutarman, Asep Sutarto Wijono Sutedja, Indrajani Suwandi Suwandi Tanaporn Hongsuchon Tangkaw, Melani Rapina Taqwa Hariguna Tejosuwito, Nikita Jova Tito Pinandita Tri Kuntoro Priyambodo Tri Purwaningsih Triyono Triyono Tsung-Hao Wu Tuti Nurhaeni Utami, Ria Valent Setiatmi Valent Setiatmi Valent Setiatmi, Valent Viktor A Sin, Muhamad Viola Tashya Devana Vivid Kristiani Alfad Zebua Wahyu Yustika Prihastiwi Wahyudi, Otniel Feliks Putra Wardani, Ayu Martha Widhy Setyowati Wijaya, Randy Wijaya, Surta Wijayanti, Lidya Wiliams, Alexander Williams, Alexander Windy Yestina Winiarti Prastiwi Yanti Yanti Yessi Frecilia Yoke Dwi Martianda Setiaji Yolandari, Aulia Yoyo Syoifana Yundari, Yundari Yusuf, Natasya Aprila Zainal Arifin Hasibuan