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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Edutech Syntax Jurnal Informatika JDM (Jurnal Dinamika Manajemen) Jurnal Teknik Elektro Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer The Journal of Pure and Applied Chemistry Research Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Educational Science and Technology Scientific Journal of Informatics Dinar: Jurnal Ekonomi dan Keuangan Islam POSITIF ANDHARUPA CESS (Journal of Computer Engineering, System and Science) Yustitiabelen UNEJ e-Proceeding 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 JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah Wahana Islamika: Jurnal Studi Keislaman Jurnal Teknoinfo Technomedia Journal JURNAL PENDIDIKAN TAMBUSAI Journal of Education Technology YUME : Journal of Management Aptisi Transactions on Management JTP - Jurnal Teknologi Pendidikan Ad-Deenar: Jurnal Ekonomi dan Bisnis Islam 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) An-Nadaa: Jurnal Kesehatan Masyarakat ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Majalah Ilmiah Dian Ilmu Jurnal Dinamika Ekonomi Syariah ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Shar-E: Jurnal Kajian Ekonomi Hukum Syariah IAIC Transactions on Sustainable Digital Innovation (ITSDI) Jurnal Alwatzikhoebillah : Kajian Islam, Pendidikan, Ekonomi, Humaniora International Journal of Engineering, Science and Information Technology MAVIB Journal : Jurnal Multimedia Audio Visual and Broadcasting Indonesian Journal Accounting (IJAcc) Az Zarqa': Jurnal Hukum Bisnis Islam International Journal of Cyber and IT Service Management (IJCITSM) Jurnal Pembelajaran Fisika Balanca : Jurnal Ekonomi dan Bisnis Islam International Journal of Biology Education Towards Sustainable Development Media Riset Akuntansi Auditing & Informasi Mutanaqishah: Journal of Islamic Banking Universal Raharja Community (URNITY Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Borneo : Journal of Islamic Studies An Nuqud: Journal of Islamic Economics Jurnal Sistem Informasi MAGNETON: Jurnal Inovasi Pembelajaran Fisika Nusantara Journal of Computers and its Applications Al-Fadlan: Journal of Islamic Education and Teaching JAT (Journal of Accounting and Tax) Wahana Islamika: Jurnal Studi Keislaman JENGGALA: Jurnal Riset Pengembangan dan Pelayanan Kesehatan Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) EduBase: Journal of Basic Education PESHUM Jurnal Lantera Ilmiah Keperawatan Southeast Asia Journal on Open and Distance Learning Journal of Computer Science and Technology Application Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain International Journal Research on Metaverse E-Jurnal Akuntansi
Qurotul Aini
Universitas Raharja
Religion Arts Humanities Astronomy 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Analysis of the potential context of Blockchain on the usability of Gamification with Game-Based Learning Tarisya Ramadhan; Qurotul Aini; Sugeng Santoso; Achmad Badrianto; Ruli Supriati
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 1 No. 1 (2021): April
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1999.111 KB) | DOI: 10.34306/ijcitsm.v1i1.24

Abstract

Within the world of gaming, there has been a move from diversions being utilized exclusively for excitement, to recreations being utilized as a medium to teach. For this matter, there are two strategies of making amusement which are gamification or game-based learning. The previous is the utilization of diversion components, such as wellbeing focuses or pioneer sheets, and they are connected to a non-gaming stage. The last mentioned, game-based learning, incorporates creating a full-fledged amusement where the means towards the conclusion, that's to say triumph, are set in a world where the player needs to apply the lessons given to progress. Since typically an IT-related investigation, the subject chosen for this study is Blockchain, an ever-expanding division over the past decade. Diverse parts of Blockchain's makeup have been dismembered into little, comprehensible pieces of data within the applications made, which innovative understudy to the frame can take in at their claimed pace. Should this study transcend this research, it might be beneficial for the experiments to possess two games designed and created by someone who has the artistic and technical capabilities of making their own assets. This is able to leave a far better impression with the test subjects and ideally receive a far better data set for examination.
Implemetation of ROP In Stock Control to Minimize Losses Due to Expiry Aziz, Lukmanul Hakim; Sunarjo, Richard Andre; Ramdani, Muhammad; Natalia, Elisa Ananda; Maria, Lily; Aini, Qurotul
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 2 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i2.1337

Abstract

Managing inventory with a limited shelf life is a crucial challenge in the supply chain, particularly in sectors where products are susceptible to rapid quality deterioration. Inaccuracies in ordering timing often lead to excess stock, which leads to financial losses due to product destruction, increased storage costs, and negative environmental impacts. This situation demands the implementation of more integrated and data-driven inventory control methods to optimize the procurement cycle sustainably. This study aims to analyze the effectiveness of implementing the Reorder Point (ROP) method integrated with historical demand and lead time data in minimizing the percentage of expired items. The main focus of the study is to establish ROP as a precise ordering timing mechanism, so that Safety Stock (SS) functions as an emergency buffer against uncertainty, rather than as excess inventory at risk of expiring. The research methodology includes analytical calculations of ROP, SS to mitigate demand and lead time variability, and Economic Order Quantity (EOQ) to determine the most economical order quantity. In addition, a literature review on the implementation of First Expired, First Out (FEFO) and First In, First Out (FIFO) systems is used as internal operational standards to ensure optimal stock rotation. The analysis results show that accurate ROP implementation is a key pillar in preventing expired goods. An optimal strategy requires synergy between prevention through precise ordering timing, internal control through strict stock rotation, and risk mitigation through proactive discount programs for products nearing expiration. The integration of ROP, SS, and EOQ has proven effective in reducing operational losses and supporting modern, efficient and sustainable inventory management practices.
Developing Sustainable Technology through Ethical AI Governance Models in Business Environments Henderi; Aini, Qurotul; Purwanti, Purwanti; Muti, Rifqa Nabila; Fletcher, Eamon
ADI Journal on Recent Innovation Vol. 6 No. 2 (2025): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v6i2.1179

Abstract

The rapid adoption of Artificial Intelligence (AI) in business offers transfor- mative opportunities but introduces ethical challenges requiring robust gover- nance models. This study investigates the development of ethical AI gover- nance frameworks to align technology adoption with societal values and sus- tainability goals. Through a mixed-methods approach, qualitative interviews with industry experts and quantitative case study analyses are conducted to ex- plore best practices and key challenges. Findings emphasize the necessity of transparency, stakeholder engagement, and regulatory compliance in fostering trust and accountability within AI-driven processes. The research concludes by proposing a comprehensive governance model that integrates ethical princi- ples with innovation, offering practical solutions for businesses to sustainably leverage AI while mitigating risks and enhancing societal benefits. This study contributes to the growing discourse on sustainable technology and responsible AI deployment in business environments.
Analysis of the potential context of Blockchain on the usability of Gamification with Game-Based Learning Tarisya Ramadhan; Qurotul Aini; Sugeng Santoso; Achmad Badrianto; Ruli Supriati
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 1 No. 1 (2021): April
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v1i1.24

Abstract

Within the world of gaming, there has been a move from diversions being utilized exclusively for excitement, to recreations being utilized as a medium to teach. For this matter, there are two strategies of making amusement which are gamification or game-based learning. The previous is the utilization of diversion components, such as wellbeing focuses or pioneer sheets, and they are connected to a non-gaming stage. The last mentioned, game-based learning, incorporates creating a full-fledged amusement where the means towards the conclusion, that's to say triumph, are set in a world where the player needs to apply the lessons given to progress. Since typically an IT-related investigation, the subject chosen for this study is Blockchain, an ever-expanding division over the past decade. Diverse parts of Blockchain's makeup have been dismembered into little, comprehensible pieces of data within the applications made, which innovative understudy to the frame can take in at their claimed pace. Should this study transcend this research, it might be beneficial for the experiments to possess two games designed and created by someone who has the artistic and technical capabilities of making their own assets. This is able to leave a far better impression with the test subjects and ideally receive a far better data set for examination.
Enhancing Blockchain Security Through Smart Contract Vulnerability Classification Using BiLSTM and Attention Mechanism Rahardja, Untung; Aini, Qurotul
Journal of Current Research in Blockchain Vol. 3 No. 1 (2026): Regular Issue March 2026
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v3i1.56

Abstract

The rapid adoption of blockchain technology has intensified the need for robust smart contract security mechanisms. However, traditional rule-based or static analysis tools often fail to detect context-dependent vulnerabilities embedded in complex contract logic. This study proposes a deep learning framework for automated smart contract vulnerability classification using a Bidirectional Long Short-Term Memory (BiLSTM) network integrated with an Attention Mechanism. The model was trained and evaluated on the SC_Vuln_8label.csv dataset, comprising 12,520 labelled Solidity smart contracts categorized into eight distinct vulnerability types, including Re-entrancy, Integer Overflow, and Short Address Attack. Through bidirectional contextual learning and attention-based feature weighting, the proposed model achieved 93.7% test accuracy, 0.93 precision, and a macro F1-score of 0.92, outperforming baseline models such as CNN, GRU, and standard LSTM by up to 5.3 percentage points. Attention heatmap analysis further revealed the model’s interpretability by highlighting vulnerability-prone code segments (e.g., call.value, send(), and withdraw() functions) consistent with expert-identified risk indicators. These results demonstrate that the BiLSTM + Attention framework not only enhances vulnerability detection accuracy but also provides transparent and explainable reasoning, offering a reliable foundation for AI-assisted smart contract auditing systems in blockchain security.
Data Driven A or B Testing Methodology for Website Effectiveness Qurotul Aini; Aulia Khanza; Vinkan Likita; Lase, Steven Harazaki; Kareem, Yasir Mustafa
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/t04mab20

Abstract

Website design and optimization decisions are often driven by subjective opinions, internal organizational preferences, or prevailing industry trends rather than empirical evidence derived from large-scale user interaction data, resulting in suboptimal performance and inconsistent user experiences. In digital environments characterized by high data volume and velocity, the absence of a structured experimentation methodology limits organizations’ ability to effectively leverage Big Data for continuous website improvement. This paper presents a comprehensive and systematic methodological guide to A or B testing as a data-driven approach for enhancing website effectiveness in data-intensive contexts. Unlike existing A or B testing guides that focus mainly on tools or isolated experimental outcomes, this study proposes an end-to-end framework integrating hypothesis formulation, scalable experimental design, statistical rigor, iterative learning, and practical decision-making into a unified and replicable process. The methodology outlines the complete A or B testing lifecycle, including alignment of business objectives with measurable data signals, development of testable hypotheses, controlled experiment implementation, large-scale data collection, and statistical analysis to ensure validity and significance of findings. The results demonstrate that a disciplined and continuous A or B testing program supported by Big Data analytics enables incremental yet compounding improvements in website performance. Through illustrative case examples, the study shows that relatively small, data-informed changes to website elements such as headlines, calls-to-action, images, and layout structures can lead to statistically significant gains in conversion rates, user engagement, and overall user experience. The paper concludes that A or B testing serves as a strategic Big Data analytics mechanism that supports evidence-based website optimization decisions grounded in empirical user behavior rather than intuition.
A Data Driven Information System for Cybersecurity Vulnerability Management Aini, Qurotul; Rizky, Agung; Rusdian, Suca; Aulia, Azwani; Erica, Archa
APTISI Transactions on Management (ATM) Vol 10 No 1 (2026): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/f3yjz324

Abstract

The rapid growth of digital infrastructures has amplified cybersecurity vulnerabilities, challenging organizations to manage risks effectively. Traditional vulnerability assessment methods, such as static scoring systems, often overlook dynamic threat information, leading to suboptimal prioritization. This study addresses the gap in existing vulnerability management approaches by introducing a data-driven framework that combines internal system data, public vulnerability databases, and external threat intelligence using predictive analytics. The proposed decision support information system employs machine learning as an analytical component to estimate the likelihood of vulnerability exploitation and support vulnerability prioritization decisions. The novelty of this approach lies in its ability to prioritize vulnerabilities not only based on technical severity but also considering the context of real-world threat activity. When benchmarked against conventional methods, this approach demonstrates superior performance in identifying exploitable vulnerabilities, improving accuracy and recall, thus optimizing resource allocation. By adopting a proactive, risk-based strategy, the framework prioritizes the most critical vulnerabilities in complex IT environments. The results highlight the potential of predictive models in enhancing cybersecurity management and supporting sustainable infrastructure, driving a shift toward more efficient, data-driven decision-making.  
Self Supervised Transformers for High Dimensional Time Series Anomaly Detection Aswadi Jaya; Derlina; Qurotul Aini; Agung Rizky; Richard Evans
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1078

Abstract

This study addresses anomaly detection in high dimensional time series data within the context of Artificial Intelligence (AI) driven software development, where modern systems generate large temporal data streams and reliable monitoring remains difficult due to noise, complexity, and limited labeled anomalies. The objective of this research is to develop an effective and scalable anomaly detection framework based on self supervised transformer models that can learn meaningful temporal representations without heavy reliance on manual annotation. The proposed method applies self supervised pretraining through masked sequence reconstruction and contrastive temporal learning on large scale, unlabeled multivariate time series datasets, followed by transformer based attention mechanisms to capture long range dependencies and compute anomaly scores. Experiments are conducted using benchmark datasets and real world system log data implemented with Python based deep learning tools and transformer architectures to evaluate detection performance. The results indicate that the proposed approach improves detection accuracy and reduces false positive rates compared to traditional statistical techniques and supervised deep learning models, particularly in high dimensional and low label settings. In conclusion, integrating self supervised learning with transformer architectures provides a robust and generalizable solution for time series anomaly detection, contributing to software analytics and monitoring systems by lowering labeling costs and improving adaptability across application domains.
Optimizing Digital Promotional Graphic Design Strategies Using the AIDA Model Rahardja, Untung; Aini, Qurotul; Supriati, Ruli; Al Hafiz, Mohammad Aditya
ADI Journal on Recent Innovation (AJRI) Vol. 7 No. 2 (2026): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i2.1425

Abstract

The rapid growth of digital platforms has intensified competition in online marketing, requiring organizations to adopt more strategic, adaptive, and data-driven promotional approaches. Digital promotional graphic design plays a crucial role in capturing consumer attention and delivering persuasive messages across various platforms. However, differences in platform characteristics and user behavior may influence the effectiveness of these visual strategies, highlighting the need for a more structured design approach. This study aims to optimize digital promotional graphic design strategies by integrating the AIDA model (Attention, Interest, Desire, and Action) into visual communication practices to improve audience engagement and promotional effectiveness. This research employs a qualitative descriptive approach, combining literature review and visual content analysis. Digital promotional designs from various online platforms were systematically analyzed using AIDA indicators, supported by engagement metrics as secondary data to strengthen the evaluation of design effectiveness. The findings indicate that integrating data-driven analytics with the AIDA model significantly enhances the effectiveness of digital promotional graphic design. Visual optimization improves attention, structured and relevant content sustains interest, emotional and value-based messaging stimulates desire, and clear, strategically placed Call To Action (CTA) elements effectively encourage user action. This study concludes that the combination of the AIDA framework and data- driven decision-making provides a comprehensive and strategic foundation for optimizing digital promotional graphic design, ultimately improving communi- cation effectiveness and promotional performance in the digital era.
Analysis of Inorganic Waste Classification Orange Box Based on TensorFlow Lite using Raspberry Pi 5 Aini, Qurotul; Faturahman, Adam; Agustian, Harry; Aritonang, Frengky Jonathan; Zainarthur, Henry
ADI Journal on Recent Innovation (AJRI) Vol. 7 No. 2 (2026): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i2.1428

Abstract

While Smart City initiatives are evolving, waste management infrastructure remains a critical bottleneck, often hindered by high energy dependency and latency issues associated with cloud computing. Traditional automated solutions lack the autonomy required for scalable, outdoor deployment. This research introduces Orange Box a self-sustaining Edge-AI waste classifier designed to bridge the gap between high-performance computing and energy efficiency. The primary goal is to demonstrate that complex Deep Learning tasks can be executed locally on renewable energy without sacrificing classification precision. The system orchestrates a MobileNetV2 architecture on the Raspberry Pi 5, utilizing TensorFlow Lite (TFLite) quantization to drastically reduce computational load. Uniquely, this Green IoT node is fully decoupled from the power grid, driven by a custom power management system utilizing a 100Wp monocrystalline solar panel to sustain both the neural processing unit and robotic actuators. Experimental benchmarks reveal a robust 92% classification accuracy with an inference latency of just 45ms, significantly outperforming previous edge-device generations. Crucially, energy analysis validates operational autonomy for up to 72 hours without sunlight, confirming the system’s reliability for continuous urban deployment. This study demonstrates that the convergence of quantized Edge AI and solar harvesting is not merely theoretical but a deployable standard for the next generation of Smart City infrastructure, directly advancing the Sustainable Development Goals (SDGs) for sustainable urbanization.
Co-Authors Aa Mustopa AA Sudharmawan, AA Abas Sunarya, Po Abdul Abdul Arribathi Abdul Hamid Arribathi Abdul Hayat Achmad Badrianto Achmad Nizar Hidayanto Adam Faturahman Ade Iriani Adi Fahrudin Aditiya Lityanian Al Nasir Afitri, Afni Agung Rizky Agung Rizky Agustian, Harry Ahmad Roihan Ahmad Roihan, Ahmad Aisiyah, Nurul Aisiyah Akhmad Taufik Akhmadi Abbas, Akhmadi Al Anwar, M. Al Hafiz, Mohammad Aditya Albertus Djoko Lesmono Alfiah Khoirunisa Alfiah Khoirunisa Alfiah Khoirunisa Alfian Dimas Ahsanul Rizki Ahmad Alfiansah, Reza Alwiyah Alwiyah Amelia, Sindy Ameliya, Ratna Aminuyati Amroni, Amroni Ana Nur Filiya Ana, Yuli Anam, Reza Khaerul Ananda, Aulia Rahma Andhika Dwi Putra Angga Febrianto, Angga Anggi Ariyanti Anggraeni, Mey Anggun Oktariyani Anggy Fatillah Anggy Giri Prawiyogi Anisatur Rofiqah, Siti Anjani, Sheila Aulia Anoesyirwan Moeins Anoesyirwan Moeins Anoesyirwan, Anoesyirwan Apriliasari, Dwi Ardila, Natta Arief Muhammad Nurhasan Arifah Aristo, Nabila Cynthia Aritonang, Frengky Jonathan Arribathi, Abdul Abdul Asep Saefullah Astriyani, Erna Aswadi Jaya Aulia Edliyanti Aulia Khanza Aulia, Azwani Ayi Rakhmat Ramdani Ayu Martha Wardani Ayu Sanjaya, Yulia Putri Ayyusuf, Imanul Achmad Al Amir Azis, Priyatna Abdul Aziz, Lukmanul Hakim Bein, Adrian Sean Bist, Ankur Singh budiarty, frizca Cahyo Anggoro Seto Cheetah Savana Putri Daelami Ahmad Danny Manongga Danny Pratama Derlina Desi Sartika Desi Suci Handayani Desy Apriani Dewi Mariana Apriani Dewi Marliyana, Soerya Dewi, Shylvia Ratna Dewi, Tri Rachma Dewi, Yustin Novita Diah Aryani Diah Aryani Diah Aryani, Diah Dian Mustika Putri DWI CAHYONO Dwi Nur Ramadhan Dyatmika, Sutama Wisnu Edward Guustaaf Efa Ayu Nabila Efendy, Rifan Effendi Effendi Eko Sediyono Elmanda, Vonda Endah Retnani Wismaningsih, Endah Retnani Erawati, Meisa Erica, Archa Erick Febriyanto Euis Sitinur Aisyah Fahmi, Qoedbudin Fajariya, Ainun Qorif Farida Agustin, Farida Faturahman, Adam Fauzul Muna Febiani, Dyah Ayu Femi Allamiah Femi Allamiah Fernanda Setyobudi Armansyah Feti Fatimah Fika Rizkia Firman Hanafi Fitra Putri Oganda Fitri Faradilla Fitriani, Radifa Rahma Fitriawati, Noura Fitriyani, Yeny Fletcher, Eamon Fuad Akhmad Yanuar Rifai Fuad, Azharul Ginting Munthe, Rusli Girinzio, Iqbal Desam Green, Thomas Guustaaf, Edward Handayani, Indri Hani Dewi Ariessanti Hani Dewi Ariessanti Harahap, Eka Purnama Harlis Setiyowati Harries Madiistriyatno Harries Madiistriyatno, Harries Haryandi, Yopi Henderi Hendra Kusumah Hendra Setiawan Heni, Tianna Hikam, Ihsan Nuril Iim Ilmiah Agustina Ikhsan, Ramiro Santiago Indahtul Mufidah Indri Handayani Indri Handayani Indri Handayani, Indri Irwan Sembiring Irwin, Rubin Hakita Isabella Yaumil Annisa Istighosah, Nurul Iswachyu Dhaniarti Iwan Ridwan Joko Tri Prasetyawan Jonathan Parker Julianingsih, Dwi Juniar, Hega Lutfilah Juniar Kareem, Yasir Mustafa Karwandi Karwandi Karwandi, Karwandi Khairunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Kristanti, Citra Yulian Lase, Steven Harazaki Leffia, Abigail leli honesti Lestari Santoso, Nuke Puji Lestari, Fauziyyah Husna Nurdiayanah Lidya Wijayanti Luthfiya, Lulu' M. Pudail Made Bunga Thalia Maharani, Afnida Putri Maharani, Herliana Wahyu Maria, Lily Marjayanti, Eka Marviola Hardini Maulana, Sabda Maulidan Firdaus Meilinda Lana Yahya Meisa Erawati Meytasari, Rista Miftakhul Khasanah Millah, Shofiyul Mochamad Heru Riza Chakim Mochamad Mansur Moh. Yusuf Dawud Mohammed Iftequar Ali Mohammed, Datu Muhamad Abdul Roziq Asrori Muhamad Widyo Wartono Muhamad Yusup Muhammad Iqbal Muhammad Suzaki Zahran Muhammad Suzaki Zahran Muhibin, Ahmad Mukti Budiarto Muna Nabila Ovia Afirka Mustofa, Kenny Ilyas Muti, Rifqa Nabila Nabila, Efa Ayu Nasiroh, Fandilatun Natalia, Elisa Ananda Natalia, Ester Ananda Naurah, Syahla Neng Enay Nesti Anggraini Santoso Ninda Lutfiani Ningsih Dewi Sumaningrum, Ningsih Dewi Novi Cholisoh Novita Heriyani Novita Sari Novitasari, Dewiana Nugraheni, Latif Sofiana Nuke Puji Lestari Santoso Nur Azizah NURAENI, RANI Nuraini, Ana Nurani, Dita Lintang Nuril Huda Nurissalma, Maulidiyah nursaputri, Pipit Oktaviani, Fanni P. O. H. Putra Panca Oktavia Hadi Putra Paroli Paroli Pasha, Lukita Pertiwi, Komala Dwi Pibriyanti, Kartika Po Abas Sunarya Prasetiyorini, Pudhak Prianingsih, Farida Ika Prihastiwi, Wahyu Yustika Primasatria Edastama, Primasatria Primawan, Afan Pudail, M. Puji Lestari Santoso, Nuke Puranti, Ayu Purnama Harahap, Eka PURWANTI PURWANTI Purwanto Purwanto Purwanto, Purwanto Putri, Dian Mustika Putri, Khairunnisa Hasna Queen, Zabenaso Rahardja.,M.T.I.,MM, Dr. Ir. Untung Rahman Rahman Raihan Raihan, Raihan Rakhman Wibowo, Fajar Ramadan, Ahmad Ramdani, Muhammad Rawat, Bhupesh RH. Fitri Faradilla Richard Evans Rifai, Fuad Yanuar Ahmad Rini Rindrayani, Sulastri Riska Laina Ulfa Risydiyani, Wilda Rizki Galang Rahmadani Rizky, Agung Romzi Syauqi Naufal Rostikawati, Diana Ayu Rosyida, Alya Ruli Supriati, Ruli Sabda Maulana Salam, Rahmat Santoso, Nesti Anggraini Santoso, Nuke Puji Lestari Sasono, Ipang Saulina Panjaitan, Aropria Septian, Rafly Ananda Dwi Septiani, Nanda Setiawan, Muhammad Ikhsan Setiwawan, Asep Shylvia Ratna Dewi Sihotang, Sondang Visiana Silawati, Emira Tri Silvia Permatasari Simbolon, Rosdiana siti Nurindah Sari Siti Ria Zuliana Siti Ria Zuliana, Siti Ria Solihin, Danna Somantri, Somantri Spits Warnar, Harco Leslie Hendric Sri Wahyuni Sri Yulianto Joko Prasetyo Suca Rusdian Suci, Kitab Sudaryono Sudaryono Sugeng Santoso Sulastrini, Lily Ratna Sulistiawati Sulistiawati Sulistiawati Sulistiawati, Sulistiawati Sunarjo, Richard Andre Supriyanti, Dedeh Supriyati, Ruli Suryaman, Fitria Marwati Suryari Purnama Susilo, David Kristian Sutarto Wijono Sutedja, Indrajani Tan, Pauline H. Pattyranie Tangkaw, Melani Rapina Taqwa Hariguna Taqwa Hariguna Tarisya Ramadhan Tasya Novelia Thomas Green Tri Astuti Handayani Triana Kusumaningsih Umi Kulsum Untung Rahardja Utami, Noviani Van Persie, Iky Vatmala, Viyayanti Venty Suryanti Vinkan Likita Vivid Kristiani Alfad Zebua Wahid, Syahrul Mu'Arif Wahyu Yustika Prihastiwi Wardani, Ayu Martha Wardhani, Listinia Widhy Setyowati Yeny Fitriyani Yessy Oktavyanti Yohanes Gunawan Wibowo Yoke Dwi Martianda Setiaji Yuliana Isma Graha Yuliana Yuliana Yulianto Yulianto Yulianto Yulianto Zaharuddin Zaharuddin, Zaharuddin Zahran, Muhammad Suzaki Zainarthur, Henry