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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Computech & Bisnis (e-Journal) Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Indonesian Journal of Artificial Intelligence and Data Mining Applied Information System and Management Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL ILMIAH MAHASISWA AGROINFO GALUH SEIKO : Journal of Management & Business CYBERNETICS IJISTECH (International Journal Of Information System & Technology) Jurnal Sistem Cerdas JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Applied Engineering and Technological Science (JAETS) Jurnal Ilmiah Manajemen Kesatuan Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advances in Data and Information Systems Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) ARSY : Jurnal Aplikasi Riset kepada Masyarakat IJISTECH Journal of Soft Computing Exploration Jurnal Abdimas Kartika Wijayakusuma Locus: Jurnal Konsep Ilmu Hukum Jurnal Administrasi Pemerintahan Desa Jurnal Locus Penelitian dan Pengabdian Nautical: Jurnal Ilmiah Multidisiplin Indonesia Jurnal Teknologi dan Manajemen Industri Terapan Edukasiana: Jurnal Inovasi Pendidikan eProceedings of Engineering Eduvest - Journal of Universal Studies Paradoks : Jurnal Ilmu Ekonomi Nuansa Informatika Informatics Management, Engineering and Information System Journal Electronic Integrated Computer Algorithm Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) International Journal of Computer Technology and Science Jurnal Pengabdian Bakti Akademisi SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Ekonomi, Manajemen Pariwisata dan Perhotelan AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal
Muharman Lubis
Universitas Telkom
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Social Sciences Other

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Development and Capability Evaluation of a Firebase-Based Pharmacy Inventory System Using COBIT 2019 Muttaqin, Alif Noorachmad; Sandy, Muhammad Dwi Hary; Lubis, Muharman
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1139

Abstract

Pharmacy inventory control systems require proper and timely data management to be able to supply medicines and function as such. The study conceptualized and tested a Firebase-based system of pharmacy inventory control. The system was conceptualized in the web and Android platforms with the key objectives of enabling real-time synchronization, tracking, and reporting functionalities. Capability measurement from utilizing the COBIT 2019 method was utilized in evaluating system governance and operational performance. Four key processes are BAI03 (Identification and Build of Managed Solutions), DSS01 (Managed Operations), DSS02 (Managed Service Requests and Managed Incidents), and MEA01 (Managed Performance Monitoring) were chosen shortlisted and mapped to system indicators. Seven pharmacy employees were subjected to the assessment with a Likert-scale questionnaire. The results showed that three processes attained Capability Level 4 (Predictable) and one attained Capability Level 5 (Optimizing), i.e., the system performs predictably and allows continuous improvement. Weakness points despite deployment of the system with proof of handling data with ease and responsiveness were the fact that the sample size of respondents was small and one pharmacy only had it deployed. Much more must be done to experiment with the system in different environments and explore integration with third-party platforms for further scalability and adherence to governance.
Pemanfaatan Aplikasi Chat Group dalam Peningkatan Partisipasi Warga pada Aktivitas Pos Kamling dan Perawatan Taman Di KPAD RT 10 RW 02 Gegerkalong Bandung Fadilah, Zikri; Lubis, Muharman
Jurnal Abdimas Kartika Wijayakusuma Vol 6 No 2 (2025): Jurnal Abdimas Kartika Wijayakusuma
Publisher : LPPM Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/jakw.v6i2.960

Abstract

Pengabdian masyarakat di Kompleks Perumahan Angkatan Darat (KPAD) RT 10 RW 02 Kelurahan Gegerkalong Kota Bandung dilakukan melalui dua kegiatan utama, yaitu pos kamling (siskamling) dan pemeliharaan taman TOGA (Tanaman Obat Keluarga). Meskipun kedua kegiatan tersebut telah berjalan secara partisipatif, masih terdapat kendala dalam hal koordinasi warga seperti kurangnya transparansi informasi dan minimnya dokumentasi kegiatan. Untuk mengatasi permasalahan tersebut, dilakukan integrasi teknologi komunikasi sederhana berupa aplikasi chat group WhatsApp sebagai sarana peningkatan partisipasi warga. Hasil kegiatan menunjukkan bahwa penggunaan aplikasi digital ini dapat meningkatkan efektivitas komunikasi, mempercepat penyebaran informasi, serta meningkatkan jumlah dan kualitas partisipasi warga dalam menjaga keamanan lingkungan dan merawat taman kompleks. Temuan ini memberikan kontribusi nyata dalam pengembangan model pengabdian masyarakat berbasis teknologi komunikasi yang bisa direplikasi di wilayah lain.
The Ensemble Supervised Machine Learning for Credit Scoring Model in Digital Banking Institution Prahastiwi, Narita Ayu; Lubis, Muharman; Fakhrurroja, Hanif
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37677

Abstract

The digital transformation of the banking industry requires credit scoring systems that are both accurate and adaptable to complex, diverse data. This study aims to develop and evaluate a credit scoring model using ensemble supervised learning to predict credit risk for a consumer loan service (Product X) at Bank XYZ. Ensemble algorithms such as Random Forest, AdaBoost, LightGBM, CatBoost, and XGBoost were compared to a single classification method, Decision Tree. Model performance was assessed using precision, recall, F1-score, and ROC-AUC. The results show that XGBoost outperformed other models, achieving the highest ROC-AUC score of 0.803, indicating strong generalization and low risk of overfitting. SHAP analysis revealed key features influencing the model, including loan tenor, loan amount (plafond), income, and Days Past Due (DPD) history. Compared to the baseline Decision Tree model (ROC-AUC 0.573), XGBoost significantly improved classification accuracy. It also showed the potential to reduce the Non-Performing Loan (NPL) rate from 4% to below 3% and increase the approval rate from 65% to over 70%, aligning with Product X’s KPIs. These findings confirm that ensemble learning models especially XGBoost offer strategic value in enhancing credit portfolio quality and decision-making in digital banking.
Integrasi Sistem Reward dan Penilaian Kinerja Berbasis KPI dalam Mendukung Knowledge Management pada Layanan Pelanggan Digital Edwinsyah, Muhammad; Hermawan, Fairuz Fernanda; Dinayatullah, Ledi; Lubis, Muharman
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.900

Abstract

In the digital service era, the role of Knowledge Management (KM) becomes increasingly critical in ensuring efficient, responsive, and high-quality customer interactions. However, the effectiveness of KM implementation is not only determined by technological infrastructure, but also by the motivation and active participation of service agents. This study examines the integration of reward systems and Key Performance Indicator (KPI)-based performance appraisal in supporting KM practices within digital customer service environments. Using a Systematic Literature Review (SLR) method and a reflective case study of the live chat service unit of a leading Indonesian e-commerce company (Bukalapak), this research reveals how reward mechanisms and KPI structures influence knowledge sharing behaviors, agent performance, and service quality. The findings indicate that hybrid KPI systems combining quantitative metrics (such as response time and CSAT) and qualitative assessments (such as communication quality) alongside tiered reward schemes, significantly enhance agent engagement and knowledge utilization. Additionally, continuous feedback from the Quality Assurance team strengthens organizational learning and service innovation. This study offers theoretical and practical contributions in designing integrated strategies to reinforce KM through performance measurement and motivation systems in digital service sectors.
PENERAPAN LAW OF UX DALAM ANALISIS DESAIN ANTARMUKA APLIKASI SHOPEE Noorachmad Muttaqin, Alif; Dwi Hary Sandy, Muhammad; Lubis, Muharman
Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Vol 7 No 2 (2025): Jurnal Sistem Informasi dan Teknologi Informasi
Publisher : Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/jursistekni.v7i2.473

Abstract

Desain antarmuka pengguna (UI) adalah pendorong utama kualitas pengalaman pengguna (UX) produk digital. Tujuan dari penelitian ini adalah untuk mengeksplorasi keberadaan dan implementasi prinsip-prinsip Law of UX di antarmuka Shopee, yang merupakan salah satu aplikasi seluler e-commerce yang kaya fitur. Penelitian ini menggunakan pendekatan deskriptif kualitatif dengan tinjauan literatur dan analisis visual antarmuka aplikasi Android Shopee. Dua belas prinsip Law of UX dibahas, yaitu Aesthetic-Usability Effect, Fitts's Law, Hick's Law, Jakob's Law, Tesler's Law, Law of Prägnanz, Miller's Law, Peak-End Rule, Von Restorff Effect, Zeigarnik Effect, Postel's Law, dan Doherty Threshold. Hasil dari analisis ini adalah bahwa semua prinsip kecuali beberapa prinsip diikuti dengan sempurna dalam desain UI Shopee. Setiap pedoman berkontribusi pada navigasi yang lebih baik, mengurangi beban kognitif, kenyamanan visual, dan meningkatkan pengalaman emosional. Melalui penggunaan pedoman ini, Shopee tidak hanya memberikan fungsionalitas tetapi juga pengalaman pengguna yang menyenangkan dan seragam. Penelitian ini berkontribusi pada pengetahuan yang ada tentang bagaimana prinsip-prinsip psikologi kognitif dapat diterapkan dalam merancang antarmuka e-commerce. Hasil penelitian ini juga memberikan daftar periksa yang berguna bagi desainer UI/UX saat merancang antarmuka digital yang berfokus pada pengguna. Penelitian di masa depan akan diuji dengan menerapkan metode kuantitatif atau bahkan pengujian pengguna nyata untuk menentukan dampak langsung dari praktik terbaik UX pada perilaku pengguna.
Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia Muttaqin, Alif Noorachmad; Lubis, Muharman; Mulhartono, Tomi; Lubis, Arif Ridho
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i4.2358

Abstract

This study quantifies the causal impact of employment trends on academic performance using a hybrid model of survey data and time-series public interest data from Google Trends in Indonesia. Employing Granger causality and regression analysis, the research investigates eight determinants of GPA and their relationship to labor indicators. A purposive sample of 40 respondents and secondary data from 2011–2019 were analyzed. Granger tests reveal significant one-way causality from employment to GPA indicators, particularly in parental monitoring (F = 7.06; p < 0.05) and learning motivation (F = 9.68; p < 0.05). Regression analysis supports these findings with R² values above 0.50. Results highlight the potential of integrating behavioral data into educational analytics. This research contributes methodological innovation by incorporating public interest data to explain academic outcomes, with implications for predictive modeling in education policy and planning.
Android App to Measure Linguistic Intelligence of Elementary Students Muttaqin, Alif Noorachmad; Lubis, Muharman; Sandy, Muhammad Dwi Hary
Edukasiana: Jurnal Inovasi Pendidikan Vol. 4 No. 4 (2025)
Publisher : Papanda Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56916/ejip.v4i4.2009

Abstract

There is an opinion that the critical period of language development occurs between the ages of two years until puberty. During this period, especially around the age of six, children tend to avoid using passive vocabulary or complex sentence forms such as conditional commands. However, as they grow older, up to and even beyond the age of nine, their comprehension of grammatical structures and ability to process more complex linguistic forms gradually improves. Given the importance of this developmental window, formal educational institutions play a crucial role in fostering various types of student intelligence, including linguistic intelligence. Linguistic intelligence refers to the capacity to effectively use language to express thoughts, whether through speaking, reading, listening, or writing. This type of intelligence not only supports academic achievement but also enhances communication skills essential in daily life. In response to the need for effective tools in education, this study introduces the development of the LIAA (Linguistic Intelligence Assessment Android) application. This mobile-based application is designed to assist teachers in efficiently assessing and identifying the linguistic intelligence levels of elementary school students through a user-friendly and systematic digital platform.
Prediction of Turbidity Removal Time in Electrocoagulation Wastewater Using Random Forest, XGBoost, and Others: A Data-Driven Information System Approach Suakanto, Sinung; See, Tan Lian; Shaffiei, Zatul Alwani; Firdaus, Taufiq Maulana; Lubis, Muharman; Bayuwindra, Anggera
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4847

Abstract

Electrocoagulation is an effective and environmentally friendly technology for treating wastewater by removing contaminants such as turbidity, heavy metals, and organic compounds. Accurately predicting turbidity removal time is essential for optimizing treatment performance and operational efficiency. However, this is challenging due to complex, nonlinear relationships between multiple parameters including current, voltage, electrode configuration, conductivity, and turbidity removal rate. This study aims to develop a predictive framework by comparing six supervised regression models, namely Linear Regression, Polynomial Regression, Random Forest, Support Vector Regression (SVR), XGBoost, and Long Short-Term Memory (LSTM), using key electrocoagulation parameters. After extensive data preprocessing, a dataset of 281 samples was used for training and validation. Among them, Random Forest achieved the best performance (R² = 0.876, RMSE = 601.15). A data-driven information system is proposed to integrate these predictive capabilities for real-time monitoring and control. By improving turbidity prediction accuracy, the system enables the sustainable utilization of water as a valuable asset, even in its wastewater form. The approach enhances decision-making by providing intelligent feedback for process optimization. This research contributes to the advancement of intelligent, sustainable wastewater treatment systems by integrating machine learning prediction models with practical process control applications in informatics.
Studi Perbandingan Naïve Bayes dan Support Vector Machine (SVM) dalam Analisis Sentimen Pengguna Metaverse Parameswari, Sang Dara; Lubis, Muharman; Suakanto, Sinung; Ramadhan, Yumna Zahran; Amanah, Raisyah Nurul; Dila, Revyolla Ananta
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 3 (2025): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i3.1122

Abstract

Penelitian ini bertujuan mengevaluasi persepsi publik di Indonesia terhadap isu metaverse melalui analisis sentimen berbasis text mining. Metaverse, yang memadukan media sosial, permainan daring, augmented reality (AR), virtual reality (VR), serta aset digital seperti cryptocurrency, semakin mendapat perhatian sejak pengumuman perubahan nama Facebook menjadi Meta pada tahun 2021 dan memunculkan beragam opini publik. Data diperoleh dari Twitter (X) dan dianalisis menggunakan dua algoritma klasifikasi teks, yaitu Naïve Bayes dan Support Vector Machine (SVM). Dalam penerapannya, Naïve Bayes menggunakan fungsi MultinomialNB, sedangkan SVM dijalankan dengan LinearSVC yang lebih sesuai untuk data teks berdimensi tinggi. Hasil penelitian menunjukkan bahwa SVM memberikan kinerja lebih baik dengan akurasi 78,3% dan Macro-F1 78,3%, dibandingkan Naïve Bayes yang memperoleh akurasi 72,4% dan Macro-F1 sebesar 60,2%. Selain itu, SVM lebih seimbang dalam mengenali seluruh kelas sentimen, khususnya kategori negatif, sementara Naïve Bayes tetap relevan sebagai baseline karena kesederhanaan dan efisiensinya. Penelitian ini berkontribusi dalam menyajikan perbandingan komparatif kedua algoritma pada analisis sentimen metaverse di Indonesia, sekaligus membuka ruang bagi pengembangan metode yang lebih mutakhir pada studi berikutnya.
Never Overlook Security Awareness on Deployment Sadewa, Rizki; Lubis, Muharman; Nuryatno, Edi Triono
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 1 No. 1 (2024): VOLUME 1, NO 1: JUNE 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v1i1.25

Abstract

Since preliminary evidence supports the association between security culture and information security awareness (ISA), more research is needed to determine how it interacts with organizational culture. Beyond variations in respondent nation or gender, the study's findings also demonstrate an association between stronger cyber expertise and level of cyber awareness. Additionally, awareness is linked to defense mechanisms but not the information they were willing to divulge.  People play an even more important role in the collaboration between those teams and the security team when security is incorporated into DevOps practices. Furthermore, security is crucial when creating essential systems since it allows us to control objectives, risks, and evidence. Labor only starts after implementing security into the DevOps toolchain. To establish a security culture, we are additionally required to start with behavioral alterations. One of the largest Sharia banks in Indonesia anticipated cyberattacks in 2023, demonstrating to us how crucial security is in the modern world. Although no one could claim that using one of the security solutions would guarantee absolute safety, information security technology is quite dynamic. Future studies could improve on the current findings by taking into account national culture. This study has the aim of proving that we are never satisfied by current security maturity even if you or your company is implementing the best security tools, because the vulnerability can come from that deployment and wherever the environment itself.
Co-Authors A. TAUPIK RAHMAN Abdul Hakim Satria Nusantara Abdullah Muhammad, Hasan Abdulmana, Sahidan Achmad Rafi Addini Firdaus, Fitri Adillah, Muhammad Fauzan Nur Adinda Laras Ayu Aditya, Anggi Yudistira Adityas Widjajarto Agus Ambarwari Agustiana, Nathifa Ahmad Musnansyah Akbar Habib Buana Wibawa Putra Akbar Nurwahyu Arifin Putra Al Khowarizmi Ali Nurdin Ali Nurdin Alqahtani, Raied Ali Alvan Kamal Amanah, Raisyah Nurul Amri Amri Amril, Salsabila Zahrani Ana, Asri Andartya Setyawan Darna Annastasia, Syifa Anuraga, Rahadhitya Artamevia, Mima Asriana Asriana, Asriana Asti Amalia Nur Fajrillah Ayu, Adinda Laras Bayuwindra, Anggera Budianto, Farhan Alif Budianto, Setyo Constantino, Matias Garcia Deden Witarsyah Dika, Dafa Dinda Bayu Rama Dila, Revyolla Ananta Dinayatullah, Ledi Dini Handayani, Dini Dini Oktarina Dwi Handayani DM, Burhanis Sulthan Dwi Hary Sandy, Muhammad Dzakiyyah Al Kaazhim Edwinsyah, Muhammad Ega Mardoyo Ega Mardoyo Erlangga, Faezal Fadilah, Zikri Fakhrurroja, Hanif Fansyah, Egi Al Farhana Zahra Farid Farid, Farid Farma, Junia Fasya, Muhammad Haikal Fathia, Dhiya Fauzan, Ratandi Ahmad Faza, Sharfina Febriyani, Widia Firdaus, Taufiq Maulana Fitrah Khairi Fitriyana Dewi Fonna, Rizki Putri Nurita Gabriel Ardi Hutagalung Garcia-Constantino, Matias Ghifari, Muhamad Yazid Gunawan, Dian Habibi Ramdani Safitri Hafiizh Maulana Halim, Hendra Harefa, Hafid Rahman Herlina, Nenden Eva Meilani Hermawan, Fairuz Fernanda Hikmah Adwin Adam Humairo, Annisa Ikbar, Thoriq Ikhlas Fuad Zamzami Ikhsan, Alif M. Ilham Ramadhan Nasution Iqbal Santosa Iqbal Yulizar Mukti Irhan Kahirul Umam Irvan, Irvan Jihan Audia Mulya Julham Julham Julham Julham Kamal, Alvan Kamil, Idham Kartini, Ani Laily Indaryani Lubis, Arif Ridho Lubis, Fahdi Saidi Lukman Abdurrahman Lukmanul Hakim Lukmanul Hakim M. K. Rizal Syahputra M. Shabri Abd. Majid Matias Garcia Constantino Matias Garcia-Constantino Mhd Faris Pratama Mikhail, Muhammad Hibban Mima Artamevia Mira Kartiwi Mochamad Hariadi Mochamad Yudha Febrianta Muhammad Dwi Hary Sandy Muhammad Haikal Fasya Muhammad Luthfi Hamzah Muhammad Mahendra Muhammad, Hasan Abdullah Muhdiantini, Cindy Mukti, Iqbal Mukti, Iqbal Yulizar Mukti, ⁠Iqbal Yulizar Mulhartono, Tomi Mulyati, Rika Muttaqin, Alif Noorachmad Nabiel Muhammad Al Ghazali Naufal Wirawan, Muhammad Neca Aqila Nelsa, Putri Nguyen Kieu Trang Ni Made Purnami Noorachmad Muttaqin, Alif Nur Ichsan Utama Nurlina, Eka Nurma Sari, Nurma Nuryatno, Edi Triono Nusantara, Abdul Hakim Satria Oktariani Nurul Pratiwi Paradita, Anggraeni Xena Parameswari, Sang Dara Paramita, Paramita Possumah, Mercy Kristina Pradana, Vega Putra Prahastiwi, Narita Ayu Prajaya, Fannzy Bayu Askar Prayoga, Danar Prayudani, Santi Putri Luthfiah Harmaya Qadhli Jafar Adrian R. Wahjoe Witjaksono Rafi, Achmad Rafian Ramadhani Rafian Ramadhani Rafsanjani, Rayhan Rafael Rahadhitya Anuraga Raharjo, Adi Rahmat Fauzi Rahmat Mulyana Rahmat, Hadian Raied Ali Alqahtani Rakan, Raihan Ramadhan, Yumna Zahran Ramadhani, Rafian Rayhan Rafael Rafsanjani Romi Fadillah Rahmat Sadewa, Rizki Sahidan Abdulmana Sandy, Muhammad Dwi Harry Sandy, Muhammad Dwi Hary Sarah Purnamawati See, Tan Lian Setiadi, Ridwan Shaffiei, Zatul Alwani Shafira Fatimah Azzahra Silvia, Vivi Sinung Suakanto Siregar, Fachrul A Sonny Zulhuda Supeno Mardi Susiki Nugroho, Supeno Mardi Susetyo Bagas Bhaskoro Syah, M. Edwin Syahrizal, Teuku Muhammad Taufiq Carnegie Dawood Teguh Kurniawan, Mochamad Thamrin, Daffa Shidqi Thoriq Ikbar Tien Fabrianti Kusumasari Trang, Nguyen Kieu Umar Yunan Kurnia Septo Hediyanto Umuri, Khairil Utami Rukmana, Putri Vega Putra Pradana Vreseliana Ayuningtyas Wihayanti, Titik Wirawan, Muhammad Naufal Yani, Mega Fitri Yulio Ferdinand Yuyun Yusnida Lase Zahran, Muhammad Hanif Zamzami, Ikhlas Fuad Zulkifli Zulkifli