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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 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) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) IJISTECH Jurnal Abdimas Kartika Wijayakusuma 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 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) Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Analisis Data dan Implementasi Customer Relationship Management (CRM) dalam Meningkatkan Efektivitas Periklanan dan Kampanye Erlangga, Faezal; Lubis, Muharman
Paradoks : Jurnal Ilmu Ekonomi Vol. 8 No. 3 (2025): May - July
Publisher : Fakultas Ekonomi, Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/paradoks.v8i3.1507

Abstract

Penelitian ini bertujuan untuk menganalisis bagaimana implementasi Customer Relationship Management (CRM) berbasis data dapat meningkatkan efektivitas kampanye periklanan dan retensi pelanggan dengan fokus pada studi kasus Reliance Trends dan UMKM. Metode penelitian menggunakan pendekatan kualitatif deskriptif dengan metode studi kasus dengan mengumpulkan data dari sumber sekunder seperti laporan, artikel ilmiah, dan studi kasus CRM yang diterapkan di perusahaan ritel besar dan pelaku usaha kecil. Analisis data dilakukan dengan teknik analisis tematik untuk mengidentifikasi pola-pola utama dalam penerapan CRM di kedua jenis perusahaan. Hasil penelitian menunjukkan bahwa penerapan CRM berbasis data di Reliance Trends meningkatkan segmentasi mikro, personalisasi pesan, serta otomatisasi kampanye yang berdampak pada pengurangan biaya iklan dan peningkatan loyalitas pelanggan. Di sisi lain, UMKM menggunakan sistem CRM lebih sederhana, mereka tetap dapat memanfaatkan teknologi untuk meningkatkan keterlibatan pelanggan dan retensi melalui komunikasi personal. Hal ini memperkuat bahwa meskipun dengan sumber daya terbatas, CRM tetap dapat meningkatkan efisiensi kampanye dan hubungan jangka panjang dengan pelanggan. Kesimpulan penelitian ini menunjukkan bahwa CRM berbasis data dapat dioptimalkan untuk memperkuat strategi pemasaran baik di perusahaan besar maupun kecil. Penelitian lebih lanjut disarankan untuk mengeksplorasi tantangan implementasi CRM pada sektor UMKM serta pemanfaatan teknologi canggih seperti AI dalam personalisasi dan otomatisasi.
Integrasi sistem inventory management berbasis IoT dalam CRM real-time: Studi kasus Zara dengan pendekatan Value Chain Porter Gunawan, Dian; Rahmat, Hadian; Lubis, Muharman
Nautical : Jurnal Ilmiah Multidisiplin Indonesia Vol. 4 No. 2 (2025): Nautical: Jurnal Ilmiah Multidisiplin Indonesia (In progress)
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/nautical.v4i2.1548

Abstract

Transformasi digital dalam industri ritel modern menuntut efisiensi operasional yang tinggi dan pengalaman pelanggan yang unggul. Zara, bagian dari Inditex Group, telah menjadi pionir dalam mengintegrasikan sistem Inventory Management (IM) berbasis Internet of Things (IoT) ke dalam sistem Customer Relationship Management (CRM) secara real-time. Penelitian ini bertujuan untuk menganalisis bagaimana penerapan teknologi sensor RFID, rak pintar, dan sistem gateway IoT di Zara mendukung aliran data langsung dari toko ke pusat distribusi dan CRM analytics, membentuk feedback loop yang meningkatkan responsivitas pelanggan. Dengan pendekatan kualitatif deskriptif dan kerangka analisis Value Chain oleh Porter, penelitian ini menemukan bahwa integrasi IM–CRM meningkatkan on-shelf availability hingga 98%, menurunkan waktu pengisian ulang menjadi di bawah 12 jam, serta meningkatkan skor kepuasan pelanggan sebesar 20%. Implikasi strategisnya menunjukkan bahwa sistem inventory tidak lagi bersifat pasif, tetapi menjadi katalisator dalam personalisasi layanan pelanggan dan pengambilan keputusan yang cepat berbasis data real-time.
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.
Co-Authors Abdullah Muhammad, Hasan Abdulmana, Sahidan Achmad Rafi Addini Firdaus, Fitri Adillah, Muhammad Fauzan Nur Adinda Laras Ayu 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 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 Hermawan, Fairuz Fernanda Hikmah Adwin Adam Humairo, Annisa Idham Kamil Ikbar, Thoriq Ikhlas Fuad Zamzami Ikhsan, Alif M. Ilham Ramadhan Nasution Iqbal Santosa Iqbal Yulizar Mukti Irvan, Irvan Jihan Audia Mulya Julham Julham Julham Julham Kahirul Umam, Irhan Kamal, Alvan 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 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 Mulhartono, Tomi 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 Satria Nusantara, Abdul Hakim See, Tan Lian 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 Thamrin, Daffa Shidqi Thoriq Ikbar Tien Fabrianti Kusumasari Trang, Nguyen Kieu Umar Yunan Kurnia Septo Hediyanto Umuri, Khairil Vega Putra Pradana Vreseliana Ayuningtyas Wihayanti, Titik Wirawan, Muhammad Naufal Yani, Mega Fitri Yulio Ferdinand Yuyun Yusnida Lase Zamzami, Ikhlas Fuad Zulkifli Zulkifli