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All Journal Teknika Jupiter Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) JUITA : Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika SemanTIK : Teknik Informasi QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama SISFOTENIKA Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial JURNAL MEDIA INFORMATIKA BUDIDARMA Informatics for Educators and Professional : Journal of Informatics SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Persada Husada Indonesia INTECOMS: Journal of Information Technology and Computer Science JSiI (Jurnal Sistem Informasi) JURNAL PENDIDIKAN TAMBUSAI Journal on Education Informasi Interaktif Progresif: Jurnal Ilmiah Komputer Jusikom: Jurnal Sistem Informasi Ilmu Komputer TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Pendidikan dan Konseling Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Sistem Informasi dan Informatika (SIMIKA) Journal of Applied Engineering and Technological Science (JAETS) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Teknik Elektro dan Komputasi (ELKOM) JATI (Jurnal Mahasiswa Teknik Informatika) INFORMASI (Jurnal Informatika dan Sistem Informasi) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pengabdian Masyarakat Khatulistiwa Just TI (Jurnal Sains Terapan Teknologi Informasi) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Nasional (JPN) Indonesia SENADA : Semangat Nasional Dalam MengabdI Jurnal Cahaya Mandalika Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Sosial dan Teknologi Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal Tika Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) JUTECH : Journal Education and Technology Jurnal Widya Conten : Computer and Network Technology AJAD : Jurnal Pengabdian kepada Masyarakat Jurnal Pendidikan Sains dan Komputer International Journal Software Engineering and Computer Science (IJSECS) Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science DEVOTE: Jurnal Pengabdian Masyarakat Global International Journal of Science and Environment Cross-border CKI On Spot SmartComp SENADA : Semangat Nasional Dalam Mengabdi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Pengabdian Nasional (JPN) Indonesia Journal Innovations Computer Science Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Informasi interaktif : jurnal informatika dan teknologi informasi
Dadang Iskandar Mulyana`
ST Ilmu Komputer Cipta Karya Informatika
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Prediksi Pemilihan Warna Hijab Berdasarkan Tone Kulit Menggunakan Algoritma K-Nearest Neighbor (KNN) Putri, Atsilah Daini; Adrianto, Sopan; Mulyana, Dadang Iskandar
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1580

Abstract

Choosing the right hijab color that matches a person's skin tone is essential for many Muslim women to achieve a harmonious and attractive appearance. However, selecting a suitable color is often subjective and requires specific knowledge of color compatibility. This study aims to develop an automated prediction system that recommends hijab colors based on the user’s skin tone using the K-Nearest Neighbor (KNN) algorithm. KNN was chosen for its simplicity and effectiveness in classifying data based on proximity. The dataset used includes skin tone and corresponding hijab color data, collected through both primary and secondary sources. The classification process involves extracting color features from images and calculating Euclidean distances to determine the best hijab color prediction. The experimental results show that the KNN model provides fairly accurate predictions in recommending hijab colors based on skin tone. This system is expected to assist users in selecting appropriate hijab colors in a more objective and efficient manner.
Pengembangan Fitur Pencarian dan Filter Produk pada Aplikasi E-Commerce Gallery Muslim Berbasis Android Mafazi, Luthfillah; Akhsani, Ziyat; Fadillah, Fauzan; Iskandar, Dadang Mulyana; Akbar, Yuma; Hidayat, Aditya Zakaria
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1587

Abstract

The primary challenge in inventory management for MSMEs like Gallery Muslim lies in the manual recording system using notebooks and Excel spreadsheets, which is prone to errors and data loss. Yet, structured offline mobile solutions for micro-scale fashion MSMEs with fragmented recording practices remain limited. This research aims to design and develop an Android-based stock management application utilizing a local Room Database for efficient and accurate digital recording. The study focuses on Gallery Muslim, a retail shop specializing in Muslim clothing and school uniforms. Data were collected through interviews, direct observation, and focus group discussions (FGD) with store owners and warehouse staff. Instruments included documentation of recording activities and analysis of feature requirements. The results demonstrate that the application accelerates the stock recording process by up to 50% compared to manual methods (based on initial simulations), enhances data accuracy, and enables offline access without an internet connection. The study concludes that this Android-based local application is highly suitable for MSMEs not yet integrated with online systems, offering a practical tool for small business owners to embark on digital transformation and improve operational efficiency.
Strategi Digital Marketing dalam Meningkatkan Efektivitas Media di IDN Boarding School Fadlan, Muhammad; Putra, Mohammad Royger Febriansyah; Khanif, Abror; Iskandar, Dadang Mulyana
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1588

Abstract

In the era of the Industrial Revolution 4.0, digital marketing strategies are essential. Therefore, the author aims to enhance the effectiveness of digital marketing strategies at the IDN Boarding School Jonggol Media Team, with the output being a web-based application. The main issues identified include a lack of structure in workflows, delays in task execution, and irregularities in progress reporting. Utilizing the Waterfall model of the Software Development Life Cycle (SDLC), the application is designed to manage task distribution, monitor progress in real-time, and ensure consistency in content publication across various social media platforms such as Instagram, YouTube, TikTok, and the school's official website. Data collection methods include observation, interviews with the Media Team Coordinator, and literature studies. The implementation results demonstrate that the application successfully improves transparency, collaboration efficiency, and reporting accuracy, thereby supporting the optimization of digital marketing strategies. This research provides a relevant technological solution to support media team task management and enhance the competitiveness of educational institutions in attracting public interest.
Implementasi Semantic Web Untuk Sistem Penilaian Kelulusan Santri Kelas Akhir Berbasis Ontologi di Ponpes Bintang Sehati Mulyana, Dadang Iskandar; Azzahra, Salma Latifa
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1592

Abstract

The determination of student graduation at Islamic boarding schools is an essential process that is often still carried out manually and subjectively, potentially leading to inconsistencies between student data and graduation decisions. This study aims to develop a graduation assessment system for final-year students using a Semantic Web approach based on ontology. This method is used to represent knowledge in the form of an ontology that includes graduation indicators such as academic scores, character (akhlaq), discipline, Qur'an memorization and arabic language. This study uses a case study at Ponpes Bintang Sehati, where the system is designed to assist the school in making student graduation decisions more objectively and systematically. Ontology development is carried out using the Protégé application, and inference is performed using a reasoner to determine student graduation status based on the input data. The test results show that the system is capable of assessing the graduation of students in Islamic boarding schools with an accuracy of 88%, producing consistent and accountable evaluations. The system can also be further developed to adapt to various academic and administrative needs within the boarding school environment. This system can also be further developed to be more adaptive to various academic and administrative needs within the boarding school environment
Real-Time Face Recognition System with Enhanced Security Using Cryptographic Hash-Based Encrypted Embedding Matching Zaidan, Rodhi Shafia; Kastum; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.322

Abstract

This study presents the development and evaluation of a secure and efficient real-time face recognition system for school attendance, integrating cancelable biometrics with cryptographic hashing. A total of 115 face samples were collected from students and teachers under diverse lighting, pose, and expression conditions. Images were pre-processed using Contrast Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction, followed by feature extraction with ResNet-128D, key-based random projection, binarization into 128-bit templates, and SHA-256 hashing. Evaluation results demonstrated an accuracy of 86.09%, precision of 100%, recall of 86.09%, and F1-score of 92.52%, with an average latency of 281.71 ms, remaining well below the operational threshold of 500 ms. Offline pre-processing improved the F1-Score by 7.50% on large datasets and 7.28% on smaller datasets without sacrificing processing speed. From a security perspective, the system achieved zero false acceptances (FAR = 0%) and allowed template regeneration when compromised, reinforcing privacy preservation. These findings validate the feasibility of combining cancelable biometrics with cryptographic hashing to balance accuracy, speed, and security in practical attendance systems. The research underscores its broader applicability to access control and public security, while future work should emphasize adaptive pre-processing, diverse hardware validation, and hardware acceleration for robust real-time deployment.
Support Vector Machine and Histogram of Oriented Gradients-Based Classification System for Waste Type Identification Notonegoro, Danendra Satriyohadi; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.315

Abstract

This study examines the effectiveness of classical computer vision methods for modern waste classification by combining Histogram of Oriented Gradients (HOG) for feature extraction with Support Vector Machine (SVM) for classification. The TrashNet dataset, consisting of five categories—cardboard, glass, metal, paper, and plastic—was used as the primary benchmark. To address data limitations and improve generalization, augmentation techniques such as random rotations, horizontal flipping, and brightness adjustments were applied. Hyperparameter optimization was further conducted using GridSearchCV with the RBF kernel to determine the most effective configuration. The optimized model achieved an accuracy of 84.36%, representing a substantial improvement from the 60% baseline. These findings confirm that non-deep learning approaches remain relevant and can serve as computationally efficient alternatives to CNNs, which typically require GPUs and extensive training time. Challenges persist in classifying reflective materials such as glass and metal, where HOG descriptors are less effective. Future work should integrate complementary descriptors, including color and texture-based features, to enhance robustness and scalability. Overall, the study demonstrates that an optimized HOG-SVM pipeline offers a practical, resource-efficient solution for automated waste classification, with strong potential to support sustainable waste management in real-world applications.
Optimisasi Penjadwalan Kegiatan Guru pada SMK IDN Boarding School Jonggol dengan Penerapan Algoritma Genetika Nuradi, Fahmi; Tundo, Tundo; Mulyana, Dadang Iskandar; Lestari, Sri
TEKNOKOM Vol. 7 No. 2 (2024): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/teknokom.v7i2.223

Abstract

This document describes guidelines for Authors in writing an article in JIMIK. This abstract section should Activity scheduling is a crucial aspect of educational management, especially in school environments with many activities and limited resources. At IDN Boarding School Vocational School, the challenges in scheduling teacher activities become increasingly complex as the number of subjects, extracurricular activities and limited resources such as space and time increase. Manual scheduling methods using spreadsheets such as Microsoft Excel take a long time and are prone to human error. This research proposes the application of a Genetic Algorithm to optimize the scheduling of teacher activities at the IDN Boarding School Vocational School. The Genetic Algorithm was chosen because of its ability to find optimal solutions through selection, crossover and mutation processes. This algorithm is able to handle various constraints in scheduling, both hard constraints (constraints that must be obeyed) and soft constraints (constraints that are desired but not mandatory). The aim of this research is to develop an automatic scheduling system that can reduce delays and the risk of errors in preparing schedules, adjust schedules quickly when sudden changes occur, and distribute teacher workload more evenly. The research results show that the application of a Genetic Algorithm can produce a more efficient and effective schedule compared to manual methods, by minimizing schedule conflicts, optimizing space use, and ensuring a more balanced distribution of teacher workload. This research not only provides a solution to scheduling problems at the IDN Boarding School Vocational School, but can also be adapted and applied to other educational institutions. Thus, this research makes a real contribution to improving the quality of educational management and teaching and learning processes in Indonesia.
Support Vector Machine and Histogram of Oriented Gradients-Based Classification System for Waste Type Identification Notonegoro, Danendra Satriyohadi; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.315

Abstract

This study examines the effectiveness of classical computer vision methods for modern waste classification by combining Histogram of Oriented Gradients (HOG) for feature extraction with Support Vector Machine (SVM) for classification. The TrashNet dataset, consisting of five categories—cardboard, glass, metal, paper, and plastic—was used as the primary benchmark. To address data limitations and improve generalization, augmentation techniques such as random rotations, horizontal flipping, and brightness adjustments were applied. Hyperparameter optimization was further conducted using GridSearchCV with the RBF kernel to determine the most effective configuration. The optimized model achieved an accuracy of 84.36%, representing a substantial improvement from the 60% baseline. These findings confirm that non-deep learning approaches remain relevant and can serve as computationally efficient alternatives to CNNs, which typically require GPUs and extensive training time. Challenges persist in classifying reflective materials such as glass and metal, where HOG descriptors are less effective. Future work should integrate complementary descriptors, including color and texture-based features, to enhance robustness and scalability. Overall, the study demonstrates that an optimized HOG-SVM pipeline offers a practical, resource-efficient solution for automated waste classification, with strong potential to support sustainable waste management in real-world applications.
Real-Time Face Recognition System with Enhanced Security Using Cryptographic Hash-Based Encrypted Embedding Matching Zaidan, Rodhi Shafia; Kastum; Mulyana, Dadang Iskandar
Journal Innovations Computer Science Vol. 4 No. 2 (2025): November
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i2.322

Abstract

This study presents the development and evaluation of a secure and efficient real-time face recognition system for school attendance, integrating cancelable biometrics with cryptographic hashing. A total of 115 face samples were collected from students and teachers under diverse lighting, pose, and expression conditions. Images were pre-processed using Contrast Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction, followed by feature extraction with ResNet-128D, key-based random projection, binarization into 128-bit templates, and SHA-256 hashing. Evaluation results demonstrated an accuracy of 86.09%, precision of 100%, recall of 86.09%, and F1-score of 92.52%, with an average latency of 281.71 ms, remaining well below the operational threshold of 500 ms. Offline pre-processing improved the F1-Score by 7.50% on large datasets and 7.28% on smaller datasets without sacrificing processing speed. From a security perspective, the system achieved zero false acceptances (FAR = 0%) and allowed template regeneration when compromised, reinforcing privacy preservation. These findings validate the feasibility of combining cancelable biometrics with cryptographic hashing to balance accuracy, speed, and security in practical attendance systems. The research underscores its broader applicability to access control and public security, while future work should emphasize adaptive pre-processing, diverse hardware validation, and hardware acceleration for robust real-time deployment.
Optimization of Text Mining Detection of Tajweed Reading Laws Using the Yolov8 Method on the Qur'an Mulyana, Dadang Iskandar; Rowis, Muhammad Arfan Irsyad
QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Vol. 14 No. 2 (2022): Qalamuna - Jurnal Pendidikan, Sosial, dan Agama
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Program Pascasarjana IAI Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/qalamuna.v14i2.3866

Abstract

The science of tajweed is a science that studies how to read the letters or readings in the Qur'an beautifully or well by the legal rules regulated therein. However, many people still do not pay attention to the legal rules of tajweed when reading the Qur'an, so it is not uncommon for them to make mistakes in pronunciation. From the legal rules of Tajweed reading, the slightest difference will change the meaning and intended meaning of the reading. So, paying attention to every rule of the law of reading Tajweed is very important. Therefore, considering the current technological advances, we plan a tajweed detection design using the YOLO algorithm optimized for the Qur'an. This study aims to determine and analyze the detection of text mining on tajweed reading. The method used in this study is the YOLO Algorithm method. This research uses 210 images of the Mushaf Al-Qur'an dataset, tested twice using Augmentation and Non-Augmentation to get optimal research results. The dataset underwent a training process of 138 images, or about 66%, and a validation process of 48 images, about 28%, and 24 images, or 11% of the total sample. Of the two tests using augmentation with no augmentation, augmentation testing produces the highest precision value with a value of 0.985 or 98.5% and the highest mAP50 with a value of 0995 or 99.5% for the Lafdzul Jalalah class group, with a total accuracy value of 92.94%. For testing without augmentation, the results show that the highest mAP50 value is the Lafdzul Jalalah class, with a value of 0.974 or 97.40% and an accuracy value of 91.37%. Based on optimization and comparison carried out for the accuracy value of research with augmentation of 92.94% and research conducted without augmentation is 91.37%. So, the study's results obtained an increased value of 1.57% by performing greyscale augmentation.
Co-Authors Abdillah, Gipari Pradina Abdul Hafidz Abdul Shomad Abdullah Al Faruq Adawiyah, Rizky Adi Riswan Afriandika, Riko Agung Pratama Agung Pratama Agung Rizki Zamzami Agung Saputra Agus Sigit Sumarsono Ahmad Bustomi Zuhari Ahmad Bustomi Zuhari Ahmad Bustomi Zuhri Ahmad Saepudin Ahmad Saepudin Ahmad Zulfikar Aidil Rizki Hidayat Aimar, Muqorrobin Aji Aji Dwi Prasetyo Aji Suswantoro Akbar, Yuma Akbarulloh, Feri Akhsani, Ziyat Akmal, Roid Adip Akmaludin Akmaludin Al Ammar, Muhammad Farros Alannuari, Fiky Albahy, Abdurrahman A. Aldi Sitohang Alfiani Damaiyanti AlfianiDamaiyanti Ali Akbar Ali Akbar Ali Akbar Ali Muhammad Faadhil Ali Yafi Zulkarnain Alifah, Rifdah Aloisius Awang Hariman Amat Solihin Amrullah, Aziz Septian Andi Anto Diarjo Andriyana Fajar Andy Manuel Prima Angga Tristhanaya Anggit Purnama Anggraeni, Eka Anisah Wulandari Apian Candra Aditya Ardana, Tegar Rizky Ardiyansyah, Ferry Ari Ramadhan Ari Surya Jaya Ari Surya Jaya Aribatullah Arief Sofyan Arief, Yoga Sofyan Arinal, Veri Aris Sufriman Arisenja, Ni Luh Bumi Arpinda Arpinda Asep Maulana Asep Ovid Afidin Asep Ovid Afidin Aswad, Hazrul Asyrofie, Maulana Azhar Atik Budi Paryanti Awaludin Awaludin Awaludin Awaludin, Awaludin Ayu Saputry, Yulia Yanti Aziz Septian Amrullah Aziz Septian Amrullah Azzahra, Salma Latifa B, Muhamad Hasbi Toharudin Banase, Samuel Figo Bashir, Ade Abdul Bela Dina Betty Yel, Mesra Bintoro, Bayu C.Afif Firas Cahyana, Adella Fitriany Calvin Bill Roring Candra Milad Ridha Eislam Choirul Huda Debby Ramadhina Salsabilla Dedi Gunawan Dedi Gunawan Dedi Iskandar Dedi Iskandar Dedi Iskandar Deny Saputra Dewi Riyanti Wibowo Dewi Riyanti Wibowo Dheo Hanif Pristian Dhiva Andini Putri Alinur Diana Barsasella Dita Yuliana Donaldo, Evan Dwi Lestari Edi Edi Eka Anggraeni Eka Maheswara Eka Okta Putri Sulaiman Eka Okta Putri Sulaiman Eka Putri Aprillia Eka Satria Maheswara Eka Satria Maheswara Ependi, Soleh Erno Sumantri F, Joe Renaldy Fadhil Khanifan Achmad Fadhil, Ali Muhammad Fadillah, Fauzan Fadlan, Muhammad Fahmi Nurul Huda Faisal Akbar Faisal Akbar Faisal Akbar Nasution Faizal Joko Perwitosari Fajar, Andriyana Farida Indah Riantini Fatchur Rochman Fatonah FauzI Ramdhani Feni Citra Dewi Feri Akbarulloh Fernanda Adhipramana Ferry Fajar Pratama FikriYadi FikriYadi Fiktor Kurnia Tofano Fiktor Kurnia Tofano Fiky Alannuari Firas, C.Afif Firhan Ali Franido, Richard Fransiscus Rolanda Malau Fransiscus Rolanda Malau Galih Satria Yacob Genisa, Lenggo Ghofurur Nawangsah Gilang Ramadhan Gilang Ramadhan Gipari Pradina Abdillah Gusniar Alfian Noor Gusniar Alfian Noor Handrianus Saldu Herdiyansyah Hartanto Herdiyansyah herdi Hartanto Hermawan Susanto Hidayat, Aditya Zakaria Hidayat, Nurhikmah Hudhoifah, Maula Abi Hudzaifah, Salim Maula Ikha Novie Tri Lestari Ikha Novie Tri Lestari Ikhsan Ikhsan Ikhwanul Kurnia Rahman Ilham Wahyudi Imam Khoeri Imantara, Alaqsha Gilang Indah Rosmalina Irbah Baihaqi Irbah Baihaqi Irfan Maulana Irfan Maulana, Irfan Istianah Istianah Istianah Jaya, Ari Surya Jaya, Rudi Tri Jodi Juliansah Joharuddin Zakaria, M Ohan Julinar Sari Hutagalung Kastum Kastum Kastum Kastum, Kastum Kemal Adnan Khanif, Abror Kolbia, Ummi Kurniawan Irfan Nauval Lerry Salasi Saptan Lintang Purnama Lintang Purnama Lorinda, Destiar Lubis, Yunita T Lutfianti, Nesti M Ainur Rofik M Ainur Rofik M Ilham Setya Aji M Ohan Joharuddin Zakaria M. Ohan Zakaria Mafazi, Luthfillah Maharanisa Maharanisa Maharanisa, Maharanisa Mainia Mayasari Marjuki Marjuki Marjuki Matheos Sarimolle, Frencis Maulana Putra Hertaryawan, Ryfan Melani Afsari Miftahul Huda Miftahul Ulum Miftahul Ulum Milli Ruswandi Mirsandi Muhamad Fikri Nugraha Muhamad Ikbal Muhamad Zaeni Nadip Muhammad Abdul Aziz Abyan Muhammad Adri Ramadhan Muhammad Adri Ramadhan Muhammad Arfan Irsyad Rowis Muhammad Arfan Irsyad Rowis Muhammad Arib Umar Sadid Muhammad Azhari Muhammad Dzaky Rahmanto Muhammad Dzaky Rahmanto Muhammad Faizal Lazuardi Muhammad Faizal Lazuardi Muhammad Fakhri Pratama Muhammad Furqan Muhammad Hafiz Siregar Muhammad Jauhar Ruliansyah Muhammad Khalid Muhammad Rifqi Syatria Muhammad Rival Muhammad Rizki Muhammad Syahrul Fattah Ramadhan Muhammad Umar Hamidi Yusuf Muhammad Zaenuddin Muhammad Zikri Muhammad Zikri Muklas Adik Putra Muklas Adik Putra Mutia Ramadhan Naini Saadah Naini Sa’adah Nana NANA NANA Nana, Nana Nandy Dinilhaq Naufal Aziz Nauval, Kurniawan Irfan Nesti Lutfianti Nimas Galuh Pramuditasari Noor, Gusniar Alfian Notonegoro, Danendra Satriyohadi Noviyanti, Irma Nugroho, Kurniawan Setyo Nunung Parawati Nuradi, Fahmi Nurfaishal, Muhammad Dzaky Nurrohman, Awaludin Taufiq Oka Prasetiyo Okta Saputra Oky Tria Saputra Paramida, Feti Paryanti, Atik Budi Pramansah, Vika Vitaloka Pramuditasari, Nimas Galuh Pratama, Ferry Fajar Pratiwi, Tiyas Aria Pristian, Dheo Hanif Putra, Guruh Taruno Putra, Mohammad Royger Febriansyah Putra, Reyga Ferdiansyah Putri Amira Sumitro Putri Nugraheni Utami Putri, Atsilah Daini Putro, Faris Widianto Radikto, Radikto Raga Permana Rahmani, Husain Rahmanto, Muhammad Dzaky Raihan Putra M Rosidi Ramadan, Anggi Rasiban Reyga Ferdiansyah Putra Reza Gustrianda Reza Wanandi Richard Franido Richardviki Beay Richardviki Beay Rifky Aldiansyah Riki Maulana Fauzi Riko Afriandika Riswan, Adi Rival, Muhammad Riza Hidayat Riza Hidayat, Riza Rizky Adawiyah Rodhi Shafia Zaidan Rofik, M Ainur Roring, Calvin Bill Rowis, Muhammad Arfan Irsyad Runi Amanda Amalia Ruswandi, Milli Sadid, Muhammad Arib Umar Sadid, Muhammad Umar Arib Sahroni sahroni Sahrul Hidayat Saifullah Ahmad Yasin Samuel Figo Banase Santi Ferawati Saputra, Mochammed Erryandra Saputri, Rosalina Saragih, Silvanus Sarimole, Frencis Matheos Sartika Mala Seli Amelia Senika, Anis Sentosa, Edwin Septiani, Novi Setiawan, Itca Bagus Setya Putra Adenugraha Shakila Shila Wati Silfia, Titi Siregar, Ikhsan Abror Siregar, Mora Hakim Siregar, Muhammad Hafiz Siti Nurhaliza Siti Raysyah Slamet Riyadi Sodik Sofia, Agiah Soleh Ependi Sony Agustian Syah Sopan Adrianto SOPAN ADRIANTO SOPAN ADRIANTO SRI LESTARI Sri Lestari Sri Lestari Stefany Tarunajaya Stepanus, Stepanus Sugeng Sugeng Sugeng Sugeng Sugiyono Sugiyono Sumantri, Dyan Bagus Sumantri, Erno Sumarsono, Agus Sigit Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Sutisna Suwandi Suwandi Syatria, Muhammad Rifqi Tarunajaya, Stefany Titi Silfia Tri Wahyuni Tristhanaya, Angga Tundo Tundo, Tundo Untung Wahyudi Vara Maulidyah Hidayah Vika Vitaloka Pramansah Wahyu Hidayat Wahyu Saputro Wahyu Saputro Wahyudi, Ahmad Arif Wicaksono, Bima Wieko Wieko Wulandari, Anisah Yacob, Galih Satria Yansen Yansen YkhSanur YkhSanur Yoni Maulana Yuliana Bachtiar Yuliana, Dita Yunita T Lubis Yusril Nurhadi AS Zaidan, Rodhi Shafia Zaky Rahman Hakim Zamzami, Agung Rizki Zidane, Ahmad Syahran Zoharuddin Zakaria, M Ohan