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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 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 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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Optimizing Contextual Features for Instagram Engagement Prediction using Long Short-Term Memory (LSTM) Aswad, Hazrul; Mulyana, Dadang Iskandar; Kastum, Kastum
TIN: Terapan Informatika Nusantara Vol 6 No 3 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i3.8166

Abstract

Instagram has become an important communication medium for academic institutions, enabling the dissemination of information, promotion of activities, and engagement with the campus community. At STIKOM CKI Jakarta, the official Instagram account plays a key role in academic communication, making it essential to optimize content strategies for higher audience interaction. This study analyzes 311 publicly available posts collected from July 2023 to July 2025 from the institution’s official account. Although relatively small for deep learning, the dataset provides representative patterns for the case study while highlighting the model’s capability under limited data conditions. A predictive framework based on Long Short-Term Memory (LSTM) was developed by integrating textual features from captions with contextual features such as posting time, content type, hashtag count, and interaction metrics. The aim is to accurately estimate engagement scores and provide actionable posting recommendations. The evaluation achieved an R² of 88.00%, MAE of 0.0450, and RMSE of 0.0720, indicating strong predictive performance. The contribution of this research lies in demonstrating that optimizing contextual features can significantly enhance academic social media engagement and in providing an adaptable methodology for institutions with limited historical data.
DETEKSI REAL-TIME DURASI KEHADIRAN PELANGGAN DI MEJA KAFE DENGAN KAMERA IP DAN ALGORITMA DEEP SORT Iskandar Mulyana, Dadang; Rizki, Muhammad
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 5 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/9rh7xv34

Abstract

Perkembangan teknologi visi komputer telah membuka peluang bagi industri jasa, khususnya kafe, untuk meningkatkan efisiensi operasional dan pemahaman perilaku pelanggan. Penelitian ini mengusulkan dan mengimplementasikan sistem real-time untuk mendeteksi dan menghitung durasi duduk pelanggan di meja kafe dengan memanfaatkan IP Camera sebagai perangkat akuisisi data, serta algoritma YOLOv8 untuk deteksi objek dan Deep SORT untuk pelacakan multi-objek. Sistem ini dirancang untuk mengidentifikasi keberadaan manusia, mengaitkannya dengan posisi meja, dan mencatat waktu kedatangan serta kepergian pelanggan secara otomatis. Data yang dihasilkan dapat digunakan untuk analisis tingkat okupansi meja, durasi kunjungan rata-rata, dan optimalisasi tata letak ruang. Evaluasi sistem dilakukan dengan menguji akurasi deteksi, pelacakan, serta perhitungan durasi duduk terhadap data ground truth. Hasil pengujian menunjukkan bahwa sistem mampu menjalankan fungsinya secara efektif dengan akurasi pelacakan mencapai lebih dari 85% pada kondisi pencahayaan dan sudut kamera yang optimal. Sistem ini diharapkan dapat menjadi solusi cerdas bagi pengelola kafe dalam pengambilan keputusan berbasis data. Kata Kunci: Computer Vision, YOLOv8, Deep SORT, IP Camera, Pelacakan Objek, Durasi Duduk, Kafe, Real-Time.
Pengembangan Sistem POS Terintegrasi QRIS Pada UMKM IDN Jonggol Jawa Barat Mulyana, Dadang Iskandar; Imantara, Alaqsha Gilang; Bashir, Ade Abdul
INTECOMS: Journal of Information Technology and Computer Science Vol. 8 No. 4 (2025): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/kbgspw64

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem Point of Sale (POS) terintegrasi dengan Quick Response Code Indonesian Standard (QRIS) dan fitur laporan   guna mendukung efisiensi transaksi dan pengelolaan keuangan bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) IDN Jonggol, Jawa Barat. Sistem ini dirancang untuk menjawab kebutuhan UMKM terhadap metode pembayaran nontunai yang cepat, aman, dan seragam, sekaligus menyediakan laporan penjualan secara otomatis dan real-time. Metode pengembangan yang digunakan adalah pendekatan Software Development Life Cycle (SDLC) model waterfall, dengan tahapan analisis, perancangan, implementasi, pengujian, dan pemeliharaan. Hasil implementasi menunjukkan bahwa sistem POS yang dibangun mampu memproses pembayaran melalui QRIS dengan akurasi tinggi, serta menghasilkan laporan penjualan harian, mingguan, dan bulanan yang dapat diakses melalui dashboard  . Respon pengguna terhadap sistem ini menunjukkan peningkatan efisiensi dan transparansi dalam pengelolaan usaha. Dengan demikian, sistem POS terintegrasi ini berpotensi menjadi solusi teknologi yang aplikatif dan relevan dalam mendukung transformasi   UMKM di daerah Jonggol maupun wilayah serupa.
Analisis Sentimen Pemecatan Shin Tae-yong pada Media Sosial X untuk Monitoring Opini Publik Menggunakan Naïve Bayes dan Support Vector Machines Arisenja, Ni Luh Bumi; 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.v6i3.1561

Abstract

Social media has become a primary platform for people to voice their opinions on national issues, including in the field of sports. One of the hotly discussed issues is the dismissal of the Indonesian National Team coach, Shin Tae-Yong. This study aims to analyze public sentiment towards the dismissal through social media platform X (formerly known as Twitter) using two machine learning algorithms, namely Naïve Bayes and Support Vector Machines (SVM). Data was obtained through a crawling process using the keyword pecat shin tae-yong, then carried out pre-processing stages such as cleaning, tokenizing, stopword removal, and stemming. The evaluation process was carried out using a confusion matrix to measure accuracy, precision, recall, and F1-score. The classification results show that the Naïve Bayes model produces an accuracy of 92.91%, while the positive precision value is 81.33%, and the negative precision is 100%. Meanwhile, the SVM (Support Vector Machine) model provided more optimal results with an accuracy of 97.97%, a positive precision of 96.72%, a negative precision of 98.53%, and a positive recall of 96.72% and a negative recall of 98.53%. Based on these results, it can be concluded that the SVM algorithm performed better in analyzing public opinion regarding the coach's dismissal issue. This research is expected to contribute as a reference data-based public opinion monitoring system for more transparent public policymaking.
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 results are expected to show that the system can assist the assessment process objectively and produce a graduation classification that is consistent and accountable. This system can also be further developed to be more adaptive to various academic and administrative needs within the boarding school environment.
Classification Optimization of Aedes albopictus and Culex quinquefasciatus Mosquito Larvae Using Vision Transformer Method Al Faruq, Abdullah; Mulyana, Dadang Iskandar; Adrianto, Sopan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5120

Abstract

Mosquito-transmitted diseases like Dengue Hemorrhagic Fever and Filariasis pose serious health threats throughout tropical regions, particularly in Indonesia. Quick and accurate identification of mosquito larvae plays a crucial role in disease prevention, especially for Aedes albopictus and Culex quinquefasciatus species that act as main disease carriers. Manual identification methods using microscopes or visual guides often struggle with time constraints, accuracy issues, and dependence on trained specialists. Our research focuses on improving the classification of Aedes albopictus and Culex quinquefasciatus mosquito larvae using Vision Transformer (ViT) technology, a deep learning method that has shown strong results in image recognition tasks. We applied the Vision Transformer model to classify mosquito larvae from microscopic field images. The study also tested how different factors impact model performance, such as image clarity, lighting conditions, and image resolution. Our findings show that using Vision Transformer in classification systems produced excellent results, achieving 98.00% accuracy in recall, precision, and F1-score measurements. The research reveals that Vision Transformer methods deliver better accuracy than traditional approaches like Convolutional Neural Networks and can be adapted into working systems for technology and healthcare sectors.
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.
Co-Authors Abdillah, Gipari Pradina Abdul Hafidz Abdul Shomad Abyan, Muhammad Abdul Aziz Adawiyah, Rizky Adi Riswan 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 Al Faruq, Abdullah Alannuari, Fiky Albahy, Abdurrahman A. Aldi Sitohang Alfiani Damaiyanti AlfianiDamaiyanti Ali Akbar Ali Akbar Ali Muhammad Faadhil Ali Yafi Zulkarnain Alifah, Rifdah Aloisius Awang Hariman Amat Solihin 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, 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 Ayu Saputry, Yulia Yanti Aziz Septian Amrullah Aziz Septian Amrullah Aziz, Naufal 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 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 Faizal Joko Perwitosari Farida Indah Riantini Fatchur Rochman Fatonah FauzI Ramdhani Feni Citra Dewi Fernanda Adhipramana Ferry Fajar Pratama FikriYadi FikriYadi Fiktor Kurnia Tofano Firhan Ali Fransiscus Rolanda Malau Fransiscus Rolanda Malau Genisa, Lenggo Ghofurur Nawangsah Gilang Ramadhan 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, Rudi Tri Jodi Juliansah Joharuddin Zakaria, M Ohan Julinar Sari Hutagalung 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 Maulana Putra Hertaryawan, Ryfan Melani Afsari Miftahul Huda Miftahul Ulum Milli Ruswandi Mirsandi Muhamad Fikri Nugraha Muhamad Ikbal Muhamad Zaeni Nadip Muhammad Adri Ramadhan Muhammad Arfan Irsyad Rowis Muhammad Arfan Irsyad Rowis Muhammad Azhari Muhammad Dzaky Rahmanto Muhammad Dzaky Rahmanto Muhammad Faizal Lazuardi Muhammad Faizal Lazuardi Muhammad Fakhri Pratama Muhammad Furqan Muhammad Jauhar Ruliansyah Muhammad Khalid Muhammad Rizki Muhammad Syahrul Fattah Ramadhan Muhammad Zaenuddin Muhammad Zikri Muhammad Zikri Muklas Adik Putra Muklas Adik Putra Mutia Ramadhan Naini Saadah Naini Sa’adah Nana NANA NANA Nandy Dinilhaq Nesti Lutfianti Nimas Galuh Pramuditasari 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 Ramadhan, Muhammad Adri 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 Rizky Adawiyah Rofik, M Ainur Roring, Calvin Bill Rowis, Muhammad Arfan Irsyad Runi Amanda Amalia Sadid, Muhammad Arib Umar Sadid, Muhammad Umar Arib Sahroni sahroni Sahrul Hidayat Saifullah Ahmad Yasin 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 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 Suwandi Syatria, Muhammad Rifqi Tarunajaya, Stefany Titi Silfia Tofano, Fiktor Kurnia Tri Wahyuni 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 Yunita T Lubis Yusril Nurhadi AS Zaidan, Rodhi Shafia Zaky Rahman Hakim Zamzami, Agung Rizki Zidane, Ahmad Syahran Zoharuddin Zakaria, M Ohan