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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ELKHA : Jurnal Teknik Elektro Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Eksplora Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) DoubleClick : Journal of Computer and Information Technology Informatik : Jurnal Ilmu Komputer Kurawal - Jurnal Teknologi, Informasi dan Industri JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Informatika Global EDUMATIC: Jurnal Pendidikan Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) JUKI : Jurnal Komputer dan Informatika TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pendidikan dan Teknologi Indonesia Jumat Informatika: Jurnal Pengabdian Masyarakat Bulletin of Computer Science Research Jurnal Abdi Masyarakat Indonesia Jurnal Pengabdian Masyarakat IPTEK Brilliance: Research of Artificial Intelligence Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Nasional Teknologi Komputer Arcitech: Journal of Computer Science and Artificial Intelligence Jurnal Informatika Progres The Indonesian Journal of Computer Science Research Mestaka: Jurnal Pengabdian Kepada Masyarakat Innovative: Journal Of Social Science Research MDP Student Conference Journal of Embedded Systems, Security and Intelligent Systems JRIIN :Jurnal Riset Informatika dan Inovasi Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Software Engineering and Computational Intelligence Scientific Journal of Informatics LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Applied Information Technology and Computer Science (AICOMS) Welfare: Jurnal Pengabdian Masyarakat Jurnal Nasional Teknologi Informasi dan Aplikasinya Jurnal Nasional Komputasi dan Teknologi Informasi
Muhammad Rizky Pribadi
Universitas Multi Data Palembang
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PREDIKSI HARGA SAHAM SEKTOR PERBANKAN LQ45 MENGGUNAKAN BILSTM DENGAN PERBANDINGAN METODE FEATURE SELECTION Jonathan Wijaya; Muhammad Rizky Pribadi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 1 (2026): JATI Vol. 10 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i1.16769

Abstract

Pergerakan harga saham yang fluktuatif menjadikan prediksi harga saham sebagai tantangan penting dalam pengambilan keputusan investasi, khususnya pada saham sektor perbankan yang tergabung dalam indeks LQ45. Permasalahan utama dalam prediksi harga saham adalah tingginya volatilitas data serta pemilihan fitur yang kurang optimal sehingga dapat menurunkan akurasi model prediksi. Penelitian ini bertujuan untuk membangun model prediksi harga saham sektor perbankan LQ45 menggunakan algoritma Bidirectional Long Short-Term Memory (BiLSTM) serta menganalisis pengaruh penerapan metode seleksi fitur terhadap kinerja model. Metode yang digunakan meliputi penerapan tiga teknik seleksi fitur, yaitu Spearman Correlation, Mutual Information, dan Lasso Regression, dengan dataset historis saham BBRI, BBNI, BMRI, dan BBTN periode 2020–2025. Data dibagi menjadi 80% data pelatihan dan 20% data pengujian, serta dievaluasi menggunakan Root Mean Squared Error (RMSE) dan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan bahwa penerapan seleksi fitur mampu meningkatkan akurasi model BiLSTM, Namun, pada saham BBTN, penerapan Spearman, Mutual information 10 fitur dan 15 fitur justru menurunkan performa model BiLSTM
DETEKSI PENYAKIT GIGI PADA CITRA DENTAL OPG X-RAYS MENGGUNAKAN ARSITEKTUR EFFICIENTDET Jesen Ong; Muhammad Rizky Pribadi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 1 (2026): JATI Vol. 10 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i1.16922

Abstract

Penelitian ini memanfaatkan deep learning untuk membantu diagnosis penyakit gigi dari citra radiografi panoramik Orthopantomogram (OPG) mengingat tingginya prevalensi masalah gigi dan mulut serta rendahnya akses perawatan (WHO, 2022; Riskesdas, 2018; Survei Kesehatan Indonesia, 2023). Analisis OPG memiliki kompleksitas visual seperti distorsi, tumpang tindih struktur, variasi kontras, serta objek patologis berukuran kecil yang menyulitkan interpretasi secara konsisten. Penelitian ini bertujuan membandingkan kinerja EfficientDet-D2, EfficientDet-D3, dan EfficientDet-D4 dalam mendeteksi lima kelas penyakit, yaitu Caries, Infection, Impacted teeth, Fracture, dan Broken crown. Dataset publik Rahman dkk. (2024) diolah melalui Roboflow dan dibagi menjadi 134 citra latih (449 anotasi), 13 citra validasi (49 anotasi), dan 12 citra uji (28 anotasi). Ukuran input disesuaikan per varian (D2: 768, D3: 896, D4: 1024) dan model diinisialisasi menggunakan pretrained weights COCO. Evaluasi menggunakan mAP50. EfficientDet-D4 memperoleh mAP50 tertinggi pada validasi sebesar 0,800, sedangkan mAP50 terbaik pada data uji dicapai EfficientDet-D2 sebesar 0,714, diikuti EfficientDet-D4 sebesar 0,701 dan EfficientDet-D3 sebesar 0,622
Klasifikasi Citra Sampah Botol Plastik Jenis HDPE dan PET Menggunakan Algoritma YOLOv7 Opita Purwasih; Wijang Widhiarso; Muhammad Rizky Pribadi
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.654

Abstract

The classification of plastic bottle waste, particularly High Density Polyethylene (HDPE) and Polyethylene Terephthalate (PET), remains a challenge in recycling processes due to their similar visual characteristics. Misclassification can lead to a decline in recycled material quality and economic losses in the waste management industry. This research aims to develop an automated image-based classification system to distinguish between HDPE and PET plastic waste using the You Only Look Once version 7 (YOLOv7) object detection algorithm. The dataset consists of plastic bottle images in various physical conditions, annotated with bounding boxes to support model training. The data were split into 70% for training, 20% for validation, and 10% for testing. The best performance was achieved with a batch size of 16 and 100 training epochs, resulting in a precision of 93.9%, recall of 91.6%, and a mean Average Precision (mAP@0.5) of 96.5%. The model demonstrated the ability to accurately classify both types of plastic bottles, even when objects were deformed. These results suggest that the YOLOv7 algorithm is highly capable for implementation in image-based waste classification systems, enhancing sorting efficiency and supporting more sustainable plastic waste management practices.
Perancangan UI/UX Pada Aplikasi Elaruna Dengan Metode Design Thinking Fellycia Caroline; Steffanie Angelica; Muhammad Fajar Ariansyah; Serenity Devina Suryanto; Muhammad Rizky Pribadi
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 2 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v4i2.1825

Abstract

Indonesia has great potential in the tourism sector due to its rich culture and natural beauty, but it still faces challenges in the form of limited access to integrated and reliable information for tourists. This study aims to design a mobile-based tourism information application user interface (UI/UX) that provides quick, accurate, and user-friendly access to information. The method used is Design Thinking, which consists of five stages: Empathize, Define, Ideate, Prototype, and Test. The design process was carried out using a user-centered approach to ensure the design meets the needs and preferences of tourists. Test results show that most users find the application interface easy to use, visually appealing, and clearly navigable, with 91.3% of respondents stating that the navigation is easy and 73.9% feeling that the application runs smoothly. This demonstrates that the Design Thinking approach is effective in producing design solutions that are responsive to user needs. This study is expected to contribute to the development of digital tourism applications in Indonesia and serve as a foundation for further research in the development of features and broader integration of information technology.
Penerapan Algoritma Hybrid pada Sistem Rekomendasi Makanan Berdasarkan Preferensi Pengguna Victoria Valensita Robert; Muhammad Rizky Pribadi
JUKI : Jurnal Komputer dan Informatika Vol. 8 No. 1 (2026): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v8i1.1981

Abstract

Perkembangan platform digital telah meningkatkan ketergantungan masyarakat dalam memilih resep makanan, namun kondisi ini sering menyebabkan informasi berlebih yang menyulitkan pengguna dalam menentukan pilihan yang sesuai dengan preferensi dan kebutuhan mereka. Penelitian ini bertujuan untuk mengembangkan sistem rekomendasi makanan berbasis pendekatan hibrida dengan mengintegrasikan penyaringan berbasis konten dan penyaringan kolaboratif menggunakan algoritma K-Nearest Neighbors pada dataset Food.com Recipes and Reviews. Metode pelaksanaan penelitian diawali dengan tahap prapemrosesan data yang meliputi pembersihan duplikasi, penanganan missing value, normalisasi data numerik, serta pembersihan teks. Analisis konten dilakukan dengan membangun representasi fitur resep berdasarkan bobot kata, sedangkan analisis perilaku pengguna dilakukan melalui pemodelan matriks interaksi pengguna dan resep untuk mengidentifikasi kesamaan preferensi. Teknik analisis yang digunakan dalam penelitian ini adalah pengukuran tingkat ketepatan rekomendasi untuk mengevaluasi relevansi hasil rekomendasi. Hasil pengujian menunjukkan bahwa pendekatan penyaringan berbasis konten menghasilkan tingkat ketepatan rata-rata sebesar 86%, sementara pendekatan penyaringan kolaboratif menghasilkan 81%. Integrasi kedua metode melalui pendekatan hibrida bertingkat mampu meningkatkan kinerja sistem dengan tingkat ketepatan mencapai 95%. Hasil tersebut menunjukkan bahwa sistem rekomendasi hibrida yang diusulkan mampu menghasilkan rekomendasi yang lebih relevan dengan memanfaatkan kesamaan karakteristik resep dan pola preferensi pengguna secara bersamaan.
Analisis Sentimen Opini Publik terhadap Dedi Mulyadi di Twitter Menggunakan Ekstraksi Fitur TF-IDF dan Klasifikasi Naive Bayes Hafizh Pebrian; Aditya Ali Kusuma; Muhammad Rizky Pribadi
Innovative: Journal Of Social Science Research Vol. 6 No. 2 (2026): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v6i2.19365

Abstract

Pertumbuhan pesat media sosial, khususnya Twitter, telah membuka ruang yang luas bagi masyarakat untuk mengekspresikan pandangan mereka secara terbuka terhadap tokoh publik dan isu-isu politik. Penelitian ini bertujuan untuk melakukan analisis sentimen terhadap opini masyarakat mengenai Dedi Mulyadi, seorang tokoh politik di Indonesia, dengan memanfaatkan data yang diperoleh dari Twitter. Metodologi yang digunakan meliputi tahapan pengumpulan data tweet, praproses teks, ekstraksi fitur menggunakan pendekatan Term Frekuensi-Inverse Document Frekuensi (TF-IDF), serta proses klasifikasi sentimen melalui algoritma Naive Bayes. Sentimen yang diklasifikasikan terdiri dari tiga kategori, yaitu positif, negatif, dan netral. Hasil evaluasi menunjukkan bahwa kombinasi antara metode TF-IDF dan Naive Bayes mampu mengidentifikasi sentimen publik secara cukup efektif, dengan akurasi mencapai 68,0%. Temuan ini diharapkan dapat memberikan kontribusi dalam bidang analisis media sosial dan pemetaan opini masyarakat terhadap figur politik.
An Efficient Two Stage Detection Segmentation Framework for Automated Road Crack Assessment Alvin Hujaya; Muhammad Rizky Pribadi
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 1 (2026): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i1.33699

Abstract

Road cracks significantly degrade infrastructure quality and pose a threat to traffic safety. To minimize manual inspection inefficiencies, this study investigates a segmentation model integrating MobileNetV3-Small as a backbone for the U-Net architecture to reduce processing time. The performance of the proposed MobileNetV3-Small-U-Net is benchmarked against a standard U-Net using three public datasets: DeepCrack (537 images), CFD (118 images), and Crack500 (3368 images) sourced from GitHub and Kaggle. This research explores the influence of optimization algorithms on evaluation results across these diverse datasets. Specifically, the study evaluates Adam, RMSprop, and SGD optimizers at an image resolution of 224 x 224 pixels, with a 0.001 learning rate and 0.9 momentum. On-the-fly augmentation techniques, including horizontal flips and brightness adjustments (0.8 to 1.2), were implemented during training. Experimental results demonstrate that MobileNetV3-Small-U-Net enhances computational efficiency by achieving a 9 ms inference time, which is 2 ms faster than the standard U-Net. These findings confirm that a MobileNetV3-Small backbone accelerates inference, despite a slight trade-off in evaluation metrics. Additionally, results reveal that the SGD optimizer is unsuitable for these segmentation tasks due to high error rates and the lack of an adaptive learning rate.
PENGENALAN TEKNOLOGI RFID DALAM SISTEM ABSENSI OTOMATIS BERBASIS KARTU FLAZZ DI SMA XAVERIUS 3 PALEMBANG Adrian Suparto; Michael Joy Clement; Jovansa Putra Laksana; Brilliant Chandra Pratama; Fernando Feliansyah; Muhammad Rizky Pribadi; Eka Puji Widiyanto
FORDICATE Vol 5 No 1 (2025): November 2025
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v4i3.11704

Abstract

Abstrak: Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperkenalkan konsep dan implementasi sistem absensi otomatis berbasis teknologi RFID di lingkungan sekolah menengah. Tujuan utama kegiatan adalah memberikan pemahaman praktis kepada siswa mengenai cara kerja sistem absensi tanpa kontak dan manfaatnya dalam meningkatkan efisiensi administrasi. Metode yang digunakan meliputi sosialisasi langsung, penyampaian materi visual, serta demonstrasi aplikasi prototipe yang dikembangkan menggunakan antarmuka berbasis web dan pemindai kartu RFID. Hasil kegiatan menunjukkan respons positif dari siswa terhadap penggunaan teknologi tersebut. Demonstrasi berhasil memperlihatkan proses pencatatan kehadiran secara otomatis menggunakan kartu RFID dan bagaimana data disimpan dalam basis data lokal. Meskipun sistem belum diadopsi oleh pihak sekolah, aplikasi ini menunjukkan potensi sebagai solusi digital yang dapat diimplementasikan di masa mendatang. Kegiatan ini memberikan manfaat edukatif sekaligus mendorong kesadaran akan pentingnya transformasi digital dalam tata kelola sekolah.
Rice Leaf Disease Classification Using ResNet-50: A Comparative Study of Adam, SGD, and RMSProp Bebin Paula; Muhammad Rizky Pribadi
Brilliance: Research of Artificial Intelligence Vol. 6 No. 1 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v6i1.7582

Abstract

Rice plant diseases significantly affect crop productivity and require accurate and timely identification to support effective management. This study proposes a rice leaf disease classification approach using the ResNet-50 convolutional neural network and compares the performance of three optimization algorithms, namely ADAM, Stochastic Gradient Descent (SGD), and RMSProp. The model was trained and evaluated on a rice leaf image dataset consisting of four classes BrownSpot, Healthy, Hispa, and LeafBlast. The dataset contains visual variations in color, texture, and disease patterns that influence classification performance. Performance was assessed using training accuracy, loss, precision, recall, F1-score, and confusion matrix analysis. These evaluation metrics provide a comprehensive measurement of model effectiveness and class-wise prediction behavior. Experimental results show that the ADAM optimizer achieved the best performance with a training accuracy of 75.84%, followed by RMSProp at 74.60%, while SGD obtained the lowest accuracy of 71.34%. The differences in performance highlight the impact of optimization strategies on deep neural network training stability. Class-wise evaluation indicates that the model performed well in detecting BrownSpot and Healthy classes, but showed lower performance on the Hispa class across all optimizers. This limitation is influenced by the visual similarity of Hispa symptoms to other classes. These findings demonstrate that adaptive learning rate–based optimizers provide faster convergence and better classification performance for deep learning–based rice disease detection. The results support the use of optimized convolutional neural networks for image-based agricultural applications.
Pelatihan Pembuatan Website HTML Menggunakan VS Code Di SMP Xaverius Maria Palembang Fellycia Caroline; Serenity Devina Suryanto; Raphael Lee; Jonathan Jason Constantine; Daniel Udjulawa; Muhammad Rizky Pribadi
Mestaka: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 3 (2026): JUNI 2026
Publisher : Pakis Journal Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58184/mestaka.v5i3.1001

Abstract

The development of digital technology requires students to possess basic skills in utilizing technology creatively and productively, including creating simple websites. However, most students still do not understand the basic process of website development. This community service activity aimed to provide training on creating profile websites using HTML with the assistance of Visual Studio Code for class 9 students at SMP Xaverius Maria Palembang. The methods used in this activity were community education and hands-on training through material presentation, demonstrations, independent practice, discussions, and evaluations. The results showed that participants were able to understand the basic structure of HTML and follow the process of creating simple websites properly. In addition, participants showed high enthusiasm during the activity and began to understand the fundamentals of simple website development. This activity provided new experiences for participants and helped improve students’ knowledge and interest in the field of information technology.
Co-Authors -, Felicia Adi Saputra Aditya Al Assad Aditya Ali Kusuma Adrian Chen Adrian Suparto Adrian Suparto Ahmad Dumyati Ahmad Zaky Nadimsyah Albert Cahayadi Alvin Hujaya Alwin Marcellino Amarullah, Rendy Ampu Syura Ananda Wijaya Andreas Andreas Andreas Danny Agus W Andreas Saputra Andrian Wijaya Angel Kelly Asyraq, Cerwyn Bakti Ananda Fernando Bautista, Christian Bebin Paula Bella Jenni Ourelia Boy Putra Brilliant Chandra Pratama Calvin Bertnas Valentino Calvin Saputra Carissa Maharani Chandra Chandra Saputra Christian Richie Wijaya Clara Meyhazlinda Putri Clement, Michael Joy Daffa Yudha Musyaffa Daniel Daniel Daniel Johan Daniel Udjulawa Daniel Wijaya Darwin Saputra David Sebastian Dedy Hermanto Desta Rahman Theja Desy Iba Ricoida Dicky Ryanto Fernandes Dina Lestari Putri Diva Putri Kynta Dwi Apriyanti Sastika Dwi Cahyadi, Ambrosius Effendi pratama, Samuel Egi Fransisco Saputra Eka Puji Widiyanto Evangs Mailoa Evi Maria Fadhel Muhammad Fadhil Sa'adat Farisi, Ahmad Farisi, Ahmad Fathimah Azzahra Felicia Felicia Felix Gunawan Fellyca Effendi Fellycia Caroline Femmy Johan Feriyanto Feriyanto Ferliansyah, Fernando Fernandi Indi Nizar G Fernando Feliansyah Fernando Fernando Fernando Namas Fionna Caroline Florence Renaldo Frans Bachtiar Fransiskus Daniel Chandra Frisky Wijaya Genisshanda Nabila Matari Geraldo Wilson Gerry Christian Pilipus Gunawan, Michael Hafidz Irsyad Hafiz Irsyad Hafizh Pebrian Hansen Hansen Hendrawan, Malvin Hendry Hindriyanto Dwi Purnomo Ilham Indra Hidayat Imelia Dwinora Cahyati Indi Nizar G, Fernandi Ivan Luthfi Laksono Jackie Wijaya Jasen Jonathan Jaysen Stephanus Ja`Far Ja`Far Jelvin Krisna Putra Jennifer Verty Jerin, Nathaniel Jesen Ong Jonathan Jason Constantine Jonathan Tanujaya Jonathan Wijaya Joseph Eduard Uly Loni Jovansa Putra Laksana Kasanova, Sinyo Kelvin Dwi Wahyudi Kevin agustria zahri Kevin Andreas KGS M Ammar Yazid Klaudius Audie Irsansaputra Kurniawan, Ricky Arie Laksono, Ivan Luthfi Laurentius Ricardo Wijaya Leo Chandra Leonardo Yahya Liem, Steven Lin, Valen Julyo Armando Davincy Lipi Amanda Putra Lucretia, Jolyn M Lazuardi Ferdillian M. Dhafa Adjie Saputra Marcelino Marcelino Mario Rivaldo Michael Michael Joy Clement michael Wijaya Migel Orvin Febryan Millenia Mudita Chandra Muhammad Abdul Azizul Hakim Muhammad Alfa Rizi Muhammad Azril Fahrezi Muhammad Dafhi Mayrizkiy Muhammad Dody Muhammad Fadli Muhammad Fajar Ariansyah Muhammad Hamdandi Muhammad Naufal Anugrah Muhammad Radja Juang Jamemiko Muhammad Redho Saputra Muhammad Reyza Nirwana Muhammad Robi, Muhammad Muhammad Tri Setianto Nabila Syiva Altarisa Nabilah Dayanah Nathacia Lais Naufal Akbar Neilsen Nicholas Komah Nicolas Jacky Pratama Hasan Nova Ariansyah Opita Purwasih Pambudi, Readysna Krisna Peter Reynard Susanto Pibriana, Desi Prasetyo, Zavier Billy Pratama, Brilliant Chandra Putra Laksana, Jovansa Putri, Agnes Anastasia Raphael Lee Regian batistuta, Putra Reza Satria Rika Maulina Riki Chandra Rio Ferdynand Riska Fajriati Rivaldo Therino Elevan Rivaldo, Mario Riza Umami Rizky Kurniawan Rizvi Roshan, Muhamad Roby Julian Romi Laxi Ronaldo Putra Rusbandi rusbandi rusbandi, rusbandi Safeti Intan Pratiwi Salwa Fakhira Imletta San Gabriel Vanness Kenrick Erwi Sanila Maharani Santoso, Fian Julio Saputra Edika, Nelson Sardika, Ricky Putra Se, Abd Rosyiid Serenity Devina Suryanto Setiawan, Thomas Shela, Shela Sherdian Djunaidi Sinshevan Viswanatan Kravizt Erwi Siska Amelia Siti Fatimah Az Zahrah Sonia Sonia Sri Yulianto Joko Prasetyo Steffanie Angelica Stephanie Stephanie Stephen Setyawan Steven Tribethran Suparto, Adrian Suryasatria Trihadaru Sutarto Wijono Syahrani Nur Hakim Syalsabilla Valentisyesa Syifa Wahyuni Tad Gonsalves Tangguh Prana Welas Sukma Vannes Wijaya Vanness Bee Victoria Valensita Robert Vincent Vincent Virgiansyah, Muhammad Rifqi Wijang Widhiarso Wijang Widhiarso Wijaya, Ananda Wilcent, Wilcent William Wijaya Yennica Valentine Hagunawan Yohanes Andika Dharma Yohanes Fransisco Mardi Chandra Yohannes, Yohannes Yoko Saputra Dewa Yosefa Camilia Moniung Yunarto Yunarto, Yunarto `Adelia Anjelina