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All Journal Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Syntax Jurnal Informatika Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Informatika dan Teknik Elektro Terapan Jurnal Inspiration INTEGER: Journal of Information Technology JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal RESISTOR (Rekayasa Sistem Komputer) Jurnal Keperawatan Komprehensif (Comprehensive Nursing Journal) Jurnal Penelitian Informatika : Jurnal Informatika, Manajemen dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal MEBIS (Manajemen dan Bisnis) JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurnal Abdi Insani Jifosi Nusantara Science and Technology Proceedings IKONIK : Jurnal Seni dan Desain Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Ilmiah Teknologi Informasi dan Robotika Jurnal Ilmiah Wahana Pendidikan Jurnal Manajemen Informatika Jayakarta KARYA: Jurnal Pengabdian Kepada Masyarakat Unram Journal of Community Service (UJCS) International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Pengabdian Multidisiplin Jurnal Pengabdian Pada Masyarakat Indonesia (JPPMI) NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Indonesia (JPMI) Safari : Jurnal Pengabdian Masyarakat Indonesia JUSIFOR : Jurnal Sistem Informasi dan Informatika INCOME: Indonesian Journal of Community Service and Engagement Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia Jurnal Nusantara Berbakti JEECS (Journal of Electrical Engineering and Computer Sciences) JURNAL PENGABDIAN MASYARAKAT AKADEMISI Jurnal Penelitian Sistem Informasi Jurnal Kabar Masyarakat Jurnal Informasi Pengabdian Masyarakat Sammajiva: Jurnal Penelitian Bisnis dan Manajemen Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Pelayanan Hubungan Masyarakat Nusantara Journal of Computers and its Applications Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Kegiatan Positif : Jurnal Hasil Karya Pengabdian Masyarakat Abdimas Terapan: Jurnal Pengabdian Kepada Masyarakat Terapan JOTTER Jurnal Riset Sistem dan Teknologi Informasi Aspirasi : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia GEMBIRA (Pengabdian Kepada Masyarakat) Harmoni Sosial : Jurnal Pengabdian Dan Solidaritas Masyarakat Jurnal Pengabdian Masyarakat Indonesia (JPMI) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Manfish: Jurnal Ilmiah Perikanan dan Peternakan Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Jurnal Teknokes
Maulana, Hendra
UPN Veteran Jawa Timur
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Traffic Sign Detection Using Region And Corner Feature Extraction Method Hendra Maulana; Yudha Kartika, Dhian Satria; Riski, Agung Mustika; Nurlaili, Afina Lina
IJCONSIST JOURNALS Vol 3 No 1 (2021): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3139.835 KB) | DOI: 10.33005/ijconsist.v3i1.54

Abstract

Traffic signs are an important feature in providing safety information for drivers about road conditions. Recognition of traffic signs can reduce the burden on drivers remembering signs and improve safety. One solution that can reduce these violations is by building a system that can recognize traffic signs as reminders to motorists. The process applied to traffic sign detection is image processing. Image processing is an image processing and analysis process that involves a lot of visual perception. Traffic signs can be detected and recognized visually by using a camera as a medium for retrieving information from a traffic sign. The layout of different traffic signs can affect the identification process. Several studies related to the detection and recognition of traffic signs have been carried out before, one of the problems that arises is the difficulty in knowing the kinds of traffic signs. This study proposes a combination of region and corner point feature extraction methods. Based on the test results obtained an accuracy value of 76.2%, a precision of 67.3 and a recall value of 78.6.
Digital Image Segmentation Resulting from X-Rays of Covid Patients using K-Means and Extraction Features Method Dhian Satria Yudha Kartika; Anita Wulansari; Hendra Maulana; Eristya Maya Safitri; Faisal Muttaqin
IJCONSIST JOURNALS Vol 3 No 1 (2021): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (970.953 KB) | DOI: 10.33005/ijconsist.v3i1.55

Abstract

The COVID-19 pandemic has significant impact on people's lives such as economic, social, psychological and health conditions. The health sector, which is spearheading the handling of the outbreak, has conducted a lot of research and trials related to COVID-19. Coughing is a common symptoms among humans affected by COVID-19 in earlier stage. The first step when a patient shows symptoms of COVID-19 was to conduct a chest x-ray imaging. The chest x-rayss can be used as a digital image dataset for analysing the spread of the virus that enters the lungs or respiratory tract. In this study, 864 x-rays were used as datasets. The images were still raw, taken directly from Covid-19 patients, so there were still a lot of noise. The process to remove unnecessary images would be carried out in the pre-processing stage. The images used as datasets were not mixed with the background which can reduce the value at the next stage. All datasets were made to have a uniform size and pixels to obtain a standard quality and size in order to support the next stage, namely segmentation. The segmentation stage of the x-ray datasets of Covid-19 patients was carried out using the k-means method and feature extraction. The Confusion Matrix method used as testing process. The accuracy value was 78.5%. The results of this testing process were 78.5% of precision value, 78% of recall and 79% for f-measure
Performance of Contrast Adjustment Techniques on The Face Recognition Method with Test Data Under Varying Lighting Conditions Nugroho, Budi; Maulana, Hendra; Yuniarti, Anny
IJCONSIST JOURNALS Vol 6 No 2 (2025): March
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v6i2.130

Abstract

In the face recognition process influenced by lighting, the application of the image enhancement process at the preprocessing stage plays an important role in normalizing image contrast so that the quality of the input image becomes better. This step is expected to improve face recognition performance. In this study, we implement a lighting-influenced face recognition method, namely Robust Regression, and test several image enhancement techniques in the preprocessing phase to determine their effects on face recognition performance under different image lighting conditions, including Contrast-limited Adaptive Histogram Equalization (CLAHE), Histogram Equalization (Histeq), and Image Intensity Adjustment (Imadjust). HE uses a global technique that adjusts the overall intensity of the image. CLAHE uses a local technique that adjusts the intensity of pixels based on their surrounding areas. Meanwhile, the Imadjust function adjusts the intensity of image pixels based on the specified minimum and maximum values. The experiment is conducted using the AR Face Database which contains images affected by lighting factors. Lighting conditions include several categories, namely low, medium, high, and very high (extreme) lighting conditions. The experimental scenario is carried out by comparing the results of face recognition using several preprocessing techniques on each test data. The experimental results show that image enhancement techniques improve the performance of face recognition. The face recognition approach that adds the CLAHE technique to the preprocessing shows the highest performance of 95.87%. Meanwhile, the face recognition approach that adds the Imadjust technique to the preprocessing shows the lowest performance of 84.38%.
IDENTIFIKASI PENYAKIT DAUN PADI DENGAN METODE TRANSFER LEARNING MOBILENET - SUPPORT VECTOR MACHINE Lizard Sambawo Dimara, Denis; Rahmat, Basuki; Maulana, Hendra
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.14245

Abstract

Padi adalah komoditas utama dalam sektor pertanian Indonesia yang sangat rentan terhadap penyakit seperti brown spot, bacterial blight, blast, dan tungro, yang dapat menurunkan hasil panen secara signifikan. Proses identifikasi penyakit secara manual oleh petani dinilai kurang efisien dan sering kali menghasilkan kesalahan. Penelitian ini bertujuan untuk mengembangkan model klasifikasi penyakit pada daun padi dengan menggunakan teknologi transfer learning, yang menggabungkan MobileNetV3-Small dan Support Vector Machine (SVM). Metode yang diterapkan mencakup pemrosesan dataset citra daun padi yang meliputi empat jenis penyakit, serta penggunaan teknik augmentasi data untuk meningkatkan keragaman dan kualitas data pelatihan. Hasil evaluasi menunjukkan bahwa kombinasi MobileNetV3-Small dan SVM memberikan akurasi tertinggi yaitu 99,66%, yang lebih unggul dibandingkan model MobileNetV3-Small 99,24% dan SVM 95,02% secara terpisah. Berdasarkan analisis confusion matrix, model ini terbukti sangat akurat dalam mengklasifikasikan penyakit meskipun ada beberapa kesalahan pada kelas-kelas dengan kesamaan visual yang tinggi
Klasifikasi Golongan Kendaraan Tol menggunakan CNN Tensorflow Rozy, Achmad; Abdurrahman Al Hakim; Chiristian K; Farrel Tiuraka Vierino; Maulana, Hendra
Jurnal Ilmiah Teknologi Informasi dan Robotika Vol. 7 No. 1 (2025): Jurnal Ilmiah Teknologi Informasi dan Robotika
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jifti.v7i1.151

Abstract

Pengelolaan lalu lintas di jalan tol memerlukan strategi yang efektif dalam mengidentifikasi jenis kendaraan untuk meningkatkan keamanan dan efisiensi transportasi. Artikel ini membahas implementasi Convolutional Neural Network (CNN) menggunakan TensorFlow untuk klasifikasi kendaraan di jalan tol. CNN telah terbukti efektif dalam mengenali pola visual kompleks, memungkinkan identifikasi kendaraan secara akurat tanpa perlu ekstraksi fitur manual. Dengan memanfaatkan arsitektur deep learning, CNN dapat mempelajari representasi fitur dari data citra dengan tingkat akurasi yang tinggi. Penggunaan TensorFlow sebagai framework deep learning memberikan keunggulan dalam pengembangan model dengan performa tinggi. Implementasi CNN dengan TensorFlow meningkatkan efisiensi dan akurasi klasifikasi kendaraan, membantu dalam mengelola lalu lintas dengan lebih efektif. Solusi ini meminimalkan kesalahan manusia, mempercepat proses klasifikasi, dan meningkatkan pengalaman pengguna jalan tol. Integrasi TensorFlow dalam sistem pengelolaan lalu lintas dapat menciptakan solusi yang lebih efektif dalam mengatasi tantangan di jalan tol. Model klasifikasi kendaraan ini mencapai 90.6% akurasi pada data uji. Sehingga dapat disimpulkan bahwa metode ini dapat secara efektif meningkatkan akurasi dan efisiensi dalam klasifikasi jenis kendaraan di jalan tol
Pendampingan Pembuatan Nomor Induk Berusaha (NIB) UMKM di Desa Rejoso, Kecamatan Rejoso, Kabupaten Nganjuk, Provinsi Jawa Timur Hendra Maulana; Chulaisy Meidianto; Naufal Hilmy Fauzan; Ismiatul Ilmiah; Fatimah Azzahra; Adisty Nadyra Kristianti
SAFARI :Jurnal Pengabdian Masyarakat Indonesia Vol. 3 No. 3 (2023): Juli : Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/safari.v3i3.676

Abstract

Business legality is an important aspect that needs to be done by every business person, especially Micro, Small, and Medium Enterprises (MSMEs). From the data collected by the group of 64 thematic KKN UPN “Veteran” East Java 2023, they found that UMKM actors in Rejoso Village, Rejoso District, Nganjuk Regency, most of UMKM do not have business legality. This paper will present the results of community service activities that have been carried out related to assistance in making business Identification Numbers (NIB). This service aims to share insights and practice making NIB so that MSME actors can have and benefit from the legality of the business.
ANALISIS EFEKTIFITAS ALGORITMA MOBILENETV3-LARGE DAN EFFICIENTNET-B0 UNTUK KLASIFIKASI CITRA PENYAKIT DAUN JERUK Dianto, Alfian Rachmad; Fetty Tri Anggraeny; Hendra Maulana
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6956

Abstract

Meningkatnya konsumsi jeruk (Citrus spp.) di masyarakat menjadikan budidaya jeruk sebagai komoditas penting, namun rentan terhadap serangan penyakit yang dapat menyebabkan gagal panen. Penelitian ini bertujuan untuk mengevaluasi kinerja dan efisiensi algoritma MobileNet V3-Large dan Efficient Net-B0 dalam mengklasifikasi citra penyakit daun jeruk, baik dari data mandiri maupun data terbuka seperti Kaggle. Metode yang digunakan adalah pendekatan kuantitatif eksperimental dengan pengujian variasi hyperparameter, optimizer, dan skenario rasio data pelatihan, validasi, serta pengujian. Evaluasi model dilakukan menggunakan metrik Accuracy, Precision, Recall, dan F1-score. Hasil penelitian menunjukkan bahwa kedua arsitektur mampu melakukan klasifikasi citra secara efektif, dengan hasil terbaik diperoleh pada konfigurasi rasio data 70-20-10, optimizer RMSprop, dan learning rate 0,1 menggunakan early stopping. Konfigurasi alternatif yang juga direkomendasikan adalah rasio 60-30-10 dengan optimizer Adam dan epoch 15 atau 30. Temuan ini menunjukkan bahwa MobileNet V3-Large dan EfficientNet-B0 dapat diandalkan untuk sistem klasifikasi penyakit daun jeruk berbasis website atau aplikasi mobile, terutama pada kondisi data terbatas dan distribusi kelas yang tidak seimbang
Sistem Pendukung Keputusan untuk Pemilihan Sepeda Motor bagi Mahasiswa dengan Menggunakan Metode Simple Additive Weighting (SAW) Anggit Suryan Rohyan; Satria Fajar Dwi Kurniawan; Hendra Maulana; Nor Anisa
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.2067

Abstract

Researchers conducted a selection process for motorcycles that align with the needs and financial conditions of students, as this process is often quite complex. This complexity arises from the wide range of options and the numerous criteria that must be considered, such as price, fuel efficiency, engine capacity, comfort level, and design aesthetics. The objective of this study is to design a Decision Support System (DSS) by implementing the Simple Additive Weighting (SAW) method to assist students in selecting the motorcycle that best fits their needs. The SAW method was chosen due to its effectiveness in handling multi-criteria decision-making problems by assigning weights to each criterion and calculating the preference value for each available alternative. The system was developed using a quantitative approach, with data collected through surveys and documentation of motorcycle specifications. The test results indicated that the system was capable of providing accurate and relevant recommendations based on user needs. Therefore, this system has the potential to serve as an effective tool in supporting students' motorcycle selection decisions.
Implementation of IoT in Shallot Farming in Nganjuk to Increase Production Atasa, Dita; Agussalim; Anggraeny, Fetty Tri; Maulana, Hendra; Alfiani, Fina
Unram Journal of Community Service Vol. 6 No. 3 (2025): September
Publisher : Pascasarjana Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ujcs.v6i3.1185

Abstract

The El Nino phenomenon in 2023 caused more than 50% of Shallot farmers in Pandean Village, Nganjuk Regency, to experience crop failure due to limited water and a weak data-based management system. The target of this community service is 30 shallot farmers who are members of the P4S Santosa Jaya group. This community service activity aims to increase farmers' understanding of the application of the Internet of Things (IoT) in shallot cultivation through socialization, training, and farmer assistance. The implementation method includes preparation, interactive socialization with pre-tests and post-tests, as well as evaluation of farmers' perceptions. The results of the activity show a significant increase in knowledge, where before the activity 50% of participants were in the less knowledgeable category, and after the activity, it increased to 50% in the knowledgeable category and 26.7% in the very knowledgeable category. In addition, farmers' perceptions of IoT are largely positive (50%), although there are still neutral (30%) and skeptical (20%) responses regarding investment costs, internet access, and technical skills. These findings demonstrate that educational assistance can enhance agricultural digital literacy while serving as a first step toward data-driven farming adoption.
Digital Innovation for Monitoring the Mental Health of Students at UPN "Veteran" East Java Using the PHQ-9 Instrument maulana, Hendra; Citra, Delia; Sari, Lintang; Safana, Tsabita; Aprilia, Erica
Jurnal Teknokes Vol. 18 No. 2 (2025): June
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Mental health issues, especially depression, are increasingly prevalent among university students in Indonesia, primarily due to academic, social, and emotional pressures during the transition from adolescence to adulthood. This study developed and evaluated UWAYS, a mobile application designed to assist the early detection of depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9). The app features include an interactive PHQ-9 self-assessment,  historical tracking of assessment results, and automatic initial recommendations based on score classifications. Involving 100 active students of UPN “Veteran” East Java, the results showed that most participants fell  within the mild to moderate depression categories, with sleep disturbance and low self-confidence as the most common symptoms. The System Usability Scale (SUS) assessment yielded an average score of 77.3, indicating good usability and positive user acceptance. These findings confirm that UWAYS provides an accessible, practical, and user-friendly tool for independent mental health screening among students. This application serves as an initial step to support mental health management in the campus environment and offers potential for further integration with university counseling services. The study also highlights that the lack of early detection mechanisms on campus remains a gap that can be addressed through digital innovation like UWAYS, which combines scientific accuracy, data confidentiality, and ease of use to encourage proactive mental health awareness among students.
Co-Authors A. Malik Haramain Abd. Ghofar Abd. Ghofar Abdurrahman Al Hakim Abyansyah Hayyu Sarwono Abyansyah Hayyu Sarwono Achmad Dhany Adam Mu'arif Achmad Syaifulloh Adelia Agatha Futti Adham Roy Bhafiel Adisty Nadyra Kristianti Adithya Daffa Rabbani Afandy Yosediputra Afitra Azzahra Agung Mustika Rizki Agung Mustika Rizki Agus Zainal Arifin Agussalim Agussalim, Agussalim Ahmad Haikal Nuqqy Zahhar Ajeng Arum Isfania Aji Bimantoro Aji Prayoga Akbar, Fawwaz Ali Alfiani, Fina Alif Syahda Adji Masyuri Alifiah Wulansari Mustofa Alit, Ronggo Alvina Widya Oktaviani Alvina Widya Oktaviani Amanda Amelia S Ananda Asa Firstha Affandi Anandah Amirah Andhika Yudha Fachriza Andi M. A. K. Parewe Andini Rahmawati Andreas Nugroho Sihananto Angga, Angga Rahmad Purnama Anggit Suryan Rohyan Anggraini Puspita Sari Ani Dijah Rahajoe Aniisah Eka Rahmawati Anita Wulansari Annis Oktaviani Anny Yuniarti Anugrah Prasetya, Rajawali Shatika Aprilia Verlianti Aprilia, Erica Ardela Putri Amalia Ardhelia Damayanti Wirawan Arnandhia Fatimah Azzahra Arya Dharma Syahputra Aziz, Muhammad Hilmy Azizah, Ratih Nuur Badriah, Lailatul Bagus Sutikno Putra Basuki Rahmat Masdi Siduppa Bisyrul Kafi I. A. Budi Nugroho Cahya Rafiyoga Harnan Chiristian K Chulaisy Meidianto Citra, Delia Darlis Herumurti Davina Azalia Erson Dewanti, Felicitas Deru Dewi Puji Arofah Dhian Satria Yudha Dhian Satria Yudha K. Dhian Satria Yudha Kartika Dhian Satria Yudha Kartika Dhian Satria Yudha Kartika Dian Anisa Raya Diana Aqidatun Nisa Dianto, Alfian Rachmad Dimas Arif Setyawan Dimas Arif Setyawan Dini Adni Navastara, Dini Adni Dita Atasa Diva Faridathul Ilmi Diva Rihhadatul ‘Aisy Divana Hikmala Salsabila Puteri Dr. Basuki Rahmat Dwi Rahma Putri, Septiani Dwi Yanti Margareta Dwiki Aditama Supangkat Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha, Eka Eristya Maya Safitri Ernik Ernawati Eva Yulia Puspaningrum Evan Saka Akhfan Fadhilah Labibah Nurjanah Fahmi Anugrah Danendra Fairuz Sany Faisal Muttaqin Faisal Muttaqin Fakhiroh, Luqy Aizzatul Farrel Tiuraka Vierino Fatchur Rozci Fatimah Azzahra Fatinena Candra Tribuana Fatma Endah Cahyaningrum Febrian Agung Dwi Karina Fery Almas Ariansyah Fetty Tri Anggraeny Figo Afriansyah Firya Nadhira Firza Prima Aditiawan Fitrianata, Muhammad Ikhsan Ghea Lintang Samputri Girycki Sana Aleffin Gusti Eka Yuliastuti Hafid Akmal Alamsah Hakim Bima Ardimas Alam Hakim Bima Ardimas Alam Hamida Seftilutfiana Hana Safira Hidayat Handayani, Alfia Indah Handika, I Putu Susila Hannah Emmanuella Delia Hapsari Wiji Utami Hayu Desthia Hena Elizabet Herawati, Yoshi Inne Herlin Dwi Dita Tamtamalia I Gusti Agung Socrates Adi Guna I Kadek Susila Satwika I Kadek Susila Satwika I Putu Susila Handika idhom, Mohammad Ignatius Bramantya Prasetyo Dewa Ilham Rahmatullah Ilham Rahmatullah Indra Rasendriya Pratama Intan Mitayani Intan Savitri Ciptaningtyas Iramandha Putri Pratiwi Ismiatul Ilmiah Ivan Ardiansyah J.A. Jelita Srikandi Pertiwi Jonathan Christianto Wibowo Kartini Kartini Kenneth Ephram Singarimbun KEZIA, KEZIA Khofiatul Rosdiana Windiarti Kowi Akbar Prasetya Kurnia Rafif Shanika KY Margiati, KY Laksamana Zulfikar Satria Decca Harits Latif Ahmad Fauzan Laycha Nazila Supoyo Putri Leli Lestari Lintang Sari Putri Wardhani Lizard Sambawo Dimara, Denis M. Abizzar Maulana Ma'ruf, Hafidz Made Hanindia Prami Swari Mandyartha, Eka Prakarsa Mannan, Abd Margarita, Devina Mastar Asran Maulana Hassan Sechuti Maulidia Zalsa Wicahyo Putri Mega Agustina Kesumaning Pertiwi Meimy Ratnakanyaka Mercy Aulia Sugiarto Merlina Aris Michael Samudra Djaja Miftah Nur Miftakhul Jannah Moch. Rafie Pratama Mochammad Rayhan Faujan Mohamad Fikri Azam Mohamad Ilham Prasetyo Raharjo Mohammad Faisal Riftiarrasyid Moy Yustiwa Mufida Diah Lestari Muhammad Bagas Ikmal Rifki Muhammad Fabbian Rachmansyah Muhammad Imam Haramain Muhammad Muharrom Al Haromainy Muhammad Nur Muhammad Rizki Firmansyah Muttaqin, Faisal Nadya Putri Najwa Belvana Nakrowiyah, Finda Rohmatin Narendra Pasha Maulana Naufal Hilmy Fauzan Nazhmi Fadhil Neri Gareta Bintang Armevia Nidya Arum Niken Hefa Zakkiya Nina Zenitha Sekar Sari Nira Fitryani Nirwana Septania Galih Perwira Moekti Nisa', Choirun Nor Anisa Nugroho Sihananto, Andreas Nur Indah Fatmala Nur Mila Eka Zaliyanty Nur Vita Dewan Tari Nurdianto, Muhammad Akbar Nurhaliza, Risma Nurlaili, Afina Lina Nurmanida Azizah Nuha Nurul Wasiela Octaviani, Vincentia Indri Praja Firdaus Nuryananda Pratama Diko Marindo Pratama, Gede Ardi Putra, Chrystia Aji Putri, Desya Ristya Rafael Octava Brilliante Rafli Aprilian Firmansyah Rahmadewi, Cynthia Dwi Ratna Yulistiani Reygita Arintya Ayu Pramesti Reynaldi Rizky Utomo Richul Munawaroh Rima Fauziyyah Rinda Purwati Rindyi Putri Lestari Risda Rosdiana Agustin Riski, Agung Mustika Rizka Fadhillah, Irnanda Rizqy Ahsana Putri Rolando Limantara, Kristian Ronggo Alit Rozy, Achmad Safana, Tsabita Safira Kusmindasari, Anggun Safira Salma Azzahra Salsabila Firdaus Sari, Lintang Satria Fajar Dwi Kurniawan Satria Yudha Kartika , Dhian Satwika, I Kadek Susila Shabirina Laila Azka Shafa Diva Syaharani Shafira Rahmawati Sharla Putri Aisha Sheidy Yudhiasta Sijabat, Riris Oktauli BR Siti Mi’Danur Rahmah Sri Trisnaningsih Sri Utami Bina Wijayanti Sufi Miftakhoneki Sufi Miftakhoneki Sugiarto Sugiarto Sugiyanto, Edi Sulastri Sulastri Sutejo, Aris Syaifullah Jauharis Saputra, Wahyu Syarifuddin Aryasatya Nugraha Tarissa Satya Laksmi Triyana, Dimas Tsabita Safana Mustofa Utami, Hapsari Wiji Vita Via, Yisti Vivi Aprilliya Ningsih Vynka Zahira Sausan Wahyu Dwi Lestari Wicaksa Putra Pribadi, Achareeya Widyana Dini Maylinda Wiji Utami, Hapsari Wilda Cahyani Sukma Wirya Atmaja, Pratama Wisnu Wardana, Mahendra Yemima Dya Novitasari Yisti Vita Via Yisti Vita Via Yisti Vita Via Yisti Vita Via Yolanda Irfania Yudha K., Dhian Satria Yurisa Wianuari Zacky Yaser Malik Gumiwang Zumrotul Liana Putri Zumrotul Liana Putri