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All Journal Lensa: Kajian Kebahasaan, Kesusastraan, dan Budaya BAHASA DAN SASTRA Kinesik BAHASANTODEA Jurnal Kreatif Tadulako Online LiNGUA: Jurnal Ilmu Bahasa dan Sastra Academica Al-Ulum Kitektro KEMBARA Jurnal Gramatika JURNAL NASIONAL TEKNIK ELEKTRO IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature Al-Adyan: Jurnal Studi Lintas Agama JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Ranah: Jurnal Kajian Bahasa JITK (Jurnal Ilmu Pengetahuan dan Komputer) Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya JURNAL PENDIDIKAN TAMBUSAI Care : Jurnal Ilmiah Ilmu Kesehatan GERVASI: Jurnal Pengabdian kepada Masyarakat JENTERA: Jurnal Kajian Sastra Jurnal Humaniora : Jurnal Ilmu Sosial, Ekonomi dan Hukum MONSU'ANI TANO Jurnal Pengabdian Masyarakat Jurnal Onoma: Pendidikan, Bahasa, dan Sastra Journal of Electronics, Electromedical Engineering, and Medical Informatics Multilingual Ghancaran: Jurnal Pendidikan Bahasa dan Sastra Indonesia Jurnal Sosial Humaniora Sigli Bubungan Tinggi: Jurnal Pengabdian Masyarakat Moderasi; Jurnal Studi Ilmu Pengetahuan Sosial International Journal of Engineering, Science and Information Technology Jurnal Ilmiah Kebidanan Imelda Jurnal EduHealth Green Intelligent Systems and Applications Jurnal Gramatika: Jurnal Penelitian Pendidikan Bahasa dan Sastra Indonesia SI-MEN (AKUNTANSI & MANAJEMEN) STIES Proceeding National Conference Business, Management, and Accounting (NCBMA) Jurnal Dinamika Akuntansi dan Bisnis (JDAB) Jurnal Edukasi dan Pengabdian kepada Masyarakat (JEPKM) Jurnal Rekayasa elektrika Jurnal INFOTEL PROSIDING SEMINAR NASIONAL DAN INTERNASIONAL HIMPUNAN SARJANA-KESUSASTRAAN INDONESIA Jurnalistrendi: Jurnal Linguistik, Sastra dan Pendidikan Jurnal Polimesin Journal of Social Work and Science Education Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Akademika Baiturrahim Jambi Al-Tadris: Jurnal Pendidikan Bahasa Arab Aksara Jurnal Pengabdian Rekayasa dan Wirausaha Nawadeepa: Jurnal Pengabdian Masyarakat Indonesian Journal of English Language Teaching and Applied Linguistics Sawerigading
Yunidar
Universitas Tadulako Jalan Soekarno Hatta, Tondo, Mantikulore, Kota Palu, Sulawesi Tengah
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Smart Door Locking System for Children Using HC-SR04 and IoT Technology Melinda, Melinda; Yunidar, Yunidar; Khairia, Syaidatul; Miftahujjannah, Rizka; Sakarkar, Gopal; Basir, Nurlida
JURNAL NASIONAL TEKNIK ELEKTRO Vol 14, No 2: July 2025
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v14n2.1293.2025

Abstract

The increasing incidence of minors accessing hazardous indoor areas—such as staircases, balconies, and rooms with sharp objects—raises serious safety concerns, often due to insufficient parental supervision. This study proposes an Internet of Things (IoT)-based automatic door lock system to enhance child safety in home environments. The system integrates dual ultrasonic sensors for distance and height detection, a KY-037 sound sensor, and an ESP32-CAM for real-time video monitoring, all accessible via a web interface. A key novelty lies in the integration of multi-sensor spatial awareness with live surveillance, enabling automated control and proactive safety features. Tested on ten children aged 4 to 6 years, the system achieved a 90% success rate in locking the door when a child under 120 cm approached within 1 meter, with an average response time of approximately 2 seconds. A sound-based alarm is also triggered when noise levels exceed 120 decibels, serving as an emergency alert. However, a 10% false negative rate was observed when children were detected at distances of 1.3 to 1.5 meters, suggesting the need for further sensor calibration. Overall, the system demonstrates strong potential as a scalable and cost-effective smart home safety solution, combining automation, real-time monitoring, and child-specific access control. Future work should focus on improving detection accuracy and extending functionality for multi-object scenarios.
Automated Z-Score Based Nutritional Status Classification for Children Under Two Using Smart Sensor System Yunidar, Yunidar; Melinda, Melinda; Ridara, Rina; Basir, Nurlida
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 4 (2025): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i4.111

Abstract

The classification of nutritional status in children under two years old is crucial for monitoring growth and early detection of nutritional problems. However, in many healthcare facilities, this classification is still performed manually, requiring relatively long processing times and being prone to human error in both measurement and data recording. The problem addressed in this study is the inefficiency and potential inaccuracy of manual nutritional status classification in toddlers. This research aims to develop an automatic and digital device capable of measuring body length and weight and classifying nutritional status in children under two years old efficiently, accurately, and in real time. The device utilizes electronic sensors integrated with a microcontroller to streamline the process and reduce measurement error. The main contribution of this study is the design and realization of a portable automation device that integrates an HC-SR04 ultrasonic sensor for measuring body length and a 50 kg full-bridge load cell sensor for measuring body weight, both controlled by an ATmega328P microcontroller. The device processes the data measurement digitally, displays the results on a 20 × 4 LCD, and provides a printed copy via a thermal printer, enhancing the data recording efficiency. The method involves the design of hardware circuits, sensor calibration, software programming using the C language in the Arduino IDE, and performance testing of the device by comparing its results to standard measuring instruments. The device’s performance is evaluated based on measurement error percentage and precision level. The results demonstrate that the device achieved an error percentage of 1.26% for body length measurement and 0.98% for body weight measurement. The overall system error is recorded at 0.5%, with a precision level ranging from ±0.08 to ±0.4.
H20 and H20 with NaOH-Based Multispectral Classification Using Image Segmentation and Ensemble Learning EfficientNetV2, Resnet50, MobileNetV3 Melinda, Melinda; Yunidar, Yunidar; Zulhelmi, Zulhelmi; Suyanda, Arya; Qadri Zakaria, Lailatul; Wong, W.K
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 4 (2025): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i4.1016

Abstract

High Multispectral imaging has become a promising approach in liquid classification, particularly in distinguishing visually similar but subtly spectrally distinct solutions, such as pure water (H₂O) and water mixed with sodium hydroxide (H₂O with NaOH). This study proposed a classification system based on image segmentation and deep learning, utilizing three leading Convolutional Neural Network (CNN) architectures: ResNet 50, EfficientNetV2, and MobileNetV3. Before classification, each multispectral image was processed through color segmentation in HSV space to highlight the dominant spectral, especially in the hue range of 110 170. The model was trained using a data augmentation scheme and optimized with the Adam algorithm, a batch size of 32, and a sigmoid activation function. The dataset consists of 807 images, including 295 H₂O images and 512 H₂O with NaOH images, which were divided into training (64%), validation (16%), and testing (20%) data. Experimental results show that ResNet50 achieves the highest performance, with an accuracy of 93.83% and an F1 score of 93.67%, particularly in identifying alkaline pollution. EfficientNetV2 achieved the lowest loss (0.2001) and exhibited balanced performance across classes, while MobileNetV3, despite being a lightweight model, remained competitive with a recall of 0.97 in the H₂O with NaOH class. Further evaluation with Grad CAM reveals that all models focus on the most critical spectral areas of the segmentation results. These findings support the effectiveness of combining color-based segmentation and CNN in the spectral classification of liquids. This research is expected to serve as a stepping stone in the development of an efficient and accurate automatic liquid classification system for both laboratory and industrial applications.
Mobile Application Development for Facial Classification of Autistic Children Based on MobileNet-V3 Ramadhan, Irsyan; Melinda, Melinda; Yunidar, Yunidar; Acula, Donata D; Miftahujjannah, Rizka; Rusdiana, Siti; Zainal, Zulfan
JURNAL INFOTEL Vol 17 No 3 (2025): August
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i3.1363

Abstract

Early detection of autism spectrum disorder (ASD) is crucial to support timely interventions that can improve children’s cognitive and social development. However, conventional approaches still rely on subjective observations and parental reports. This study proposes the development of a Flutter-based mobile application for face classification of autistic and non-autistic children using the MobileNetV3-Small architecture. The dataset contains 600 original facial images of children aged 4 to 14 years (300 autistic and 300 non-autistic), which were expanded to 1,860 images through augmentation techniques such as Gaussian noise addition, flipping, and contrast adjustment. The model was trained using transfer learning and optimized with the SGD optimizer and sigmoid activation function. During training, the model achieved a training accuracy of 95.27% and a validation accuracy of 97.92%, indicating effective learning with minimal overfitting. Evaluation on the test data showed perfect performance, with accuracy, precision, recall, and F1-score all reaching 100%. The model was then converted to TensorFlow Lite format to allow on-device inference on mobile platforms. The app enables users to upload photos via camera or gallery and instantly receive classification results, which are also saved to Firebase for history tracking. Testing showed a fast response time (1–2 seconds) and a smooth, user-friendly experience. These results highlight the potential of the system as a lightweight, efficient, and accessible facial image-based ASD screening tool, particularly in regions with limited access to specialized healthcare. Future work should include validation using larger and more diverse datasets across different demographics to ensure model robustness, fairness, and generalizability in real-world environments.
Performance Analysis of H2O and H2O with HCl Material Image Classification Using Inception V3, VGG19, DenseNet201, and Otsu Segmentation Yunidar, Yunidar; Melinda, Melinda; Putri, Mauliza; Irhamsyah, Muhammad; Basir, Nurlida; Khairah, Alfita
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1253

Abstract

Challenges in classifying signals with fluctuations remain a focus in the field of image and signal processing. Deep learning technology, especially CNN (Convolutional Neural Network), has proven effective for complex visual classification; however, its performance can still be improved, particularly for signal nonlinearity distributions that are not evenly distributed. This study develops a system for classifying signals that exhibit high fluctuations using a merged Otsu segmentation and deep learning ensemble approach with InceptionV3, VGG19, and DenseNet201 models. The methodology employed is a quantitative study based on a deep learning ensemble. H?O and H?O with HCL signal datasets were processed using Otsu segmentation and then extracted using three CNN architectures, which were then combined with the methods of soft voting and stacking. Evaluation is conducted through the analysis of accuracy, precision, recall, loss, and a confusion matrix. DenseNet201 records the highest accuracy of 95%, precision of 0.90, recall of 0.86, and f1-score of 0.95. InceptionV3 achieves equivalent accuracy (95%) but with a recall of 0.83. VGG19 noted an accuracy of 91%, a precision of 0.82, and a recall of 0.78. The ensemble results show improvement in stability classification, especially in class H?O segmentation. However, the classification class HCL segmentation still shows more mistakes. The integration of Otsu segmentation and deep learning ensemble models has been proven effective in increasing the accuracy of classifying signal fluctuations. Segmentation helps highlight the importance of spatial features, while ensemble enhances model generalization. Research furthermore recommended exploring method segmentation and adaptive data augmentation to handle more complex and unbalanced distributions.
Penerapan Sistem Identifikasi Ekspresi Wajah Anak Penyandang Autisme Berbasiskan Citra Termal pada Sekolah Berkebutuhan Khusus di Banda Aceh Melinda, Melinda; Yunidar, Yunidar; Irhamsyah, Muhammad; Mina Rizky, Muharratul; Leo, Hendrik; Fahmi, Fahmi; Dewi, Cut; Away, Yuwaldi; Misbahuddin, Misbahuddin
Jurnal Pengabdian Rekayasa dan Wirausaha Vol 2, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jprw.v2i1.45635

Abstract

This community service activity aims to apply technology to detect facial expressions of children with autism through thermal images. The activity was carried out at My Hope Special Need Center, Banda Aceh, an educational center for orphans and children with special needs. By utilizing a combination of psychological and technological approaches, data collection is carried out in the form of thermal images of the faces of children with and without autism. The data obtained was analyzed using the Convolutional Neural Network (CNN) approach to develop an automatic facial expression detection method. The results of this activity show the potential use of facial recognition technology in supporting education and therapy for children with special needs.
Implementasi Sistem Informasi Pengelolaan Aset Desa Berbasis Web pada Desa Tingkeum, Kabupaten Aceh Besar Yunidar, Yunidar; Irhamsyah, Muhammad; Amalia, Amalia; Akbar, Muhazir; Rafiqi, Ashaf
Jurnal Pengabdian Rekayasa dan Wirausaha Vol 1, No 2 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jprw.v1i2.42914

Abstract

Desa Tingkeum, Kabupaten Aceh Besar, menghadapi tantangan dalam pengelolaan aset desa yang masih dilakukan secara manual, menyebabkan kesulitan dalam pelacakan dan pengelolaan aset secara efisien. Untuk mengatasi masalah ini, dikembangkan Sistem Informasi Pengelolaan Aset Desa Berbasis Web menggunakan platform SIMAssets yang dirancang dengan framework CodeIgniter dan basis data MySQL. Sistem ini memungkinkan pencatatan aset secara terpusat, otomatisasi kodefikasi aset, dan pelabelan aset dengan kode unik untuk memudahkan pelacakan. Implementasi sistem dilakukan dengan pelatihan kepada perangkat desa, termasuk Keuchik dan pengelola aset. Hasil pengujian menunjukkan bahwa sistem ini berhasil meningkatkan efisiensi pengelolaan aset, memudahkan pembuatan laporan, dan mempercepat proses inventarisasi. Pengguna melaporkan bahwa antarmuka sistem user-friendly dan fitur kodefikasi sangat bermanfaat dalam pengelolaan aset secara berkelanjutan.
Pemanfaatan Alat Ukur Status Gizi Otomatis Berbasis Mikrokontroler di Posyandu Meulati Gampong Blang Krueng Kecamatan Baitussalam, Aceh Besar Yunidar, Yunidar; Arnia, Fitri; Melinda, Melinda; Away, Yuwaldi; Fathurrahman, Fathurrahman
Jurnal Pengabdian Rekayasa dan Wirausaha Vol 1, No 1 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jprw.v1i1.36528

Abstract

Posyandu merupakan salah satu program pemerintah Indonesia sebagai fasilitas layanan kesehatan masyarakat yang dikelola oleh masyarakat. Posyandu Balita dilaksanakan secara rutin untuk memantau perkembangan pertumbuhan pada balita dengan mengukur tinggi badan, berat badan dan lingkar kepala. Selama ini alat ukur yang digunakan oleh petugas kesehatan di posyandu merupakan alat ukur yang konvensional, dan penentuan status gizi anak masih dilakukan secara manual oleh petugas posyandu yang telah mahir mengkonversi nilai ukur yang diperoleh kedalam rumus skor-z. Hal ini tentu memakan waktu dan kurang efektif sehingga dari hasil penelitian mahasiswa prodi Teknik Elektro telah berhasil merancang alat ukur status gizi otomatis berbasis mikrokontroler dan telah diuji nilai presisi dan keakuratannya. Melalui program pengabdian kepada masyarakat kami akan mensosialisasikan alat ukur otomatis ini pada posyandu Meulati Gampong Blang Krueng, Kecamatan Baitussalam Kabupaten Aceh Besar. Tujuan dari kegiatan ini untuk meningkatkan mutu pelayanan posyandu sehingga dapat berjalan lebih efektif den efisien. Alat ukur ini terdiri dari modul status gizi berdasarkan nilai skor-z dilengakapi dengan LCD sebagai tampilan keluaran dan sensor ultrasonik yang berfungsi sebagai pengukur tinggi badan dan sensor load cell untuk mengukur berat badan. Hasil yang diperoleh dari kegiatan melalui survey kepuasan yang dibagikan ternyata semua orang tua dan wali balita setuju kegiatan pengabdian yang telah dilakukan sangat bermanfaat terutama bagi Masyarakat Blang Krueng.
Nilai Sosial dalam Syair Karambangan Suku Pamona Ciptaan Nardi Banggai Yunidar, Yunidar; Khairunnisa Bakari
Jurnal Onoma: Pendidikan, Bahasa, dan Sastra Vol. 10 No. 4 (2024)
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/onoma.v10i4.4466

Abstract

Suku Pamona adalah suku yang memiliki berbagai macam budaya dan kesenian yang diwariskan secara turun-temurun oleh leluhur mereka. Salah satu kesenian yang masih bisa kita dapatkan hingga saat ini adalah syair karambangan yang di dalamnya memuat nilai-nilai kehidupan. Fokus permasalahan dalam penelitian ini yaitu: bagaimanakah nilai sosial yang terdapat dalam syair karambangan Suku Pamona ciptaan Nardi Banggai. Tujuan pada penelitian ini adalah mendeskripsikan nilai sosial yang terdapat dalam syair karambangan suku pamona ciptaan Nardi Banggai. Penelitian ini termasuk jenis penelitian kualitatif. Data penelitian ini berupa syair karambangan yang diperoleh melalui narasumber langsung. Penelitian ini dilaksanakan di Pamona Selatan, Kabupaten Poso. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah observasi, wawancara, dan studi dokumentasi. Hasil penelitian ini metemukan bahwa syair karambangan Suku Pamona memiliki nilai-nilai sosial seperti: Nilai kasih sayang, Nilai tanggung jawab, dan Nilai keserasian hidup. Nilai kasih sayang terdiri atas Nilai pengabdian, Nilai menolong, Nilai kesetiaan, dan Nilai kepedulian. Nilai tanggung jawab terdiri atas nilai rasa memiliki, nilai disiplin, dan nilai empati. Nilai keserasian hidup terdiri atas nilai keadilan, nilai toleransi, nilai kerja sama, dan nilai demokrasi . Nilai-nilai sosial tersebut dapat kita lihat pada Suku Pamona dalam menjalankan kehidupan sehari-hari.
An-Naẓariyyah Al-Ma’rifiyyah Wa Istikhdāmuhā Fī Ta’līmi Al-Lugah Muna, Lia Aulial; Ningrum, Yunidar Ayu; Pertiwi, Rizqina Wahyu Laras
Al-Tadris: Jurnal Pendidikan Bahasa Arab Vol 8 No 2 (2020): Al-Tadris: Jurnal Pendidikan Bahasa Arab
Publisher : Faculty of Education and Teachers Training of UIN Sayyid Ali Rahmatullah Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21274/tadris.2020.8.2.222-236

Abstract

Cognitive theory is the main stream that makes learning and teaching closer to the realities of human learning, because cognitive theory takes into account the characteristics of learners and the factors that influence learning and the process. Cognitive theory aims to answer the basics that help students prepare and processing information so that this information is relevant which means for them become independent in their learning. This cognitive theory is based on attention to internal cognitive process, namely: attention, perception, acceptance, processing, and information processing. And the applicaton of this cognitive theory in language learning is possible in learning material, learning methods, learning media, teaching methods and so on. In this article the writer shows the application of this cognitive theory in the design of subject in speech skill.
Co-Authors . Roslidar Abdul Kamaruddin Acula, Donata D Acula, Donata D. Ade Nurul Izatti G. Yotolembah Akbar Akbar Akbar, Muhazir Albahri, Albahri Alfariz, Muhammad Fauzan Ali Karim Ali Karim Ali Karim Amalia Amalia Aman Aman Amrie Firmansyah Andi Safutra Suraya Anizar, Lis Arini Nurazizah Arum Pujining Tyas Arum Pujiningtyas Asniar Asniar Asrianti, Asrianti Azhari, Rizki Aziz, Zulfadli Abdul Azra, Ery Bashir, Nurlida Basir, Nurlida Christi L., Rita Cindy Afitasari Cut Dewi, Cut D Acula, Donata Darmawan Darmawan Daud, Bukhari Dian Safitri Dwi Yunita Efendi Elfalini Warnelis Elizar Elizar, Elizar Fahmi Fahmi Farhan Fathur Rahman, Imam Fathurrahman Fathurrahman Fauzan, Arfan Fauziah Gusvita Syarah Femmy Jacoba Ferdi Nazirun Sijabat, Ferdi Nazirun Ferdinand, Frans Fitri Arnia Gazali Lembah Ghimri, Agung Hilm Golar Golar Gopal Sakarkar Gusti Alit Saputra Gusti Alit Suputra Gusti Ketut Alit Suputra Harisa, Sitti Hasan, Hafidh Hasan, Vania Pratama Hasriani Muis Heltha, Fahri Herlina Dimiati, Herlina Hidayat Hidayat I Gusti Ketut Alit Saputra I Ketut Agung Enriko I Made Sukanata Ida Nuraeni Indarwati , Retno Indra Indra Irdawati Irdawati Islamy, Fajrul Jayanti Puspita Dewi Joko Pitoyo Jumeil, T Muhammad Juniati Juniati Karlisa Priandana Khairah, Alfita Khairia, Syaidatul Khairunnisa Bakari Khairunnisa Bakari Laguliga, Syapril A. Lailatul Qadri Zakaria Lantuba, Yanis Men Leo, Hendrik Luluk Khusnul Dwihestie M Asri B M. Asri B Malahayati, M. Masyithah, Syarifah Mauli Maulida, Zenitha Maulisa, Oktiana Melinda Melinda Miftahujjannah, Rizka Mina Rizky, Muharratul Misbahuddin Misbahuddin Moh. Tahir Moh. Tahir Mohd. Syaryadhi Mohd. Syaryadhi Muh Tahir Muhammad Irhamsyah Muhammad Muhammad Muhammad Ridwan Muna, Lia Aulial Mursidin . Muthia Aryuni Muttaqin, Ikram Nabila, Nissa Hasna Nasaruddin Nasaruddin Nazilla, Izza NFN Nursyamsi NFN TAMRIN Nirmayanti, Nirmayanti Nizam Salihin Nur Ahyani Nur Fadilah Nur Halifah Nur Halifah, Nur Nur'aeni, Ida Nuraedah Nurbadriani, Cut Nanda Nurbaya Nurbaya, Nurbaya Nurbismi, Nurbismi Nurlida Basir Nurrahmad, Nurrahmad Nursyamsi Nursyamsi Oktiana, Maulisa Pandaleke, Alex Y. Pertiwi, Rizqina Wahyu Laras Putri Mauliza, Putri Qadri Zakaria, Lailatul Rafiqi, Ashaf Rahmatika, Laily Raihan, Siti Ramadani, Nurhaliza Ramadhan, Irsyan Ramadhani, Hanum Aulia Ramdhana, Rizka Rhamdhani, Rhamdhani Ridara, Rina Rini Safitri Roslawa, Roslawa Sabiran, Sabiran Sadia, Fachrudin Saharudin Barasandji Sahrul Saehana Sakarkar, Gopal Salsabila, Unik Hanifah Samad, Muhammad Ahsan Santi Santi Sarmin Sarmin Sarmin Sarmin Satria Satria, Satria Setiawan, Verdy Siti Fatinah Siti Rusdiana Sitti Harisah Sri Jelis Suci Rahayu Suharja, Anggi Auliyani Sukma, Sukma Suyanda, Arya Syahyadi, Rizal Syakir, Fakhrus Syamsuddin Syamsuddin Tamrin Tamrin Tamrin Tamrin Tanjung, Wilda Nurafdila Tiara Artamefia Ulfah Ulinsa, Ulinsa Ulinsa, Ulinsa Ulul Azmi Vilzati, Vilzati Wachidi, Achmad Wahyuni, Silvya Dwi Wardana, Surya Wong, W.K Wong, W.K. Yazid Yaskur Yudha Nurdin Yusni, Y Yuwaldi Away Zainab Zainal, Zulfan Zulfikar Taqiuddin Zulhelmi, Zulhelmi Zulianto, Sugit