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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA Teknika Jurnal Teliska Proceedings of KNASTIK Elkom: Jurnal Elektronika dan Komputer PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Prosiding SNATIF Teknika: Jurnal Sains dan Teknologi Annual Research Seminar SMATIKA Jurnal Ampere Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Informatika Upgris Tech-E International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Wikrama Parahita : Jurnal Pengabdian Masyarakat VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal TIPS : Jurnal Teknologi Informasi dan Komputer Politeknik Sekayu Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal RESISTOR (Rekayasa Sistem Komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Qua Teknika Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Jurnal Informatika dan Rekayasa Elektronik bit-Tech Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) International Journal of Advances in Data and Information Systems Journal of Innovation Information Technology and Application (JINITA) Jurnal Teknik Informatika (JUTIF) Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Advance Sustainable Science, Engineering and Technology (ASSET) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bangsa Enrichment: Journal of Multidisciplinary Research and Development Prosiding Seminar Hasil Penelitian dan Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Sultan Indonesia Journal of Environment and Sustainability Education JEPEmas: Jurnal Pengabdian Masyarakat (Bidang Ekonomi) Jurnal Pengabdian Masyarakat Mentari semanTIK Smatika Jurnal : STIKI Informatika Jurnal
Ade Silvia Handayani
Politeknik Negeri Sriwijaya
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Field-Level AES-128 Encryption in Laravel-based E-Commerce for MSME Data Protection Afifah, Luthfia; Nurdin, Ali; Handayani, Ade Silvia
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37675

Abstract

The increasing digitization of micro, small, and medium enterprises (MSMEs) in e-commerce brings critical challenges in protecting customer data. Despite the widespread use of encrypted communication protocols such as HTTPS and TLS for secure data transmission, many MSMEs still fail to implement encryption at the data storage level. This means that once the data reaches the server, it is often stored in unencrypted form within the database. This study implemented AES-128 encryption at the field-level in a Laravel-based e-commerce system to protect MSME customer data. The encryption was applied to sensitive data fields and tested through black-box testing and benchmark analysis. A dataset of 10,000 records was used to compare performance between plaintext and encrypted operations. Results showed an average encryption overhead of 0.0409 seconds, indicating minimal impact on performance. The encryption-decryption process consistently returned correct outputs across all trials. This solution offers an affordable and scalable encryption model for MSMEs, enhancing customer data security without relying on external tools or infrastructure.
Perancangan Sistem Monitoring Kadar Kualitas Udara Menggunakan Particulate Matter 2,5 Berbasis Website Felisia Talitha Aprilia; Ahmad Taqwa; Ade Silvia Handayani
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 11 No 02 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i02.594

Abstract

In this study, designing a mobile web to carry out the process of monitoring air quality levels that is integrated intoa system so that it is able to detect the state of air quality in the area in Palembang. This mobile web uses devices/tools at the BMKG (Meteorolog, Climatology and Geophysics Agency) Sultan Mahmud Badaruddin II Palembang that can work in real-time with an Internet of Things based platform. This research uses the SDLC (System Development Life Cycle) web development method. The results of this study are a monitoring system designed to automatically detect the state of Particulate Matter 2,5 air quality and then provide notifications to the connected gmail, without time lapse and air quality information data recording which will automatically be displayed in real-time on the user’s smartphone and give an emergency message when it is in the threshold of unhealthy or dangerous. Air quality information can be accessed online via the mobile web anywhere and anytime.
EduKopi Sriwijaya Membangun Wisata Kopi Edukatif untuk Peningkatan Pengetahuan dan Ekonomi Masyarakat M Arief Rahman; Ade Silvia Handayani; Nabiel Arinaullah; M Lutfi Kurniawan; Ghina Maysya Ayu; Ella Rosita
Jurnal Pengabdian Masyarakat Sultan Indonesia Vol. 2 No. 1 (2025): Abdisultan
Publisher : Sultan Publsiher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/abdisultan.v2i1.363

Abstract

  Kegiatan pengabdian masyarakat EduKopi Sriwijaya tidak hanya dirancang sebagai sarana pelatihan, tetapi juga sebagai strategi pembangunan ekonomi lokal yang mengedepankan pendekatan partisipatif dan berkelanjutan. Kegiatan ini dilaksanakan di Rumah Kopi Sriwijaya, Provinsi Sumatera Selatan, yang memiliki potensi kopi unggulan dan komunitas penggiat kopi aktif. Melalui kolaborasi antara institusi pendidikan dan komunitas kopi lokal, kegiatan ini membuka ruang interaksi produktif antara akademisi, petani kopi, pelaku UMKM, dan masyarakat umum. Selain memberikan pelatihan teknis, program ini membangun pemahaman peserta terhadap pentingnya nilai tambah kopi, mulai dari branding produk, pengemasan yang menarik, hingga strategi pemasaran berbasis digital. Pendekatan wisata edukatif yang digunakan tidak hanya berfokus pada transfer ilmu, tetapi juga memberikan pengalaman menyeluruh yang menyenangkan dan inspiratif, sehingga menarik minat generasi muda untuk terlibat dalam sektor pertanian kreatif. Dampak jangka pendek yang terlihat adalah tumbuhnya semangat wirausaha berbasis kopi pada beberapa peserta, serta meningkatnya ketertarikan masyarakat terhadap pariwisata tematik. Penelitian ini menggunakan pendekatan kualitatif partisipatif, dengan teknik observasi, wawancara, dan diskusi kelompok sebagai metode pengumpulan data. Ke depan, EduKopi Sriwijaya diharapkan dapat direplikasi di daerah lain yang memiliki potensi serupa, sebagai bagian dari upaya pelestarian budaya lokal sekaligus pengembangan ekonomi berbasis komunitas.
Analysis of Frequency Spectrum in Digital Image Transmission Using Orthogonal Frequency Multiplexing Sarjana Sarjana; Ade Silvia Handayani; Devi Wahyuni
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2749

Abstract

Accurate and efficient data transmission is increasingly essential due to the growing reliance on digital communication, particularly for multimedia content such as images. Orthogonal Frequency Division Multiplexing (OFDM) provides high bandwidth efficiency and strong noise resilience by transmitting data over multiple orthogonal subcarriers. Despite its advantages, limited studies have explored how modulation schemes influence frequency-domain characteristics during image transmission under different noise conditions. This study addresses that gap by evaluating digital image transmission through OFDM using Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation. The objective is to compare spectral performance across various signal-to-noise ratio (SNR) levels. A grayscale image is converted into a binary stream, modulated using BPSK and QPSK, and processed through an OFDM system with 512 subcarriers and a 25% cyclic prefix. The signals are transmitted through an Additive White Gaussian Noise (AWGN) channel at SNR values of 0 dB, 5 dB, and 10 dB. Power Spectral Density (PSD) is measured using the Welch method with a Hamming window, 50% overlap, and 1024-point Fast Fourier Transform (FFT). The results show that increasing SNR improves spectral sharpness, reduces the noise floor, and enhances symmetry. BPSK offers better performance in noisy conditions, while QPSK is more efficient in high-SNR environments. These findings provide practical insight for optimizing modulation choices in OFDM-based image transmission systems where spectral efficiency and noise robustness must be balanced.
Multi-Step GRU Model for River Water Level Prediction with IoT Sensors Ahmad Satrio Perdana; Ade Silvia Handayani; Ciksadan Ciksadan; Carlos RS; Asriyadi Asriyadi
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2846

Abstract

The Simpang Lima PUPR Pump Station on Jalan Radial, Palembang, serves as a critical drainage point for the largest water discharge in the downstream area, making the surrounding region highly vulnerable to surface runoff and flooding, especially during short-duration high-intensity rainfall events. This study aims to develop a 24-hour ahead multi-step river water level prediction model using the Gated Recurrent Unit (GRU) algorithm, powered by real-time data from Internet of Things (IoT) sensors installed at the pump station. The collected dataset spans from June to July and includes water level, rainfall, temperature, humidity, and barometric pressure. The data was preprocessed through normalization before being used as input to the GRU model. The GRU-based prediction model demonstrated strong performance with a Mean Squared Error (MSE) of 0.394, Root Mean Squared Error (RMSE) of 0.628, coefficient of determination (R²) of 0.99, and Nash-Sutcliffe Efficiency (NSE) of 0.9853. These results indicate high predictive accuracy and model reliability. The proposed model has strong potential for integration into early warning dashboards to support flood mitigation strategies and improve the operational efficiency of pump stations in high-risk urban zones. Additionally, this research offers a data-driven framework for the Ministry of Public Works and Housing (PUPR) to design real-time, predictive flood control systems. The approach can optimize pump operations, enhance emergency response planning, and guide drainage infrastructure improvements. Furthermore, it promotes climate-resilient flood adaptation policies and serves as a model for smart technology deployment in other Indonesian cities.
Comparative Analysis Of Random Forest and Naive Bayes for Flood Classification Using Sentinel-1 SAR Clara Silvia Rotua Aritonang; Ade Silvia Handayani; Suroso Suroso; Wahyu Caesarendra; Asriyadi Asriyadi
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.2852

Abstract

This research introduces a framework for classifying flood inundation utilising Sentinel-1 Ground Range Detected (GRD) radar imagery alongside machine learning algorithms.  Radar backscatter values from pre- and post-event Sentinel-1 images were processed with SNAP and QGIS to extract spatial features and change indicators in decibel (dB) format.  The tabular dataset, comprising 500,000 samples that equally represent flooded and non-flooded areas, was utilised for model training. Two models, Random Forest and Naive Bayes, were assessed for their classification efficacy.  The Random Forest model demonstrated exceptional performance, attaining an accuracy of 99.81%, precision of 99.75%, recall of 99.67%, and an F1-score of 99.71%.  Naive Bayes achieved an accuracy of 52.63%, with precision and F1-score notably impacted by elevated false positive rates, although recall was 86.36%.  Analysis of confidence distribution indicated that Random Forest exhibited low-confidence errors at the decision boundary, whereas Naive Bayes demonstrated confident misclassifications. Analysis of computation time indicated that Naive Bayes required less than 0.1 seconds per run, whereas Random Forest completed training in under 3 minutes.  The trade-off between speed and reliability underscores the appropriateness of Random Forest for operational flood mapping applications.  This research provides a practical comparison of classification models utilising open-access radar data and establishes a dependable pipeline for pixel-level flood identification.
SYSTEM DESIGN FOR EARLY DETECTION OF DIABETES MELLITUS USING IOT-BASED NON-INVASIVE SENSORS Widya, Afni Rara; Handayani, Ade Silvia; Rakhman, Abdul
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6198

Abstract

This research aims to design a diabetes mellitus early detection tool using IoT-based non-invasive sensors. This tool uses blood pressure sensors and color sensors to detect glucose levels in urine. The data obtained from these sensors is sent to the Arduino Uno microcontroller, displayed on the LCD screen, and saved to the Firebase platform for further monitoring and analysis. The test results show that this tool is able to measure and display blood pressure data and urine glucose levels accurately and in real time so that it can be used as a practical and efficient diabetes mellitus diagnostic tool. This research makes a very important contribution to the development of IoT-based health technology, especially in facilitating early detection of diabetes non-invasively. This research aims to design a diabetes mellitus early detection tool using IoT-based non-invasive sensors. 
Strengthening Small-Scale Snakehead (Channa Striata) Aquaculture through the Implementation of the IoT-Based “Channa Sense” Monitoring System Latifah Husni Nyayu; Muslim Muslim; Rusman Ariyanto; Ade Silvia Handayani; Umul Salamah; Muhammad Ardiansyah; Rita Martini; Rusman Ariyanto; Ekawati Prihatini; Cinda Anugrah Citra
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 10 No. 1 (2026): May 2026
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v10i1.11574

Abstract

Small-scale snakehead (Channa striata) farmers commonly rely on manual and periodic water quality monitoring, which often results in delayed responses to environmental fluctuations and high fry mortality rates. This community service program aimed to strengthen technological literacy and improve hatchery management practices through the implementation of an Internet of Things (IoT)-based “Channa Sense” real-time monitoring system. The intervention adopted a structured three-phase approach consisting of pre-implementation assessment, participatory workshop and system installation, and post-implementation evaluation. The program involved 37 participants representing farmers, entrepreneurs, and community members, with baseline data collected from 30 small-scale farmers across Palembang, Indralaya, and Musi Banyuasin. Pre-intervention findings showed that 56.76% of participants were unaware of the technology and none had prior experience with digital monitoring systems. Following experiential learning activities, 64.86% of participants reported a moderate to full understanding of the system, and recognition of Channa Sense as a water quality monitoring device increased from 13.51% to 60.42%. At the partner hatchery (Kandang Om Bobby), real-time monitoring reduced fry mortality from approximately 40% to 5–10%, representing a survival improvement of 30–35%. The findings indicate that participatory and context-adapted IoT interventions can effectively bridge digital literacy gaps while generating measurable operational benefits in small-scale aquaculture. However, adoption intentions remained moderate due to cost and maintenance concerns. Continued mentoring, cost optimization, and cooperative-based implementation strategies are recommended to ensure long-term sustainability and broader community uptake
Sistem Pemilihan Rekomendasi Produk UMKM Kopi menggunakan Metode K-Nearest Neigbors M. Ardiansyah; Ahmad Taqwa; Ade Silvia Handayani
SemanTIK : Teknik Informasi Vol. 11 No. 2 (2025): SemanTIK : Teknik Informasi
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v11i2.177

Abstract

Seiring dengan meningkatnya tren konsumsi kopi di berbagai kalangan dan semakin beragamnya preferensi konsumen terhadap produk kopi, hal ini juga dipicu oleh banyaknya produk kopi bermunculan di pasaran dengan berbagai varian harga, jenis olahan, dan asal kopi yang ditawarkan oleh pelaku Usaha Mikro, Kecil, dan Menengah (UMKM). Semakin banyaknya varian produk yang beredar membuat konsumen semakin sulit menemukan produk kopi yang sesuai dengan preferensi mereka. Metode K-Nearest Neighbors (KNN) menawarkan pendekatan yang efektif untuk membantu konsumen dalam menemukan rekomendasi produk kopi. Penelitian ini mengimplementasikan metode KNN mengukur jarak kedekatan antara preferensi pengguna dan karakteristik produk menggunakan dua metrik pengukuran, yaitu Euclidean dan Manhattan. Hasil evaluasi pengujian menunjukkan bahwa metrik jarak Euclidean memberikan tingkat akurasi tertinggi sebesar 92.2%, diikuti oleh Manhattan sebesar 91.8%. Berdasarkan hasil tersebut, Euclidean merupakan pilihan optimal dalam sistem rekomendasi yang dikembangkan, terbukti mampu memberikan rekomendasi produk kopi kepada konsumen dengan tingkat akurasi mencapai 92,2%. Along with the increasing trend of coffee consumption across various demographics and the growing diversity of consumer preferences for coffee products, this is also driven by the multitude of coffee products emerging in the market with various price ranges, types of processing, and origins offered by micro, small, and medium enterprises (MSMEs). The increasing variety of products available makes it more difficult for consumers to find coffee products that match their preferences. The K-Nearest Neighbors (KNN) method offers an effective approach to help consumers find coffee product recommendations. This research implements the KNN method to measure the proximity between user preferences and product characteristics using two measurement metrics, namely Euclidean and Manhattan. The evaluation results show that the Euclidean distance metric provides the highest accuracy level of 92.2%, followed by Manhattan at 91.8%. Based on these results, Euclidean is the optimal choice in the developed recommendation system and has proven capable of providing coffee product recommendations to consumers with the best recommendation results.
IoT-Based Medical Health Monitoring System with a Web Interface Cantika Tri Inayah; Ade Silvia Handayani; Nasron Nasron
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9830

Abstract

Health technology is increasingly developing along with the development of information and communication technology, where these advances are used to improve the quality of health services, especially in remote patient monitoring through telemedicine, M-Health and Telehealth. The development of the times has also brought telemedicine to a wider realm through M-Health and Telehealth which uses digital technology and wireless communication to enable monitoring of patient conditions, besides that websites are also used for wireless monitoring and data collection of patients because they have wide accessibility. This study aims to design a website that can integrate the data of the size of health sensor devices into an Internet of Things-based platform to display body temperature, blood oxygen, and ECG data in real-time. The test results show that all website features are running well, where the website runs well depending on the network used.
Co-Authors A. Rahman AA Sudharmawan, AA Aan Sugiyanto Abdul Rakhman Abdurahman Abdurrahman Abu Hasan Aditya, M Rizky Vira Afifah, Luthfia Afiifa Aaliyah Maharani Agung, Muhammad Zakuan Ahmad Satrio Perdana Ahmad Taqwa Ahmad Taqwa Al Fatur Sayid Al-Kausar, Jefri Albertia Youlanda Alfarizal, Niksen Ali Nurdin Ali Nurdin Ali Nurdin Alquratu SeptriaPS, Annies Ambar Sehatiningsih Amperawan Amperawan Andry Meylani Angguna, Welan Mauli Anisah Fadhilah Aryanti Aryanti Aryanti Asriyadi Asriyadi Asriyadi Asriyadi Aswarisman, Novie Rahmadani Auditra Faza Amira Az-zahra, Maudhy Banu Putri Pratiwi Br Ginting, Nurul Devani Btari Puspa Yahya C. Ciksadan Cantika Tri Inayah Carlos R Sitompul Carlos RS Ciksadan Ciksadan Ciksadan Ciksadan Ciksadan, Ciksadan Cinda Anugrah Citra Clara Silvia Rotua Aritonang Dely Andini Destra Andika Destra Andika Pratama Devi Indah Pujiana Devi Wahyuni Dewi Ekha Harlasyanti Dewi, Tresna Dody Novriansyah DWI RAMADHANI Dzikrillah, Muhammad Ekawati Prihatini Ekawati Prihatini Elisa Islami Putri Ella Rosita Ella Rosita Emilia Hesti Endri, Jon Endri, Jon Enri, Jon Evelina Evelina Evelina Evelina Evelina, Evelina Faisal Damsi Farid Jatri Abiyyu Faris, Fakhri Al Farozi, Ahmad Felia, Okta Felisia Talitha Aprilia Firdaus Firdaus Ghina Maysya Ayu Hani Marta Putri Hertani Indah Lestari Hetty Meileni Hj. Lindawati Husni, Nyayu Latifah Ibnu Ziad, Ibnu Ihsan Mustaqiim Irawan Hadi Irawan Hadi Irdayanti, Yeni Irma Salamah Irsyadi Yani Iryadi Yani Iryadi Yani, Iryadi Iskandar Lutfi Jon Endri Kaila, Afifah Syifah Kinasih, Ayu Antika Sekar Latifah Husni Nyayu Leni Novianti Linda Wati Lindawati Lindawati M Arief Rahman M Arief Rahman M Lutfi Kurniawan M. A. Racka Eratama M. Ardiansyah M. Ardiansyah M. Ilham Akbar M. Sobri M.Arief Rakhman Maharani, Ullya Dwi Mardiani, Mega Marieska Lupikawaty Martinus Mujur Rose Masayu Anisah Medina Nadila Prima Putri Mega Hasanul Huda Meranda, Arganda Meutia Deli Rachmawati Mieska Despitasari Moh. Heri Kurniawan Mohammad Fadhli Msy Aulia Hasanah Muhamad Rizki Harahap Muhammad Ardiansyah Muhammad Hanif Fatin Muhammad Rafly Wijaya Muslim Muslim Nabiel Arinaullah Nabila, Puspita Aliya Nasron Nasron Nasron Nasron Nasron Nasron Nofriyanti, Duwi Novriansyah, Dody Nur Agustini Nur Hopipah Nurhajar Anugraha Nyanyu Latifah Husni Nyayu Latifah Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni Nyayu Latifah Husni, Nyayu Latifah Oktariani, Clara Permata Sari, Mira Permatasari, Rosmalinda Plowerita, Sanyyah Pratama, Destra Andika Prihatini, Ekawati Putra, Muhammad Rizki Ganda Putra, Yogie Dwi Putri, Amanda Kanaya Rahman, M. Arief Rakhman, M Arief Rasyad, Sabilal Riska Handayani Riswal Hanafi Siregar Rivaldo Arviando Rizkiyanti, Shally Rizky Vira Robi Robi Rosita, Ella Rossi Passarella Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Rumiasih Rusman Ariyanto Rusman Ariyanto Sabilal Rasyad Sabilal Rasyad Safitri, Rahmi Dian Salsabillah, Farhah Sanyyah Plowerita Sarjana Sarjana Sarjana Sarjana, Sarjana Selamat Muslimin Sinaga, Putri Sitangsu Sitangsu Siti Chodijah Siti Nurmaini Sitompul, Carlos R Sobri, M. Sopian Soim Sopian Soim Sopian Soim, Sopian Sri Chodidjah Sugiyanto, Aan Suroso Suroso Suroso Suroso Suroso Suroso suzan zefi Syauqiyah, Khansa Ghazalah Taqwa, Ing Ahmad Tarmidi Tarmidi Theresia Enim Agusdi Tresna Dewi Tresna Dewi Ulandari, Monica Umul Salamah Wahyu Caesarendra Wahyu Caesarendra Widya, Afni Rara Wildan Putra Pratama Wirayudha, Ikhwan Adhi Yani, Iryadi Yeni Irdayanti Yudi Wijanarko