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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal INKOM TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Building of Informatics, Technology and Science Journal of Electronics, Electromedical Engineering, and Medical Informatics IJAIT (International Journal of Applied Information Technology) Journal of Applied Engineering and Technological Science (JAETS) Jurnal Abdi Insani Madani : Indonesian Journal of Civil Society JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Charity : Jurnal Pengabdian Masyarakat JURNAL ILMIAH GLOBAL EDUCATION Prosiding Konferensi Nasional PKM-CSR Jurnal Nasional Teknik Elektro dan Teknologi Informasi eProceedings of Applied Science eProceedings of Engineering Abdibaraya: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL Journal of Applied Engineering and Social Science Proceeding of Community Service and Engagement
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Pemberdayaan PKK melalui Implementasi Pertanian Hidroponik di RW. 08 Desa Cipagalo, Kabupaten Bandung Guna Mendukung Ketahanan Pangan Anwar, Radial; Hadiyoso, Sugondo; Putri, Hasanah
Abdibaraya Vol 4 No 01 (2025): Abdibaraya: Jurnal Pengabdian Masyarakat
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/abdibaraya.v4i01.1510

Abstract

This community service activity aims to implement hydroponic farming in the PKK group of RW 08, Cipagalo Village, Bandung Regency, as an effort to support local food security. Hydroponics is a farming method that does not use soil but instead relies on water enriched with essential nutrients required by plants. This method was chosen due to its efficiency in land and water usage, as well as its ability to produce faster and higher-quality harvests. The training and implementation of hydroponic farming involved the women of the PKK group as the primary participants, with the goal of enhancing their knowledge and skills in modern farming techniques. This activity also aims to empower the local community, especially women, to support family and community food security. In the context of the Sustainable Development Goals (SDGs), this initiative contributes to several objectives, including zero hunger, decent work and economic growth, and sustainable cities and communities..The results of this activity demonstrate that hydroponic farming can be successfully applied in the PKK environment of RW 08, Cipagalo Village. The training participants were able to master basic hydroponic techniques and independently produce fresh vegetables. Additionally, this program successfully raised community awareness about the importance of food security and environmental sustainability
Security System for Door Locks Using YOLO-Based Face Recognition Putri, Hasanah; Hadiyoso, Sugondo; Putri Fatoni, Salwa Berliana; Octaviany, Vany; Wulandari, Astri; Aprilina, Riska; Rosmiati, Mia
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2410

Abstract

Di era kemajuan teknologi dan algoritma canggih yang memudahkan hidup manusia, kunci pintar pengenalan wajah merupakan sistem yang menggunakan salah satu algoritma tersebut dan mengatasi masalah keamanan dalam teknologi rumah pintar. Kunci pintar ini dapat dipasang di dekat pintu untuk memantau rumah, perusahaan, dan universitas. Masalah dengan solusi kunci pintar pengenalan wajah saat ini adalah bahwa kunci pintar tersebut kurang cepat dan tepat. Pintu merupakan salah satu komponen bangunan yang perlu diperhatikan keamanannya untuk mencegah upaya pencurian. Bangunan yang memiliki banyak ruang harus memiliki pintu dengan sistem keamanan yang kuat, salah satunya adalah hotel. Alat yang sering digunakan untuk mengakses kamar hotel adalah RFID. Mobil RFID memiliki banyak kekurangan, antara lain tamu sering meninggalkan kartu RFID mereka di kamar sehingga mereka tidak dapat lagi memasuki kamar dan harus melapor ke resepsionis terlebih dahulu, kartu RFID juga mudah hilang sehingga tamu yang kehilangan kartu RFID akan didenda sebagai biaya penggantian kartu. Oleh karena itu, dibuatlah sistem keamanan pintu menggunakan pengenalan wajah dengan algoritma YOLO. Algoritma YOLO digunakan untuk mendeteksi wajah siapa saja yang ingin mengakses pintu. Hasil pengujiannya adalah sistem dapat mendeteksi wajah dengan tingkat akurasi 94,4%.
Application of Hybrid Metaheuristic Algorithms for Feature Selection in Event-Related Potential Classification in Problematic Gamers Using Electroencephalograph Signal Wijayanto, Inung; Hadiyoso, Sugondo; Safitri, Ayu Sekar; Rahmaniar, Thalita Dewi
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 2 (2025): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i2.638

Abstract

Online games have become a popular form of entertainment, particularly for relieving stress, and the rise in online gaming has led to an increase in problematic gaming behaviors. Excessive use of the internet for gaming has raised concerns about its neurophysiological impact, particularly on cognitive and emotional functions. Electroencephalogram signal and Event-Related Potential analysis are valuable tools for monitoring these effects. Given the vast amount of features that can be extracted from EEG signals, it is crucial to apply efficient feature selection methods to identify the most informative ones. This study utilizes the Go/No-Go Association Task combined with the recording of 16-channel EEG signals, chosen as the data-recording method to observe the response of individuals who are problematic online gamers to several stimulus themes. In this context, metaheuristic algorithms like Genetic Algorithm, Ant Colony Optimization, and Particle Swarm Optimization are employed to enhance feature selection. A hybrid approach, combining one of these methods with Binary Stochastic Fractal Search is proposed to improve classification accuracy and optimize feature selection. The results demonstrate that the hybridization of the best algorithm with B-SFS successfully selects the optimal features, achieving perfect classification performance, with an accuracy, sensitivity, and specificity of 1.00 for all respondents. This emphasizes the effectiveness of B-SFS, particularly its diffusion process, where Gaussian distribution facilitates the search for the best solution, thereby improving the reliability of feature selection for detecting problematic gaming behavior.
DCT and SVD Sparsity-Based Compressive Learning on Lettuces Classification Lutvi Murdiansyah Murdiansyah; Gelar Budiman; Indrarini Dyah Irawati; Sugondo Hadiyoso; A. V. Senthil Kumar
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.4506

Abstract

Compressive Sensing (CS) technique in image compression represents efficient signal which offering solutions in image classification where the resources are constrained especially on a large image processing, storage resource, and computing performance. Compressive learning (CL) is a framework that integrates signal acquisition via compressed sensing (CS) and machine/deep learning for inference tasks directly on a small number of measurements, On the other hand, in real-world high-resolution (HR) data, where the image dataset is very limited CL, has the drawback of reduced accuracy under conditions of aggressive compression ratio. Here, a reconstruction method is necessary to maintain high levels of accuracy. To address this, we proposed a framework Deep Learning (DL) and Compressive Sensing that processing a small dataset of 92 images maintaining high accuracy. The framework developed in this paper employs processing sensing matrix A in compressive sensing with two transformation methods: DCT CL with Multi Neural Networks and the SVD method with GoogleNet framework. To maintain the same computation efficiency as DCT Compressive learning, SVD with GoogleNet framework provides a solution for object recognition, achieving accuracy values ranging from 89.47% to 63.15% for compression ratios of 3.97 to 31.75. This performance shows a linear tendency concerning the PSNR level, an index of signal reconstruction quality, and demonstrates an efficient process in the S matrix.
Advanced Smart Bracelet for Elderly: Combining Temperature Monitoring and GPS Tracking Sugondo Hadiyoso; Indrarini Dyah Irawati; Akhmad Alfaruq; Tasya Chairunnisa; Muhamad Roihan; Suyatno Suyatno
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.6182

Abstract

Indonesia is entering an aging population period, marked by an increase in the number of elderly individuals, accompanied by a rise in dementia cases. This situation leads to higher dependency among the elderly on others for assistance or long-term care. Dementia can cause elderly people to lose their sense of direction, often wandering aimlessly, making them difficult to track. To address this issue, a wearable smart bracelet is proposed to monitor the location and a vital body parameter such as body temperature. The system is equipped with a tracking application that can send an alert if the user is outside a designated area. It automatically sends a warning message to the caregiver's or family member's smartphone when abnormal signs are detected. The bracelet is designed like a wristwatch, to be worn on the wrist. It is small, lightweight, and battery-operated. Temperature and location data can be transmitted in real-time using an internet network to mobile devices. The device can notify when the user is outside the specified area. Test results indicate that the device has high accuracy and reliability in monitoring location and body temperature with accuracy around 98.5%, as well as sending notifications through a Telegram bot when certain thresholds are exceeded. This device can work properly for up to 5 hours on a single battery charge. With this device, it is expected to help monitor and support the care of the elderly so that they can improve their quality of life. This device can also provide an emergency alarm if the elderly are outside the area.
Penerapan Sensor Akselerometer dan Giroskop untuk Membedakan Pola Berjalan Militer dan Non-Militer Meidatomo , Muhammad Haykal; Wijayanto, Inung; Hadiyoso, Sugondo
eProceedings of Engineering Vol. 12 No. 3 (2025): Juni 2025
Publisher : eProceedings of Engineering

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

Abstract

Mengkaji pola gerakan berjalan (GAIT)menggunakan perangkat sensor yang menggabungkanakselerometer dan giroskop pada prajurit militer. Pola gerakanyang khusus, seperti cara berjalan tegap, memainkan peranvital dalam membedakan antara prajurit TNI dan individupada umumnya. Dalam penelitian ini, sensor MPU6050dikenakan pada perangkat wearable berbasis ESP32 untukmerekam gerakan tiga dimensi (x, y, z) yang dihasilkan olehakselerometer dan giroskop ketika subjek berjalan. Data yangdiperoleh kemudian dikirimkan melalui Bluetooth Low Energy(BLE) untuk dianalisis lebih lanjut. Tujuan dari penelitian iniadalah untuk mengidentifikasi perbedaan pola gerakan antaraprajurit militer dan individu dengan tingkat kebugaran fisikyang lebih rendah. Klasifikasi dilakukan dengan membagi duakategori berdasarkan gaya berjalan: tegap (militer) dan lemas(individu dengan kondisi fisik tidak optimal). Analisa statistikdan variabel gerakan digunakan guna mendalami perbedaangerak berjalan. Temuan yang dihasilkan diharapkan dapatmenunjang pengembangan sistem otomatis untuk mengenaliprajurit militer berdasarkan pola gerakan berjalan mereka.Kata kunci—GAIT, BLE, akselerometer, MPU6050, ESP32,militer
Perancangan Alat Monitor Parameter Lingkungan Green House Portable Di Fakultas Ilmu Terapan Nasution, Muhammad Ilham Kurniawan; Hadiyoso, Sugondo; Alfaruq, Akhmad
eProceedings of Applied Science Vol. 11 No. 2 (2025): April 2025
Publisher : eProceedings of Applied Science

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Abstract

Abstrak — Di era Revolusi Industri 4.0, penerapan sistemotomatisasi yang terhubung dengan internet semakinmendominasi berbagai sektor, termasuk sosial, pendidikan, danpertanian. Tujuan utama dari teknologi ini adalah untukmengoptimalkan hasil dan meningkatkan efisiensi penggunaansumber daya, terutama dalam menghadapi tantangan sepertiperubahan cuaca ekstrem yang berdampak pada produktivitaspertanian. Dalam konteks ini, proyek akhir ini merancang alatmonitoring parameter lingkungan Greenhouse berbasis Internetof Things (IoT) yang diimplementasikan di rooftop Fakultas IlmuTerapan (FIT). Sistem ini menggunakan Microcontroller ESP32dengan sensor DHT22 dan MQ135, di mana data yangdikumpulkan dikirimkan ke Firebase untuk ditampilkan secarareal-time pada dashboard monitoring. Alat ini juga dirancangportable dengan sumber daya dari baterai 18650.Hasil pengujian menunjukkan akurasi sensor yang baik,dengan percent error untuk sensor suhu berkisar antara 1.4%hingga 1.8% dan kelembapan antara 1.6% hingga 1.9% padaberbagai waktu pengukuran. Monitoring ruangan Greenhousedilakukan setiap 2 menit selama 40 menit, menghasilkan rata-ratasuhu pagi 28°C, siang 33°C, sore 31°C, serta kelembapan dankadar CO2 yang bervariasi sepanjang hari. Dengan data ini,sistem terbukti efektif dalam membantu mengurangi waktu dantenaga yang diperlukan untuk merawat tanaman di ruanganGreenhouse, sekaligus memberikan informasi yang bergunauntuk pengambilan keputusan dalam pertanian.Kata kunci — IoT, Suhu, Greenhouse, Tanaman.
Pemberdayaan Masyarakat Pesantren Husnul Khotimah berbasis Teknologi dengan Implementasi Pembangkit Listrik Tenaga Terbarukan Budi Prasetya; Yuyun Siti Rohmah; Kris Sujatmoko; Dharu Arseno; Sugondo Hadiyoso
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 6 No. 3 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v6i3.2290

Abstract

Husnul Khotimah Islamic Boarding School faces challenges in meeting the need for electricity supply due to 24-hour operations. This causes high operational costs, especially for electricity. Until now, there have been no efforts to implement alternative energy sources due to limited knowledge and budget. This research in the form of community service proposes empowering the Islamic boarding school community through renewable energy-based power generation technology, namely solar and wind power. This implementation aims to reduce dependence on conventional electricity, reduce operational costs, and increase the understanding of the Islamic boarding school community regarding green energy technology, namely solar and wind energy. The methods used include feasibility studies, planning, installation, and training the Islamic boarding school community. The expected results are the creation of an efficient and sustainable renewable energy system, as well as increasing the capacity of the Islamic boarding school community in managing independent energy resources. This empowerment is expected to be a model that can be replicated by other Islamic boarding schools in overcoming similar problems.
Scrambling and De-Scrambling Implementation Using Linear Feedback Shift Register Method on FPGA Lurina, Manda; Hadiyoso, Sugondo; Pudji Astuti, Rina
IJAIT (International Journal of Applied Information Technology) Vol 01 No 01 (May 2017)
Publisher : School of Applied Science, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijait.v1i02.876

Abstract

Digital broadband communications require a fast, functional and efficient system. In a digital communication system, a long sequence of bits '0' or '1' will inherits the loss of bit synchronization, and hence it can cause the false detection on the receiver. To avoid this, long sequence of bits will be randomized first so that long sequence of bits '0' or '1' can be removed. This randomization process is called scrambling and the circuit that works for the process is a scrambler. In the receiver there is a descrambler that serves to return the bits to their original information. This paper presents a design of scrambler and descrambler using a combination of Linear Feedback Shift Register (LFSR) with 15 registers, XOR logic gates, and Pseudo Random Binary Sequence (PRBS) generator structure with polynomial 1 + x14 + x15. One of the two main parts of LFSR is the shift register while the other is the feedback. In LFSR, the bits contained within the selected position in the shift register will be combined in a function and the result will be put back into this register's input bit. Feedback also makes the system more stable and no error occurrence. Then special tap is taken from a certain point in XOR and returned as a feedback register. The system is implemented on FPGA board Altera De0-Nano EP4CE22F17C6 Cyclone IV E. Resource memory required <1% of available memory. Bit rate that can be achieved with clock speed 50MHz is 335570.47 bps.
Peningkatan Citra Untuk Klasifikasi Gangguan Paru-Paru Menggunakan Deep Learning Adiwijaya, Agustinus Aldian; Hariyani , Yuli Sun; Hadiyoso, Sugondo
eProceedings of Applied Science Vol. 10 No. 3 (2024): Juni 2024
Publisher : eProceedings of Applied Science

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Abstract

Gangguan pada paru-paru seperti pneumonia,tuberculosis, dan Covid-19 merupakan gangguan yang cukupserius dimana dapat menyerang sistem pernapasan manusiadan bisa berakibat fatal jika tidak ditangani dengan serius.Gejala yang muncul yaitu sakit tenggorokan, batuk, demam,dan kesulitan dalam bernapas. Pengamatan kondisi paru-parupasien dilakukan paramedis melalui foto rontgen (Chest Xrays). Namun, kualitas citra rontgen terkadang kurang optimal,sehingga dikembangkan sistem otomatisasi berbasis CAD.Oleh karena itu, pada proyek akhir ini merancang sistem untukmeningkatkan citra pada kinerja deep learning. Terutama padaperbandingan performasi sistem sebelum preprocessing dansetelah preprocessing. Penelitian ini bertujuanmengembangkan sistem otomatisasi untuk mendeteksi danmengklasifikasikan penyakit paru-paru pada citra rontgenmenggunakan Convolutional Neural Network (CNN) denganarsitektur Inception V3. Sebuah dataset multi-kelas yangmencakup Normal, Pneumonia, Tuberkulosis (TB), dan Covid19 digunakan untuk melatih dan menguji model. Evaluasiperforma sistem dilakukan sebelum dan setelah preprocessingcitra dengan metode Unsharp Masking (UM) dan HighFrequency Emphasis Filtering (HEF). Hasil penelitian Padadata latih tanpa preprocessing, model mencapai akurasi sekitar86.11%, dengan tingkat presisi, recall, dan F1-Score yang cukupseimbang. Sedangkan data latih sesudah preprocesing modelmencapai akurasi sekitar 99.31%, dan presisi, recall, serta F1-Score mendekati 99.32%. Kata kunci— Chest X-Ray, Convolutional Neural Network (CNN), Inception V3, Tuberculosis, Pneumonia, COVID-19
Co-Authors -, Suryatiningsih A. V. Senthil Kumar A.A. Ketut Agung Cahyawan W Aaron Abel Abi Hakim Amanullah Achmad Rizal Achmad Rizal ADIANGGIALI, ANYELIA Adisaputra, Rangga Adiwijaya, Agustinus Aldian Adjie Gery Ramadhan Adnan Azhary Afandi, Mas Aly Agung Muliawan Ahmad Hilmi Ahmad Muammar Agusti Akhmad Alfaruq Akhmad Alfaruq Alfaruq, Akhmad Alfaruq, Akhmad Aliffansyah, Lingga Alvinas Deva Sih Illahi Ana Durrotul Isma Anatasya Bella Andhita Nurul Khasanah Andri Juli Setiawan Andro Harjanto Anggit Syorgaffi Anggun Fitrian Isnawati ANGGUNMEKA LUHUR PRASASTI Arfianto Fahmi Arif Indra Irawan ARIS HARTAMAN Ashshiddiqqi, Muhammad Arhizal Asma Zahira Asril Ibrahim Astri Wulandari Audry Stevany Aulia Ayu Dyah Lestari Ayu Chellsya, Ananda Ayu Tuty Utami Azahra, Yasmin Azriel Gilbert Samuel Rogito Azzahra, Salwa Bagus Tri Astadi Balova , Fathrurrizqa Bambang Hidayat Bandiyah Sri Aprillia Barus, Exal Deo Jayata Bayu Erviga Yulanda Setiawan Bayuaji Kurniadhani Bimo Rian Tri Nugroho Budhi Irawan Budi Prasetya Budi Prasetya Budiyawan Naztin Burhanuddin D. Burhanuddin Dirgantoro Cucu Fitri Dadan Nur Ramadan Dadan Nur Ramadhan Dadan Nur Ramadhan Denny Darlis Dewi Budiwati, Sari Dewi Rahmaniar, Thalita Dharu Arseno Didin Bramastya Dieny Rofiatul Mardiyah Diliana, Faizza Haya Efri Suhartono Ema ERVIN MASITA DEWI Exal Deo Jayata Barus Ezi Rohmat Fadiaga Omar Michlas Fairuz Azmi FAJRI, SETIO EKA FARDAN FARDAN Farhan Alghifari Chaniago Saputro, Muhammad Farrel Fahrozi Fathrurrizqa Balova FATURRAHMAN, RAIHAN Fauzia Anis Sekar Ningrum Fony Ferliana Widianingrum Gadama, Melsan Gartina Husein, Inne Gelar Budiman Ghilman Hafizhan Gifari, Rizqi Al Goldfried Manuel Lbn Tobing Habib, Arrijal Hadjwan, Razel Hannissa Sanggarini Hariyani , Yuli Sun Hasanah Putri Hengky Yudha Bintara Heru Nugroho Hilman Fauzi, Hilman HUMAIRANI, ANNISA Hurianti Vidyaningtyas HW, EVA AISAH Ilham Edwian Berliandhy Ilmi, M. Bahrul Indrarini Dyah Irawati Inung Wijayanto Irsyad Abdul Basit Istikmal Ivany Sesa Rehadi Ivosierra Andrea Larasaty Jannah, Firna Noor Jannah, Sabila Hayyinun Jasmine, Diva Dhila Jauhari, Muhammad I Javani Sekar Larasati Jehan Pratama Herdaning Jondri Jondri Koredianto Usman Kridanto Surendro Kris Sujatmoko Kurnia Ismanto, Rima Ananda Larasaty, Ivosierra Andrea Lata Tripathi, Suman LATIP, ROHAYA Ledya Novamizanti Lurina, Manda Luthfi Muhammad Pahlevi Lutvi Murdiansyah Murdiansyah M. Nur Imam DJ Mahmud Dwi Sulistiyo Manda Lurina Meidatomo , Muhammad Haykal Milan Adila Amalia Mohamad Ramdhani Muh. Kurniawan, A. Muhamad Roihan Muhammad Adnan Muhammad Afif Ridwansyah Muhammad Alfachri Akbar Muhammad Arhizal Ashshiddiqqi Muhammad Farhan Alghifari Chaniago Saputro Muhammad Iqbal MUHAMMAD JULIAN, MUHAMMAD Nadya Silva Arline Nasution, Muhammad Ilham Kurniawan Nasution, Seri Wahyuni Naufal Juhaidi Jafal Naufal Rizky Pratama Nur Arviah Sofyan Nur Pratama, Yohanes Juan Nur Ramadhani Nursanto Nursanto NURSANTO NURSANTO, NURSANTO Nurwan Reza Fachrurrozi Okki Rahmalisty, Fiona Pahira, Ela Diranda Patricia Lovenia Garcia Periyadi Permana, Andri Satia Prahara, Dzakwan Bahar Prajna Deshanta Ibnugraha Putra, I Gusti Ngurah R. A. Putri Fatoni, Salwa Berliana Putri, Athaliqa Ananda Putri, Silvi Dahlia R. Dhenake Aghni Bunga R. Yunendah Nur Fu’adah Radial Anwar, Radial Radian Sigit Raditiana Patmasari Rahmaniar, Thalita Dewi Rahmat Widadi Ramdani, Ahmad Zaky Ratna Mayasari Reivind P. Persada RENALDI, LUKY RENALDI, LUKY RENDIKA, ANANDA Rendy Munadi Reni Dyah Wahyuningrum Reny Yuliani Arnis Ridha Muldina Negara Rina Pudji Astuti Riska Aprilina Rita Magdalena Rita Purnamasari Rizal Fachrudin Maulana Rizky Aulia Rahman Robinzon Pakpahan Rogito, Azriel Gilbert Samuel ROHMAT TULLOH Rosmiati, Mia Ruli Pandapotan, Bagas Ryan Bagus Wicaksono Safitri, Ayu Sekar Said, Ziani Sania Marcellina Bryan Sasmi Hidayatul Yulianing Tyas Sa’idah, Sofia Sekar Safitri, Ayu Septiansyah, Rizky SETIAWAN, AWAN WAHYU Sianturi, Kristian Fery Sidqi, Anka Sigit, Radian Siti Sarah Maidin Siti Zahrotul Fajriyah Sofia Naning Hertiana Suci Aulia Sugeng Santoso Sulistyo, Tobias Mikha Surya Putra Agung Saragih Suyatno Suyatno Syifa Nurgaida Yutia Tasya Chairunnisa Tati Latifah Erawati Rajab Teguh Musaharpa Gunawan Thomhert Suprapto Siadari Tita Haryanti Tobing, Goldfried Manuel Lbn Tri Nopiani Damayanti Triadi Triadi Unang Sunarya Untari Novia Wisesty Vany Octaviany Vera Suryani Wahyu Hauzan Rafi Wibowo, Raiyan Adi Wirakusuma, Muhammad P. Yasmin Azahra Yoza Radyaputra Yudha Purwanto Yudiansyah Yudiansyah YULI SUN HARIYANI YUYUN SITI ROHMAH Zahrah, Nasywa Nur Zhillan Al Rashif, Mohammad Zulfikar F.M. Ramli