Article Per Year (5 Year)
p-Index From 2021 - 2026
7.918
P-Index
This Author published in this journals
All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika Sistemasi: Jurnal Sistem Informasi Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) METIK JURNAL Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal Jurnal Sosial Humaniora Sigli Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia International Journal of Engineering, Science and Information Technology JUTECH : Journal Education and Technology Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika Journal of Information Technology (JINTECH) Jurnal Teknologi Terapan and Sains 4.0 Journal of Computer Engineering, Electronics and Information Technology Journal Of Artificial Intelligence And Software Engineering Jurnal Informatika: Jurnal Pengembangan IT Jurnal Komputer dan Teknologi (JUKOMTEK) Jurnal Malikussaleh Mengabdi Jurnal Ragam Pengabdian Teewan Journal Solutions Proceeding of The International Conference on Electrical Engineering and Informatics Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI) Jurnal Teknologi dan Otomasi
Muhammad Fikry
Teknik Informatika Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

Published : 71 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 71 Documents
Search

 4   5   6   7   8 
DAMPAK PENGGUNAAN MBANGKING PADA DIGITAL NATIVE MENGGUNAKAN METODE TECHNOLOGY ACCEPTANCE MODEL (TAM) maksal mina; Muhammad Fikry
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.568

Abstract

The rapid development of information technology has accelerated the transformation of banking services into digital-based systems, one of which is mobile banking (Mbanking). This service enables users to conduct financial transactions efficiently without physical interaction with bank offices. This study aims to analyze the effect of perceived usefulness, perceived ease of use, and perceived risk on the intention to use Mbanking among digital native generations using the Technology Acceptance Model (TAM) approach. This research employs a quantitative method with data collected through a Likert-scale questionnaire. The population consists of Generation Z and Millennials in Banda Aceh who use Mbanking services, with a total sample of 70 respondents selected using purposive sampling techniques. Data analysis was conducted using multiple linear regression with the assistance of SmartPLS software. The results indicate that perceived usefulness and perceived ease of use have a positive and significant effect on the intention to use Mbanking. In addition, perceived risk also shows a significant influence, indicating that security and trust are crucial factors in adopting digital banking services. Simultaneously, all independent variables significantly affect the intention to use Mbanking. These findings suggest that improving service benefits, ease of use, and system security can enhance users’ interest and sustained use of Mbanking, particularly among digital native groups.
IMPLEMENTASI MACHINE LEARNING UNTUK PREDIKSI PENGELUARAN KEUANGAN BERDASARKAN POLA EKSTERNAL DAN INTERNAL (SEASONALITY, KEGIATAN RUTIN & INSIDENTIL) STUDI KASUS: FAKULTAS TEKNIK UNIVERSITAS ALMUSLIM Siti Hajar; Asrianda Asrianda; Muhammad Fikry
JUTECH : Journal Education and Technology Vol 6, No 2 (2025): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i2.6008

Abstract

Perencanaan anggaran yang akurat merupakan faktor penting dalam pengelolaan keuangan perguruan tinggi. Fakultas Teknik Universitas Almuslim menghadapi fluktuasi pengeluaran yang dipengaruhi oleh pola internal dan eksternal, seperti seasonality, kegiatan rutin akademik, serta kegiatan insidentil. Penelitian ini bertujuan untuk mengimplementasikan metode machine learning dalam memprediksi pengeluaran keuangan fakultas berdasarkan pola-pola tersebut. Data historis pengeluaran keuangan pada anggaran tahun 2021 – 2025 digunakan sebagai dataset, yang dikombinasikan dengan variabel waktu dan jenis kegiatan. Tahapan penelitian meliputi preprocessing data, pemodelan, serta evaluasi kinerja model menggunakan metrik kesalahan prediksi. Hasil penelitian menunjukkan bahwa model machine learning mampu menghasilkan prediksi pengeluaran yang lebih akurat dibandingkan metode perencanaan konvensional. Model prediksi ini diharapkan dapat menjadi alat bantu pengambilan keputusan dalam penyusunan anggaran, meningkatkan efisiensi pengelolaan keuangan, serta mendukung penerapan data-driven decision making di lingkungan Fakultas Teknik.
Integrated Emergency Communication System for Disaster Areas Using Long Range Mahadika Luqman; Muhammad Fikry; Yesy Afrillia
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12753

Abstract

Natural disasters disrupt communication infrastructure, hindering emergency response coordination. This study designs and evaluates an integrated emergency communication system combining LoRa for transmission, GPS for geolocation, and BLE for alternative interface. The system comprises a Field Device with a 9-state finite-state machine, a Beacon Network forming a linear multi-hop relay chain with heartbeat-based node failure detection, and a Headquarter Device connected to the Blynk platform for monitoring and notifications. A custom binary protocol with 8 message types uses packed structures. All performance was evaluated in urban area, except maximum communication direct range in urban area and rural area. PDR achieves 100% up to 1,000 m Line-of-Sight with an average end-to-end latency of 1.02 s. A single beacon relay extends communication range to 2000 m compared to maximum direct communication range, 1288 m in rural area and 1044 m in urban campus area. Outdoor GPS accuracy measures 0.945 m, while indoor accuracy 28.68 m due to building attenuation. The system successfully detected motion >5 m with 100% sensitivity within 5 s. Usability testing average completion times of 14.84 s via physical interface and 23.85 s via mobile application. BLE range reaches 16 m outdoors and 11 m indoors. Operational durations were 4.32 h for the Field Device, 9.18 h for the Beacon Network, and 8.03 h for the Headquarter Device, falling short of the 12-hour target, necessitating aggressive GPS duty cycling and Wi Fi sleep modes. This study evaluates three critical factors for emergency response: network determinism, payload efficiency, and power autonomy.
Comparative Analysis of CNN and YOLO for Aromatic Leaf Detection on Android-Based Deep Learning Applications Yuli Safrina; Muhammad Fikry; Mukhlis Abd Muthalib
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13015

Abstract

Commonly used aromatic leaves in Indonesian cuisine include bay leaves (Syzygium polyanthum), pandan leaves (Pandanus amaryllifolius), lime leaves (Citrus hystrix), curry leaves (Murraya koenigii), and turmeric leaves (Curcuma longa). Their similar shapes, colors, and textures often make manual identification difficult. Therefore, deep learning technology can be utilized to automatically identify and detect aromatic leaf types through digital images. This study aims to analyze the performance of a Convolutional Neural Network (CNN) using the EfficientNet-B0 architecture and the YOLOv11 model with the AdamW optimizer in detecting and classifying aromatic leaves. The system is implemented using a Python Flask framework for the web based backend and Flutter for the mobile application interface on Android devices. The dataset used in this study consists of 671 digital images obtained through direct image collection and supporting datasets. The dataset is categorized into five classes: bay leaf, pandan leaf, lime leaf, curry leaf, and turmeric leaf. Furthermore, the dataset is divided into training data (89%), validation data (7%), and testing data (4%). The results show that the YOLOv11 model outperforms the CNN (EfficientNet-B0) model. YOLOv11 achieved a precision of 73.36%, recall of 84.35%, mAP50 of 83.93%, and mAP50-95 of 71.38%. Meanwhile, EfficientNet-B0 achieved a best validation accuracy of 81.40% and a test accuracy of 62.07%. Based on experimental results, YOLOv11 demonstrates higher detection confidence and more consistent performance compared to EfficientNet-B0. In addition, YOLOv11 is more suitable for mobile deployment due to its real-time object detection capability with faster inference speed, while the system is supported by a Flask based backend and a Flutter mobile application interface.
Peramalan Jumlah Mahasiswa Baru di Universitas Malikussaleh Menggunakan Metode Double Exponential Smoothing dan Bayesian Updating Indah Chairunnisa; Muhammad Fikry; Hafizh Al Kautsar Aidilof
Jurnal Pendidikan dan Teknologi Indonesia Vol 6 No 7 (2026): JPTI - Juli 2026
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.2052

Abstract

Jumlah mahasiswa baru merupakan informasi krusial bagi perguruan tinggi dalam perencanaan akademik dan strategi penerimaan. Universitas Malikussaleh mengalami fluktuasi jumlah mahasiswa baru periode 2021–2025, sehingga diperlukan metode peramalan yang akurat. Penelitian ini bertujuan meramalkan jumlah mahasiswa baru Universitas Malikussaleh tahun 2026–2030 menggunakan metode Double Exponential Smoothing (DES) Holt, serta memperbarui hasil ramalan dengan Bayesian Updating berdasarkan informasi dari kuesioner calon mahasiswa. Data historis yang digunakan adalah jumlah mahasiswa baru tahun 2021–2025. Data kuesioner diperoleh dari 205 responden siswa SMA/SMK di Kota Lhokseumawe. Analisis korelasi Pearson digunakan untuk menyeleksi indikator yang paling berpengaruh terhadap jumlah mahasiswa baru. Hasil penelitian menunjukkan bahwa metode Double Exponential Smoothing (DES) menghasilkan nilai MAPE 7,88% (kategori sangat akurat) dengan ramalan jumlah mahasiswa baru tahun 2026–2030 berturut-turut 5.626, 6.197, 6.767, 7.338, dan 7.908. Lima indikator terpilih (minat, KIP-Kuliah, reputasi, fasilitas, kemudahan informasi) menghasilkan nilai evidence 0,533. Setelah Bayesian Updating (?=0,3), diperoleh hasil posterior 5.682, 6.258, 6.834, 7.411, dan 7.986. Korelasi Pearson antara evidence dan jumlah mahasiswa baru menunjukkan hubungan sangat kuat (r=0,9271; p=0,0234). Penelitian ini membuktikan bahwa integrasi Double Exponential Smoothing (DES) dan Bayesian Updating menghasilkan peramalan yang lebih adaptif terhadap informasi terkini calon mahasiswa.
Klasifikasi Skor Action Research Arm Test Menggunakan Wearable sensor Berbasis IoT dan Random Forest untuk Rehabilitasi Pasca Stroke Ilmi Sinambela; Muhammad Fikry; Defry Hamdhana
Jurnal Pendidikan dan Teknologi Indonesia Vol 6 No 7 (2026): JPTI - Juli 2026
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.2199

Abstract

Pemantauan fungsi ekstremitas atas merupakan bagian penting dalam rehabilitasi pascastroke, tetapi penilaian secara konvensional masih bergantung pada pengamatan tenaga kesehatan dan sulit dilakukan secara berkelanjutan. Penelitian ini bertujuan mengembangkan prototipe hand wearable sensor berbasis Internet of Things untuk mengklasifikasikan kualitas gerakan tangan berdasarkan skor Action Research Arm Test (ARAT). Perangkat dibangun menggunakan mikrokontroler ESP32 dan dua sensor MPU6050 yang ditempatkan pada punggung tangan dan lengan bawah untuk merekam data akselerometer dan giroskop dari 10 subjek sehat pada tujuh gerakan ARAT yang mencakup kategori gross movement dan grip. Fitur statistik diekstraksi dari sinyal sensor dan ketidakseimbangan data pada setiap kelas ditangani sebelum tujuh model Random Forest dikembangkan secara terpisah untuk memprediksi skor ARAT 0–3 pada setiap gerakan. Hasil pengujian menunjukkan rata-rata akurasi sebesar 89%, presisi makro 0,83, recall makro 0,84, dan F1-score makro 0,84, dengan model gerakan tangan ke belakang kepala mencapai performa tertinggi (akurasi 94%, F1-score 0,90). Hasil tersebut menunjukkan bahwa sistem mampu mengenali pola kualitas gerakan secara menjanjikan sebagai prototipe pendukung pemantauan rehabilitasi, meskipun validasi klinis pada pasien pascastroke masih diperlukan sebelum sistem digunakan dalam pelayanan kesehatan.
APLIKASI TEKNOLOGI INTERNET OF THING PADA ROBOT PENDETEKSI KEBOCORAN GAS AMONIA (NH3) Jikti Khairina; Nurdin Nurdin; Muhammad Fikry
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7457

Abstract

Amonia adalah senyawa kimia dengan rumus NH3 Senyawa ini didapati berupa gas dengan bau tajam yang sangat khas, inilah yang disebut dengan bau amonia. Amonia memiliki sumbangan penting bagi keberadaan nutrisi di bumi, tetapi amonia sendiri adalah senyawa yang dapat merusak kesehatan. Jika terjadi kontak dengan gas amonia berkonsentrasi tinggi dapat menyebabkan kerusakan pada paru-paru bahkan sampai kematian. Amonia digolongkan sebagai bahan beracun jika terhirup langsung, pengangkutan amonia yang berjumlah lebih besar dari 3.500 galon (13,248 L) harus disertai dengan surat izin. Amonia umumnya bersifat basa (pKb=4.75), tetapi dapat juga bersifat sebagai asam yang amat lemah (pKa=9.25), amonia dapat terbentuk secara alami maupun sintetis. Amonia yang berada di alam merupakan hasil dekomposisi bahan organik. Di industri banyak yang menggunakan amonia sebagai salah satu bahan baku, contohnya seperti dalam penggunaan campuran bahan baku pembuatan pupuk. Gas amonia terkadang beresiko terjadi kebocoran pada pipa gas, jika terjadi kebocoran pada pipa maka dibutuhkan teknisi yang harus segera dikirimkan ke lokasi untuk mencari sumber kebocoran atau titik kebocoran pada pipa. Hal itu membuat teknisi membutuhkan tabung oksigen dan hal ini beresiko sangat tinggi dikarenakan daya tahan tabung oksigen hanya bertahan selama ±15 menit. Maka dibuatkanlah robot untuk dikirimkan ke lokasi yang berfungsi agar mengetahui informasi tentang lokasi kebocoran pipa gas dan informasi kadar gas langsung dapat diketahui melalui Android. Dalam kasus ini, rancang bangun robot menggunakan sensor MQ135. Oleh karena itu dibuatkanlah robot pendeteksi kebocoran gas dan mengetahui kadar dari gas amonia agar mempermudah teknisi dalam menemukan lokasi dan kadar gas amonia.
Real-Time Heart Rate Pattern Analysis During Computer-Based Work Activities Muhammad Fatiha Assyfa; Muhammad Fikry; Zara Yunizar
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13148

Abstract

The development of Internet of Things (IoT) technology provides opportunities for real-time health monitoring systems, including stress detection based on users’ physiological conditions. This study aims to develop an IoT-based heart rate monitoring and stress detection system using a Pulse Sensor and ESP8266 microcontroller. The system is designed to read heart rate signals in real-time and transmit the data to a computer through serial USB communication for further processing using the Python programming language. The data processing stages include signal preprocessing, Beats Per Minute (BPM) calculation, sliding window processing, and kurtosis analysis as an indicator of user stress levels. The processed data are visualized through a Streamlit-based monitoring dashboard in the form of time-series graphs, gauge meters, and real-time user condition status. The study involved 20 Informatics Engineering students performing computer-based work activities within a certain duration. The results show that the system is capable of performing real-time heart rate monitoring and stress analysis effectively. The kurtosis values indicate changes in heart rate signal distribution patterns that can be used as indicators of normal and stress conditions. The developed system is expected to provide a simple, affordable, and extensible health monitoring solution.
Peningkatan Keterampilan Pekerja Konstruksi Desa Paya Gaboh Melalui Pelatihan Pemasangan Keramik Sesuai dengan SNI: Pendekatan Partisipatif Berbasis Pelatihan Vokasional pada Tenaga Kerja Lokal David Sarana; Nura Usrina; Muhammad Fikry; Sofyan; Syibral Malasyi; Rizal
Jurnal Malikussaleh Mengabdi Vol. 5 No. 3 (2026): Jurnal Malikussaleh Mengabdi, Juli 2026
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v5i3.27126

Abstract

Desa Paya Gaboh di Kabupaten Aceh Utara memiliki tenaga kerja konstruksi lokal yang keterampilannya diperoleh secara turun-temurun tanpa mengacu pada standar baku, sehingga mutu pemasangan keramik belum optimal. Permasalahan yang ditemukan meliputi permukaan keramik tidak rata, nat tidak sejajar, dan efisiensi kerja rendah, yang berdampak pada pemborosan bahan dan biaya. Kegiatan pengabdian ini bertujuan meningkatkan keterampilan teknis pekerja melalui pelatihan pemasangan keramik berdasarkan Standar Nasional Indonesia Nomor 7395 Tahun 2008. Metode yang digunakan adalah partisipatif-edukatif dengan pendekatan hands-on training, meliputi observasi, penyusunan materi aplikatif, pelatihan teknis (persiapan permukaan, pemotongan, perataan, pengisian nat), penggunaan teknologi tepat guna seperti tile cutter, waterpass, dan benang ukur, serta evaluasi hasil pekerjaan. Hasil kegiatan menunjukkan peningkatan keterampilan peserta dalam memasang keramik secara rapi dan presisi sesuai standar mutu, serta tumbuhnya kepercayaan diri tenaga kerja lokal. Dampak kegiatan ini antara lain terbukanya peluang kerja yang lebih luas, peningkatan pendapatan masyarakat, dan terjalinnya kerja sama berkelanjutan antara pemerintah desa dengan perguruan tinggi dalam program pemberdayaan masyarakat. Luaran yang diperoleh berupa modul pelatihan pemasangan keramik dan terbentuknya kelompok tukang terlatih di tingkat desa yang mampu menerapkan keterampilan secara mandiri.
Internet of Things Based Detection System for Pencak Silat PSHT Basic Technique Movements Using the Support Vector Machine Method Putri, Ayunda; Yunizar, Zara; Fikri, Muhammad; Fadlisyah; Al Kautsar Aidilof, Hafiz
Jurnal Ragam Pengabdian Vol. 3 No. 2 (2026): Mei-Agustus, Sustainable Development Goals (SDGs): Multidisciplinary Perspectiv
Publisher : Lembaga Teewan Journal Solutions

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62710/j3rq4t73

Abstract

The utilization of technology in sports has become a crucial need to enhance modern coaching efficiency. In pencak silat, particularly within Persaudaraan Setia Hati Terate (PSHT), accurate mastery of basic techniques is essential. However, when students practice independently without supervision, they often struggle to ensure correct hand movements, lowering training quality and increasing injury risks. As a solution, this study develops a real-time, Internet of Things (IoT)-based hand movement monitoring system using Inertial Measurement Unit (IMU) sensors. The sensor data is processed via a Machine Learning approach utilizing a 7-SVM Pipeline architecture. The Support Vector Machine (SVM) algorithm is applied to Model 0 (Movement Classifier) for movement classification, and Models 1–6 (Correctness Classifier) to evaluate quality into "Correct" or "Incorrect". The model is tested using the Leave-One-Subject-Out (LOSO) Cross-Validation method. Results show that Model 0 recognizes movement types with a 63.3% accuracy on unseen subjects. Meanwhile, the correctness models yield varying results; the highest achievement reaches 100% for the Left Jab, whereas the lowest is 55% for the Right Combination due to subjects' biomechanical variations. The results are displayed on a website dashboard as an objective companion tool for independent training while supporting digitalization in preserving pencak silat culture.  
Co-Authors Al Kautsar Aidilof, Hafiz Aldo januansyah. H Amalia, Iklasni Ananda, Silvia Angela, Angela Annisa Annisa Annisa Helmina Aprian Gigin Prasetia Ar Razi Ar Razi Asrianda Asrianda Asrianda Asrianda Asrillah Asrillah Aynun, Nur Ayunda Putri Azzahra Iskandar, Farah Budi Bahreisy Bustami Bustami Bustami Chrisnata Manihuruk Cut Ita Erliana Dahlan Abdullah David Fadlianda David Sarana Defry Hamdhana Dessayani Putri Dimas Pratama, Dimas Dyah Ika Rinawati Ella Suzanna Erwanda, Ade Putra Eva Darnila Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fadlisyah Faiz Syukri Arta Faiz Fajar Rivaldi Chan Fajriana, Fajriana Faradilla, Cut Meutia Hadi Iskandar Hafizh Al Kautsar Aidilof Hafizh Al Kautsar Aidilof Hamdhana, Defry Hasan Tahir Helmi Naluri Herman Fithra Hidayatsyah Hidayatsyah Hizamrul jaen Hutagalung, Yorio Arwandi Wisdom Ibnu Khaldun Ida Wahyuni Ilmi Sinambela Ima Pratiwi Imam Rosadi Irfan Sahputra Iskandar, Fahra Azzahra Ismail Ismail Jikti Khairina Khaidar, Al Khairina, Jikti Kurnia Amanda, Destiara Kurniawati Kurniawati Lidya Rosnita Lutfi, Raihansyah Luthvy Ilhamdi M Ishlah Buana Angkasa M. Rafli Al Thoriq Mustafa Mahadika Luqman Maharani, Silfa Maksal Mina Mardiansyah, M Rizki Maulana, OK Muhammad Majid Mhd Firza Ryzaaldy Muchlis Abdul Muthalib Muhammad Al Imran Muhammad Dastur Muhammad Fatiha Assyfa Muhammad Fikry Muhammad Iqbal Muhammad Iqbal Muhammad Sapriadi Muhammad Yani, Muhammad Muhammad Zikri Mukhlis Mukhlis Mukti Qamal Muqarrabin, Khalis Al Nanda Nan Arif H Nazwa Aulia NELI SUSANTI, NELI Nunsina Nura Usrina Nurdin Nurdin nuryana nuryana, nuryana Rahma, Mutiara Raihansyah, Khananda Rifkial Iqwal Rini Meiyanti Risawandi, Risawandi Rizal Rizal S.Si., M.IT, Rizal Rizki Suwanda Romi Asmara Rozzi Kesuma Dinata Safwandi Safwandi Said Fadlan Anshari Salahuddin Salahuddin Saputra, Ferdy Sari, Cut Jora Sayed Fachrurrazi Sembiring, Vivi Dista Br Silfa Maharani Br Padang Siti Hajar Sofyan Subhan Hartanto Subhan Hartanto Sudirman Sudirman Sujacka Retno Sukma Rizki Syibral Malasyi Tarigan, Anggun Kinanti Taufiq Taufiq Taufiqurrahman Taufiqurrahman Tejas Shinde Teuku Nabil Muhammad Dhuha Umar Khalil Utomo, Muhammad Fikri Wahdana, Aldi Wirda Syahrifa Yani, Muhamamd Yesy Afrillia Yesy Afrillia Yuli Safrina Yulinazira, Ulfa Yusriyana, Yusriyana Yusrizal Hasbi Zaharatul Ulfa Zahratul Fitri Zara Yunizar Zara Yunizar zulfhazli zulfhazli