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All Journal Journal of Applied Data Sciences SAINSTEK TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Rometdo Muzawi
Universitas Sains dan Teknologi Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering

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Implementasi Jaringan LAN dan WLAN pada Mikrotik: Studi Kasus Laboratorium Jaringan Komputer UIN Suska Riau Haris Tri Saputra; Rometdo Muzawi; Rahmad Kurniawan; Teguh Sujana; Evfi Mahdiyah
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp284-291

Abstract

In today's digital age, the existence of computer networks has become a crucial necessity for various institutions and organizations. Local Area Networks (LANs) and Wireless Local Area Networks (WLANs) are commonly used network infrastructures that support connectivity and information exchange between devices. MikroTik, as one of the network device providers, offers reliable solutions for managing LAN and WLAN networks. With its reputation as a leading network device provider, MikroTik is attracting attention as a potential choice to meet these needs. Additionally, the successful implementation of LAN and WLAN networks on MikroTik can provide practical guidance for organizations currently considering or planning to upgrade their network infrastructure. The focus of this research is the Computer Network Laboratory at UIN Suska Riau, where the effectiveness and efficiency of MikroTik routers and access points are evaluated in a real-world educational environment. This study begins with an overview of MikroTik technology, emphasizing its role in creating a robust and scalable network infrastructure. Furthermore, this research delves into the specific requirements and challenges faced by the Computer Network Laboratory, providing insights into the need for LAN and WLAN integration for seamless connectivity. With a better understanding of MikroTik's potential, it is hoped that the organization's information technology foundation can be strengthened and competitiveness increased in this digital era.
Desain Dashboard Web Real-Time untuk Kendali Lampu Neon Box dengan ESP8266 dan Panel Surya Rometdo Muzawi; Helda Yenni; Irwansyah Sidabutar; Windy Fahrurozi
SAINSTEK Vol. 13 No. 2 (2025)
Publisher : Sekolah Tinggi Teknologi Pekanbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35583/js.v13i2.369

Abstract

Perkembangan teknologi Internet of Things (IoT) mendorong terciptanya sistem otomasi pintar yang efisien dan hemat energi, termasuk pada pengendalian pencahayaan ruang publik seperti neon box. Penelitian ini bertujuan untuk merancang dan mengimplementasikan antarmuka pengguna berbasis web yang terintegrasi dengan sistem kendali lampu neon box menggunakan mikrokontroler ESP8266 dan sumber daya panel surya. Sistem mencakup dua sensor utama, yaitu INA219 untuk pemantauan tegangan dan arus baterai serta DS18B20 untuk pengukuran suhu baterai. ESP8266 berperan sebagai unit pengendali pusat yang mengakuisisi data dari sensor melalui antarmuka I²C dan OneWire, mengatur status lampu neon melalui relay atau MOSFET, serta mengirimkan data ke server secara nirkabel menggunakan protokol HTTP atau MQTT melalui koneksi Wi-Fi. Pada sisi server, data diterima dan disimpan dalam basis data MySQL melalui layanan web berbasis PHP, yang sekaligus menyediakan endpoint API untuk keperluan monitoring. Antarmuka dashboard dikembangkan dengan menggunakan Chart.js guna menampilkan visualisasi real-time dari tegangan, arus, suhu baterai, serta status lampu. Sistem juga memungkinkan kontrol manual lampu secara jarak jauh melalui dashboard tersebut. Hasil pengujian menunjukkan bahwa sistem mampu memberikan respons kendali yang andal, visualisasi data yang informatif, serta konsumsi daya yang rendah. Integrasi antara panel surya, IoT, dan antarmuka web ini menjadikan sistem sebagai solusi mandiri yang efisien untuk manajemen pencahayaan luar ruang, khususnya di lokasi yang minim akses listrik konvensional.
MYCD: Integration of YOLO-CNN and DenseNet for Real-Time Road Damage Detection Based on Field Images Helda Yenni; Rometdo Muzawi; Karpen Karpen; M. Khairul Anam; Michel Kasaf; Tjut Rizqi Maysyarah Hadi; Dewi Sari Wahyuni
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1040

Abstract

Road damage such as cracks, potholes, and uneven surfaces poses serious risks to transportation safety, logistics efficiency, and maintenance budgeting in Indonesia. Manual inspection is time consuming, labor intensive, and prone to error, motivating the use of reliable computer vision solutions. This study proposes MYCD, a hybrid and mobile ready architecture that combines the fast detection ability of YOLO with the dense feature reuse of DenseNet, enhanced by the Convolutional Block Attention Module (CBAM) for spatial and channel focus and Spatial Pyramid Pooling (SPP) for multi scale context understanding. The system detects and classifies the severity of road damage into minor, moderate, and severe categories using images captured by standard cameras. MYCD was trained and validated on 1,120 field images using an 80/20 split to simulate realistic deployment. Validation achieved 64 percent accuracy, with the highest per class precision of 0.72 for minor damage and mAP@0.5 = 0.677. The confusion matrix showed that most errors occurred in the moderate category because of visual similarity with minor and severe damage. Unlike earlier studies that extended YOLO with heavy backbones such as ResNet or EfficientNet, MYCD focuses on feature propagation (DenseNet), attention precision (CBAM), and multi scale fusion (SPP) optimized for real time operation on standard hardware. Efficiency profiling confirmed its deployability. After compression, the model size is 46.8 MB and it requires 3.7 GFLOPs per inference at 640×640 resolution. On a mid-range Android device (Snapdragon 778G, 8 GB RAM), MYCD runs at 19 frames per second with 1.2 GB peak memory. Compared with YOLOv8 WD (68 MB; 5.2 GFLOPs), MYCD reduces computation by 31 percent while maintaining similar accuracy. Overall, MYCD achieves a practical balance of speed, accuracy, and efficiency, providing a deployable and reproducible framework for real time road damage detection in resource limited settings.
Co-Authors Anam, M Khairul Dewi Sari Wahyuni Haris Tri Saputra Helda Yenni Irwansyah Sidabutar Karpen Karpen Mahdiyah, Evfi Michel Kasaf Rahmad Kurniawan Teguh Sujana Tjut Rizqi Maysyarah Hadi Windy Fahrurozi