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All Journal CESS (Journal of Computer Engineering, System and Science) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Djtechno: Jurnal Teknologi Informasi Jurnal Pengabdian Masyarakat IPTEK Jurnal Minfo Polgan (JMP) Digital Transformation Technology (Digitech) Journal Of Artificial Intelligence And Software Engineering eProceeding of TIK
Umri Erdiansyah
Politeknik Negeri Lhokseumawe
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Social Sciences

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Implementation of Website-Based Graduate Learning Outcomes Measurement System Erdiansyah, Umri; Syahputra, Guntur; Rudi, Fachri Yanuar
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.8584

Abstract

Digital transformation in higher education quality assurance has become imperative following the enactment of the Minister of Education, Culture, Research, and Technology Regulation No. 53 of 2023. This study proposes the development of a web-based Graduate Learning Outcomes (GLO) measurement system to accelerate academic evaluation effectiveness at Politeknik Negeri Lhokseumawe. Employing a Research and Development (RD) approach with the Waterfall development model, this research designs the system architecture using the Model-View-Controller (MVC) pattern to ensure application scalability and modularity. The system integrates academic data management features, automated GLO calculations, and analytical data visualization to support data-driven decision-making. System testing involved User Acceptance Testing (UAT), yielding a System Usability Scale (SUS) score of 82.3, indicating an 'excellent' user acceptance level. The results confirm that this platform not only meets national regulatory compliance standards but also enhances transparency and objectivity in graduate quality reporting. This implementation makes a strategic contribution to the modernization of institutional academic governance.
Implementation of WebSocket in an IoT-Based Smart Home Door Security System Using ESP32-CAM with Face Recognition Safriadi, Safriadi; Nasir, Muhammad; Erdiansyah, Umri
Journal of Artificial Intelligence and Software Engineering Vol 6, No 1 (2026): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i1.9052

Abstract

The advancement of Internet of Things technology, especially in the field of information technology, opens up opportunities in the development of smarter, more efficient, and flexible home security systems. Frequently used systems such as fingerprints and RFID still have limitations in flexibility, scalability, and effectiveness against threats. To overcome these problems, an IoT-based home door security system was developed using ESP 32 - CAM and face recognition technology. This system utilizes the Haar Cascade Classifier algorithm for face detection and the Local Binary Pattern Histogram for face recognition. Test results show a fast response, communication stability, and an increase in accuracy of 66.07% with 10 datasets, 86.07% with 50 datasets, and 93.03% with 100 datasets. This shows that the more datasets used, the higher the system's accuracy in recognizing user faces.
PENERAPAN RANDOM SAMPLING WITHOUT REPLACEMENT PADA GAME KUIS MATEMATIKA DESKTOP MENGGUNAKAN FITUR SEQUENTIAL LEVEL UNLOCKING Umri Erdiansyah
Djtechno: Jurnal Teknologi Informasi Vol 7, No 1 (2026): April
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v7i1.8613

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi game kuis edukasi matematika berbasis desktop yang ditujukan bagi siswa  sekolah dasar. Aplikasi ini dirancang dengan dua fitur utama: penerapan metode Random Sampling Without Replacement untuk pengacakan soal dan mekanisme penguncian level secara berurutan (sequential level unlocking). Tujuan metode pengacakan adalah untuk menjamin tidak ada soal yang berulang dalam satu sesi permainan dan urutan soal selalu bervariasi, sementara mekanisme penguncian level memastikan alur pembelajaran yang progresif. Prosedur pengembangan aplikasi menggunakan metodologi Penelitian dan Pengembangan (R&D) yang mencakup beberapa fase, khususnya pra-produksi, produksi, dan pasca-produksi. Hasil pengujian fungsional menunjukkan bahwa metode pengacakan berhasil diimplementasikan, terbukti dengan tidak adanya duplikasi soal dalam beberapa sesi percobaan. Selain itu, mekanisme penguncian tingkat juga beroperasi sesuai dengan desain, di mana tingkat selanjutnya bisa diakses hanya setelah individu menyelesaikan tingkat sebelumnya.
Penerapan Real-ESRGAN untuk Restorasi dan Rekompresi Arsip Penyiaran Video Resolusi Standar Umri Erdiansyah; Novira Dwina; Afla Nevrisa; Hosea Sitepu
Jurnal Minfo Polgan Vol. 15 No. 3 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i3.16521

Abstract

The modern broadcasting industry requires visual content in high-definition (HD) resolution. This technological transition creates critical issues in digital asset management, specifically regarding legacy broadcasting archives that are primarily recorded in standard definition (SD) formats. Conventional spatial interpolation approaches fail to address this issue, producing blurry and pixelated images. The application of artificial intelligence, particularly the Real-ESRGAN algorithm, offers a promising restoration solution. However, this implementation significantly increases the raw file size, making it impractical for local server storage. This research aims to find a precise equilibrium between visual quality enhancement using AI and storage efficiency through High-Efficiency Video Coding (HEVC) compression. This study uses a quantitative experimental method via laboratory-scale software engineering. The intervention phases include pixel reconstruction using the AI model and file size reduction using the HEVC standard. Data collection involved ten SD video samples. Real-ESRGAN qualitatively restores texture details and removes analog noise without excessive artifacts. Due to file size expansion, further compression using HEVC with varying Constant Rate Factor (CRF) parameters is being conducted to reduce the size by over 50% without severe Video Multimethod Assessment Fusion (VMAF) metric degradation. The integration of AI upscaling and HEVC compression creates a highly applicable workflow for television industry needs.
Co-Authors Abdi, Mustainul Afla Nevrisa Ahmadi Irmansyah Lubis Ananta, Adam bin Amirudin, Iphonsyah Feri Setiawan Guntur Syahputra Guntur Syahputra, Guntur Hosea Sitepu Ilham safar kamil erwansyah Lusiyanti Lusiyanti Muhammad Nasir Mukhlis Ramadhan Mursyidah Mursyidah Novira Dwina Rifki, Muhammad Aidil Rosma Siregar Rudi F, Fachri Yanuar RUDI, FACHRI YANUAR Safriadi Safriadi, Safriadi