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All Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Jurnal Tika Jurnal Pengabdian Rekayasa dan Wirausaha
Ramadhana, Rizka
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Game Edukasi Pengenalan Nama-Nama Sayuran Menggunakan Metode Development Life Cycle Rizani, Fitri; Ramadhana, Rizka
Jurnal Tika Vol 7 No 3 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v7i3.1605

Abstract

This study aims to produce and test the feasibility of an educational game to recognize the names of vegetables for kindergarten children aged 4 to 6 years made using Construct 2 software. This game contains several games, namely guess pictures and arrange letters where the game is used as a learning medium for children. kindergarten level. The research method used is the Multimedia Development Life Cycle method that uses research stages (1) Concept, (2) Design, (3) Material Collection, (4) manufacture, (5) testing, (6) distribution. This study concludes that attractively designed interactive learning multimedia will generate motivation and stimulation for student learning activities, help students improve understanding of learning materials and foster learning creativity so that it will have an impact on improving the quality of learning. The results of this study are an application of the introduction of the names of vegetables that can help teachers in conveying material about learning the names of vegetables to students
Penerapan Sistem Pengelolaan Air Sisa Wudhu Otomatis Berbasis IoT di Mushalla Darul Faizin, Desa Kopelma Darussalam Amanda, Silviani; Yufnanda, Muhammad Aditya; Rizky, Muharratul Mina; Ramadhana, Rizka; Aulia, Niza; Dawood, Rahmad; Leo, Hendrik
Jurnal Pengabdian Rekayasa dan Wirausaha Vol 2, No 2 (2025)
Publisher : Universitas Syiah Kuala

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Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan di Mushalla Darul Faizin, Banda Aceh, yang menghadapi permasalahan tingginya konsumsi air bersih akibat belum adanya sistem pengelolaan air wudhu yang efisien. Air sisa wudhu yang masih tergolong layak digunakan kembali selama ini langsung dibuang ke saluran pembuangan tanpa pemanfaatan lebih lanjut. Melalui kegiatan ini, tim pengabdian mengembangkan dan menerapkan sistem daur ulang air wudhu otomatis berbasis Internet of Things (IoT) yang berfungsi untuk mendeteksi, mengumpulkan, menyaring, serta mendistribusikan kembali air sisa wudhu untuk keperluan non-konsumsi seperti pembersihan lantai dan penyiraman tanaman. Sistem ini menggunakan mikrokontroler ESP32, sensor ultrasonik untuk pemantauan level air secara real-time, serta integrasi platform Telegram bot untuk memudahkan pengurus mushalla dalam melakukan monitoring dan kontrol jarak jauh. Hasil implementasi menunjukkan bahwa sistem beroperasi stabil dengan reliabilitas mencapai 98,2% dan mampu menghemat penggunaan air bersih hingga sekitar 30%. Selain menghasilkan solusi teknologis yang efisien, kegiatan ini juga meningkatkan kesadaran dan kapasitas pengurus mushalla dalam pengelolaan sumber daya air secara mandiri dan berkelanjutan.
Enhancing Face Detection Performance in Low-Light Conditions Using NIR Thermal Imaging and Image Morphology Oktiana, Maulisa; Azra, Cut Salsabilla; Muharar, Rusdha; Islamy, Fajrul; Ramadhana, Rizka; Melinda, Melinda; Aulia, Niza; Rizky, Muharratul Mina; Fitria, Maya
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 2 (2025): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.7.2.108786

Abstract

Face detection plays a vital role in biometric, security, and surveillance systems. Conventional approaches based on the visible light (VIS) spectrum often suffer performance degradation under poor lighting conditions, limiting their reliability. To address this issue, this study employs thermal imagery in the Near-Infrared (NIR) spectrum, which is less affected by ambient light, combined with image morphology operations to enhance segmentation accuracy. Experiments were conducted using the LDHF-DB dataset (300 images at distances of 1 m, 60 m, and 100 m) and a subset of the Tuft dataset (60 images). Face detection was performed using the HOG + SVM method, followed by Otsu thresholding and morphological operations. Performance was evaluated using Peak Signal-to-Noise Ratio (PSNR). Results show that applying morphological operations significantly improves PSNR values, with an average increase of more than 35%. The best performance was achieved on the 1 m subset, while longer distances presented greater challenges. These findings highlight the potential of integrating NIR thermal imagery and morphological processing to improve the robustness and reliability of face detection systems in low-light environments.
Co-Authors Amanda, Silviani Aulia, Niza Azra, Cut Salsabilla Islamy, Fajrul Leo, Hendrik Maya Fitria Melinda Melinda Muharratul Mina Rizky Oktiana, Maulisa Rahmad Dawood Rizani, Fitri Rizky, Muharratul Mina Rusdha Muharar, Rusdha Yufnanda, Muhammad Aditya