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All Journal Jurnal Informatika: Jurnal Pengembangan IT Jurnal PRINTER : Jurnal Pengembangan Rekayasa Informatika dan Komputer
Zulkipli Zulkipli
Universitas Hamzanwadi
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Rancang Bangun Sistem Smart Home Berbasis Google Assistant dengan Kendali Perintah Suara Muh Sofiyan; Aris Sudianto; Zulkipli Zulkipli
Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer Vol. 4 No. 1 (2026): Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jprinter.v4i1.32686

Abstract

Perkembangan teknologi Internet of Things IoT memberikan peluang besar dalam menciptakan sistem rumah cerdas (smart home) yang mampu meningkatkan efisien, kenyamanan, serta aksesibilitas bagi pengguna. Penelitian ini merancang dan membangun sistem smart home berbasis Google Assistant dengan kendali perintah suara untuk mengontrol perangkat elektronik rumah tangga, khususnya lampu dan kipas. Sistem ini menggunakan mikrokontroler ESP32 sebagai pengendali utama, modul relay sebagai saklar elektronik, serta integrasi dengan Arduino Cloud yang berfungsi sebagai perantara komunikasi antara Google Assistant dengan perangkat keras. Metode pengembangan sistem menggunakan pendekatan prototype dengan tahapan identifikasi masalah, pengumpulan kebutuhan sistem, perancangan sistem, pengembangan sistem, pengujian sistem, dan evaluasi sistem. Hasil implementasi menunjukkan bahwa sistem mampu mengendalikan perangkat elektronik secara otomatis melalui perintah suara dengan tingkat keberhasilan rata-rata 98.33% dan rata-rata waktu respon 1.83 detik. Hal ini membuktikan bahwa sistem yang dibangun cukup responsif, akurat, serta dapat diandalkan dalam penggunaan sehari-hari. Sistem ini juga memberikan kemudahan bagi pengguna dengan keterbatasan mobilitas seperti lansia dan penyandang disabilitas.
Analisis Perbandingan Kinerja Metode GFPGAN dan RestoreFormer dalam Restorasi Foto Lama Hariman Bahtiar; Amri Muliawan Nur; Almi Yulistia Alwanda; Zulkipli Zulkipli
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10291

Abstract

A This study aims to analyze and compare the performance of two artificial intelligence–based image restoration methods, namely GFPGAN (Generative Facial Prior GAN) and RestoreFormer, in enhancing the quality of old photographs of TGKH. Muhammad Zainuddin Abdul Madjid. Both methods were tested on images that had undergone visual degradation, with OpenCV used as a conventional baseline. The evaluation was conducted using two main parameters: processing time and result quality, measured through the Peak Signal-to-Noise Ratio (PSNR) metric. The results show that GFPGAN produced the best outcome, achieving the highest PSNR value (32.8 dB) and the fastest processing time (9 seconds), generating sharp and realistic facial details. RestoreFormer yielded nearly comparable quality with a PSNR of approximately 30 dB and a slightly longer processing time (10 seconds), but it demonstrated greater consistency in preserving the authenticity of textures and structural details. Meanwhile, the manual OpenCV-based method achieved only moderate improvement (25.2 dB) with the longest processing time (12.5 seconds). These findings indicate that AI-based technologies, particularly GFPGAN and RestoreFormer, hold great potential for the preservation of historical visual archives, as they can significantly enhance the quality of old photographs while maintaining their original visual character. The combination of both methods is recommended for digital restoration efforts that balance technical efficiency and cultural authenticity.
Co-Authors Almi Yulistia Alwanda Aris Sudianto Bahtiar, Hariman Muh Sofiyan Nur, Amri Muliawan