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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Jaringan Telekomunikasi Jurnal ELTEK Science Information System and Technology Jurnal ELTEK
Abdul Rasyid
Jurusan Teknik Elektro, Politeknik Negeri Malang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Implementation of Convolutional Neural Network (CNN) Method for Fish Processed Cuisine Image Identification Application with Google Maps Features Rachmad Saptono; Abdul Rasyid; Waluyo Waluyo; Farida Arinie Soelistianto
West Science Information System and Technology Vol. 2 No. 01 (2024): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v2i01.863

Abstract

The rapid advancement of science and technology encourages dynamic transformation in various sectors, especially in the field of information and communication technology (ICT), especially with the existence of Android-based smartphones. This advancement revolutionizes the way we access information, especially about various processed fish dishes in Indonesia. However, despite the plethora of culinary offerings, travelers often find it difficult to discover traditional dishes through social media platforms. To bridge this gap, a new app that utilizes artificial neural networks has been developed. The app allows users to photograph and upload images of processed fish dishes to recognize and provide detailed descriptions and recipes. In addition, integrating Google Maps makes it easy for users to find nearby places that serve these dishes. Testing the app with a dataset consisting of 1577 images of six types of processed fish dishes yielded promising results, with accuracy reaching 97.57% over 120 epochs. This innovation not only preserves cultural heritage but also enhances the culinary experience for locals and tourists.
Implementasi peer to peer networking pada headset untuk streaming audio berbasis internet of things Rizky Ardiansyah; Anita Marselia; Rieke Adriati Wijayanti; Putri Elfa Masudia; Abdul Rasyid; Adzikirani Adzikirani; Arinalhaq Fatachul Aziz
JURNAL ELTEK Vol. 24 No. 1 (2026): April 2026
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/eltek.v24i1.8498

Abstract

Penelitian ini mengevaluasi headset berbasis IoT untuk komunikasi di lingkungan kampus menggunakan protokol UDP dan ESP32 dalam jaringan peer-to-peer untuk streaming suara real-time. Hasil pengujian menunjukkan bahwa ketiga headset menghasilkan suara dengan intensitas rata-rata 65.62 dBA, nyaman untuk penggunaan sehari-hari, dan lebih efisien dalam memperkuat suara ponsel (65.82 dBA) dibandingkan suara manusia (65.43 dBA). Delay meningkat seiring bertambahnya jarak: 1.15 detik pada 1.5 meter, 3.18 detik pada 3 meter, dan 4.02 detik pada 4.5 meter. Survei pengguna menunjukkan pandangan positif terhadap kualitas suara dan minimnya noise, meskipun beberapa melaporkan adanya delay. Headset ini terbukti andal dan serbaguna, memberikan pengalaman mendengarkan yang konsisten dan efisien.   ABSTRACT This study evaluates IoT-based headsets for campus communication using UDP and ESP32 protocols in a peer-to-peer network for real-time voice streaming. Test results show that all three headsets produce sound with an average intensity of 65.62 dBA, comfortable for everyday use, and more efficient in amplifying mobile phone sounds (65.82 dBA) than human voices (65.43 dBA). Delay increases with distance: 1.15 seconds at 1.5 meters, 3.18 seconds at 3 meters, and 4.02 seconds at 4.5 meters. User surveys show positive views on sound quality and minimal noise, although some report delays. The headsets prove to be reliable and versatile, providing a consistent and efficient listening experience.
Co-Authors Adzikirani Adzikirani Ahmad Wahyu Purwandi Ahmad Wilda Y Aisah Aisah Allyza Nanda Purwari Anggita Sukma Nur Anggraini Anita Marselia Arinalhaq Fatachul Arinalhaq Fatachul Aziz Binti Asfaki Ludiyah Dania Sartika Anggraeni Ellen Kurniawati Farida Arinie Soelistianto Ganner Antero Guntur Wahyu Sejati Hudiono Hudiono Kalam Achmad Nabila Lis Diana Mustafa Malika Aditya Marina Annisa Fitri Martono Dwi Atmadja Mochammad Junus Moh. Abdullah Anshori Muhammad Syirajuddin S. Nugroho Suharto Putri Elfa Masudia Rachmad Saptono Rieke Adriati Wijayanti Rieke Wijayanti Rizky Ardiansyah Waluyo Waluyo wildana ahmad priadiyatna Yoga Kholilul Akbar Pradana S