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Telcomatics
Published by Universitas Internasional Batam
ISSN : -     EISSN : 25415867     DOI : http://dx.doi.org/10.37253/telcomatics.v5i1.838
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Telcomatics is a peer reviewed Journal in English or Bahasa Indonesia published two issues per year (June and December). The aim of Telcomatics is to publish articles dedicated to all aspects of the latest outstanding developments in the field of Electrical Engineering and Information System. Telcomatics Journal welcomes full research articles in the following engineering subject areas: Telecommunication and Information Technology Applied Computing and Computer Instrumentation and Control Electronic Computer Security Computer Network Image Processing Mechatronic and Robotic Network Traffic Modeling Game Technology Intelligent System
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 1 Documents
 1 
Search results for , issue "Vol 5 No 2 (2020)" : 1 Documents clear
Penentuan Posisi Objek Berbasis Image Processing Dengan Menggunakan Metode Convolutional Neural Network Ni'matul Ma'muriyah; Hendra Son Simon
Telcomatics Vol 5 No 2 (2020)
Publisher : Universitas Internasional Batam

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Abstract

Sistem yang dirancang menggunakan Raspberry Pi sebagai mikrokontroller yang akan melakukan pengolahan data-data pembelajaran machine learning dengan bantuan pi camera sebagai sensor pembacaan. Pembacaan melalui kamera digunakan untuk mengidentifikasi posisi objek sesuai dari pembelajaran data. Sistem machine learning yang digunakan berupa tensorflow. Hasil Pembacaan dan analisa menunjukkan sistem dapat mengidentifikasi posisi objek yaitu dari penempatan objek dalam gambar. Terdapat juga kesalahan pembacaan pada objek dikarenakan pembelajaran disesuaikan dengan data yang diberikan, dimana data yang diberikan tersebut dipilah secara manual oleh penulis. The system is designed to use the Raspberry Pi as a microcontroller that will process machine learning data with the help of a pi camera as a reading sensor. Reading through the camera is used to identify the position of the object according to the learning data. The machine learning system used is tensorflow. The results of reading and analysis show that the system can identify the position of the object, namely from the placement of the object in the image. There are also reading errors on the object because learning is adjusted to the data provided, where the data provided is manually sorted by the author.

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