Article Per Year (5 Year)
p-Index From 2019 - 2024
2.189
P-Index
This Author published in this journals
All Journal Jurnal Sistem Komputer Journal of Information System Jurnal Komputer Terapan Techne : Jurnal Ilmiah Elektroteknika Jurnal ULTIMA Computing KOMPUTIKA - Jurnal Sistem Komputer KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Majalah Ilmiah UNIKOM JTT (Jurnal Teknologi Terapan) Indonesian Community Service and Empowerment Journal (IComSE) Jurnal Pengabdian Teknik dan Ilmu Komputer (PETIK)
Hidayat, Hidayat
Program Studi Teknik Komputer Universitas Komputer Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JTT (Jurnal Teknologi Terapan)

 1 
RANCANG BANGUN PENDETEKSI TINGKAT KEHIJAUAN WARNA DAUN PADI MENGGUNAKAN SENSOR WARNA TCS230 Hidayat Hidayat; Yazid Baihaqy
Jurnal Teknologi Terapan Vol 8, No 2 (2022): Jurnal Teknologi Terapan
Publisher : P3M Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31884/jtt.v8i2.435

Abstract

Fertilization of rice plants according to the dose of their needs is one of the important things to produce an optimal rice harvest. Giving less or more fertilizer can cause rice plants not to grow optimally and even cause crop failure. The need for fertilizer doses can be determined by changing the color of the rice leaves using the Leaf Color Chart (LCC). However, obstacles in the field are challenging for novice farmers to predict fertilizer needs just by looking at the color of the leaves with the naked eye. The application of information technology is expected to help farmers, especially novice farmers, in measuring the dose of fertilizer needed for rice plants. The technology that will be applied is an electronic device that can detect the color of rice leaves and provide information for users from the measurement results through an android application on a smartphone device. The electronics modules used are the TCS320 color sensor module which functions to detect the color of objects, the Arduino UNO microcontroller module which contains ATMega128 as a data processor, and the Bluetooth module as a communication liaison between the microcontroller device and the android application on the smartphone. The test results show that the built device can function properly. All tested leaves can be classified according to the greenish level of the leaf color.
Co-Authors A.A. Ketut Agung Cahyawan W Abd. Rasyid Syamsuri Afrizal Imanullah Andi Lasa Andre Ryadi Wardana Boni Al Amin Cecep Wiliam Depema Ginting Dwi Rahmatya, Myrna fajar rahmatullah Fajarianti, Oktavia Feri Moch. Suandi Liling Saputra Jaya Mudin Linda Nurjanah Maskie Z Oematan Muchammad Yaasiin Asshobry Muhammad Mahardiansyah Muhammad Yana Mulyana Mustopa Nur Hayat Myrna D Rahmatya Riani Lubis Ridlo Ferari Mauludi Sri Nurhayati Tri Pamungkas Usep Mohamad Ishaq Usep Mohamad Ishaq Wendi Zarman Wicaksono, Mochamad Fajar Yanti H. Puji Rahayu Yazid Baihaqy