Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal PROXIES Jurnal Litbang Provinsi Jawa Tengah Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Yulianto Tejo Putranto
Fakultas Llmu Komputer Unika Soegijapranata Semarang
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Public Health Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
SISTEM PENYIRAMAN TANAMAN OTOMATIS BERBASIS ARDUINO Herawati, Rosita; Putranto, Yulianto Tejo
PROXIES Vol 2, No 1 (2013)
Publisher : PROXIES

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper discusses the automatic plant watering system, a simple but useful by using Arduino. Watering systems based on sensor readings at a planting medium (soil), which is read by the Arduino. The sensor detects the level of humidity and dryness of the planting medium. Arduino connected to a relay system that will disconnect or connect the electrical cu"ent of the solenoid valve. Thus, at a certain level of dryness or humidity, the solenoid valve opens, and the watering process takes place. The level of dryness of the media obtalnedfrom the initial experiment Keywords: Ardulno, automatic watering, dryness sensor
PERANCANGAN PENGATURAN SISTEM TRAFFIC LIGHT BERDASARKAN JUMLAH KENDARAAN DENGAN MENGGUNAKAN CCTV DINAMIS Florentinus Budi Setiawan; Erdhi Widyarto Nugroho; Yulianto Tejo Putranto
JURNAL LITBANG PROVINSI JAWA TENGAH Vol 8 No 2 (2010): Jurnal Litbang Provinsi Jawa Tengah
Publisher : Badan Perencanaan Pembangunan, Penelitian dan Pengembangan Daerah Provinsi Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36762/jurnaljateng.v8i2.263

Abstract

Intelligent Traffic System (ITS) implementation as an integrated control system needs some up-to-date data and many detectors for supporting system. Some research use the static CCTV camera to detect traffic density, vehicle speed and vehicle quantity. But there is no method for detecting the dynamic area with dynamic CCTV. The ain of the research is design of controlled traffic light system based on data of the vehicle quantity obtained by CCTV picture capture. The advantage of the research result is obtain the automatic and adaptive traffic light system based on the number of the vehicle. The recent ITS need some camera for some road that enter the crossing. The proposed systems only need one CCTV that dynamically supervising the number of vehicle. Conclusion of the research is that the camera can be used as traffic density detector. The picture that captured by this camera can be processed digitally, so that we obtain the traffic data. Data of the traffic condition are used as the reference for controlling the green lamp on each road on the cross. The other result is obtaining the prototype of hardware and software based on the research conclusion.
Modifikasi Fitur dengan Differential Asymmetry untuk Meningkatkan Akurasi Klasifikasi EEG Motor Imagery Yulianto Tejo Putranto; Tri Arief Sardjono; Mochamad Hariadi; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 8 No 1: Februari 2019
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1090.653 KB)

Abstract

Brain-Computer Interface (BCI) technology has enabled people with motor disabilities to interact with their environment. The electroencephalograph (EEG) signals related to a motor imagery movement were used as a control signal. In this paper, EEG motor imagery signals from the 2-class data have been processed into features and classified. The power and standard deviation of EEG signals, mean of absolute wavelet coefficients, and the average power of the wavelet coefficients were used as features. The purpose of this paper is to apply the differential asymmetry of these features as new features to improve the system accuracy. As a classifier, Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), and Tree were used. The result shows that for dataset I the use of differential asymmetry as feature can increase the system accuracy up to 47.8%, from 52.20% to 100%, with Tree as a classifier. For dataset II, it can increase accuracy by 8.46%, from 54.42% to 62.48%.
Co-Authors Erdhi Widyarto Florentinus Budi Setiawan Florentinus Budi Setiawan Mauridhi Hery Purnomo Mochamad Hariadi Rosita Herawati, Rosita Tri Arief Sardjono