Article Per Year (5 Year)
p-Index From 2020 - 2025
4.328
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) TEKNIK Jurnal Teknik Elektro Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Seri Kajian Ilmiah ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika PROtek : Jurnal Ilmiah Teknik Elektro Sinkron : Jurnal dan Penelitian Teknik Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Elektronika dan Telekomunikasi KACANEGARA Jurnal Pengabdian pada Masyarakat PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Journal of Robotics and Control (JRC) JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Journal of Telecommunication, Electronics and Control Engineering (JTECE) Jurnal INFOTEL Emitor: Jurnal Teknik Elektro
Leonardus Heru Pratomo
Seogijapranata Catholic University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : PROtek : Jurnal Ilmiah Teknik Elektro

 1 
Design of Audiosonic Frequency Wave Therapy Tool With Arduino Mega-Based Spectrum Analyzer Monitoring Setiawan, Florentinus Budi; Prasetyo, Daniel Danin; Pratomo, Leonardus Heru
PROtek : Jurnal Ilmiah Teknik Elektro Vol 10, No 1 (2023): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v10i1.5536

Abstract

As technology develops, more and more devices can produce or record sound waves. There are currently a lot of sound wave generators in use; however, the frequency output range of these generators is highly constrained. This study is being done to help doctors or the general public treat specific illnesses or disorders such as neurological disorders, headaches, and stomach digestion issues. This prototype was created using experimental or lab techniques. by running tests on the variables being utilized. The Arduino Mega 2560 microcontroller is used to operate this prototype. The Arduino Mega 2560 employs the C and C+ programming languages for its code. The Arduino Mega 2560 may be used to modify the keypad's output frequency, amplitude, and data input. This tool is designed to be able to output frequencies of 20 Hz to 20,000 Hz (human sound). In this study, it has an output in the form of frequencies produced from speakers with test frequencies, namely 200 Hz, 10 kHz, and 17 kHz
Fruit Ripeness Classification System Using Convolutional Neural Network (CNN) Method Setiawan, Florentinus Budi; Adipradana, Christophorus Bramantya; Pratomo, Leonardus Heru
PROtek : Jurnal Ilmiah Teknik Elektro Vol 10, No 1 (2023): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v10i1.5549

Abstract

The increasing consumer demand in the fruit industry has also demanded that various sectors of the fruit processing industry be able to adapt to this situation. The demand for good quality and fresh fruit requires technological advances and supporting systems that can be used in the fruit processing industry to produce the best quality fruit. Referring to this, this study aims to detect the type and maturity of fruit using machine learning with the CNN (Convolutional Neural Network) method using the function of a camera that is integrated with the program algorithm. This research is a refinement of previous research that has been made at the university by increasing the ability to read objects based on color with different methods. In this programming language, Python also requires several additional libraries to carry out the object detection process, namely by using the cvzone library as the main library. This study shows that the detection of fruit and ripeness using the CNN method was successful in detecting the type and maturity of the fruit. In the design and trial of this research, it can run well according to the algorithm created by the researcher. The success rate and accuracy of the detection of the type and maturity of this fruit reach 90%.
Co-Authors Adipradana, Christophorus Bramantya Anggoro, Giovani Chrisantus Budi Setiawan, Florentius Cahyadi, Bagus Kusuma Candra, Kevin CHRISTIAWAN, HAPPY DIPTYA EKA DAGOMIS, IVANILES PUTRA UTAMA Daniel Santoso FIRMANTO, DANIEL RAHADIAN Florentinus Budi Setiawan Kariman, Paskal Kristiawan, Iwan Kusumaningrum, Nazila Muntaha, Ilyas Nugraha, Rico Adrian Paudel, Sushil Prasetyo, Daniel Danin Pujianto, Eko Yoyok Rizky Amalia Selamet Riyadi Setiawan, Florentinus Budi Setiyawan, Fahrul Indra SETO, EMANNUEL BAYU Setyawan, Florentinus Budi Siregar, Pascal Slamet Riyadi Tantyono, Neru Hatta Wardani, Agata Dita Wasiatno, Juan Marco Alexander Wijaya, Jonathan