Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Energy: Jurnal Ilmiah Ilmu-ilmu Teknik
Walid , Miftahul
Unknown Affiliation
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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

Found 3 Documents
Search

 1 
Development of Automatic Sprinklers and Monitoring of Red Chilli Cultivation Based on the Internet of Things (IoT) Walid , Miftahul; Burhan , Sohibul
ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK Vol. 13 No. 1 (2023): ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK
Publisher : Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/energy.v13i1.p1-7

Abstract

Current technology has significantly impacted various sectors of life, including education, government offices, and agriculture. The use of information technology aims to simplify and bring efficiency to various aspects. In this era of globalization, technology plays a crucial role for Indonesia, a country that lags behind in technological advancements, especially in the field of agriculture. Clear innovation is needed for this nation to compete on the international stage. The presence of technology that helps improve human work efficiency and effectiveness should undoubtedly be developed in the a gricultural sector. Traditional farmers can utilize technology to enhance their performance and achieve better and higher yields. Red chili peppers are one of the important agricultural commodities that need to be developed due to their high economic value. They are a national and regional flagship commodity and hold a significant position in the food menu as they are consumed daily by almost the entire population of Indonesia, albeit in small quantities. This plant can grow well in both lowland and highland areas, but its growth is better in lowland regions. The ideal air temperature for chili pepper growth is between 18-27°C, as temperatures below 16°C and above 32°C can hinder fertilization. As for soil moisture, chili pepper plants require 60% - 80%  humidity. Cultivating red chili peppers in limited land, either directly or in pots, can be a solution to address scarcity and meet family needs. Smart garden technology serves a purpose and provides benefits to farmers or plant owners, serving as a communication solution with plants.
Document Signature Image Recognition System Using the CNN (Convolutional Neural Network) Method Jannah, Raudlatul; Walid , Miftahul; Hoiriyah
ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK Vol. 12 No. 2 (2022): ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK
Publisher : Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/energy.v12i2.p54-61

Abstract

A signature is a marker or identity in a document. Signatures have an essential role in verifying and legalizing documents. The signature is not just any sign but is a legal one and is the original image of the owner. With the development of today's technology, signature pattern identification can not only be done manually but can also be  done  with  the  help  of  a  computer.  However,  computers  cannot  immediately  carry  out  the  identification process, instead, a pattern recognition process is needed beforehand which can be done by extracting signature features.  This  research  aims  to  determine  signature  ownership,  so  identification  is  required.  Identification  of signature  patterns  is  needed  to  recognize  and  distinguish  the  signatures  of  each  individual based  on  the characteristics  of  the  signature.  Therefore  this  research  is  expected  to  be  an  alternative  to  minimize  signature recognition errors using the CNN (convolutional neural network) method. then taken with a scanner. The results of this research are that the Convolutional Neural Network method can recognize each signature image with an accuracy of 100% in the validation testing process and 85% in the testing process.
Digital Image Processing for Identification of Types of Skin Diseases Using the Convolutional Neural Network (CNN) Method Ria, Sona Nova; Walid , Miftahul; Umam, Busro Akramul
ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK Vol. 12 No. 2 (2022): ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK
Publisher : Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/energy.v12i2.p62-67

Abstract

Skin disease is the most common disease and the fastest to infect the human body. This happens because the skin is the first organ to receive stimulation from the outside in the form of touch, temperature and other stimuli. Skin disease  consists  of  several  types  that  have  a  color  texture  that  is  almost  the  same  by  naked  eye.  Thus,  an approach  is  needed  to  recognize  the  types  of  skin  diseases  with  the  help  of  image  processing  systems  and artificial  neural  networks.  The  identification  method  used  in  this  study  is  the  Convolutional  Neural  Network (CNN).  The  infected  skin  image  is  used  as  an  input  image for  image processing.  Prior  to identification,  image pre-processing was carried out, namely resizing, grayscaling, using the Convolutional Neural Network method. The  testing  process  in  this  study  used  70  types  of  skin  disease  images  for  validation  data  and  35  types  of  skin disease  images  for  data  testing.  The  results  of  this  study  the  Convolutional  Neural  Network  method  can recognize  each  image  of  a  type  of  skin  disease  with  anaccuracy  of  98%  in  the  validation  testing  process  and 85% in the testing process.
Co-Authors Burhan , Sohibul Hoiriyah Raudlatul Jannah Ria, Sona Nova Umam, Busro Akramul