Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Software Engineering, Information and Communication Technology Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Aditia Sanjaya
Universitas Negeri Medan
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Determination of Mango Fruit Maturity on the Tree Based on Digital Image Processing and Artificial Neural Networks Aditia Sanjaya; Ichwanul Muslim Karo Karo
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 1: June 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i1.52916

Abstract

Until now, humans have determined the ripeness of mangoes on the tree by hand. Losses are caused by the insecurity of the human state and a misunderstanding of the maturity level of mangoes. In the future, a system that can detect the ripeness of mangoes on the tree will be required. This research provides a preliminary examination of the technology's implementation. The study created a computerized image processing method for determining the ripeness of mangoes on the tree. The neural network backpropagation algorithm was employed in this investigation. The feature extraction model employed in the image is a hybrid of the RBG and HSV models. The best accuracy level is 72%, with an 80:20 ratio of test data to training data. 
Application of the Tsukamoto Fuzzy Inference System Method for Rainfall Prediction in the Adolina Area Aditia Sanjaya
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2281

Abstract

Rainfall is one of the key elements in the climate system that significantly affects various sectors, such as agriculture, spatial planning, and disaster mitigation. Adolina, a region with tropical weather characteristics and highly fluctuating rainfall, requires an accurate prediction system to support informed decision-making. This study applies the Fuzzy Inference System (FIS) Tsukamoto method to predict rainfall based on input variables such as air temperature, humidity, and wind speed. The Tsukamoto method is chosen for its capability to handle uncertainty and produce crisp output values through inference and defuzzification processes based on a set of fuzzy rules. The results show that the Tsukamoto FIS provides reasonably accurate and consistent rainfall predictions with a low error rate. Therefore, this approach can serve as an effective alternative in weather decision-support systems for the Adolina area.
Co-Authors Ichwanul Muslim Karo Karo