Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH
Solikhun Solikhun
STIKOM Tunas Bangsa Pematang Siantar, Indonesia
Automotive Engineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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

Found 2 Documents
Search

 1 
Fletcher-reeves algorithm for predicting the quantity of production tomato plants in indonesia Rifani Haikal; Mochamad Wahyudi; Lise Pujiastuti; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 3 (2022): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v11i3.47

Abstract

The growth of Indonesia's tomato plants continues to increase, and this increase needs to be balanced, according to data from 2015 to 2020. Tomatoes should be used all the time, even in Indonesia. Tomatoes are not only edible but also good for your health and appearance. For the government and various conferences to include this as a point of view in dealing with this problem, it is important to look at the amount of tomato production in Indonesia. Data from the Central Statistics Agency was used to obtain statistics on tomato plant cultivation in Indonesia from 2015 to 2020. This data is solved using the Fletcher-Reeves algorithm using architectural models 2-10-1, 2-20-1, 2-30-1, and 2-35-1. Model 2-10-1 is the best architectural model to predict the amount of tomato production compared to other models, according to the training and testing results of the four models. Model 2-10-1 is used to measure the accuracy of the Fletcher-Reeves method, with MSE Training set at 0.00008463 and MSE Testing at 0.0006094.
Implementation of Conjugate Gradient Bacpropagation Algorithm in Predicting the Percentage of Formal Labor in Sumatran Pulau Julius Sitanggang; Verdi Yasin; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 3 (2022): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v11i3.49

Abstract

Formal workers work for companies as trained workers or those whose job status is employees and employees. They get stronger legal protection and official employment contracts and are in organizations that are legal entities. This paper aims to prove and implement the conjugate gradient backpropagation algorithm that can predict data on trends in formal labour on the island of Sumatra's impact Covid-19. The research data is on the percentage of formal workers on the island of Sumatra in 2015-2021, whose source is the Central Statistics Agency (BPS). This study uses 5 architectural models, namely 5-10-1, 5-15-1, 5-20-1, 5-25-1, 5-25-1, 5-30-1, 5-35-1. Of the five architectural models that have been used, the best architecture is obtained, namely the 5-20-1 model with a perf result of 0.000000002, literacy 292 in 4 seconds
Co-Authors Julius Sitanggang Lise Pujiastuti Mochamad Wahyudi Rifani Haikal Verdi Yasin