Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Civil Engineering Dimension Dimensi Utama Teknik Sipil
Doddy Prayogo
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture

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

Found 3 Documents
Search

 1 
Metaheuristic-Based Machine Learning System for Prediction of Compressive Strength based on Concrete Mixture Properties and Early-Age Strength Test Results Doddy Prayogo
Civil Engineering Dimension Vol. 20 No. 1 (2018): MARCH 2018
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (887.032 KB) | DOI: 10.9744/ced.20.1.21-29

Abstract

Estimating the accurate concrete strength has become a critical issue in civil engi­neer­ing. The 28-day concrete cylinder test results depict the concrete's characteristic strength which was prepared and cast as part of the concrete work on the project. Waiting 28 days is important to guarantee the quality control of the procedure, even though it is a slow process. This research develops an advanced machine learning method to forecast the concrete compressive strength using the concrete mix proportion and early-age strength test results. Thirty-eight historical cases in total were used to create the intelligence prediction method. The results obtained indicate the effectiveness of the advanced hybrid machine learning strategy in forecasting the strength of the concrete with a comparatively high degree of accuracy calculated using 4 error indicators. As a result, the suggested study can provide a great advantage for construction project managers in decision-making procedures that depend on early strength results of the tests.
OPTIMIZED MANAGEMENT STRATEGY FOR CONSTRUCTION PROJECTS CONSIDERING THE TRADE-OFF OF ESTIMATE SCHEDULE AND COST AT COMPLETION Liem Stefani Meilia Gunawan; Min-Yuan Cheng; Doddy Prayogo
Dimensi Utama Teknik Sipil Vol 6 No 2 (2019): October 2019
Publisher : Program Studi Magister Teknik Sipil - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (817.013 KB) | DOI: 10.9744/duts.6.2.26-37

Abstract

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. In this research, SOS-NN-LSTM is required to establish the estimate schedule to completion (ESTC) and estimate cost to completion (ECTC) prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between estimate schedule at completion (ESAC) dan estimate cost at completion (ECAC) which give the decision-maker preference.
OPTIMIZED MANAGEMENT STRATEGY FOR CONSTRUCTION PROJECTS CONSIDERING THE TRADE-OFF OF ESTIMATE SCHEDULE AND COST AT COMPLETION Liem Stefani Meilia Gunawan; Min-Yuan Cheng; Doddy Prayogo
Dimensi Utama Teknik Sipil Vol. 6 No. 2 (2019): October 2019
Publisher : Program Studi Magister Teknik Sipil - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/duts.6.2.26-37

Abstract

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. In this research, SOS-NN-LSTM is required to establish the estimate schedule to completion (ESTC) and estimate cost to completion (ECTC) prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between estimate schedule at completion (ESAC) dan estimate cost at completion (ECAC) which give the decision-maker preference.
Co-Authors Liem Stefani Meilia Gunawan Min-Yuan Cheng