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All Journal Majalah Ilmiah Pengkajian Industri
Adityo Suksmono, Adityo
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Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Engineering Industrial & Manufacturing Engineering Transportation

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PREDICTION OF INTERNAL COMBUSTION ENGINE PERFORMANCE USING ARTIFICIAL INTELLIGENCE Shalahuddin, Lukman; Suksmono, Adityo; Sembiring, Yohanes P
Majalah Ilmiah Pengkajian Industri Vol. 14 No. 2 (2020): Majalah Ilmiah Pengkajian Industri
Publisher : Deputi TIRBR-BPPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29122/mipi.v14i2.4164

Abstract

The potential of artificial intelligence (AI) application for prediction of internal combustion engine performance is assessed in this paper. A literature survey on this subject is first reviewed, in which previous researches utilized the advance of artificial neural networks (ANN) as one type of AI. Previous works commonly obtained the data from experimental engine tests. Under the same engines, they varied the fuel compositions or the engine operating conditions. Whereas in this study, an ANN model is developed to calculate the inputs from an engine simulation software package database and to predict the engine performance based on the simulation software outputs as the ANN target outputs. Results from the ANN model in the “learning” step indicates good agreement with the software simulation outputs. Improvement and development of the program are required, including optimation of the ANN model architecture, such as the choice of activation function, the number of neurons in the hidden layer, and the number of iterations, as well as the number and option of input engine parameters. The ANN model seems promising to predict engine performance, with root mean square errors in the range of 0.4-1.8%. Keywords: Artificial Intelligence; Neural Networks; Engine Performance.
CHARACTER RECOGNITION FOR INDONESIAN LICENSE PLATE BY USING IMAGE ENHANCEMENT AND CONVOLUTIONAL NEURAL NETWORK Bismantoko, Sahid; Rosyidi, M.; Chasanah, Umi; Suksmono, Adityo; Widodo, Tri
Majalah Ilmiah Pengkajian Industri Vol. 14 No. 2 (2020): Majalah Ilmiah Pengkajian Industri
Publisher : Deputi TIRBR-BPPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29122/mipi.v14i2.4198

Abstract

Many Intelligent Transport System technology have been applied in real world problems such as traffic monitoring, parking management, toll collection, law enforcement. ALPR system is one of the ITS technologies that is widely applied, however this ALPR system can not produce faultless recognition yet, especially for Indonesia license plate. In this research, image enhancement and Convolution Neural Network are proposed to the character recognition. The dataset used in this research are Indonesia license plate. The first step is train dataset to recognize character and evaluate the model with recall, precision, and f-1 score from test dataset. The model achieves accuracy and loss just over 0.99 and just below 0.01 on validation dataset respectively.Key Words : ALPR; ITS; Recall; Precision; F-1 Score; Accuracy; Loss.
Co-Authors Bismantoko, Sahid Chasanah, Umi Rosyidi, M. Sembiring, Yohanes P Shalahuddin, Lukman Tri Widodo