Application of Genetic Algorithm-Multiple Linear Regression and Artificial Neural Network Determinations for Prediction of Kovats Retention Index

Idroes, Rinaldi; Noviandy, Teuku Rizky; Maulana, Arif; Suhendra, Rivansyah; Sasmita, Novi Reandy; Muslem, Muslem; Idroes, Ghazi Mauer; Kemala, Pati; Irvanizam, Irvanizam

doi:10.15866/iremos.v14i2.20460

Cited by 28 publications

(24 citation statements)

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“…where t k is output target. With giving a training parameter value α, it then calculates the weight and bias corrections that will be used later to update the w jk value by using Equations ( 10) and (11), respectively.…”

Section: Methodology a The Procedures Of Backpropagation Ann Algorithmmentioning

confidence: 99%

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Applying Artificial Neural Network Based on Backpropagation Method for Indonesian Sign Language Recognition

Irvanizam,

Horatius,

Sofyan

2023

IJCDS

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Sign-language is a nonverbal language utilized by hearing loss and speech disorder people to interact and speak with each other. Sometimes people call it a visual-language utilizing hand gestures and changes in hand shape to express intentions and thoughts. In Indonesia, people use two sign language types commonly. They are Indonesian Signal System (ISS) and Indonesian Sign Language (ISL). In this paper, we investigated research on the recognition of ISL alphabets by proposing an application using the Artificial Neural Network algorithm with the principle of the Backpropagation method for dealing with this research. Firstly, we performed preprocessing the image data sequentially by splitting the dataset, labeling the dataset based on the alphabet types, scaling the images into a size of 150x150 pixels, and segmentizing the datasets to eliminate noise in the image to yield color, grayscale, binary segmentations, and image edge detection. Later on, we split the dataset and distributed them into training and testing sets with two different proportions, 70:30 and 80:20 percent. After applying the algorithm, we obtained the highest accuracy at 80:20 data proportions using an epoch of 700, a learning rate of 0.001, a batch size of 25, and some hidden nodes of 100 was 98.41 percent.

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Section: Methodology a The Procedures Of Backpropagation Ann Algorithmmentioning

confidence: 99%

“…Maulana et al [10] utilized ANN to predict Kovats retention indices for some chemical compounds. Idroes et al [11] integrated ANN and genetic algorithms to forecast Kovats retention indices.…”

Section: Related Workmentioning

confidence: 99%

Applying Artificial Neural Network Based on Backpropagation Method for Indonesian Sign Language Recognition

Irvanizam,

Horatius,

Sofyan

2023

IJCDS

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“…In recent years, AI has witnessed important breakthroughs, particularly in machine learning [3,4] and natural language processing [5,6]. The remarkable success of AI in addressing complex tasks like image recognition [7][8][9], language translation [10], and predictive modeling [11,12] has sparked the development of even more sophisticated applications across various sectors of life.…”

Section: Introductionmentioning

confidence: 99%

Student Perspectives on the Role of Artificial Intelligence in Education: A Survey-Based Analysis

Idroes,

Noviandy,

Maulana

et al. 2023

J. Educ. Manag. Learn.

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Artificial intelligence (AI) has emerged as a powerful technology that has the potential to transform education. This study aims to comprehensively understand students' perspectives on using AI within educational settings to gain insights about the role of AI in education and investigate their perceptions regarding the advantages, challenges, and expectations associated with integrating AI into the learning process. We analyzed the student responses from a survey that targeted students from diverse academic backgrounds and educational levels. The results show that, in general, students have a positive perception of AI and believe AI is beneficial for education. However, they are still concerned about some of the drawbacks of using AI. Therefore, it is necessary to take steps to minimize the negative impact while continuing to take advantage of the advantages of AI in education.

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“…Recent developments in machine learning, chemometrics and data analysis methods have created new opportunities for automating quality evaluation procedures [5][6][7][8][9]. It is now possible to examine enormous databases of wine samples, integrating both chemical composition measurements and sensory assessment ratings, and construct models that can precisely classify wine quality.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Red Wine Quality Classification Using Ensemble Voting Classifiers

Supriatna,

Saputra,

Hasan

2023

Infolitika J. Data Sci.

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This study introduces an ensemble voting classifier for red wine quality classification using machine learning algorithms. Wine quality assessment, traditionally reliant on subjective expert evaluations, is addressed through data-driven methodologies. The dataset comprises physicochemical attributes and quality ratings of red wines. Results reveal individual models with accuracy ranging from 0.816 to 0.873, while the ensemble approach significantly enhances accuracy. The combination of Random Forest and XGBoost achieves an accuracy of 0.885, demonstrating its potential in red wine quality assessment. In conclusion, this study showcases the potential of machine learning in enhancing the classification of red wine quality, offering a more objective and precise alternative to traditional sensory evaluation. The ensemble voting classifier, especially when combining Random Forest and XGBoost, provides a robust solution for this task, improving the accuracy of wine quality assessments.

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Application of Genetic Algorithm-Multiple Linear Regression and Artificial Neural Network Determinations for Prediction of Kovats Retention Index

Cited by 28 publications

References 0 publications

Applying Artificial Neural Network Based on Backpropagation Method for Indonesian Sign Language Recognition

Applying Artificial Neural Network Based on Backpropagation Method for Indonesian Sign Language Recognition

Student Perspectives on the Role of Artificial Intelligence in Education: A Survey-Based Analysis

Enhancing the Red Wine Quality Classification Using Ensemble Voting Classifiers

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