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All Journal International Journal of Advances in Intelligent Informatics Journal of Business, Management, and Accounting
Nanang Fitriana Kurniawan
Institut Teknologi Tangerang Selatan
Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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How Website's Atmosphere affect Consumer Behavior: a new model based on the stimulus- organism-response (SOR) framework Nanang Fitriana Kurniawan; Eko Madiasto; Primidya KM Soesilo
Journal of Business, Management, & Accounting Vol. 3 No. 2 (2021): September
Publisher : Kusuma Negara Business School

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Abstract

In these decades, there have been many researchers discussing this field of study, but currently little is known about the factors designed and configured using atmospheric websites that optimize the experience for consumers (flow experiences) in increasing the desire to conduct transactions (Purchase Intention) on the website. Based on the subject matter that has been discussed previously, then in an effort to increase competitive web. So it is necessary to increase the role of web interface design and the delivery of atmospheric websites that are controlled in facilitating visitors. The S-O-R model consists of a stimulus that functions as an independent variable, organism as a mediator variable and the response functions as a dependent variable. Limitations in this study, that the respondents were selected based on the criteria of the researcher, as well as limitations in obtaining respondents to fill their perceptions of the use of online travel services and lack of documentation of the characteristics of the respondents. all variables have a significant influence on experience. Thus, it is important for future research to use several other behavioral factors that can influence website usage in creating consumer intentions and satisfaction. It is also recommended to use actual tourist samples
IDSX-Attention: Intrusion detection system (IDS) based hybrid MADE-SDAE and LSTM-Attention mechanism Hanafi Hanafi; Andri Pranolo; Yingchi Mao; Taqwa Hariguna; Leonel Hernandez; Nanang Fitriana Kurniawan
International Journal of Advances in Intelligent Informatics Vol 9, No 1 (2023): March 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v9i1.942

Abstract

An Intrusion Detection System (IDS) is essential for automatically monitoring cyber-attack activity. Adopting machine learning to develop automatic cyber attack detection has become an important research topic in the last decade. Deep learning is a popular machine learning algorithm recently applied in IDS applications. The adoption of complex layer algorithms in the term of deep learning has been applied in the last five years to increase IDS detection effectiveness. Unfortunately, most deep learning models generate a large number of false negatives, leading to dominant mistake detection that can affect the performance of IDS applications. This paper aims to integrate a statistical model to remove outliers in pre-processing, SDAE, responsible for reducing data dimensionality, and LSTM-Attention, responsible for producing attack classification tasks. The model was implemented into the NSL-KDD dataset and evaluated using Accuracy, F1, Recall, and Confusion metrics measures. The results showed that the proposed IDSX-Attention outperformed the baseline model, SDAE, LSTM, PCA-LSTM, and Mutual Information (MI)-LSTM, achieving more than a 2% improvement on average. This study demonstrates the potential of the proposed IDSX-Attention, particularly as a deep learning approach, in enhancing the effectiveness of IDS and addressing the challenges in cyber threat detection. It highlights the importance of integrating statistical models, deep learning, and dimensionality reduction mechanisms to improve IDS detection. Further research can explore the integration of other deep learning algorithms and datasets to validate the proposed model's effectiveness and improve the performance of IDS.
Co-Authors Andri Pranolo Eko Madiasto Hanafi Hanafi Leonel Hernandez Primidya KM Soesilo Taqwa Hariguna Yingchi Mao