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All Journal IPTEK The Journal of Engineering
Nadhila Nurdin
AGH University of Science and Technology
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Mechanical Engineering

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Explainable Artificial Intelligence (XAI) towards Model Personality in NLP task Nadhila Nurdin; Dimas Adi
IPTEK The Journal of Engineering Vol. 7 No. 1 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v7i1.a8989

Abstract

In recent years, the development of Deep Learning in the field of Natural Language Processing, especially in sentiment analysis, has achieved significant progress and success. It is because of the availability of large amounts of text data and the ability of deep learning techniques to produce sophisticated predictive results from various data features. However, the sophisticated predictions that are not accompanied by sufficient information on what is happening in the model will be a major setback. Therefore, the significant development of the Deep Learning model must be accompanied by the development of the XAI method, which helps provide information about what drives the model to get predictable results. Simple Bidirectional LSTM and complex Bi-GRU-LSTM-CNN model for Sentiment Analysis were proposed in the present research. Both models were analyzed further using three different XAI methods (LIME, SHAP, and Anchor) in which they were used and compared to two proposed models, proving that XAI is not limited to giving information about what happens in the model but can also help us to understand and distinguish models’ personality and behaviour.
Agent-Based Simulation for Evaluating the Effect of Different Walking and Driving Speed on Disaster Evacuation in Aceh Sinung Widiyanto; Dimas Adi; Nadhila Nurdin; Fadila
IPTEK The Journal of Engineering Vol. 7 No. 2 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v7i2.a9255

Abstract

Agent-Based Modeling and Simulation (ABMS) was implemented to build and develop an evacuation simulation model. In this research, ABMS is simulated in several evacuation scenarios with an output: the evacuation rate of two different decision choice evacuation modes (walking or driving to the evacuation points). The result of this tsunami evacuation simulation shows that the decision choices on the evacuation mode are highly correlated to the evacuation rate. Observed in the simulation that there is a typical choice that leads to the higher evacuation rate, the choice is by maximizing the pedestrian agents on the population distribution.
Co-Authors Dimas Adi Fadila Sinung Widiyanto