Journal of ICT Research and Applications 

About: Journal of ICT Research and Applications is an academic journal published by ITB Journal Publisher, LPPM ITB. The journal publishes majorly in the area(s): Computer science & Artificial intelligence. It has an ISSN identifier of 2337-5787. It is also open access. Over the lifetime, 228 publications have been published receiving 1306 citations.

The Investigation on Using Unity3D Game Engine in Urban Design Study

Abstract: Developing a virtual 3D environment by using game engine is a strategy to incorporate various multimedia data into one platform The characteristic of game engine that is preinstalled with interactive and navigation tools allows users to explore and engage with the game objects However, most CAD and GIS applications are not equipped with 3D tools and navigation systems intended to the user experience In particular, 3D game engines provide standard 3D navigation tools as well as any programmable view to create engaging navigation thorough the virtual environment By using a game engine, it is possible to create other interaction such as object manipulation, non playing character (NPC) interaction with player and/or environment We conducted analysis on previous game engines and experiment on urban design project with Unity3D game engine for visualization and interactivity At the end, we present the advantages and limitations using game technology as visual representation tool for architecture and urban design studies

Topic Modeling in Sentiment Analysis: A Systematic Review

Abstract: With the expansion and acceptance of Word Wide Web, sentiment analysis has become progressively popular research area in information retrieval and web data analysis. Due to the huge amount of user-generated contents over blogs, forums, social media, etc., sentiment analysis has attracted researchers both in academia and industry, since it deals with the extraction of opinions and sentiments. In this paper, we have presented a review of topic modeling, especially LDA-based techniques, in sentiment analysis. We have presented a detailed analysis of diverse approaches and techniques, and compared the accuracy of different systems among them. The results of different approaches have been summarized, analyzed and presented in a sophisticated fashion. This is the really effort to explore different topic modeling techniques in the capacity of sentiment analysis and imparting a comprehensive comparison among them.

A Combination of Inverted LSB, RSA, and Arnold Transformation to get Secure and Imperceptible Image Steganography

Abstract: Securing images can be achieved using cryptography and steganography. Combining both techniques can improve the security of images. Usually, Arnold’s transformation (ACM) is used to encrypt an image by randomizing the image pixels. However, applying only a transformation algorithm is not secure enough to protect the image. In this study, ACM was combined with RSA, another encryption technique, which has an exponential process that uses large numbers. This can confuse attackers when they try to decrypt the cipher images. Furthermore, this paper also proposes combing ACM with RSA and subsequently embedding the result in a cover image with inverted two-bit LSB steganography, which replaces two bits in the bit plane of the cover image with message bits. This modified steganography technique can provide twice the capacity of the previous method. The experimental result was evaluated using PSNR and entropy as the parameters to obtain the quality of the stego images and the cipher images. The proposed method produced a highest PSNR of 57.8493 dB and entropy equal to 7.9948.

A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction

Abstract: Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting. Various techniques are available for prediction and forecasting on the basis of time series data. Presently, the use of data mining techniques for this purpose is increasing day by day. In the present study, a comprehensive survey of data mining approaches and statistical techniques for rainfall prediction on time series data was conducted. A detailed comparison of different relevant techniques was also conducted and some plausible solutions are suggested for efficient time series data mining techniques for future algorithms.Â

Fuzzy MADM Approach for Rating of Process-Based Fraud

Abstract: Process-Based Fraud (PBF) is fraud enabled by process deviations that occur in business processes. Several studies have proposed PBF detection methods; however, false decisions are still often made because of cases with low deviation. Low deviation is caused by ambiguity in determining fraud attribute values and low frequency of occurrence. This paper proposes a method of detecting PBF with low deviation in order to correctly detect fraudulent cases. Firstly, the fraudulence attributes are established, then a fuzzy approach is utilized to weigh the importance of the fraud attributes. Further, multi-attribute decision making (MADM) is employed to obtain a PBF rating according to attribute values and attribute importance weights. Finally, a decision is made whether the deviation is fraudulent or not, based on the PBF rating. Experimental validation showed that the accuracy and false discovery rate of the method were 0.92 and 0.33, respectively.