Forthcoming articles

International Journal of Digital Enterprise Technology

International Journal of Digital Enterprise Technology (IJDET)

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International Journal of Digital Enterprise Technology (4 papers in press)

Regular Issues

  • The Implementation of Fuzzy Logic Controller for Defining the Ranking Function on Malay Retrieval System   Order a copy of this article
    by Shaiful Bakhtiar Rodzman, Normaly Kamal Ismail, Nurazzah Abd Rahman, Zulhilmi Mohamed Nor 
    Abstract: Ranking is likely the most important process of an Information Retrieval (IR) system that will be used to evaluate and measure the effectiveness of an IR system. This paper aims to produce the implementation of Fuzzy Logic Controller of Mamdani-type Fuzzy Inference System for defining the ranking function by using the BM25 Model in the Malay IR System that also includes the Malay Stemmer. The result of the ranking function then will be compared to the result of Vector Space Model that is also applied in Malay IR System and be evaluated using relevant document by the Hadith expert. The results showed that FBMIR has slightly outperformed Vector Space Model on 3 Topic Set of query results such as Iman,Ilmu and Wuduk on the Precision at Rank 10 and the percentage of no relevant document in the top ten retrieved measures.
    Keywords: Fuzzy Logic; Malay Text Corpus; fuzzy set; fuzzy rule; Vector Space model; Probabilistic model; BM25 model; ranking function.

    by Krishna Kumar Mohbey 
    Abstract: In every sector, turnover is a major concern, whether it be about an organization's workforce turnover, or an e-commerce site 's consumer attrition. If we can foresee how which client or employee will leave their current company / organization / website, and so on, so that can save the employer a lot of time, effort, and expense and help them hire / acquire workforce / customers in advance. It does not generate an obstacle in an organisation's continuing growth. A robust predictive model has been introduced in this article, which will help us classify the actions of certain workers who might be drawn in the coming years. The methodology suggested for the estimation of employee turnover uses the survival analysis and the Cox proportional hazard methodology.
    Keywords: Employee attrition; Behaviour prediction; Survival analysis; Cox model.

  • Design a leaning model of mobile vision to detect diabetic retinopathy based on the improvement of MobileNetV2   Order a copy of this article
    by Hieu Nguyen, Vinh Tran, Vuong Pham, Hien Nguyen 
    Abstract: Diabetes is a leading cause of blindness cases in the world. Early detection of diabetic retinopathy can prevent or delay diabetic related blindness. Nowadays almost people use mobile phone supporting their work, especially using the camera phone. Thus, an application on mobile for checking the eye to diagnosis Diabetic Retinopathy early is very helpful. In this paper, a method for building a mobile application to detect Diabetic Retinopathy is studied based on MobileNetV2. This method is built on the improvements of depthwise separable convolution combining the layers of Linear Bottleneck and Inverted Residuals. Those layers are effective to keep more useful features by using linear layers, and they do not increase the cost of computing a lot. They make the method more effective when it is run on mobile. The proposed method has been tested on two dataset EyePACs 2015 and APTOS 2019. The positive results of the experiment are emerging to build an application for detecting Diabetic Retinopathy which is used on the mobile phone.
    Keywords: Diabetic Retinopathy; Diabetes; Deep Learning; Ordinal Regression; MobileNetV2; convolutional neural network; mobile application; software engineering.

  • A Review on the Ways to Determine At-Risk Students in Online Learning   Order a copy of this article
    by Si Na Kew, Zaidatun Tasir 
    Abstract: The emergence of Learning Analytics aims to collect, measure, analyse and report students learning behaviours by using data analytics techniques. A large amount of log data on student activity generated in Learning Management System can be tracked and analysed in order to find out the hidden information about students learning behaviours and from this, at-risk students can be identified and additional interventions can be provided for them. However, the systematic review on the ways to identify at-risk students are still limited. Hence, the purpose of this paper is to review the related papers so as to show a clear picture on the way to identify at-risk students by analysing their learning behaviours in online learning, including (i) a brief introduction of each related research, (ii) the purpose and the setting of the research, (iii) the determinant of at-risk students, (iv) the types of data being analysed to find out at-risk students, (v) the kind of tools or analytics methods used to determine at-risk students and (vi) the strategies or intervention being suggested or applied to assist at-risk students. The results show that most of the data analytics techniques such as regression analysis have successfully identified at-risk students and various types of data such as learning behaviour data are determined as attributes in predicting at-risk students. Moreover, the determinant of at-risk students such as course grades, etc, and different strategies and intervention such as instructional materials are summarized in this paper.
    Keywords: online learning; at-risk students; log data; data analytics technique; Learning Analytics; learning behavior.