| Assessment of E-learning Systems: A Systems Engineering Approach System |
| Pages: 173-179 (7) | [Full Text] PDF (388 KB) |
| A Al-Shagran, A Sahraoui |
| FCIT-Information System Department, Sudan University of Science and Technology, Khartoum, SudanLAAS-CNRS, Universite de Toulouse, CNRS, UT2J, Toulouse, France |
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Abstract - This paper is on the issue of assessment of E-Learning systems. The originality of the work is to identify main drawbacks mentioned in the literature and propose a systems engineering framework approach.E-learning is more and more used and mainly in developing countries. A large number of E-learning systems have been developed in the institution around the world. These systems can be assessed using multiple dimensions and criteria. KSA started implementing the E-Learning since 2002. Although of this evolution up to our knowledge, limited research work have been carried out on assessing such system. In response to this limitation this paper is a preliminary research study that attempts to propose the requirements list needed to develop a reliable technique or methodology to evaluate an E- learning system. The contribution of this position paper proposition of a framework for future research as seeing ELearning as a system as any other system, and hence the assessment becomes a partial validation of the systems with respect to requirements. Requirements can be criteria of ABET accreditation. The methodology will be based on best practices of systems engineering approach. |
| Index Terms - ELearning, Systems Engineering, Modelling, Assessment, Evaluation Criteria |
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C itation - A Al-Shagran, A Sahraoui. "Assessment of E-learning Systems: A Systems Engineering Approach System." International Journal of Computer Science and Software Engineering 6, no. 8 (2017): 173-179. |
| Sentiment Analysis Model Based On Youtube Comment Using Support Vector Machine |
| Pages: 180-185 (6) | [Full Text] PDF (639 KB) |
| FI Tanesab, I Sembiring, HD Purnomo |
| Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana, Jl. Diponegoro 52-60, Salatiga 50711, Indonesia |
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Abstract - Opinion mining or comment toward attitude evaluation, individual entity, are usually called sentiment. Everyone is free to give opinion related with the present opinions on youtube. Hence people have a free will to express their opinion regarding the performance. Due to the raise of many critics that appear in a short amount of time, there a needs to conduct research on opinion mining. In this research, opinion mining is applied on the peformance of Ahok as a governor. The sentiment analysis is used to find a pattern or a certain character of Ahok. Support Vector Machine is used to classified the opinion into positive class, neutral class and negative class. 1000 recorded data is used as a sample data. Preprocessing phase is needed before classifying the data. The preprocessing phase consist of preprocessing the data, tokenizing, cleansing and filtering. In order to determine the percentage of the class sentiment, Lexicon Based method is used. The experiment shows that the proposed method are calculating the percentage weight in this research had used Lexicon Based and Confusion Matrix to know the result of weighting percentage of analysis to SVM. It had been found the result as follows : accuracy 84%, precision 91%, recall 80%, TP rate 91.1 and TN rate 44.8%. |
| Index Terms - Youtube, Analysis Sentiment, Support Vector Machine, Opinion Mining, Lexicon Based |
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C itation - FI Tanesab, I Sembiring, HD Purnomo. "Sentiment Analysis Model Based On Youtube Comment Using Support Vector Machine." International Journal of Computer Science and Software Engineering 6, no. 8 (2017): 180-185. |
| Smoke Detection Algorithm for Outdoor Environment Based on Image Processing |
| Pages: 186-188 (3) | [Full Text] PDF (524 KB) |
| NT Son, BN Anh |
| ICT Department, FPT University, Hanoi, Vietnam |
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Abstract - At this point, the conventional smoke detection often requires many smoke sensors but they have weakness in wide coverage area and low response time. In order to overcome these shortcomings, this paper presents a method based on image processing techniques, capable to detect the smoke from video taken from camera. The proposed detection method consists of the following steps: slow motion detection, smoke color detection, inverse edge detection, AND operator and then classification phase. This will provide early warnings such as fire, thus reducing economic losses and casualties. In addition, it will help to improve the rate of smoke detection, as well as reducing the false detection rate of other suspected object. |
| Index Terms - Smoke Detection, Moving Region Detection, Smoke Features |
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C itation - NT Son, BN Anh. "Smoke Detection Algorithm for Outdoor Environment Based on Image Processing." International Journal of Computer Science and Software Engineering 6, no. 8 (2017): 186-188. |