Indonesian Journal of Electrical Engineering and Computer Science 

Abstract: In this competitive scenario of the educational system, the higher education institutes use data mining tools and techniques for academic improvement of the student performance and to prevent drop out. The authors collected data from three colleges of Assam, India. The data consists of socio-economic, demographic as well as academic information of three hundred students with twenty-four attributes. Four classification methods, the J48, PART, Random Forest and Bayes Network Classifiers were used. The data mining tool used was WEKA. The high influential attributes were selected using the tool. The internal assessment attribute in the continuous evaluation process makes the highest impact in the final semester results of the students in our dataset. The results showed that random forest outperforms the other classifiers based on accuracy and classifier errors. Apriori algorithm was also used to find the association rule mining among all the attributes and the best rules were also displayed.

Abstract: The popularity, great influence and huge importance made wireless indoor localization has a unique touch, as well its wide successful on positioning and tracking systems for both human and assists also contributing to take the lead from outdoor systems in the scope of the recent research works. In this work, we will attempt to provide a survey of the existing indoor positioning solutions and attempt to classify different its techniques and systems. Five typical location predication approaches (triangulation, fingerprinting, proximity, vision analysis and trilateration) are considered here in order to analysis and provide the reader a review of the recent advances in wireless indoor localization techniques and systems to have a good understanding of state of the art technologies and motivate new research efforts in this promising direction. For these reasons, existing wireless localization position systems and location estimation schemes are reviewed. We also made a comparison among the related techniques and systems along with conclusions and future trends to identify some possible areas of enhancements.

Abstract: The process of analysis of such images is important in order to improve quantify medical imaging systems. It is significant to analysis the dental x-ray images we need features of image. In this paper we present a method for segmentation and feature extraction of dental x-ray images. The proposed method has been implemented by using level-set method for segmentation after image enhancement and illustrate contour for teeth to complete the segmentation step. Furthermore, we extracted multiple features of dental x-ray images using texture statistics techniques by gray-level co-occurrence matrix. Extracted data can perform to obtain the teeth measurements for automatic dental systems such human identification or dental diagnosis systems. Preparatory experiments show the significance of the proposed method to extract teeth from an x-ray image. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2655 Full Text: PDF

Abstract: The cost minimization with due dates in cloud computing workflow is an intractable problem. Taking the characteristics in cloud computing of pay-per-use and resource virtualization into account, in this paper, we present a QoS-based hybrid particle swarm optimization (GHPSO) to schedule applications to cloud resources. In GHPSO, crossover and mutation of genetic algorithm is embedded into the particle swarm optimization algorithm (PSO), so that it can play a role in the discrete problem, in addition, variability index, changing with the number of iterations, is proposed to ensure that population can have higher global search ability during the early stage of evolution, without the premature phenomenon. A hill climbing algorithm is also introduced into the PSO in order to improve the local search ability and to maintain the diversity of the population. The simulation results show that the GHPSO achieves better performance than standard particle swarm algorithm used in minimize costs within a given execution time. DOI: http://dx.doi.org/10.11591/telkomnika.v10i7.1452 Full Text: PDF

Abstract: Security is one of the imperative issues in an advanced local condition. The current center around formative and research issues of Wireless Sensor Network(WSN) based Smart Home. WSN based shrewd home detection system gives a safe and safe living condition. A Wireless Sensor System (WSN) is a system which is building by utilizing little independent hubs (sensors). Its motivation is to screen certain ecological parameters, for example, temperature, dampness, brilliance, weight, sound, movement, and so forth. This paper depicts the improvement of a smart home condition dependent on exact Wireless Sensor Network and furthermore depicts private vitality observing and controlling procedures for keen home systems administration framework. This paper proposes a basic and adaptable remote arrange for domestics computerization of temperature, moistness, gas, movement and light by executing dependable sensor hubs which can be controlled too observed. This innovation offers energizing and new chance to build the availability of devices inside the home for the home computing.