Abstract In developing cities such as in Jakarta, there are a lot of vehicle parking locations that still use conventional methods, which can harm drivers and also parking area owners alike, the process is slow and unsafe, making many people around feel afraid to use parking locations that are still conventional, the conventional parking lots in Jakarta is too many, sometimes also make people... In developing cities such as in Jakarta, there are a lot of vehicle parking locations that still use conventional methods, which can harm drivers and also parking area owners alike, the process is slow and unsafe, making many people around feel afraid to use parking locations that are still conventional, the conventional parking lots in Jakarta is too many, sometimes also make people have no other choice but to use unsecured parking lots, theft is the main factor that is difficult to avoid, especially in developing countries like Indonesia, which are not safe, and the location of the parking lot that is very open, makes a lot of opportunities which of course can be used by thieves or irresponsible people. Not only thieves, drivers who do not want to pay for parking, are also a problem for owners of parking lots. With the problems of these users, we plan to make modular parking applications that can be installed easily and cheaply, but because our group is not so large, there are several challenges that we face, such as time and requirements that can increase later, with thus we plan to make this parking application using the Extreme Programming method, which is possible and very suitable for the problems that our group is facing. The use of Extreme Programming turned out to be very helpful, and can also produce an application that matches the existing user stories. Read More Read Less

Abstract In system engineering process, descriptive system models seem to be insufficient in order to perform a system verification which fulfils various stakeholder's requirements. This aspect is well handled by simulation process through the use of several simulation techniques or algorithms. As a consequence, design process efficiency is considerably reduced by the fact that both system modeling and simulation tools are... In system engineering process, descriptive system models seem to be insufficient in order to perform a system verification which fulfils various stakeholder's requirements. This aspect is well handled by simulation process through the use of several simulation techniques or algorithms. As a consequence, design process efficiency is considerably reduced by the fact that both system modeling and simulation tools are often used separately. This study introduces an integration process to unify the potential provided by systems modeling languages and simulation environments, through the definition of a Domain Specific Language, namely Simulation Modeling Language, that is built on the basis ofa deep study of common constructs, semantics and modeling methodologies of several simulation environments, in addition to the specification of a model transformation between this language and a simulation environment (MATLAB/SImulink) in order to illustrate both its importance et its efficiency in our integration approach. Through the specification of its syntaxes and semantics, the defined intermediate modeling language allows modeling systems by using common constructs and modeling methodologies of simulation process in order to ensure their modeling with simulation environments and, thus, conduct experiences and system verifications. The definition of this language constitutes the basis of our integration approach aiming to bridge the gap between system modeling and simulation aspects in order to benefit from the strengths and potentials of both approaches. The integration approach consists on the specification of a bidirectional transformation, based on the concepts of Model- Driven Engineering, to perform in future works. Read More Read Less

Abstract Software Process Model deviation management allows to supervise process model execution and its adaptation when an inconsisteny is detected. The process model should be adjusted based on specified rules in order to ensure the continuity of the process model execution. Some works attempted to handle process model deviation by adjusting fragments and considering some rules to ensure that all constraints are met. Other studies considered only critical constraints in... Software Process Model deviation management allows to supervise process model execution and its adaptation when an inconsisteny is detected. The process model should be adjusted based on specified rules in order to ensure the continuity of the process model execution. Some works attempted to handle process model deviation by adjusting fragments and considering some rules to ensure that all constraints are met. Other studies considered only critical constraints in order to avoid cost/ schedule overrun: rules considering the criticality of the activities and their order. However, it is still generating uncertain executions with no mastery on the final result. However, execution history can help to identify the best choice and improve the control of the model. Machine learning techniques will investigate this execution history and predict the behavior of a future execution. In this paper, we present an approach using machine learning techniques to combine the Micro-Analyze method “priority and dependency of sub-activities “ and data from previous executions to predict the appropriate software process model. Read More Read Less

Abstract Due to the increased volume of Arabic opinionated posts on different social media, Arabic sentiment analysis is viewed as an important research field. Identifying the target or the topic on which opinion has been expressed is the aim of this work. Opinion target identification is a problem that was generally very little treated in Arabic text. In this paper, an opinion target extraction method from Arabic tweets... Due to the increased volume of Arabic opinionated posts on different social media, Arabic sentiment analysis is viewed as an important research field. Identifying the target or the topic on which opinion has been expressed is the aim of this work. Opinion target identification is a problem that was generally very little treated in Arabic text. In this paper, an opinion target extraction method from Arabic tweets is proposed. First, as a preprocessing phase, several feature forms from tweets are extracted to be examined. The aim of these forms is to evaluate their impacts on accuracy. Then, two classifiers, SVM and Naive Bayes are trained. The experiment results show that, with 500 tweets collected and manually tagged, SVM gives the highest precision and recall (86%). Read More Read Less