Business Value of Information Technology Service Quality Based on Probabilistic Business-Driven Model

The business value of information technology (IT) services is often difficult to assess, especially from the point of view of a non-IT manager. This condition could severely impact organizational IT strategic decisions. Various approaches have been proposed to quantify the business value, but some are trapped in technical complexity while others misguide managers into directly and subjectively judging some technical entities outside their domain of expertise. This paper describes a method on how to properly capture both perspectives based on a  probabilistic business-driven model. The proposed model presents a procedure to calculate the business value of IT services. The model also covers IT security services and their business value as an important aspect of IT services that is not covered in previously published researches. The impact of changes in the quality of IT services on business value will also be discussed. A simulation and a case illustration are provided to show the possible application of the proposed model for a simple business process in an enterprise

Service Computing System Engineering Life Cycle

The development of service computing technology has triggered the need for organizations to build a service computing system. This system is able to deliver IT services that can meet the challenges and needs of business services. An understanding of the service computing systems engineering life cycle is necessary to model and build the systems. This paper conducts the study of the service computing systems concepts and proposes the life cycle of service computing system engineering. First, some publications relevant to the service computing systems are reviewed systematically in order to develop fundamental concepts and elements of the systems. Second, a metamodel of service computing systems is built based on those concepts. Third, the life cycle model of service computing systems engineering is proposed based on the metamodel. Finally, the verification of the life cycle is conducted by comparing the proposed life cycle to the life cycle of software engineering, service engineering, and service system engineering. The contribution of this paper is to provide a coincise understanding of the components that are needed to build such systems and show the interaction and collaboration between the components in the service computing systems

Application Development Risk Assessment Model Based on Bayesian Network

This paper describes a new risk assessment model for application development and its implementation. The model is developed using a Bayesian network and Boehm’s software risk principles. The Bayesian network is created after mapping top twenty risks in software projects with interrelationship digraph of risk area category. The probability of risk on the network is analyzed and validated using both numerical simulation and subjective probability from several experts in the field and a team of application developers. After obtaining the Bayesian network model, risk exposure is calculated using Boehm's risk principles. Finally, the implementation of the proposed model in a government institution is shown as a real case illustration

Information Interchange Layer based on Classification of Information Use (IU)

Information characteristics in classification of IU directly related to aspects of information usage by user in enterprise to accomplish their activities. Feature extraction from information usage in three layer of enterprise management used as parameter for this characteristic. Characteristics and dimension applied to develop middle-ware system (called Information Interchange Layer) that bridges a common issue ie information silo, to optimize a services of information resources in enterpris

Residential load event detection in NILM using robust cepstrum smoothing based method

Event detection has an important role in detecting the switching of the state of the appliance in the residential environment. This paper proposed a robust smoothing method for cepstrum estimation using double smoothing i.e. the cepstrum smoothing and local linear regression method. The main problem is to reduce the variance of the home appliance peak signal. In the first step, the cepstrum smoothing method removed the unnecessary quefrency by applying a rectangular window to the cepstrum of the current signal. In the next step, the local regression smoothing weighted data points to be smoothed using robust least squares regression. The result of this research shows the variance of the peak signal is decreased and has a good performance with better accuracy. In noise enviromment, performance prediction quite good with values greater than 0.6 and relatively stable at values above 0.9 on SNR> 25 for single appliances. Furthermore, in multiple appliances, performance prediction quite good at SNR> 20 and begins to decrease in SNR <20 and SNR> 25

Modeling IT Value based on Meta-Analysis

Over the last two decades, research about IT value has been done. The main purpose of IT values research is to determine how IT investment gives impact and value to organization performance. Because of vital role and function of IT, the organization required to understand how IT could create business value. Therefore, an understanding of IT value is needed. Systematic literature review in meta-analysis is required to determine the relationship between IT resources, organization capabilities, organization core competencies, and organization performances. The research was conducted on 53 publications which generate the classification matrix components that have an impact on organization performance. Hypothesis testing results that organization has the best performance on financial, efficiency, and other performance through external capability and core competence. So, indirect effect model is better than direct effect model in explaining IT value

Multi-agent information-inferencing fusion system for decision support system

In this paper we address the utilization of multi-agent approach to an information-inferencing fusion system.Information-inferencing fusion is an emulation of the way human fuses information delivered by human sensing organs after observing a phenomenon in his/her environment.The fused information is used as the basis for making a decision or an action to face the current situation or anticipate the situation that can probably occur in the future.This human capability is then emulated to Multi-Agent Information-inferencing Fusion System (MAIIFS) based on A3S (ArwinAdang-Aciek-Sembiring). From the results presented in this paper, the A3S method information-inferencing fusion method can deliver comprehensive information in a very quick manner so the decision maker can have situation awareness quicker.Therefore, he can to make the decision in accurate and quick manner

Incentive mechanism design for citizen reporting application using Stackelberg game

The growing utilization of smartphones equipped with various sensors to collect and analyze information around us highlights a paradigm called mobile crowdsensing. To motivate citizens’ participation in crowdsensing and compensate them for their resources, it is necessary to incentivize the participants for their sensing service. There are several studies that used the Stackelberg game to model the incentive mechanism, however, those studies did not include a budget constraint for limited budget case. Another challenge is to optimize crowdsourcer (government) profit in conducting crowdsensing under the limited budget then allocates the budget to several regional working units that are responsible for the specific city problems. We propose an incentive mechanism for mobile crowdsensing based on several identified incentive parameters using the Stackelberg game model and applied the MOOP (multi-objective optimization problem) to the incentive model in which the participant reputation is taken into account. The evaluation of the proposed incentive model is performed through simulations. The simulation indicated that the result appropriately corresponds to the theoretical properties of the model

REKAYASA SISTEM KOGNITIF BERBASIS MULTI-AGEN: PENDEKATAN PENALARAN BERBASIS KASUS

Cognitive system modeling first introduced by psychology researchers. Unfortunately, the model has not been sufficient in supporting computer based problem solving. For that reason, artificial intelligence tries to propose a computational model of cognitive system. The main purpose of the computational model is to support human in solving complex problems, especially problems that involve large number of data, uncompleted data, and problem solving that requires systematic approach as human does. This research proposes an engineering of such multiagent based cognitive system, which employs case based reasoning as imitation of human reasoning to maintain the knowledge base