Faktor-faktor Yang Memengaruhi Kinerja Dosen

: Factors Affecting Lecturers' Performance. This study aims to find out the effects of smart campus information technology, implementation of ISO 9001:2008 quality management system, and leadership skills on lecturers' knowledge management, work motivation, and performance. Using a ran­dom-proportional-sampling technique, the study involved 175 lecturers, a number required in SEM analysis. Data were analyzed using a structural equation modeling of AMOS19 software. The findings indicate that smart campus information technology and leadership skills significantly affect lecturers' knowledge management, and that leadership skills as well as motivation influence lecturers' performance significantly

Ontology-based Model of a Smart City

The city environment is a complex, dynamic and distributed system. Effective management of the city environment presents a major challenge for a smart city. Effective city management must seek to improve urban infrastructure while minimising the costs, to stimulate innovations in different industries and to improve the quality of life for citizens. To create an adequate model of city’s environment structure it is necessary to analyse all the city’s components that influence the city environment management and to define data flows between these components. The most effective tool for representation of knowledge about the city environment, its components and relationships between them is the organisation of information in the form of an ontology-based model. In this paper we would like to introduce a novel ontology-based model for the smart city that includesdefinitions of entities and their properties, classes and their attributes and relationships between them. Such ontology enables us to use a knowledge base for the smart city as a basis of the decision-making support system for smart city management

A Knowledge Management-extended Gamified Customer Relationship Management System

The growth of Smart Cities often depends on global trends, human capital, foreign investments and partnerships, as well as citizen participation. With these drivers in mind, we focus on the question of how to attract and maintain customers first through a Gamified Customer Relationship Management System and subsequently, its enhancement via a Knowledge Management approach. The design of the gamified customer relationship management system and subsequently, its extension via a Knowledge Management approach are presented along with simple text mining on data from the Website’s forum. Findings towards user acceptance and user satisfaction are positive and directly lends towards possible Big Data and possibly, IoT applications in the future

A Knowledge Based System for Supporting Sustainable Industrial Management in a Clothes Manufacturing Company Based on a Data Fusion Model

In this paper we propose a knowledge based system (KBS), based on smart objects and a data fusion model to support industrial management decision making applied to a clothes manufacturing enterprise. The management processes cover factory-production levels to higher decision-making levels. Therefore, the proposed KBS contributes to solving different kind of decision problems, including factory supervision, production planning and control, productivity management, real-time monitoring, and data acquisition and processing. The web access via different middleware devices and tools at different process levels, along with the use of integrated algorithms, decision methods, and smart objects, promote an optimized use of knowledge and resources. In this paper the proposed KBS is introduced and an example of its use is illustrated with an example of a clothes manufacturing resources selection, using the embedded dynamic multi-criteria fusion model.This work was supported by FCT “Fundação para a Ciência e a Tecnologia” under the program: PEST2015-2020, reference: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Integrating building and urban semantics to empower smart water solutions

Current urban water research involves intelligent sensing, systems integration, proactive users and data-driven management through advanced analytics. The convergence of building information modeling with the smart water field provides an opportunity to transcend existing operational barriers. Such research would pave the way for demand-side management, active consumers, and demand-optimized networks, through interoperability and a system of systems approach. This paper presents a semantic knowledge management service and domain ontology which support a novel cloud-edge solution, by unifying domestic socio-technical water systems with clean and waste networks at an urban scale, to deliver value-added services for consumers and network operators. The web service integrates state of the art sensing, data analytics and middleware components. We propose an ontology for the domain which describes smart homes, smart metering, telemetry, and geographic information systems, alongside social concepts. This integrates previously isolated systems as well as supply and demand-side interventions, to improve system performance. A use case of demand-optimized management is introduced, and smart home application interoperability is demonstrated, before the performance of the semantic web service is presented and compared to alternatives. Our findings suggest that semantic web technologies and IoT can merge to bring together large data models with dynamic data streams, to support powerful applications in the operational phase of built environment systems