Knowledge Management portal is a system to support Knowledge Management process, in order to create, capture, develop, share, reuse and optimize the knowledge and particularly in Bina Nusantara University which has im...
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ISBN:
(纸本)9781509023240
Knowledge Management portal is a system to support Knowledge Management process, in order to create, capture, develop, share, reuse and optimize the knowledge and particularly in Bina Nusantara University which has implemented Knowledge Management System (KMS) since 2002. However, this KMS need to be measured in order to know how better this KMS in term of the software size. The binus KMS will be measured in term of their software size in functionality perspective with use case point method. This metric of KMS will be used by management to know how better the software size, complexity level and effort to development in numbering. Measurement of software size with software metric such as Use Case Point upon use case diagram for binus knowledge Management Portal shows that the project has medium software size with score Use Case Point (UCP) = 108.56 and has estimate effort will be developed in 2,064 hours (or in 258 days or 51.6 weeks or 12.9 months) and has development cost for 516,000,000.00 rupiah (Indonesian currency). Use Case Point, estimate effort and project value will powerful to help management in order to make decision regarding the implementation of IT software project development in term of time, money and people.
The objective of this study is to develop learning media by using the computer Based Instruction (CBI) model for GOST algorithm cryptographic material (Gosudarstvennyi Standard). Besides, the study serves to present l...
The objective of this study is to develop learning media by using the computer Based Instruction (CBI) model for GOST algorithm cryptographic material (Gosudarstvennyi Standard). Besides, the study serves to present learning using computer media, especially in the Informatics Engineering study program. The method used in this study uses the Research and Development (R & D) method. The results of this development research are learning media products in the form of tutorial CDs with the contents of the material: GOST Cryptographic Theory, Encryption Process and Decryption process using alphabet text data. Based on the results of the application and testing of the program, it can be concluded that this application is easy to use. Learning the Gost algorithm in the encoding method utilizing the computer Based Instructions (CBI) method helps to understand the material and facilitate the learning process.
This paper presents a real case study pertaining to an issue related to waste collection in the northern part of Malaysia by using a constructive heuristic algorithm known as the Nearest Greedy (NG) technique. This te...
This paper presents a real case study pertaining to an issue related to waste collection in the northern part of Malaysia by using a constructive heuristic algorithm known as the Nearest Greedy (NG) technique. This technique has been widely used to devise initial solutions for issues concerning vehicle routing. Basically, the waste collection cycle involves the following steps: i) each vehicle starts from a depot, ii) visits a number of customers to collect waste, iii) unloads waste at the disposal site, and lastly, iv) returns to the depot. Moreover, the sample data set used in this paper consisted of six areas, where each area involved up to 103 customers. In this paper, the NG technique was employed to construct an initial route for each area. The solution proposed from the technique was compared with the present vehicle routes implemented by a waste collection company within the city. The comparison results portrayed that NG offered better vehicle routes with a 11.07% reduction of the total distance traveled, in comparison to the present vehicle routes.
This work discusses a method to count the number of passengers waiting in Bus Rapid Transit station. The proposed system relies on computer vision technique to monitor the movement of passengers crossing doors on the ...
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This work discusses a method to count the number of passengers waiting in Bus Rapid Transit station. The proposed system relies on computer vision technique to monitor the movement of passengers crossing doors on the station. In this work, three background subtraction techniques, namely, Running Gaussian Average, Gaussian Mixture Model, and Adaptive Gaussian Mixture Model, were used to count the passengers crossing an entrance on a BRT station from a pre-recorded motion picture. The results indicates that the tree algorithms are able to identify the passenger crossing with a reasonable high level of recall and but low level of precision. These results indicates that many false positives are identified by the three algorithms. In addition, the empirical data indicate that the three algorithms tend to have better performance with higher value of the learning rate.
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