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ISSN: 2162-6359
International Journal of Economics & Management Sciences
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Management and Artificial Intelligence: Note

Wily Julitawaty*

STIE Professional Management College Indonesia, Indonesia.

*Corresponding Author:
Wily Julitawaty
STIE Professional Management College Indonesia
Tel: +62 61 4578818
E-mail: [email protected]

Received Date: June 30, 2016; Accepted Date: July 29, 2016; Published Date: August 01, 2016

Citation: Julitawaty W (2016) Management and Artificial Intelligence: Note. Int J Econ Manag Sci 5:367. doi: 10.4172/2162-6359.1000367

Copyright: © 2016 Julitawaty W. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Limitations faced by the company, both in the ownership of resources, information and technology affect the company's ability to enter into and or maintain the market that has been mastered. Therefore, companies should make proper planning in allocating its resources in support of operations to be done to achieve the goals set. Planning made included the operational limits to be done, both the wide scope of operations (volume production, promotion, customer service, and so on) as well as the consumption of resources (acquisition of production capacity, payments to suppliers and employees, as well as the settlement of other short-term liabilities. Planning properly structured can provide guidance passage of efficient operation and are effectively able to achieve its goal, Bayangkara [1].

Then Bayangkara efficiency relates to how the company conducts its operations, so as to achieve optimal use of available resources. Efficiency relates to methods of work (operations). In conjunction with the concept of input-process-output, efficiency is the ratio between output and input. How big is the output generated by using a certain amount of input-owned company? Good working method will be able to guide the process of running operations by optimizing the use of resources of the company. So efficiency is a measurement process that connects between the input and output of the company's operations.

Public and private organizations are two different types of organizations in the output (performance) in which the main task of a public organization is “service making” while the organization of private (non-public) are “profit making”. Under no circumstances should public organizations still provide good service to the public. He chooses a role and obligations that the role and obligations of the public that is always sensitive and oriented to the public interest, Sudiyono [2].

Stahl in Sudiyono distinguishing between the administration and private as follows:

a) The services provided by the public administration is more urgent/pressing than that done by the private sector

b) Services provided by the public administration in general, are a monopoly or semi-monopoly

c) Public administration activities associated with formal administration

d) The act of public administration is in the surveillance society

e) The services provided by the public administration are not bound by the market price.

Sudiyono, all power and funds owned by the public administration intended solely to serve the interests of society in enhancing prosperity and welfare. The problems of public administration oriented on the public interest and public affairs or public affairs. So the selection carried out by the public administration (hospitals, universities and other government offices) rather look at the output are usually shaped innatura (services), which are manifold and difficult to quantify the amount of the price. Finally, to measure the work of government officials (the performance of) frequently used approach that compares “the realization of the target” can be achieved and even sometimes ignores input factors or in other words more put the effectiveness than the level of efficiency.

Knowledge Management has emerged as a predominantly management discipline in the early to mid-90s. The American Productivity and Quality Centre have identified six common strategic elements, [C. O’Dell and S. Elliott] among US firms that have embraced this new field. Two elements are the formulation of business strategies and the appointment of Chief Knowledge Officers to better focus on the exploitation of core intellectual assets by business and Governments, specifically the need to capitalize on increasingly expensive human resources/process knowledge to achieve competitive advantage in global procurement (supply chain management), in product development, in customer relationship management (CRM) and in value-added services, Tsui [3].

Knowledge management to improve the integration of a new employee: This scenario aims at analyzing the different solutions that can be provided to improve the newcomer integration in the organization. For the organisation, it is important to make newcomers rapidly operational by providing them with the information they need about their environment, the people and the resources they have access to. Integration is usually supported by the personnel department or/ and by more experimented and skilled employees, usually colleagues who play more or less officially the role of tutors, Gandon [4].

McMahon [5] approaches to data collection, and establishment of data for educational administrators to be used in making decisions which include put anything into the database, as well as all the data into a report including the kitchen sink is ineffective and wasteful. Developing countries and the (industrialized countries, for that matter) could not maintain and continuously update the data sets that are no longer used. It's a waste of resources that could be used to improve the equality of MIS system itself, and its effectiveness. Similarly, many lists of raw data that is not interpreted that do not get attention from policy makers. Level analysis of the most simple but adequate (eg: trends and other comparisons of cost-effectiveness ratios) are much more likely to get attention and have a significant impact.

Artificial Intelligence (AI) encompasses the following general areas of research: (1) automatic programming, (2) computer vision, (3) expert systems, (4) intelligent computer-assisted instruction, (5) natural language processing, (6) planning and decision support, (7) robotics, and (8) speech recognition [Henry C. Mishkoff]. Intelligent library systems utilize artificial intelligence technologies to provide knowledge-based services to library patrons and staff. Artificial Intelligence is a broad, complex area of study, which can be difficult for nonspecialists to understand. Yet, its ultimate promise is to create computer systems that rival human intelligence, and this clearly has major implications for librarianship, Bailey [6].

Based on a review of major models of human intelligence [John Cook et al.] conclude that the following ten factors are most pertinent to expert system research:

a) Acquisition: the ability to acquire new knowledge.

b) Automatization: the ability to refine procedures for dealing with a novel situation into an efficient functional form.

c) Comprehension: the ability to know, understands, cognize and deal with novel problems.

d) Memory management: the ability to represent knowledge in memory, to map knowledge on to that memory representation, and to access the knowledge in memory.

e) Metacontrol: the ability to control various processes in intelligent behaviour.

f) Numeric ability: the ability to perform arithmetic operations.

g) Reasoning: the ability to use problem-solving knowledge.

h) Social competence: the ability to interact with and understand other people, machines or programs.

i) Verbal perception: the ability to recognize natural language.

j) Visual perception: the ability to recognize visual images, Bailey [6].

Kumbhar [7] use of artificial intelligence is new technology science to research and development expansion of human intelligence. Artificial intelligence is branch of Computer Science working similar to human brain. It gives rise to human intelligence through the machine perspective. The research in Artificial intelligence started in 1956. The University of Dartmouth firstly used the Artificial Intelligence term officially. The most of research in Artificial Intelligence is related to the logical reasoning where research began from the problem solving, reasoning, learning, and expert systems, gaming etc. The mass quantity of research yet to be carried out in this field as it has wide scope. The AI has ability to solve the differential equation, playing chess, integrated circuit design analysis, speech recognition, handwriting recognition, expert system for disease diagnosis, control of aircraft submarine without operator, Bot players introduced in computer games etc. The evolution of AI takes in the generation from 1950 to till date. Today it supposed that the robotics machine can do the human task with special capability like a human.


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