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Firdha Ruvania
Faculty of Industrial Engineering, Swiss German University, Indonesia
Engineering Industrial & Manufacturing Engineering

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Knowledge Management Evaluation in Oil and Gas Company Using Analytic Hierarchy Process Firdha Ruvania; Tanika D Sofianti; Ivanos Tertiana
Performa: Media Ilmiah Teknik Industri Vol 14, No 1 (2015): PERFORMA Vol. 14 No 1, Maret 2015
Publisher : Industrial Engineering Study Program, Faculty of Engineering, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (474.826 KB) | DOI: 10.20961/performa.14.1.11010

Abstract

In today’s competitive business environment, competition between organizations has become strict and more competitive. Oil and Gas Company is a learning organization that manages knowledge for implementing Knowledge Management (KM) as company intangible asset in order to reach higher competitive advantage. The investment in KM needs to be evaluated to assure the advantage obtained from the investment. The objective of this study is to evaluate knowledge management performance by comparing and ranking each division to find division that represents the most desirable performance to the least performance. The methodology used to evaluate is Analytic Hierarchy Process (AHP). The AHP arranges the decision problem into a hierarchy of more easily comprehended. This research adopts SECI model as a criteria that correlated to KM performance. In order to identify the area for improvements by means of determine the differences between division, gap analysis was conducted. Prioritize of criteria socialization (37.68%), internalization (23.63%), combination (23.61%), and externalization (15.08%). The result of division with highest weight of KM performance is planning and the lowest is financial. Financial division needs to improve the overall SECI process by increasing interaction between team members, routine progress reports and also verbalizing knowledge based on documents. A case study in an oil and gas company was conducted to demonstrate how to evaluate KM using AHP.
Co-Authors Ivanos Tertiana Tanika D Sofianti