지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.25 No.1
- 발행연도
- 2025.3
- 수록면
- 37 - 54 (18page)
- DOI
- 10.5391/IJFIS.2025.25.1.37
이용수
초록· 키워드
오류제보하기
The integration of fuzzy logic with the Information Technology Infrastructure Library (ITIL) practices for incident prioritization in technological development represents an innovative proposal, especially for systematizing processes in large organizations, including private universities. This study aimed to design and develop a fuzzy inference system (FIS) model for incident prioritization using the educational processes of a private university during periods 2023-II and 2024-I as a case study. This approach focused on evaluating how the ITIL-fuzzy model can improve response times in managing technological incidents, ensuring a high quality of service. The FIS model was implemented with 432 fuzzy rules using the Mamdani method to generate an inference engine. During the research, the current “AS-IS” incident management process (96 rules), the fuzzy logic-based prioritization model, and the optimized “TO-BE” process (178 rules) were analyzed. The results showed a significant reduction in incident resolution times: the average time for the “AS-IS” model was 119.64 hours. In comparison, the “TO-BE” model managed to reduce it to 43.91 hours, representing a decrease of 63.30%. The effectiveness of the model was validated by a Student t-test, obtaining t<sub>ca</sub> = −4.88, tcritical = −1.65 and p-value = 0.000, confirming that the resolution time of the “TO-BE” model is significantly shorter. In addition, the process capability index C<sub>p</sub> = 1.423 and the Taguchi index C<sub>pm</sub> = 1.12 were determined, complying with the specifications of the optimized “TO-BE” process (7.99 ± 1.55 minutes, with a goal of 7.99 minutes). In conclusion, the integration of ITIL and fuzzy logic significantly improved incident resolution times, suggesting a high potential for its implementation in other private universities with similar operational structures.
목차
Abstract
1. Introduction
2. Methodology
3. Results
4. Discussion
5. Conclusion
References
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