Search for collections on Undip Repository

SISTEM INFORMASI MITIGASI RISIKO BERBASIS ANALISIS MULTIKRITERIA UNTUK SISTEM TENAGA LISTRIK

WULLER, Arief Ibrahim and Surarso, Bayu and Jie, Ferry (2024) SISTEM INFORMASI MITIGASI RISIKO BERBASIS ANALISIS MULTIKRITERIA UNTUK SISTEM TENAGA LISTRIK. Masters thesis, UNIVERSITAS DIPONEGORO.

[thumbnail of Cover dll.pdf] Text
Cover dll.pdf

Download (2MB)
[thumbnail of Bab 1 Arief.pdf] Text
Bab 1 Arief.pdf

Download (108kB)
[thumbnail of Bab 2 Arief.pdf] Text
Bab 2 Arief.pdf

Download (298kB)
[thumbnail of Bab 3 Arief.pdf] Text
Bab 3 Arief.pdf
Restricted to Repository staff only

Download (188kB)
[thumbnail of Bab 4 Arief.pdf] Text
Bab 4 Arief.pdf
Restricted to Repository staff only

Download (1MB)
[thumbnail of Bab 5 Arief.pdf] Text
Bab 5 Arief.pdf
Restricted to Repository staff only

Download (79kB)
[thumbnail of Daftar Pustaka Arief.pdf] Text
Daftar Pustaka Arief.pdf

Download (180kB)

Abstract

Tesis ini menyajikan aplikasi Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), suatu metode analisis keputusan multi-kriteria (MCDA), untuk memprioritaskan upaya mitigasi risiko dalam perencanaan operasional perusahaan listrik. Studi ini menekankan integrasi pertimbangan risiko, biaya, dan dampak kinerja ke dalam proses pengambilan keputusan. Dengan memanfaatkan Tableau Prep dan Tableau Desktop, sebuah proses perhitungan dan dasbor visualisasi data interaktif dikembangkan untuk membantu para pengambil keputusan dalam memprioritaskan proyek secara efektif. Hasil studi kasus menunjukkan bahwa penerapan TOPSIS menghasilkan performa skor kumulatif yang 96,92% lebih tinggi dibandingkan dengan metode prioritas yang ada. Hal ini menunjukkan bahwa TOPSIS mampu menyediakan solusi yang lebih optimal dan objektif dalam pengambilan keputusan mitigasi risiko, terutama dalam hal penentuan prioritas dan alokasi anggaran. Dashboard visualisasi yang dikembangkan juga memungkinkan para pengambil keputusan untuk memahami manfaat relatif dari setiap proyek dan mengintegrasikan batasan anggaran secara dinamis, sehingga mendukung proses pengambilan keputusan yang lebih efektif. Temuan ini menggarisbawahi potensi sistem informasi berbasis MCDA dalam meningkatkan strategi manajemen risiko di sektor ketenagalistrikan.
Kata kunci : TOPSIS, MCDA, Perencanaan Operasional, Tableau, Manajemen Risiko

This thesis presents the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision analysis (MCDA) method, to prioritize risk mitigation efforts in the operational planning of an electricity company. This study emphasizes the integration of risk, cost, and performance impact considerations into the decision-making process. By utilizing Tableau Prep and Tableau Desktop, a calculation process and interactive data visualization dashboard are developed to assist decision makers in prioritizing projects effectively. The case study results show that the application of TOPSIS produces a cumulative score performance that is 96.92% higher compared to existing prioritization methods. This indicates that TOPSIS is able to provide a more optimal and objective solution in risk mitigation decision making, especially in terms of prioritization and budget allocation. The developed visualization dashboard also allows decision makers to understand the relative benefits of each project and integrates budget constraints dynamically, thus supporting a more effective decision-making process. These findings underscore the potential of MCDA-based information systems in improving risk management strategies in the electricity sector.
Keywords : TOPSIS, MCDA, Operational Planning, Tableau, Risk Management

Item Type: Thesis (Masters)
Uncontrolled Keywords: TOPSIS, MCDA, Perencanaan Operasional, Tableau, Manajemen Risiko
Subjects: Sciences and Mathemathic
Divisions: Postgraduate Program > Master Program in Information System
Depositing User: ekana listianawati
Date Deposited: 20 Dec 2024 09:04
Last Modified: 20 Dec 2024 09:04
URI: https://eprints2.undip.ac.id/id/eprint/28225

Actions (login required)

View Item View Item