Supplier Relationship Management using Quality Based Data Analytic (Case Study: PT.X)

Sukma, Anggi Prienda (2020) Supplier Relationship Management using Quality Based Data Analytic (Case Study: PT.X). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

PT. X is a branch of a global manufacturing company who focused on producing the component, equipment, and system for automation. Recently, there are 62 suppliers take as big as 70% portion of all parts. Meaning that the quality of company’s product mainly derived by the quality of supplier’s parts. Therefore, the company manage their suppliers through Supplier Relationship Management (SRM) activities. The suppliers are clustered using grade of supplier performance, which is the result of monthly evaluation. However, the current response from performance evaluation is not triggered by the performance grade. There is also a problem in their grading process. The supplier data within their database also not being considered optimally. Hence, this research aims to support PT. X SRM using data analytic. The data analytic uses K-Means Clustering technique resulting 3 optimal supplier clusters. The formation of these three clusters is due to the similarity of data. Therefore, each of the clusters has their own prominent characteristics that differentiate one another. The cluster characteristics and the lack on company current response are the consideration in the construction of supplier development program. This research provide supplier development program which considers that two factors. The programs are divided into basic supplier development programs for all suppliers and programs focused for the main characteristics of the cluster. Keywords: Data Analytic, K-Means Clustering, Supplier Relationship Management (SRM)

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Data Analytic, K-Means Clustering, Supplier Relationship Management (SRM) Data Analytic, K-Means Clustering, Manajemen Hubungan Supplier
Subjects: Q Science > QA Mathematics > QA76.9.D343 Data mining
Divisions: Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26201-(S1) Undergraduate Thesis
Depositing User: Anggi Prienda Sukma
Date Deposited: 23 Aug 2020 06:31
Last Modified: 23 Aug 2020 06:31
URI: http://repository.its.ac.id/id/eprint/79954

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