“…More precisely, the positive-ideal solution is the one that maximizes the benefit and simultaneously minimizes the total costs. On the contrary, the negative-ideal solution is the one that minimizes the benefit and simultaneously maximizes the cost (Lai et al, 1994;Wu et al, 2010).…”
“…More precisely, the positive-ideal solution is the one that maximizes the benefit and simultaneously minimizes the total costs. On the contrary, the negative-ideal solution is the one that minimizes the benefit and simultaneously maximizes the cost (Lai et al, 1994;Wu et al, 2010).…”
“…Metode TOPSIS digunakan untuk memilih alternative yang secara bersamaan memiliki jarak terpendek dari solusi ideal positif dan jarak terjauh dari solusi ideal negatif (Behzadian et al, 2012;Kusumadewi et al, 2006). Wu et al (2010) (Shyur, 2006). Suatu rangkaian aktifitas perusahaan tidak dapat terlaksana tanpa ada dukungan dari human resources (HR) yang kompeten dalam menjalankan aktifitas dari perusahaan itu.…”
One practice is important in a company's performance is in the process of procurement. Performance of human resources in a company shows a measure of the quality of work and is used as a measure to observe the performance levels of employees in a company. The level of underperformance will have an impact on the quality of jobs that will be performed that could have a serious impact on the company. It is necessary to develop a human resources performance measurement using ANP method and TOPSIS, the procurement section of the company. This study aims to assist in the decision making process and seek alternative solutions to address the issues in order to measure the level of performance of each employee. In this study, the method used to obtain the ANP normal weight that will be used for calculations on TOPSIS method. The input parameters in the weighting process ANP is also very affecting for ranking process to be performed on TOPSIS. The input parameter is the ratio of any existing KPI indicators on procurement section. The results showed that the proposed method can be used to build a predictive performance measurement on procurement human resources section. From the research the highest performance values obtained on procurement section is 0.6936 while the lowest value was 0.3584.
Keywords: ANP; TOPSIS; KPI; Human Resources; Procurement Section
AbstrakSalah satu praktek kinerja penting dalam suatu perusahaan adalah pada proses pengadaan. Kinerja human resources pada suatu perusahaan menunjukkan ukuran kualitas suatu pekerjaan dan digunakan sebagai ukuran untuk mengamati tingkat kinerja dari pegawai dalam suatu perusahaan. Tingkat kinerja yang kurang akan berdampak pada kualitas perkerjaan yang akan dilakukan yang bisa berdampak serius pada perusahaan. Maka perlu dikembangkan sebuah pengukuran kinerja human resources dengan menggunakan metode ANP dan TOPSIS, pada procurement section dalam perusahaan. Penelitian ini bertujuan untuk membantu dalam proses pengambilan keputusan dan mencari alternatif solusi untuk mengatasi permasalahan untuk mengukur tingkat kinerja dari setiap pegawai. Pada penelitian ini, metode ANP digunakan untuk memperoleh bobot normal yang nantinya akan digunakan untuk perhitungan pada metode TOPSIS. Parameter masukan pada proses pembobotan ANP juga sangat mempengaruhi untuk proses perangkingan yang akan dilakukan pada TOPSIS. Adapun parameter inputnya adalah perbandingan setiap indikator KPI yang ada padaprocurement section tersebut. Hasil penelitian menunjukkan bahwa metode yang diusulkan dapat digunakan untuk membangun sebuah prediksi pengukuran kinerja human resources padaprocurement section. Dari penelitian diperoleh nilai kinerja tertinggi pada procurement sectionadalah 0,6936 sedangkan nilai terendah adalah 0,3584.
“…The MCDM framework has been extensively applied in economy, engineering, marketing, management, military, and technology, and many other areas [2,3]. In general, a MCDM problem with alternatives, namely, …”
Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.
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