A Fuzzy AHP Model for Selection of University Academic Staff

Abstract

There is a growing interest in university academic staff selection since the quality of staff has a direct influence on any organization's effectiveness. The process of selecting suitable academic staff for employment is complex and involves taking multiple criteria into consideration for good decision making. Analytic Hierarchy Process (AHP) is a Multi-Criteria Decision Making (MCDM) model for dealing with decision making problems affected by several conflicting factors. It is useful for selecting the best among alternatives based on certain criteria. However, academic staff selection also contains uncertainties which pose another problem, since the AHP lacks the ability to deal with imprecise and subjective judgment in its pair-wise comparison process. This problem can be overcome by the use of AHP model with fuzzy logic, called Fuzzy AHP model, where triangular fuzzy numbers (TFNs) and linguistic variables are used to achieve better accuracy and consistency in the decision makers' (DM) judgment. A system architecture is developed for problem solving using this model. This paper uses Chang's synthetic extent analysis with TFNs to improve human experts' decision making when recruiting by generating a range of values to incorporate DMs' uncertainty, instead of a crisp value. Numerical example using three alternative candidates based on these criteria: work experience, academic background, and individual skill is presented. The result indicates that the alternative with the highest normalized weight is the most suitable candidate to be selected for employment. This work could be very useful to university establishment and to any other organization that may be interested in fair and efficient recruitment exercise.

Enhancing Job Recruitment Prediction through Supervised Learning and Structured Intelligent System: A Data Analytics Approach

“…However, these approaches are computational complex with inherent inconsistencies and uncertainties in the decision process. Asuquo and Onuodu [13] developed a fuzzy AHP model for selection of university academic staff aimed at utilizing fuzzy logic principles to handle the imprecision, uncertainties, fuzziness and vagueness that exist in the selection process by decision makers. Academic qualification, research experience, and individual factor were used as selection criteria.…”

Penilaian Keberlanjutan Padi Pada Tingkat Lahan Pertanian/Field Level Menggunakan Fuzzy Analytical Hierarchy Process (Fuzzy-Ahp

“…Metode fuzzy AHP adalah pengembangan dari metode AHP standar, menggunakan ketidakpastian yang melekat pada pendekatan AHP dengan menggunakan rasio perbandingan yang didefinisikan dengan fungsi keanggotaan segitiga (Asuquo & Onuodu, 2016), sehingga F-AHP menghasilkan hasil pengambilan keputusan yang lebih akurat (Gnanavelbabu & Arunagiri, 2018) Adapun langkah-langkah fuzzy AHP adalah sebagai berikut 1) perbandingan berpasangan; 2) perbandingan rasio konsistensi; 3) transformasi bilangan fuzzy intro segitiga; 4) perhitungan mean geometrik; 5) perhitungan bobot fuzzy relatif; dan 6) defuzzyfied dan normalisasi untuk menentukan bobot.…”

Comparison of Cash Crop Suitability Assessment Using Parametric, AHP, and FAHP Methods

“…The FAO has created a framework for land suitability. The principle that underlies this framework is the ability of physical environments, such as climate, relief, soil, hydrology, and Table 1 provides the linguistic variable matching triangular fuzzy numbers [39,[43][44][45], trapezoidal fuzzy numbers [46][47][48], and the corresponding membership functions in.…”