The Best Selection of Programmers in Generation 4.0 Using AHP and ELECTRE Elimination Methods

Abstract

The quality of data processing in information systems in the 4.0 industrial era is expected to be in the form of paperless-based digitalization, thus a number of capable and reliable users are needed in terms of data processing in the form of digitalization, the means developed can be through the internet or via smartphone-based on Android. The need for The best programmer is certainly very needed in terms of data development and processing and information delivery. This needs to be done so that the process of sending data and information can be done simply and very high speed, because the transfer of resources has been converted into digital form. The need for programmer staff must be selected consistently so that users who are accepted as the best and reliable programmers according to job requirements, from ten programmers with collaboration AHP method and ELECTRE can provide optimal decisions with the following results, programmer code P5, P6, P7 and P10 get the biggest score with weight of 3, followed by programmer code P9 with weight of 2, and followed by programmer code P1, P2, P8 with weight of 1, and there are two programmer codes which are eliminated by the ELECTRE method, P3 and P4. The collaboration in the method of Analytic Hierarchy Process (AHP) and ELECTRE Elimination which is the crystallization of the Multi-criteria Decision Making (MCDM) can be a decision support in the selection process of the best programmers to produce optimal decisions.

MCDM-AHP and PROMETHEE methods integrated for base service strategy vendor evaluation and selection

“…This has been substantiated by previous studies utilizing mathematical algebra matrices [15], [16] as well as expert choice apps [16], [17]. The significance of the eigenvector's magnitude is a remarkable phenomenon in rating systems and has garnered extensive utilization [18], The process involves iteratively multiplying matrices until the reduction in the value of the last eigenvector is indistinguishable from that of the previous eigenvector [19]. Ultimately, the optimal eigenvector value will be determined, signifying the completion of the eigenvector calculation process without any further iterations [20].…”

Comparison of Smartphone Technology using AHP, ELECTRE, and PROMETHEE Methods

“…Sourced from the instrumentation in the form of questionnaires filled out by the respondents using conventional methods, the determination of the eigenvector values of the criteria used must be completed with the concept of multiplication matrices. The matrices multiplication process that occurs aims to obtain the optimal eigenvector value which is known from the results of repetitions that occur repeatedly, to find no difference between the last eigenvector and the previous eigenvector value, if you still find the difference value of the eigenvector, then repetition must be done continuously to find the optimal eigenvector (Akmaludin et al, 2020). This process takes quite a long time because it is done using the mathematical algebra matrices method.…”

Sistem Pendukung Keputusan Untuk Menentukan Penerima Beasiswa Menggunakan Metode Electre

“…Diantara berbagai metode SPK yang ada, salah satu metode yang terbaik untuk digunakan untuk pemilihan penerima beasiswa adalah metode Electre. Metode Electre telah digunakan untuk memecahkan berbagai masalah [18]- [20], [21], [22]. Oleh karena itu, untuk mengatasi proses seleksi siswa/i yang layak menjadi penerima beasiswa sehingga dapat mempermudah pihak sekolah SMK Pembangunan Jaya dalam seleksi penerima beasiswa pada sekolah tersebut, maka dirancang sebuah sistem pendukung keputusan dengan menggunakan metode Elimination Et Choix Traduisant La Realite (ELECTRE).…”