Konferensi ini bertujuan untuk menyediakan platform bagi para peneliti dan praktisi baik dari akademisi maupun industri untuk bertemu dan berbagi perkembangan inovatif. Program ini diselenggarakan di Allium Hotel Tangerang dan didukung oleh beberapa perguruan tinggi sebagai Co-Host, antara lain Universitas Muhammadiyah Tapanuli Selatan, Universitas Jenderal Achmad Yani, Universitas Muhammadiyah Kudus, STIKES Muhammadiyah Klaten, Universitas Muhammadiyah Sukabumi, STKIP Muhammadiyah Sampit, Universitas Langlangbuana, dan Universitas Widyatama. Kami mengucapkan terima kasih kepada panitia ilmiah dan reviewer serta panitia Universitas Muhammadiyah Tasikmalaya, Universitas Muhammadiyah Tangerang dan Co-Host yang telah turut serta mensukseskan acara ini sehingga acara ini dapat terselenggara sesuai dengan rencana.
Kami juga menginformasikan kepada Rektor Universitas Muhammadiyah Tasikmalaya yang mendukung acara ini dari segi keuangan dan sarana pendukung lainnya. Mustafa Bin Mamat, Universitas Sultan Zainal Abidin, Malysia Prof. Sundarapandian Vaidyanathan, Universitas Vel Tech, India Prof. Wahyu Widada, Universitas Bengkulu, Indonesia. Ade Gafar Abdullah, Universitas Pendidikan Indonesia, Indonesia Dr. Mumu Komaro, Universitas Pendidikan Indonesia, Indonesia Dr. Iwa Kuntadi, Universitas Pendidikan Indonesia, Indonesia Dr. Janner Simarmata, Universitas Negeri Medan.
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The Best Selection of Programmers in Generation 4.0 Using AHP and ELECTRE Elimination Methods
Introduction
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. A number of methods can be done to measure the selection of reliable and best programmers, one of which is the analytic hierarchy process (AHP) [4], which can be collaborated with elimination methods such as ELECTRE (Elimination Et ChoixTraduisant La Realite) [5 ],[6 ]. This collaboration method has a good level of accuracy, so it can be used to select programmers to get the best rating among them.
AHP can be used to determine the preferred size of a number of criteria for determining each criterion weight, while the Elimination ELECTRE method is used to determine the alternatives for programmers in the reliable category. The collaboration between the two methods will provide the optimal solution [7] for determining the selection process for reliable programmers. Criteria parameters used as a barometer [8]for selecting programmers include seven criteria, namely abstract representation, conceptual design, logical data model, physical data model, encoder, cyclomatic logical and logical matrices.
While alternative programmers consist of ten people to become the best programmers in the 4.0 generation era.
Methods
It can thus determine the value of the value of the consistency vector, which is the result of multiplying the matrices in pairs with the optimal eigenvector [15], from this the optimal length of the vector can be obtained where the vectors are arranged in layers to determine the size of average. Then determine the consistency ratio (CI) shown in (equation-2) and test the consistency ratio (CR) on the feasibility of the value provided that <= 0.1 or vice versa if it is more than 10% then the decision should be checked again the possibility of placing matrices in pairs has wrong input [16], pay attention (equation-3). The results of this optimal eigenvector can be used as a preference for evaluating each criterion.
The selection system with the elimanasi concept is a method that can be done with ELECTRE (Elomination Et Choix Taduisant La Realite), this method requires a long step in the preparation of extended data through a comparison of each row of data of each element criterion [17]. The steps that can be done through the ELECTRE method are (1) data initialization; (2) normalization of data sets; (3) compare each row of data with other rows; (4) quantify compliance and noncompliance; (5) determine the threshold value; (6) determine the dominant aggregate matrices; (7) Define alternative estimates [6]. ELECTRE which is used in the case of selecting the best programmers will need a support formulation that helps in each step of the calculation of selecting the best programmers.
Alternative data and criteria that are adjusted so that they can be processed mathematically, must go through the stages of normalization that can be done using (equation-4) [3]. The aggregate of the matrices can be used as a basis for determining the ranking of each alternative [20], the highest ranking being given to the point with the largest cumulative number of multiplication concordance scores and dominant discordance matrices. The input data of the questionnaire can be processed with the concept of algebra matrices and can be tested with the help of the expert choice application as a logical comparison.
The accumulation of data is expressed in the form of pairwise matrices containing points consisting of seven criteria seen in (Table 2) and (Figure 2). Decisions that can be made as preferences for seven criteria are made through an iteration process that has taken place five times. It turns out that it is capable of providing optimal eigenvector values, things can be known by the difference in eigenvector values obtained with the previous eigenvector value zero at the decimal value position. The value of the interval value as a rating has a range from one to five.
Thus, the stages of elimination with the ELECTRE method began to be clearly visible at the stage of finding agreement and discordance of matrices, by looking at the size of the threshold value of each of them. The value of the threshold size can be searched using (Equations 9 and 10). This can be done to determine the dominant concordance matrices and dominant discordance matrices. Where the value of the requirements determined on the basis of the threshold value is a definitive reference and must be valued above the threshold value.
Conclusion
After obtaining each value for the dominant matrices, you will carefully find the total dominant matrices. Aggregate dominant matrices can also occur in the second phase of elimination, where the results of multiplication using (equation 11) form the basis of ranking by obtaining the number of weights obtained from the seven criteria used, note in (table 5). . Lipovetsky, “An Interpretation of the AHP Eigenvector Solution GfK Custom Research North America 8401 Golden Valley Rd., Minneapolis, MN 55427, USA 2.
The AHP solution and its interpretation for the maximum eigenvalue λ gives the principal eigenvector α which ser,” vol. Ercan, "Analytic hierarchy & network analytic processes in multi-criteria decision-making: A comparative study", J. Milic-Markovic, "Multi-criteria decision-making when choosing highway route variants at the preliminary design level", Facta Univ.
Santoso, "Employee Promotion Basis in Job Performance Specification Using: MCDM, AHP and ELECTRE Methods", 2018 6th Int.
SURAT TUGAS
309/B.01/PPPM-NM/III/2020 Tentang
PENELITIAN YANG DIPUBLIKASIKAN DALAM JURNAL ILMIAH Periode Maret - Agustus 2020
The 2nd International Conference on Computer, Science, Engineering, and Technology 15-16 October 2019, Banten, Indonesia
Judul
The Best Selection of Programmers in Generation 4.0 Using AHP and ELECTRE Elimination Methods
MEMUTUSKAN
34;The selection of periodic salary increase for civil servants using Fuzzy MADM th International Conference on Information Technology,. Base System and TOPSIS Technique for Multi-Attribute Decision Making", Proceedings of the 3rd International Conference on Software. 34; The Little Ice Age: evidence from a sediment record in Gullmar Fjord, Swedish west coast", Biogeosciences, 2013.