scholarly journals New parametric prioritization methods for an analytical hierarchy process based on a pairwise comparison matrix

2011 ◽  
Vol 54 (11-12) ◽  
pp. 2736-2749 ◽  
Author(s):  
Liang-an Huo ◽  
Jibin Lan ◽  
Zhongxing Wang
Keyword(s):  
Analytical Hierarchy Process ◽  
Pairwise Comparison ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
Hierarchy Process

scholarly journals SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN BEASISWA BIDIKMISI DI UINSA DENGAN MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS (AHP)

2021 ◽  
Vol 10 (2) ◽  
pp. 188
Author(s):  
Mila Iflakhah ◽  
Moh. Hafiyusholeh
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Science And Technology ◽  
Pairwise Comparison ◽  
Primary Data ◽  
Eigenvalues And Eigenvectors ◽  
Pairwise Comparison Matrix ◽  
Screening Process ◽  
Comparison Matrix ◽  
Hierarchy Process

<p class="AfiliasiCxSpFirst" align="left"><strong>Abstrak:</strong></p><p class="AfiliasiCxSpMiddle">            Beasiswa merupakan pemberian bantuan biaya pendidikan kepada mahasiswa yang mampu dalam bidang akademik tetapi tidak dalam perekonomian. Namun masih sering terjadi kendala dalam pemrosesan seleksi pendaftar beasiswa, yaitu banyaknya kriteria yang harus diperhatikan dan banyaknya data pendaftar sehingga pengambilan keputusan menjadi relatif lebih sulit. Tujuan dari penelitian ini adalah memberikan alternatif dalam pengambilan keputusan penerima bantuan beasiswa untuk mahasiswa fakultas sains dan teknologi UINSA dengan menggunakan metode <em>Analytical Hierarchy Process (</em>AHP). Data yang diolah adalah data primer yang diperoleh dari angket. Data yang telah terkumpul selanjutnya dianalisis dengan matriks perbandingan berpasangan untuk menentukan nilai eigen dan vektor eigen. Hasil penelitian menunjukkan bahwa dari 39 pendaftar diperoleh 12 pendaftar yang menjadi prioritas dalam mendapatkan beasiswa Bidikmisi. Berturut-turut mahasiswa dengan kode Z1, Z2, Z5, Z7, Z10, Z19, Z20, Z21, Z23, Z29, Z32, Z35 dengan masing-masing bobot sebesar 0.34%, 0.27%, 0.27%, 0.28%, 0.36%, 0.33%, 0.29%, 0.31%, 0.34%, 0.29%, 0.27%, 0.35%.</p><p class="AfiliasiCxSpMiddle" align="left"> </p><p class="AfiliasiCxSpLast" align="left"><strong>Kata Kunci</strong>:</p><p>Vektor<em> </em>Eigen<em>, Analytical Hierarchy Process </em>(AHP)<em>, </em>Nilai<em> </em>Eigen</p><p> </p><p class="AfiliasiCxSpFirst" align="left"><strong><em>Abstract:</em></strong></p><p class="AfiliasiCxSpMiddle"><em>The scholarship is the provision of tuition assistance to students who are capable of academics but have difficulties economically. However, some obstacles are often found throughout the screening process of scholarship applicants, such as the number of criteria to fulfill and the number of registrant data that results in difficulties in making a decision</em><em>. </em><em>This study aims to provide an alternative in decision making on the screening process of scholarship applicants for students from the Faculty of Science and Technology at the Universitas Islam Negeri Sunan Ampel by using the Analytical Hierarchy Process (AHP)</em><em>. </em><em>The data processed are from the primary data obtained from questionnaires. The data obtained were analyzed by using a pairwise comparison matrix to determine the eigenvalues and eigenvectors. The results indicate that of 39 registrants, 12 of them became a priority in getting the Bidikmisi scholarship</em><em>. </em><em>Consecutively, students with codes</em><em> Z1, Z2, Z5, Z7, Z10, Z19, Z20, Z21, Z23, Z29, Z32, Z35 </em><em>have the score of</em><em> 0.34%, 0.27%, 0.27%, 0.28%, 0.36%, 0.33%, 0.29%, 0.31%, 0.34%, 0.29%, 0.27%, 0.35%.</em><em></em></p><p class="AfiliasiCxSpMiddle" align="left"><strong><em> </em></strong></p><p class="AfiliasiCxSpLast" align="left"><strong><em>Keywords</em></strong><em>:</em></p><em>Eigenvector, Analytical Hierarchy Process</em> (AHP), <em>Eigenvalue</em>

Improved Consistency Ratio for Pairwise Comparison Matrix in Analytic Hierarchy Processes

2016 ◽  
Vol 33 (03) ◽  
pp. 1650020
Author(s):  
L. N. Pradeep Kumar Rallabandi ◽  
Ravindranath Vandrangi ◽  
Subba Rao Rachakonda
Keyword(s):  
Error Function ◽  
Pairwise Comparison ◽  
Large Set ◽  
Simulation Experiments ◽  
Analytic Hierarchy ◽  
Chi Square ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
Hierarchy Process ◽  
Original Information

The analytical hierarchy process (AHP) uses pairwise comparison matrix (PCM) to rank a known set of alternatives. Sometimes the comparisons made by the experts may be inconsistent which results in incorrect weights and rankings for the AHP. In this paper, a method is proposed which identifies inconsistent elements in a PCM and revises them iteratively until the inconsistency is reduced to an acceptable level. An error function similar to chi-square is used to identify the inconsistent elements which are revised with suitable values. The method is illustrated with some numerical examples mentioned in the literature and a comparative study of the results in terms of deviation from the PCM and preservation of original information is taken up. Monte Carlo simulation experiments over a large set of random matrices indicate that the proposed method converges for the moderately inconsistent matrices.

scholarly journals Analytical hierarchy process (AHP) approach to the selection of heritage building element

2018 ◽  
Vol 250 ◽  
pp. 05001
Author(s):  
Siti Nor Fatimah Zuraidi ◽  
Mohammad Ashraf Abdul Rahman ◽  
Zainal Abidin Akasah
Keyword(s):  
Analytical Hierarchy Process ◽  
Pairwise Comparison ◽  
Pairwise Comparison Matrix ◽  
Building Element ◽  
Structure Building ◽  
Heritage Buildings ◽  
Heritage Building ◽  
Selection For ◽  
Hierarchy Process ◽  
Selection Of

In order to bring the reduction of damage and defect of heritage buildings, the management needs to use an suitable methodology approach for the element heritage building. The goal of this paper is to make the selection of criteria and attribute by using the Analytical Hierarchy Process (AHP) for heritage building. The selection of criteria and attributes for heritage building are divided into three criteria which are building the structure, building fabric, and building service. By pairwise comparison matrix, the process of selection for criteria and attribute to to enable possible improvements. This finding has shown that all element criteria and attributes in heritage building are important with their function.

Electronic Market Credit Risk Evaluation for Agricultural Products Based on Analytic Hierarchy Process

2011 ◽  
Vol 99-100 ◽  
pp. 852-856
Author(s):  
You Zhu Li ◽  
De Hua He
Keyword(s):  
Analytic Hierarchy Process ◽  
Credit Risk ◽  
Risk Evaluation ◽  
Pairwise Comparison ◽  
Agricultural Products ◽  
Electronic Market ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
Hierarchy Process

In the study, electronic market credit risk evaluation for agricultural products based on analytic hierarchy process is proposed.Firstly, the evaluation indexes are analyzed and the hierarchic tree is formulated based on the evaluation indexes.Then, pairwise comparison matrix is established,and the consistency of discriminant matrix is judged.When the consistency of discriminant matrix is satisfied,the weight vector of the indexes which are used to establish the pairwise comparison matrix are obtained. And weight of each index is obtained.Finally,final decision making is obtained. The experimental results show that the evaluation of electronic market credit risk evaluation for agricultural products based on analytic hierarchy process is effective.

scholarly journals APPLYING THE ANALYTIC HIERARCHY PROCESS TO OIL SANDS ENVIRONMENTAL COMPLIANCE RISK MANAGEMENT

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Izak Johannes Roux ◽  
Dr. Christos Makrigeorgis
Keyword(s):  
Analytic Hierarchy Process ◽  
Oil Sands ◽  
Pairwise Comparison ◽  
Environmental Compliance ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
Risk Criteria ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

<p>In 2013, oil companies in Alberta, Canada invested $32 billion in new oil-sands projects.  Despite the size of this investment, there is a demonstrable deficiency in the uniformity and understanding of environmental legislation requirements that translate into increased project compliance risks. In this paper, we applied the Analytic Hierarchy Process (AHP) to develop a priority list of environmental regulatory compliance risk criteria for oil-sands projects.  AHP belongs to the family of multicriteria decision-making (MCDM) techniques that utilizes a pairwise comparison matrix solicited from subject matter experts (SMEs) in the field as input.  The overall methodology itself consisted of 4 phases: (1) identification of the initial list of N potential environmental compliance risk criteria and verification of these criteria via a pilot survey; (2) formation of a pairwise comparison survey in the form of an N(N-1)/2 comparison matrix based on the verified criteria; (3) administration of the pairwise comparison matrix to a sample of 16 industry-specific SME’s; and (4) the application of the AHP method using SuperDecisions as a tool on the collected sample to rank the identified risk criteria. Our demonstrated results can potentially inform Alberta oil sands industry leaders about the ranking and utility of specific compliance risks as understood by experts and enable a more focused environmental compliance action to help increase legislative and public trust.</p>

scholarly journals Proposed Method for Supplier Selection

2020 ◽  
Vol 13 ◽  
pp. 376-394
Author(s):  
Agus Ristono ◽  
Tri Wahyuningsih ◽  
Eko Junianto
Keyword(s):  
Network Model ◽  
Analytical Hierarchy Process ◽  
Supplier Selection ◽  
Pairwise Comparison ◽  
Pairwise Comparisons ◽  
Chain Process ◽  
Ahp Method ◽  
Pairwise Comparison Matrix ◽  
Consistency Ratio ◽  
Hierarchy Process

The use of the Analytical Hierarchy Process (AHP) is frequent in supplier selection. First, AHP is a pairwise comparison between criteria. If the pairwise comparisons are inconsistent, the result is invalid. Thus, the process of comparing criteria must be repeated continuously until valid results are obtained. This process takes time and costs so it is considered inefficient. This research proposes the application of the Hamilton chain process into the pairwise comparison matrix. One criterion is symbolized as a knot, while the arc is symbolized as the pairwise comparison value between the two nodes or the connected criterion. In the network model of the AHP method, each node is connected to all other nodes without exception. Whereas in the proposed method, each criterion or node is compared only once. That said, avoiding inconsistencies can be made. The consistency ratio result of the proposed method is found to be consistent

Materials selection criteria weighting method using analytic hierarchy process (AHP) with simplest questionnaire and modifying method of inconsistent pairwise comparison matrix

2021 ◽  
pp. 146442072110399
Author(s):  
Won-Chol Yang ◽  
Jae-Bok Ri ◽  
Ji-Yon Yang ◽  
Ju-Song Kim
Keyword(s):  
Analytic Hierarchy Process ◽  
Selection Criteria ◽  
Pairwise Comparison ◽  
Hot Water ◽  
Materials Selection ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

The analytic hierarchy process has been widely used to determine subjective weights of materials selection criteria in materials selection using multi-criteria decision-making. However, the analytic hierarchy process has some drawbacks: it is difficult to construct a pairwise comparison matrix and meet the consistency requirement. First, we propose a new simplest questionnaire to perform the pairwise comparison without confusion, conventionally and easily. Next, we propose an improved modifying method for inconsistent pairwise comparison matrix according to the following principles: (1) the elements of the reconstructed pairwise comparison matrix should be nine-point scales, (2) the number and modifying the amount of the modified elements should be as small as possible and (3) the deviation between the original and reconstructed pairwise comparison matrixes should be as small as possible. The outline of the proposed modifying method is as follows: (1) calculate the consistency ration decrements of all the pairwise comparison matrixes reconstructed by modifying every element of the original pairwise comparison matrix to the lower and upper adjacent nine-point scales and (2) find the element with the maximum consistency ratio decrement and modify it to the lower or upper adjacent scale. To illustrate the effectiveness, we apply the proposed methods to determine the criteria weights for selecting the best phase change material used in a solar domestic hot water system, and apply the proposed modifying method to some examples from the published papers, and compare the performances with some previous methods. The simplest questionnaire and improved modifying method help materials designers and engineers to apply the analytic hierarchy process method in materials design and optimization problems, much more actively.

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