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 Utilization of AHP-MAUT Method to Determine the Country of Exhibition Abroad in Batik Hatta Boutique

2021 ◽  
Vol 5 (02) ◽  
pp. 52-56
Author(s):  
Saifur Rohman Cholil ◽  
Tria Ardianita
Keyword(s):  
Decision Making ◽  
Rank Correlation ◽  
Pairwise Comparison ◽  
Hierarchical Level ◽  
Spearman Rank Correlation ◽  
Ahp Method ◽  
Pairwise Comparison Matrix ◽  
Spearman Rank ◽  
Comparison Matrix ◽  
A Value

This research was conducted with the aim of helping decide the destination country for overseas exhibitions at the Batik Hatta Boutique. By knowing all the data and information of a country, boutique owners can decide which country to visit in the batik exhibition. Because if you attend the cast in all countries, there will be overruns in costs. The methods used are AHP and MAUT. The AHP method is used as a weighting using a linguistic value scale. Weights are obtained from the pairwise comparison matrix between two elements of all elements that occur at the same hierarchical level. The MAUT method is used to determine the importance of each alternative for the ranking process. The results of this study indicate that Cambodia was chosen as the location to be visited for the batik exhibition. The results of the validation using the Spearman Rank correlation comparison obtained a value of 0.951 meaning that this method can be used as a decision making.

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 A Discussion on “Pythagorean fuzzy AHP based risk assessment methodology for hazardous material transportation: an application in Istanbul”

2022 ◽  
Author(s):  
Shahid Bhat ◽  
Akanksha Singh
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Value Added ◽  
Pairwise Comparison ◽  
Ahp Method ◽  
Hazardous Material ◽  
Pairwise Comparison Matrix ◽  
Comparison Matrix ◽  
Hazardous Material Transportation ◽  
Material Transportation

Abstract Ayyildiz et al. (Environmental Science and Pollution Research (2021), 1-13) pointed out that it is important to identify and minimize the critical risks in the transportation of hazardous material. For the same, Ayyildiz et al. proposed an effective integrated decision-making methodology by combining the Modified Delphi Method (MDM) and Pythagorean fuzzy analytic hierarchy process (PF-AHP). In this integrated methodology, PF-AHP method is utilized to obtain weights of main and sub-risk factors in order to rank these factors. In Step 5 of PF-AHP method an interval valued Pythagorean fuzzy pairwise comparison matrix is transformed into a crisp matrix and then crisp AHP is applied to obtain the normalized weights from the transformed crisp matrix. It is quite evident that the crisp AHP is used only for crisp pairwise comparison matrix. However, after a deep study, it is observed that the transformed crisp matrix, obtained on applying the steps of Ayyildiz et al. methodology, violates the reciprocal propriety of pairwise comparison matrix. Therefore, to apply crisp AHP on the transformed crisp matrix is mathematically incorrect and will lead to problematic decision-making approach. Hence, may result in a heavy loss in any value-added model such as hazardous material transportation problems. Therefore, the Ayyildiz et al. methodology is not valid in its present form and cannot be used to find the solution of such type of real-life problem. Keeping the same in mind, the focus of this discussion is to make the researchers aware about these mathematical incorrect assumptions and the necessary modification is suggested.

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

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