Aggregating GIS and MCDM to Optimize Wave Energy Converters Location in Tasmania, Australia

2015 ◽  
pp. 141-164
Author(s):  
Phuc Le ◽  
Andrew Fischer ◽  
Irene Penesis ◽  
Rahman Rahimi
Keyword(s):  
Wave Energy ◽  
Analytical Hierarchy Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Wave Energy Converters ◽  
Order Preference ◽  
A Chain ◽  
Hierarchy Process ◽  
Energy Converters

The aim of this chapter is to develop a framework to guide Wave Energy Converters (WECs) sites using the coastal waters of Tasmania as a case study. This chapter proposes a combined two-stage Multi-Criteria Decision Making (MCDM) methodology to determine suitable locations for WECs siting with overlapping and minimal conflicting uses. A methodology combining MCDM and Geographic Information Systems (GIS) was developed combining the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the Analytical Hierarchy Process (AHP). Priority rankings for each of the human uses and ocean features were prioritized using AHP and were then applied to TOPSIS analyses. A chain of optimal locations were determined, stretching from the southwest to southeast coast of Tasmania, where presently low densities of human activities overlap with high wave height. The result shows that suitable areas for harnessing WECs may not always be located in the highest wave energy areas.

Aggregating GIS and MCDM to Optimize Wave Energy Converters Location in Tasmania, Australia

2016 ◽  
pp. 943-966
Author(s):  
Phuc Le ◽  
Andrew Fischer ◽  
Irene Penesis ◽  
Rahman Rahimi
Keyword(s):  
Wave Energy ◽  
Analytical Hierarchy Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Wave Energy Converters ◽  
Order Preference ◽  
A Chain ◽  
Hierarchy Process ◽  
Energy Converters

The aim of this chapter is to develop a framework to guide Wave Energy Converters (WECs) sites using the coastal waters of Tasmania as a case study. This chapter proposes a combined two-stage Multi-Criteria Decision Making (MCDM) methodology to determine suitable locations for WECs siting with overlapping and minimal conflicting uses. A methodology combining MCDM and Geographic Information Systems (GIS) was developed combining the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the Analytical Hierarchy Process (AHP). Priority rankings for each of the human uses and ocean features were prioritized using AHP and were then applied to TOPSIS analyses. A chain of optimal locations were determined, stretching from the southwest to southeast coast of Tasmania, where presently low densities of human activities overlap with high wave height. The result shows that suitable areas for harnessing WECs may not always be located in the highest wave energy areas.

Customer and Order Prioritization With Multi-Criteria Decision Making

2021 ◽  
pp. 57-75
Author(s):  
Emre Aslan
Keyword(s):  
Analytical Hierarchy Process ◽  
Production Systems ◽  
Customer Relationship ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Make To Order ◽  
Order Preference ◽  
Production Manager ◽  
Metal Processing ◽  
Hierarchy Process

Customer and order prioritization is prioritizing the orders according to features of customers and orders. In make-to-order production systems, especially when demand exceeds the capacity, a need arises for prioritizing the orders. As a customer may have more than one order and as one type of order may belong to different customers, every job order must be prioritized according to both customer and order features. Prioritization values may be used for accepting and scheduling orders or selecting customers as a reflection of supplier selection. In this chapter, the production manager and customer relationship manager of a metal processing firm were interviewed for determining the criteria for prioritizing customers and orders. After determining the criteria, the managers were asked to pairwise compare the criteria for weighting with analytical hierarchy process (AHP). Then by considering scores of customers and orders for each criterion, orders were prioritized with technique for order preference by similarity to ideal solution (TOPSIS).

A FUZZY APPROACH TO BUSINESS TRAVEL AIRLINE SELECTION USING AN INTEGRATED AHP-TOPSIS-MSGP METHODOLOGY

2013 ◽  
Vol 12 (01) ◽  
pp. 119-137 ◽  
Author(s):  
CHIN-NUNG LIAO
Keyword(s):  
Analytical Hierarchy Process ◽  
Real Life ◽  
Evaluation Process ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Business Travel ◽  
Or Organization ◽  
Hierarchy Process ◽  
A Company

Airline selection is a multi-criteria decision-making (MCDM) problem faced in business travel. The evaluation process primarily involves the evaluation of several complex factors for selecting an airline that will best meet business travel needs. Previous studies have proposed several different methods that a company or organization can use to evaluate or select an airline. In its proposed approach to solving airline selection, this study integrates the analytical hierarchy process (AHP) with a type of preference ordering involving the determination a solution's similarity to an ideal solution (TOPSIS) and multi-segment goal programming (MSGP). A real-life case study on selecting an airline is also presented.

TERAPAN KOMBINASI METODE TOPSIS DAN ANALYTICAL HIERARCHY PROCESS PADA PEREKOMENDASIAN PENERIMA BEASISWA PENINGKATAN PRESTASI AKADEMIK (Studi Kasus pada STMIK PPKIA Tarakanita Rahmawati)

2017 ◽  
Vol 8 (2) ◽  
pp. 663 ◽  
Author(s):  
Muhammad Fadlan ◽  
Muhammad Muhammad ◽  
Hadriansa
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
Ideal Solution ◽  
Microsoft Excel ◽  
Order Preference ◽  
Hierarchy Process

Beasiswa Peningkatan Prestasi Akademik (PPA) sebagai salah satu bentuk dukungan pemerintah Republik Indonesia terhadap dunia pendidikan. Beasiswa yang disalurkan oleh pemerintah melalui Perguruan Tinggi yang ada di Indonesia ini, penyeleksian dan penetapan penerimanya sepenuhnya diserahkan kepada pihak Perguruan Tinggi yang bersangkutan. Tahap inilah yang sangat rentan terjadinya kecurangan. Pada objek penelitian  yang diteliti hingga saat ini proses penyeleksian masih dilakukan dengan menggunakan Microsoft Excel, hal ini tentu saja kurang efektif dan efisien, serta rentan akan terjadinya kesalahan bahkan kecurangan. Untuk itu, diperlukan suatu metodologi dan aplikasi yang tepat dalam melakukan penyeleksian penerima beasiswa tersebut. Decision Support System digunakan sebagai solusi untuk melakukan perekomendasian penerima beasiswa, khususnya dengan menggunakan Metode Technique  for  Order  Preference  by  Similarity  to  Ideal  Solution  (TOPSIS)  dan  Analytical  Hierarcy Process (AHP). Penggunaan kombinasi dua metode tersebut dilakukan agar memiliki tingkat akurasi yang baik jika dibandingkan  dengan menggunakan satu metode. Hasilnya,  aplikasi  decision support system dengan penerapan kombinasi metode Topsis dan AHP berhasil di rancang dan di ujicoba, serta sukses dalam perekomendasian penerima beasiswa PPA dengan menghasilkan data alternatif mahasiswa yang terurut mulai dari nilai preferensi yang paling tinggi 0.764 hingga terendah 0.189. Hasil ini dapat menjadi rekomendasi bagi pengambil keputusan dalam mengambil keputusan yang efektik, efisien dan dapat dipertanggung jawabkan.

Sistem Pendukung Keputusan untuk Menentukan Penerima Bantuan Beasiswa dengan Metode AHP dan TOPSIS

Sainteks ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 65
Author(s):  
Rima Dwi Mainingsih ◽  
Muhammad Hamka
Keyword(s):  
Analytical Hierarchy Process ◽  
Black Box ◽  
Ideal Solution ◽  
Order Preference ◽  
Black Box Testing ◽  
Hierarchy Process

Salah satu program LAZISMU Banyumas adalah beasiswa. Beasiswa merupakan pemberian bantuan keuangan yang diberikan kepada perorangan yang bertujuan untuk meningkatkan kapasitas SDM atau Sumber Daya Manusia melalui pendidikan. Permasalahan di LAZISMU, sistem bantuan beasiswa masih bersifat manual maka diperlukan suatu sistem pendukung keputusan (SPK) untuk memperhitungkan segala kriteria yang mendukung pengambilan keputusan guna membantu, mempercepat dan mempermudah proses pengambilan keputusan. Metode yang digunakan pada sistem pendukung keputusan adalah metode Analytical Hierarchy Process (AHP) dan metode TOPSIS. Analytical Hierarchy Process (AHP) yang digunakan untuk memperbaiki nilai bobot dari kriteria. Nilai bobot yang dihasilkan dari metode AHP selanjutnya digunakan untuk menentukan proses peranking calon penerima bantuan beasiswa menggunakan metode Technique For Order Preference By Similarity To Ideal Solution (TOPSIS). Metode AHP dan TOPSIS digunakan untuk meningkatkan hasil rekomendasi calon penerima bantuan beasiswa. Hasil klasifikasi kemudian dievaluasi menggunakan Black Box Testing untuk mengetahui apakah fungsi, masukan dan keluaran dari perangkat lunak sesuai dengan spesifikasi yang dibutuhkan. Dengan demikian dapat disimpulkan bahwa sistem aplikasi telah berjalan sesuai dengan tujuan yang diharapkan, karena tidak ditemukan adanya kesalahan pada interface serta sistem yang dirancang dan dibangun mampu mengatasi kelemahan-kelemahan yang terdapat pada sistem yang lama dan memberikan hasil rekomendasi calon penerima bantuan beasiswa.Kata-kata Kunci: sistem pendukung keputusan, penerima beasiswa, AHP, TOPSIS, black box testing

Sistem Pendukung Keputusan Pemilihan Bibit Padi Berkualitas Dengan Metode AHP Dan Topsis

2021 ◽  
Vol 10 (2) ◽  
pp. 162-169
Author(s):  
Istna Mar`atul Khusna ◽  
Novita Mariana
Keyword(s):  
Analytic Hierarchy Process ◽  
Analytical Hierarchy Process ◽  
Ideal Solution ◽  
Analytic Hierarchy ◽  
Order Preference ◽  
Hierarchy Process

Abstrak— Bibit merupakan salah satu penentu dalam keberhasilan budidaya tanaman padi. Budidaya tanaman padi dimulai dari memilih bibit tanaman yang berkualitas karena bibit termasuk objek utama yang dikembangkan pada budidaya selanjutnya. Bibit sebagai pembawa gen dari induknya yang akan menentukan sifat dari tanaman setelah berproduksi dan untuk mendapatkan bibit padi yang berkualitas dapat diperoleh dari memilih dan menentukan bibit yang berasal dari induk berkualitas. Kualitas bibit merupakan kunci keberhasilan dalam budidaya padi. Bibit yang berkualitas mampu beradaptasi, memiliki pertumbuhan yang cepat serta seragam, tumbuh lebih cepat, tahan hama dan tinggi nilai produktivitasnya. Untuk mendapatkan bibit padi berkualitas, petani sering mengalami kesulitan. Berdasarkan kesulitan yang dialami petani, maka akan dibangun sebuah sistem pendukung keputusan untuk membantu petani memutuskan bibit yang akan ditanam sesuai dengan kondisi lingkungan tanam dengan mempertimbangkan beberapa aspek kriteria. Dalam mengatasi masalah pemilihan bibit padi tersebut dibuat sebuah program sistem pendukung keputusan agar memudahkan informasi dan rekomendasi kepada petani padi tentang bibit yang berkualitas. Dengan menggunakan dua metode yaitu Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Penentuan bobot kriteria dilakukan dengan menggunakan metode Analytic Hierarchy Process (AHP), sedangkan untuk tahap perankingan dikerjakan dengan menggunakan metode TOPSIS. Hasil yang didapatkan dari penelitian ini adalah padi berkualitas dari lima alternatif yang sudah ditetapkan, yaitu: Sunggal, Inpari32, Ciherang, IR64, Situbagendit. Sistem menghasilkan nilai preferensi tertinggi yaitu 0,858 pada padi Sunggal di urutan pertama dan  0,767 pada padi Inpari32 diurutan kedua. Jadi dari hasil penelitian ini, peneliti merekomendasikan bibit padi berkualitas yang cocok ditanam di di desa sambongbangi yaitu Sunggal dan Inpari32..Kata Kunci : Bibit Padi, DSS, TOPSIS, AHP, Kualitas Bibit Padi

scholarly journals SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI PEMBUKAAN CABANG USAHA ONLINE BICYCLE INDONESIA DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) DAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS)

2021 ◽  
Vol 11 (2) ◽  
pp. 469-479
Author(s):  
Rizki Adha ◽  
Tjahjanto Tjahjanto
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
Food Delivery ◽  
Ideal Solution ◽  
Fixed Costs ◽  
Topsis Method ◽  
Order Preference ◽  
Hierarchy Process

The choice of business location will affect the risks and benefits of the company as a whole. This condition occurs because the location greatly affects the fixed costs and variable costs, both in the medium term and long term. The location of the business should be taken into account at the time of planning, so that the business to be run can be organized implementation in the future. Online Bicycle Indonesia is a startup engaged in goods and food delivery services by using online-based bike, will open branches in several cities and districts in Tangerang Raya area so that the result of choosing the right branch location, required a dynamic decision support system that can later be used as consideration of managers in the process of selecting branch locations. Problems in selecting branch of this company can be used Decision Support System using AHP-TOPSIS method. Analytical Hierarchy Process (AHP) method has advantages based on pair comparison matrix and perform consistency analysis, while Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method can solve practical decision making, because the concept is simple and easy to understand, and have the ability to measure the relative performance of decision alternatives. The results of the study show Kota Tangerang Selatan is superior to the weight of 0.824, the two Kota Tangerang with a weight of 0.732 and three Kabupaten Tangerang with a weight of 0.0, The decision taken can be accounted for by the calculation of AHP-TOPSIS as a model in the decision support system

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