Abstract
Each organization must collect data as a result of the use of information technology. Over time the data is processed into information. The information collected is used as a basis for decision making. But not all information can be directly used for the decision making process. Necessary methods and weighting in the process of getting information. One model in a decision support system is Multi Criteria Decision Making (MCDM). The MCDM model makes it possible to provide the best choice of information from several choices of the many criteria and alternatives used. This study compares the MCDM model, namely the ELECTRE (Elimination Et Choix Traduisant la Realite) method, SMART (Simple Multi-Attribute Rating Technique), ARAS (Additive Ratio Assessment) as a priority determination for the handling of areas affected by natural disasters which must be addressed first in the RENAKSI (Reconstruction and Rehabilitation Action Planning), in this case earthquake natural disasters. The ELECTRE method has a different algorithmic process than SMART and ARAS. The validation test method ELECTRE, SMART and ARAS against dataset occurrence of the earthquake is become the results of this research. Spearman rank correlation values for the three methods amounted to 0.96. And another correlation method value of 0.85 for the ARAS method and 0.82 for the ELECTRE and SMART methods.
Highlights
Each organization must collect data as a result of the use of information technology
“An extension system using fuzzy ELECTRE III method for of the Electre I method for group decision-making vendor selection,” Expert Systems with under a fuzzy environment,” Omega, vol 39, no
Ekstrakurikuler untuk Siswa SMA,” JIM, vol 13, impact assessment,” Expert Systems with no
Summary
Informasi diperoleh dari perpaduan data dan pemroses. Proses SPK terdiri dari alternative atau sebagai dibandingkan karena memiliki pola algoritma yang pilihan dan kriteria sebagai data atau parameter yang berbeda dengan metode ELECTRE dan SMART. SMART termasuk dalam metode MAUT (Multi-Attribute Utility Technique) dimana proses pengambilan keputusan menggunakan banyak Matrik keputusan ternormalisasi untuk semua kriteria kriteria dan kriteria-kriteria yang digunakan menggambarkan parameter penentu proses perangkingan dengan membandingkan nilai setiap pengambilan keputusan [15]. Pada metode ARAS nilai perusahaan atau seorang dan atau lebih dari satu orang fungsi utilitas yang menentukan hasil dengan yang memiliki wewenang dalam menentukan pilihan mengikutsertakan alternatif optimum kedalam proses terhadap keputusan atas objek yang ada [26]. Proses algoritma pada metode SMART pada tahapan awal sama seperti metode ELECTRE, yaitu tahapan dari matrik keputusan hingga matrik normalisasi terbobot: Menentukan nilai utiliti dengan mengkonversikan nilai kriteria pada masingmasing kriteria di setiap alternatif menjadi nilai kriteria atau matrik keputusan.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
