Decision support system for considering the best teacher performance using MOORA method

Hanifatulqolbi, D; Ismail, Iklima Ermis; Hammad, Jehad; Al-Hooti, Mohammed Hatem Ali

doi:10.1088/1742-6596/1193/1/012018

Cited by 10 publications

(10 citation statements)

References 4 publications

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“…Making a decision matrix [10], as below : Explanation : X = Decision matrix X ij = m alterntive values in n criterion 3. Normalization matrix [6] X…”

Section: B Mooramentioning

confidence: 99%

“…4. Calculating preferences value [6] [8] Before determining the preference value, do a multiplication of each value in the normalization matrix with the weight of each criterion.…”

Section: B Mooramentioning

confidence: 99%

“…This method is multi-criteria techniques which has five main steps: determining goals and identifying attributes or criteria, displaying all alternatives in the form using decision matrix, then normalizing the decision matrix and multiplying the matrix with each weight of criteria to produce a weighted normalization matrix, after that determine the value of preferences in each alternative by adding up all the criteria in benefit (beneficial attributes) and reduce them to the criteria that are non beneficial (non-beneficial attributes), and make a sequence or ranking based on the value of the highest preference to the lowest. The conclusion was the best alternative has the highest preference value while the worst alternative has a low preference value [5] [6].…”

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confidence: 99%

“…In this study used 2 main criteria, that was hard competency and soft competency that having supported in competency. Based on these studies it was concluded that the MOORA method can help in determining the teacher who has the best performance quickly and more objectively [6]. Other research using the MOORA method is to provide recommendations regarding students who are eligible to receive scholarships at the AMIK Tunas Bangsa foundation (Andani SR, et al, 2019) [7] and was also used to evaluate the performance of 4 machines in an industry consisting of 6 criteria (Domínguez L Perez, et al, 2018) [8].…”

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confidence: 99%

“…=1 .............................(3) Then calculate the optimization value by adding up the maximum value type (beneficial attributes) for each alternative and subtracting it from the minimum value type (non-beneficial attributes) for each alternative on the all alternative belong to the interval (0;1) [6][13] with the following formula [13]: ...............(4) 5. RankingThe ranking is done by sorting the preference value, which the alternative having the highest preference value is considered the best alternative while the lowest preference value is considered as the worst alternative[6] [8].…”

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confidence: 99%

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Implementation of MOORA Method for Determining Prospective Smart Indonesia Program Funds Recipients

Zaitun¹,

Mustakim²,

Kamila³

et al. 2019

IJEAT

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 Abstract: Presidential Instruction No. 7 of 2014 mandates PIP to the Ministry of Education and Culture to summarize Indonesia Smart Card (KIP) and spread PIP funds to students that cannot afford to pay education. However, Indonesia Corruption Watch (2018) explained that the data used for the Smart Indonesia Program (PIP) was still inaccurate because almost half of the poor people with a percentage of 42.9% were not registered as participants in the Smart Indonesia Program (PIP). According to ICW, this is due to the data used for the process of determining the candidates for the Smart Indonesia Program recipients of the funds are still inaccurate and harming others who supposed to get funds. One method that usually used as a decision-making technique in the research is the Multi-Objective Optimization Ratio Analysis (MOORA) method which is a multi-criteria decision-making that has five main steps as a technique and it can be used to rank prospective PIP fund recipients based on the highest to the lowest preference values. The results of this studyindicate that the first rank with the highest value was 0.0539 and the last rank with the lowest value was 0.0211 so it used to ease the stakeholders to determine the amount of KIP recipients based on the preference values. This method can be applied for stakeholders needed in compared to monotonous data processing using estimates.

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“…Making a decision matrix [10], as below : Explanation : X = Decision matrix X ij = m alterntive values in n criterion 3. Normalization matrix [6] X…”

Section: B Mooramentioning

confidence: 99%

“…4. Calculating preferences value [6] [8] Before determining the preference value, do a multiplication of each value in the normalization matrix with the weight of each criterion.…”

Section: B Mooramentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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