Decision Support System for Service Quality Using SMART and Fuzzy ServQual Methods

Lestari, Sri; Romahdoni, Muhammad Reza

doi:10.30595/juita.v9i1.9644

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…The average results of prediction observations with non-stationary fuzzy will be calculated for the error value against the average results of the actual observations. The calculation of the error value is done using MAPE (mean absolute percentage error), which can be written using (7) [22].…”

Section: Fig 1 Flowchart Of Research Methodologymentioning

confidence: 99%

“…Based on (7), Ai is the average result of actual observations, while Fi is the average result of prediction observations with non-stationary fuzzy. The resulting error values will be stored for a single instance.…”

Section: Fig 1 Flowchart Of Research Methodologymentioning

confidence: 99%

“…However, there is uncertainty in determining how much influence meteorological factors have on the level of O3 concentration [6]. This uncertainty can be modelled using fuzzy logic [7].…”

Section: Introductionmentioning

confidence: 99%

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Prediction of O3 Concentration Level Using Fuzzy Non-Stationary Method

Suksmawati

Wardoyo²

2022

JUITA

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The composition of air concentration is not constant. It constantly changes with minor changes at any time, so more than one measurement is needed to represent the air concentration level for a full day. The fuzzy non-stationary method can overcome uncertainty in an environment that is not constant or caused by minor temporal changes based on time variables. This study uses a non-stationary fuzzy method to determine the level of O3 concentration based on the input variables of temperature, humidity, and wind speed. The tests were conducted in September, October, and November using four types of implication process interpretation, namely interpretation 1 (classical logic), interpretation 2 (classical logic), interpretation 3 (algebraic), and interpretation 3 (standard). The test results in September showed a tendency for error percentage using the MAPE amount of 19, October's amount of 25, and November's amount of 18.

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Section: Fig 1 Flowchart Of Research Methodologymentioning

confidence: 99%

Section: Fig 1 Flowchart Of Research Methodologymentioning

confidence: 99%

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Prediction of O3 Concentration Level Using Fuzzy Non-Stationary Method

Suksmawati

Wardoyo²

2022

JUITA

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“…Penelitian tentang sistem pendukung keputusan yang dilakukan dengan menggunakan metode SMART antara lain, untuk menentukan penempatan karyawan baru [2], untuk menentukan layanan verifikator [3], untuk pemilihan lokasi perumahan [4], untuk pemilihan smartphone [5], untuk merekrut anggota KPPS pemilu [6], untuk pemilihan pejabat struktural perguruan tinggi [7], untuk menentukan kualitas pelayanan [8], dan untuk mengevaluasi kinerja karyawan [9].…”

Section: Pendahuluanunclassified

Penerapan Metode SMART untuk Rekomendasi Pencari Kerja Terbaik

Sukamto

Andriyani²,

Oktaviani³

2022

mib

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PT. PLN (Persero) in serving the community requires quality human resources. The quality of employees in supporting the advancement of a company is very important, so many companies are trying to have quality employees. The way that can be done is by recruiting prospective job seekers in accordance with the criteria desired by the company, it's just that so far many companies have problems in the filing and sorting process because it is done manually, so the results do not match the criteria for the desired job seekers So we need a decision support system with the Simple Multi Attribute Rating Technique method to provide recommendations for the best job seekers with the criteria for Endurance tests, academic tests, psychological tests, laboratory tests and interview tests. The final result of this SPK is that it can provide recommendations for the best job seekers in accordance with the specified criteria.

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