Implementation of Equal Width Interval Discretization on SMARTER Method for Selecting Computer Laboratory Assistant

Saleh, Alfa; Puspita, Khairani; Sanjaya, Andi; Daifiria,; Giovani,

doi:10.1109/citsm.2018.8674289

Cited by 8 publications

(7 citation statements)

References 9 publications

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“…Decision support systems were first put forward in the early 1970s by Michael S. Scott Morton. It was term Management Decision Systems to assist managers in making decisions on semi-structured problems, providing support for managers, increasing managers' decisions, speed computing, and productivity enhancement [10] [14]. Decision support systems are considered capable of solving problems and solving semi-structured issues [13].…”

Section: B Decison Support Systemmentioning

confidence: 99%

“…Each standard has a weight that describer how important criteria are compared with other criteria [4]. The SMARTER method is developing the Simple Multi-Attribute Rating Technique ( SMART ) method introduced by Edward in 1977 [10]. In the SMARTER method, the Rank Order Centroid (ROC) weighting formula is used [6].…”

Section: Simple Multi-attribute Rating Technique Exploitingmentioning

confidence: 99%

“…Several studies on the SMARTER and BARS methods have been carried out to optimize of decision-maker. Alfa Saleh et al in 2018 determine the selection of laboratory assistants by applying the Simple Multi-Attribute Rating Technique Exploiting Ranges (SMARTER) method by applying six criteria and weighting accordingly [10]. With assessment priorities and produce research results that the technique used can provide useful recommendations.…”

Section: F Related Researchmentioning

confidence: 99%

“…As stated by [7] which states that employee Behavior Assessment can be said to be effective if it includes the following two things, namely (1) the existence of a set of standards and (2) information communication (feedback). Dessler [10] "Effective appraisal also requires that the supervisor set performance standards. And it requires that the employee receives the training, feedback, and incentives required to eliminate performance deficiencies".…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Employee Using Simple Multi-Attribute Technique Exploiting Rank (SMARTER) and Behaviorally Anchor Rating Scale (BARS) Method

Sulastri

2021

JISA

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Lecturers' active role as the spearhead of higher education has an essential role in improving higher education quality and sustainability. Therefore, assessing work behaviour is needed to measure how lecturers participate in achieving the vision and mission, quality improvement, and service guarantee to students and complementary documentation. This condition became the basis of research. They are implementing decision support systems with Simple Multi-Attribute Rating Technique Exploiting Ranges (SMARTER) and Graphic Rating Scale (GRS) to measure a lecturer's behaviour by using multiple criteria. With the SMARTER method and Behaviorally Anchor Rating Scale (BARS). By applying the impermeable BARS method, the work behaviour assessment process results in ease and accuracy that is more in line with the employees' behaviour being assessed. With the SMARTER approach, an assessment of employee work behaviour is produced, with 90% of alternatives used. The results are Good.

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Section: B Decison Support Systemmentioning

confidence: 99%

Section: Simple Multi-attribute Rating Technique Exploitingmentioning

confidence: 99%

Section: F Related Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of Employee Using Simple Multi-Attribute Technique Exploiting Rank (SMARTER) and Behaviorally Anchor Rating Scale (BARS) Method

Sulastri

2021

JISA

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“…During the velocity synthesis, the prediction length of the macroscopic velocity profile is the same with that of the microscopic profile. In the velocity prediction, the data are discretized by an equalwidth interval method [32]. The data for macroscopic and microscopic predicted velocity are discretized with the same time step (1s).…”

mentioning

confidence: 99%

Integrated Velocity Prediction Method and Application in Vehicle-Environment Cooperative Control Based on Internet of Vehicles

Zhang

Chen

et al. 2022

IEEE Trans. Veh. Technol.

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Rapid progress has been gained in the field of advanced communication technologies, which also promote parallel developments in the Internet of Vehicles (IoVs). In this context, vehicle-environment cooperative control can be integrated into next-generation vehicles to further improve the vehicle's performance, in particular energy efficiency. Accurate prediction of future velocity profiles on basis of IoVs can be a critical breakthrough, which can contribute much to vehicle operation efficiency promotion. In this paper, an integrated velocity prediction (IVP) method fully taking advantage of IoVs is proposed and demonstrated through a case study. In the IVP method, both the macroscopically and microscopically predicted velocity profiles are considered. The macroscopic velocity profiles are predicted via traffic flow analysis (TFA) in multi-access edge computing units (MECUs) which are situated alongside the route. Microscopic velocity profiles are forecasted through Mondrian forest (MF) algorithm in the on-board vehicle control unit (VCU). Final velocity prediction is generated through combination of the macroscopic and microscopic profiles in frequency domain in onboard VCU through fast Fourier transform (FFT) and inverse FFT. A case study validates the distinguished performance of IVP method and demonstrates its significant contribution to vehicle performance improvement. 1 Index Terms-Velocity prediction, multi-access edge computing units (MECUs), traffic flow analysis (TFA), Mondrian forest (MF), Fast Fourier Transform (FFT).

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A refined representation method of the particle size distribution curve based on grading entropy

Li,

Chen,

Liu

et al. 2024

Particuology

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Implementation of Equal Width Interval Discretization on SMARTER Method for Selecting Computer Laboratory Assistant

Cited by 8 publications

References 9 publications

Assessment of Employee Using Simple Multi-Attribute Technique Exploiting Rank (SMARTER) and Behaviorally Anchor Rating Scale (BARS) Method

Assessment of Employee Using Simple Multi-Attribute Technique Exploiting Rank (SMARTER) and Behaviorally Anchor Rating Scale (BARS) Method

Integrated Velocity Prediction Method and Application in Vehicle-Environment Cooperative Control Based on Internet of Vehicles

A refined representation method of the particle size distribution curve based on grading entropy

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