Page 27 - POSTER FYP MAC-OGOS 2025

FUZZY PREFERENCE RELATION BASED FUZZY VIKOR METHOD

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E - H A I L I N G P R O V I D E R S A M O N G S T U D E N T S U S I N G
E-HAILING PROVIDERS AMONG STUDENTS USING
F U Z Z Y P R E F E R E N C E R E L A T I O N B A S E D F U Z Z Y V I K O R M E T H O D

CHE KU ROSSUHAILA BINTI CHE KU RAMLI SUPERVISOR: NUR ELINI BINTI JAUHARI

ABSTRACT PROBLEM STATEMENT

The rising demand for e-hailing services has created the need for a structured decision making RESEARCHERS STUDIES

approach to evaluate and compare multiple providers. This research aims to evaluate suitable e-

hailing platforms based on influencing criteria by student’s preferences. The main objectives of Past studies have explored user

this research are determining the weightage of the influencing criteria and then applying it to rank satisfaction factors such as safety and

e-hailing platforms using fuzzy preference relation based fuzzy VIKOR method. This method is affordability, while there are study

implemented to handle uncertainty and subjectivity in human judgement. The influence criteria used AHP to rank providers based on

have been identified through a review of existing literature which includes price , service quality, safety-related subcriteria. However,

safety and accessibility. The results indicate that safety and accessibility are the most importance most studies focus on individual

criteria, followed by price and service quality. Meanwhile, it conclude that the students from UiTM criteria rather than providing a

Shah Alam’s most preferred e-hailing providers are Pink Rider and inDrive. The results provide comprehensive ranking across multiple

valuable implications for user in choosing suitable e-hailing and assist companies aiming to criteria.

optimize their service by addressing the criteria that most influence user preferences.

GAP IN RESEARCH

There is limited research using

mathematical models to evaluate and

OBJECTIVES rank e-hailing platforms based on

multiple user preferences.

To determine the

weightage of

each criteria in To rank e-hailing

choosing providers based

e-hailing provider on influencing

by aggregating criteria using TS 371 SG

fuzzy importance fuzzy preference IMPLEMENTATION

ratings of criteria relation based STEP 3: NORMALIZE THE VALUES UNDER QUANTITATIVE CRITERIA STEP 6: DETERMINE THE IMPORTANCE WEIGHTS OF CRITERIA

Fuzzy VIKOR.

METHODOLOGY

START STEP 4: DETERMINE THE FUZZY BEST VALUES STEP 7: COMPUTE THE SEPERATION MEASURES OF SI AND RI

IDENTIFY CRITERIA AND ALTERNATIVES

DATA COLLECTION

CONSTRUCT FUZZY PREFERENCE RELATION MATRIX

APPLY FUZZY VIKOR METHOD

RANK THE ALTERNATIVES

STEP 5: DETERMINE THE BEST DOMINANCE OF FUZZY BEST VALUE STEP 8: COMPUTE THE SEPERATION MEASURES OF QI

END OVER AVERAGE RATINGS OF ALTERNATIVES UNDER CRITERIA

RESULTS AND DISCUSSION

STEP 9: DEFUZZIFIED WEIGHTS

CONCLUSION RECOMMENDATIONS

The fuzzy preference relation-based fuzzy VIKOR

method effectively handled uncertainty and Increase the sample size and include
The most important criterias are safety and subjective judgment in evaluating e-hailing respondents from diverse demographics or

accessibility since both have the highest platforms. The most influenced criteria were locations to improve generalizability.

weight. Price is the third important criteria safety (C3) and accessibility (C4), while service Incorporate real-world data like pricing

and service quality is the least important quality was least important. The ranking showed trends, travel time, driver behavior) for

criteria. Pink Rider (A1) and inDrive (A5) as the top more objective evaluation.

Pink Rider and inDrive rank as first, indicate preferred providers, both identified as Apply and compare with other fuzzy MCDM

both are the most preferred providers. compromise solutions. Then, it followed by methods such as fuzzy AHP, fuzzy

Meanwhile, Maxim is ranked third, followed Maxim (A2), Grab (A4) and Uber (A3). These DEMATEL, or fuzzy TOPSIS.

by Grab and Uber. findings help users choose suitable e-hailing Extend the method to other service-based

The Fuzzy VIKOR inicate that both top services and support companies in improving industries to explore broader insights into

alternatives are compromise solutions. service quality and customer satisfaction. user satisfaction.