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THE SELECTION OF E-COMMERCE PLATFORMS k242/18

USING SPHERICAL FUZZY TOPSIS METHOD

SITI NUR ATHIRAH BINTI JAFFAR (K242/18)

SUPERVISOR: MADAM NURUL SUHADA AZIZ

ABSTRACT

The rapid growth of e-commerce has transformed consumer behavior, particularly among university students, who frequently shop online using

platforms such as Shopee, Lazada, TikTok Shop, and Mudah.my. However, the abundance of choices often makes it difficult for students to make

optimal purchasing decisions. This study aims to assist students in selecting the most preferable e-commerce platform by applying the Spherical

Fuzzy TOPSIS method, a preferred multi-criteria decision-making (MCDM) technique that incorporates human hesitation and uncertainty through

spherical fuzzy sets. Four platforms were evaluated based on four key criteria, which are ease of usage, brand image, product variety, and privacy

and security. A fuzzy linguistic questionnaire was distributed to a group of students from UiTM Cawangan Kelantan, and their decisions were

aggregated using the Spherical Weighted Arithmetic Mean (SWAM) operator. The defuzzification process and computation of closeness ratios

enabled the ranking of the alternatives.

PROBLEM STATEMENT IMPLEMENTATION OBJECTIVES

University students often face difficulties in step 1: Data Collection 1.To apply Spherical Fuzzy Number (SFN)

making the best e-commerce decisions due to and Spherical Weighted Arithmetic Mean

too many product choices and complex criteria. (SWAM) operators in Multi-Criteria

The overwhelming information such as Decision Making (MCDM).

numerous reviews, ads, and product details can 2.To apply a spherical fuzzy TOPSIS

lead to confusion and poor decision-making. method in the selecting the most

Reviews are often biased or manipulated, and preferable e-commerce platforms.

sponsored ads may unfairly promote certain 3.To rank the e-commerce platforms

brands. On top of that, students have different step 2: Aggregation

preferences like brand image, variety, and ease

of use, which adds to the complexity. RESULTS AND DISCUSSION

step 3: Aggregate weight The final ranking of the e-commerce

METHODOLOGY platforms based on the closeness

coefficient is as follows: Shopee (0.960),

Lazada (0.915), TikTok Shop (0.557), and

step 4: Defuzzification Mudah.my (0.135). Shopee was identified

as the most preferred platform, which

reflects its strong brand image, user-

friendly interface, wide product selection,

step 5: Compute SN-PIS & SN-NIS and trustworthy privacy features. Lazada

followed closely, while TikTok Shop, being

relatively new, ranked third due to lower

scores in brand recognition and security.

Mudah.my ranked lowest, likely due to its

limited features and traditional interface.

step 6: Distance step 7: Ratio

The results validate the effectiveness of

the Spherical Fuzzy TOPSIS method in

differentiating alternatives based on

vague and subjective data. The method

step 8: Ranking provided meaningful insights into how

university students perceive and

prioritize different platform features.

CONCLUSION RECOMMENDATION

This study successfully applied the Spherical Fuzzy TOPSIS method Future research can be expanded by including a larger and more

to evaluate and rank e-commerce platforms based on multiple diverse group of decision-makers to improve the reliability of the

criteria. The approach proved to be effective in handling linguistic findings. Additional criteria such as delivery time, mobile app

and uncertain information. All research objectives were achieved, performance, customer support, and promotional features can also be

and the findings showed that Shopee is the most suitable platform included for a more comprehensive analysis. Moreover, comparing the

for university students. The methodology allows for a structured, results of Spherical Fuzzy TOPSIS with other decision-making methods

data-driven evaluation process that accommodates human like Fuzzy AHP or VIKOR would help validate the robustness of the

hesitation, making it highly suitable for real-world decision-making model. Incorporating real transactional data alongside subjective

in digital commerce. evaluations is also recommended to enhance the practicality and

depth of future studies.