Sales Performance, Business Product Feasibility, and Consumer Repurchase Intention Analysis of Munchcupp Products in the Market Day Capstone Project Using Descriptive Statistics and One-Sample T-Test

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Authors

  • Funny Alrijanto Telkom University Surabaya
  • bila Telkom University Surabaya
  • renaldy
  • rion
  • vino Telkom University Surabaya
Issue Vol. 1 No. 1 (2026)
Published 30 June 2026
Section Articles
Pages 1-6
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subject

Abstract

Purpose - This study evaluates the sales performance, business product feasibility (BPF), and consumer repurchase intention (RI) of Munchcupp, a food product marketed during the Market Day Capstone Project of the Digital Business Study Program, addressing the need for data-driven evaluation of student-run business ventures.

Design/Methodology/Approach - A descriptive quantitative approach was employed using actual sales data and survey responses from 30 consumers collected through a five-point Likert scale. Business product feasibility and repurchase intention were examined through a One-Sample t-Test with a test value of 4.00 at a significance level of 0.05.

Findings - Munchcupp generated total revenue of Rp2,400,000 and a net profit of Rp432,000, resulting in a profit margin of 18.00%. Statistical testing showed that both business product feasibility (t = 10.094; p < 0.001) and repurchase intention (t = 15.545; p < 0.001) were significantly higher than the benchmark value, indicating that consumers perceive Munchcupp as commercially viable and are inclined to purchase it again.

Originality/Value - This research offers a practical, replicable framework for evaluating student entrepreneurship projects by combining descriptive sales analysis with inferential testing of consumer perception, providing evidence-based guidance for further business development of Munchcupp and similar Capstone Project ventures

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How to Cite

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[1]
Alrijanto, F. et al. 2026. Sales Performance, Business Product Feasibility, and Consumer Repurchase Intention Analysis of Munchcupp Products in the Market Day Capstone Project Using Descriptive Statistics and One-Sample T-Test. Digital Business Ecosystem Journal. 1, 1 (Jun. 2026), 1–6.

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