Evaluating Usability and Clustering of SILCARE System for MSME Shipping: A Data-Driven Approach Using SUS and User Behavior Analysis

The SILCARE system is a digital logistics platform designed to optimize shipping operations for Micro, Small, and Medium Enterprises (MSMEs). This study evaluates its usability and user behavior patterns through System Usability Scale (SUS) assessments and clustering analysis. The research involved 100 SME users performing key system tasks such as registration, product management, and order confirmation. The SUS results showed a significant usability improvement, with the pre-test score of 74.5 (B grade) increasing to 90.25 (A grade) in the post-test, indicating enhanced user experience. User interaction data analysis revealed that registration took an average of 7.11 minutes, product addition 8.91 minutes, and order confirmation 5.15 minutes. Clustering using DBSCAN identified four distinct user groups, highlighting behavioral differences, where 37% of users struggled with complex tasks while 25% displayed balanced engagement. These findings inform targeted system improvements, such as simplifying workflows for new users and enhancing features for power users. The novelty of this study lies in integrating usability testing with behavior-driven clustering to refine a logistics platform tailored to MSMEs. By leveraging data-driven insights, the SILCARE system contributes to digital transformation in MSME logistics, improving operational efficiency and user satisfaction The paper explores the development process of the system, starting from the requirements gathering phase, where user needs were identified through extensive surveys and interviews with stakeholders. The iterative prototyping method allowed for the creation of an initial version of the system that was refined based on user feedback, ensuring that the final product met both functional and usability standards. The SILCARE system holds substantial promise for MSMEs, offering a digital solution for streamlining logistics and shipping processes and contributing to the overall success of small businesses.

Authors

Institutions

Publication Details

Journal
Journal of Applied Data Sciences
Published
2025-03-16
DOI
https://doi.org/10.47738/jads.v6i2.590
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
1.24
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating Usability and Clustering of SILCARE System for MSME Shipping: A Data-Driven Approach Using SUS and User Behavior Analysis

Ririt Dwiputri Permatasari
1 citations
Journal of Applied Data Sciences
Advanced Manufacturing and Logistics Optimization
1.24
article

Evaluating Usability and Clustering of SILCARE System for MSME Shipping: A Data-Driven Approach Using SUS and User Behavior Analysis

Ririt Dwiputri Permatasari
article en
1 citations

Abstract

The SILCARE system is a digital logistics platform designed to optimize shipping operations for Micro, Small, and Medium Enterprises (MSMEs). This study evaluates its usability and user behavior patterns through System Usability Scale (SUS) assessments and clustering analysis. The research involved 100 SME users performing key system tasks such as registration, product management, and order confirmation. The SUS results showed a significant usability improvement, with the pre-test score of 74.5 (B grade) increasing to 90.25 (A grade) in the post-test, indicating enhanced user experience. User interaction data analysis revealed that registration took an average of 7.11 minutes, product addition 8.91 minutes, and order confirmation 5.15 minutes. Clustering using DBSCAN identified four distinct user groups, highlighting behavioral differences, where 37% of users struggled with complex tasks while 25% displayed balanced engagement. These findings inform targeted system improvements, such as simplifying workflows for new users and enhancing features for power users. The novelty of this study lies in integrating usability testing with behavior-driven clustering to refine a logistics platform tailored to MSMEs. By leveraging data-driven insights, the SILCARE system contributes to digital transformation in MSME logistics, improving operational efficiency and user satisfaction The paper explores the development process of the system, starting from the requirements gathering phase, where user needs were identified through extensive surveys and interviews with stakeholders. The iterative prototyping method allowed for the creation of an initial version of the system that was refined based on user feedback, ensuring that the final product met both functional and usability standards. The SILCARE system holds substantial promise for MSMEs, offering a digital solution for streamlining logistics and shipping processes and contributing to the overall success of small businesses.

Journal of Applied Data SciencesVol. 6(2)
Universitas Batam (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Advanced Manufacturing and Logistics Optimization
1.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.