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Analyzing Public Perception on Integrating Ride-Hailing with Emergency Health Services Megantara, Tubagus Robbi; Hidayana, Rizki Apriva; Hasanah, Indah Mauludina
International Journal of Business, Economics, and Social Development Vol. 7 No. 1 (2026): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v7i1.1086

Abstract

Traditional Emergency Health Services (EHS) face numerous challenges, including response time efficiency. The integration of ride-hailing platforms offers an innovative solution, yet public perception of this concept remains underexplored. This study investigates public perception through a quantitative survey of 100 respondents, analyzed as a whole and as two subgroups: those with prior EHS experience (n=48) and those without (n=52). The results reveal exceptionally strong and broad public support for this integration. A key finding is a significant "experience gap": respondents with prior EHS experience demonstrate confident demand with less hesitation, while non-users show more theoretical support with higher neutrality, particularly regarding personal adoption. Despite this difference, both groups show a high consensus on fundamental requirements such as patient safety, driver competency, and the availability of medical equipment. This study concludes that there is high social viability for integrating ride-hailing and EHS. The findings provide a clear mandate for stakeholders to proceed with innovation, on the condition that system development prioritizes the safety and reliability standards expected by the public. This research lays the groundwork for the next stage: the development of mathematical models for a decision-support system to translate this concept into an effective and trustworthy solution. Keywords: ride-hailing, emergency health services, public perception, mathematical modeling, decision-support systems.
Evaluating the Effectiveness of Spreadsheet-Based Instruction on High School Students’ Data Literacy: A Pre-test–Post-test Study Megantara, Tubagus Robbi; Hidayana, Rizki; Nurkholipah, Nenden Siti; Amelia, Rika; Syarifudin, Abdul Gazir
International Journal of Research in Community Services Vol. 7 No. 1 (2026): International Journal of Research in Community Service (IJRCS)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v7i1.1187

Abstract

Data literacy has become an essential competency for students in the digital era, particularly at the secondary education level where foundational numeracy skills are developed. Spreadsheet software such as Microsoft Excel offers an accessible platform for integrating mathematical concepts with practical data analysis and visualization. This study aims to quantitatively evaluate the effectiveness of a spreadsheet-based instructional intervention in improving high school students’ data literacy skills. A quasi-experimental one-group pre-test–post-test design was employed involving 12 senior high school students from SMAS Sebelas Maret, Bandung. The instructional intervention consisted of three integrated modules: Introduction to Excel and Data Literacy, Data Analysis and Logical Functions, and Data Visualization. Students’ competencies were assessed before and after the intervention using a structured test aligned with these modules. Data were analyzed using descriptive statistics, paired-sample t-tests, and effect size estimation (Cohen’s d). The results indicate a statistically significant improvement in overall performance from pre-test to post-test (p < 0.05), accompanied by a large effect size (d = -0.96), demonstrating substantial practical impact. The strongest learning gains were observed in data visualization skills, while data analysis and logical functions showed more moderate improvement. These findings suggest that spreadsheet-based instruction is an effective approach for enhancing data literacy and applied numeracy skills among high school students.