Transforming Fragmented Tourist-Visit Reporting into Integrated Tourism Monitoring: The Qinanti Dashboard and Business Process Redesign

Galih Darmawan Hidayatullah; Muharman  Lubis

doi:10.71435/741691

Authors

Galih Darmawan Hidayatullah Master of Information Systems Study Program, School of Industrial Engineering, Telkom University, Bandung, Indonesia
Muharman Lubis School of Industrial Engineering, Telkom University, Bandung, Indonesia

DOI:

https://doi.org/10.71435/741691

Keywords:

Business Process Redesign, Critical to Quality, DMADV, Information System, RSM, Tourist-Visit Data

Abstract

Delayed and fragmented tourist-visit data weaken government responses to traffic congestion, overtourism, illegal levies, uneven visitor flows, and declining service quality. Dependence on late and inconsistent records also increases the risk of resource misallocation and may reduce destination competitiveness and investor confidence. This study redesigns the tourist-visit data collection process in West Java, Indonesia. A sequential explanatory design combined secondary records, interviews, observation, and document analysis. Recognize–Scrutinize–Materialize (RSM) approach was aligned with the Define–Measure–Analyze–Design–Verify (DMADV) framework to link user needs, root causes, and system design. The as-is business process required 435 minutes of processing and 9,645 minutes of waiting, producing a seven-day lead time and an active-time ratio of 4.32%. A 21-feature Requirement Feature Matrix and a role-based use-case model translated the redesign into implementable functions and actor responsibilities. The proposed process introduces single-entry recording, preventive validation, staged review, visible reporting status, automatic recapitulation, audit trails, controlled interoperability, analytical dashboards, and geospatial monitoring. Under a conservative simulation with one correction cycle, projected lead time declined to 504 minutes or 8 hours 24 minutes. Black-box testing confirmed the expected behaviour of all 19 implemented functions; anomaly detection and visit-trend prediction were excluded because they were classified as Won't Have. Heuristic interviews identified five areas for refinement. The findings demonstrate traceability from user needs and quality targets to role allocation, process design, and functional verification, although the simulated gains require post-implementation measurement.

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