QRIS Refund Reconciliation System

Dec 2025 - Jan 2026

Role: Full-Stack Developer

Project Link Access to this project is restricted because it runs in an internal environment.
QRIS Refund Reconciliation System thumbnail
Tech Stack

Overview

Built an internal QRIS refund reconciliation system that helps finance operations validate refund submissions against transaction data from multiple sources. The application combines a web-based dashboard with spreadsheet-driven processing to make refund review more structured, traceable, and easier to manage.

In Collaboration With: Oden Team, Research Team, and Data Mining Team

Responsibilities

  • Developed the application interface for refund submission, monitoring, and report generation
  • Implemented flow between spreadsheet-based upload process and backend validation logic
  • Worked on data comparison and status handling for refund eligibility and duplicate detection
  • Integrated the application with internal transaction data sources and Google-based spreadsheet workflow
  • Collaborated across multiple teams to align UI behavior, data processing, and supporting integrations
  • Helped translate operational refund requirements into a structured and production-ready system flow

Outcome

The result was a more reliable internal workflow for handling refund requests, with clearer validation, better visibility into processing outcomes, and a centralized way to track uploaded files, review results, and export reports for operational follow-up.

Detailed Breakdown

The section above is optimized for fast recruiter review. If you want the full implementation context, open the details below.

Refund handling involved spreadsheet-based submissions and cross-checking against transaction records from different systems. Without a dedicated workflow, the process could become difficult to monitor, repetitive to validate, and harder to scale operationally.

The solution was to build a centralized web application that bridges spreadsheet uploads, backend validation, transaction comparison, and reporting. This made the process more structured by giving users a clear place to upload data, monitor processing status, review results, and export finalized reports without exposing raw system complexity.

Primary Flow

01

Users generate or upload a spreadsheet in the required format through the web application.

02

The system reads and validates the uploaded data before starting the processing flow.

03

Uploaded records are compared against transaction data from internal sources to determine whether they are eligible, invalid, or duplicated.

04

Users can review the processing result from the dashboard, open detailed views, and export reports for follow-up.

This project was more than a standard internal dashboard because it connected interface work, spreadsheet-based processing, and transaction reconciliation logic in one operational flow. A key challenge was ensuring the system stayed understandable for users while still handling validation and comparison rules behind the scenes.

Implementation Flow

01

Uploaded spreadsheets are parsed and validated first so malformed data can be stopped before it enters the reconciliation stage.

02

Validated records are compared with transaction sources and classified through backend rules into valid, unmatched, or duplicate outcomes.

03

The processed result is stored and exposed back to the dashboard so users can review details, monitor status, and export reports.

Implementation Details

  • Built the UI flow for dashboard, upload, detail, and reporting pages
  • Worked with spreadsheet generation and reading flow as part of the upload-processing lifecycle
  • Handled validation rules before records entered the comparison stage
  • Implemented status-based outcomes for valid, unmatched, and duplicate submissions
  • Collaborated with supporting teams for Google-related integration, internal framework support, and transaction data availability
  • Worked in a multi-system environment where application behavior depended on both interface logic and backend processing results

Some implementation details have been intentionally generalized because this was an internal operational system.

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