From a feature-complete app to one that’s actually easy to use

Platform audited DaPung — a digital system for managing neighborhood dues, community funds, night-watch (ronda) schedules, and financial reporting for Indonesian RT/RW (neighborhood associations)
Document type Self-initiated audit — carried out on our own initiative as a demonstration of methodology, not commissioned or requested by DaPung’s owner
Prepared by Pixelzenic — Tony Wu, UX Optimization
Date August 2026
Intended for Product owners, product managers, and non-technical decision-makers

Executive Summary

DaPung already has a solid feature foundation: house records with barcodes, resident records, staff/officer records, three fund types, night-watch groups, attendance tracking, transactions, and reporting. The core problem isn’t a lack of features.

Auditing nine admin panel pages surfaced one recurring pattern: the app reports state, but rarely points toward action. Users see zeros, “Unknown” labels, and empty tables — with no explanation of what to do next.

The three highest-impact findings:

  1. The product’s signature feature is treated as a second-class option. The website sells “Scan • Record • Done” as its single core value proposition, but inside the app, the Scan Barcode button sits as the fourth choice, below three manual-entry cards.
  2. The system allows staff records to be saved without a name. As a result, staff cards and the attendance table display “Unknown” — on an app that handles residents’ money, this immediately undermines trust.
  3. A default date filter makes the transaction page look empty by default. The starting range is set to today through today, so new users can easily conclude the system isn’t saving their data.

All three can be fixed without adding a single new feature. Two of them qualify as quick fixes that could be completed within a short sprint.

Decision requested: approval to run a limited UX Optimization Sprint focused on three core flows — initial setup, scan-to-record, and an action-oriented dashboard — before further feature development continues.

1. About This Document

1.1 Data sources

This analysis draws on three sources:

Source Coverage
Admin panel screenshots (11 pages) Dashboard, House Records, Resident Records, Staff Records, Fund Types, Night-Watch Groups, Fund Transactions, Attendance, Reports & Recaps
Public landing page [1] Value proposition, feature claims, user role structure
Direct inspection of the admin panel [2] Verification of three critical findings on the live system, including opening modals and detail dialogs not visible in static screenshots

1.2 Methodological limitations

This section matters enough that we put it up front rather than in a footnote.