ABILISTO: A DIGITAL PLATFORM CONNECTING SKILLED WORKERS AND CLIENTS THROUGH VERIFIED JOB MATCHING AND ON-DEMAND ASSISTANCE

The localized service economy within the CarCanMadCarLan (Carrascal, Cantilan, Madrid, Carmen, and Lanuza) municipalities of Surigao del Sur, Philippines, is severely constrained by persistent information asymmetry, operational trust deficits, and an over-reliance on highly fragmented, informal word-of-mouth referral networks. Consequently, skilled micro-laborers—encompassing both Technical Education and Skills Development Authority (TESDA)-certified professionals and experiential, non-certified artisans—endure irregular employment cycles and restricted market visibility, while consumers encounter significant friction in verifying and procuring reliable domestic service providers. To mitigate these structural market inefficiencies, this study developed Abilisto, a localized, web-based digital labor marketplace engineered specifically for the socio-technical dynamics of rural Philippine municipal clusters. Anchored empirically on the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) systems framework, the platform introduces two core structural innovations: a Dual-Path Verification System that reconciles formal institutional credential authentication with decentralized, community-backed vouching mechanisms, and an algorithmic heuristic matching engine powered by a Weighted Multi-Criteria Decision-Making (MCDM) framework. System architecture follows a decoupled client-server paradigm implemented via PHP, HTML5, Tailwind CSS, asynchronous Vanilla JavaScript, and a MySQL relational database backend, supplemented with Socket.io for real-time state synchronization, Leaflet.js for geospatial mapping, and VAPID-compliant push notification configurations. The platform underwent comprehensive empirical evaluation via structured User Acceptance Testing (UAT) with $n = 115$ purposively sampled pilot participants ($n = 54$ skilled workers; $n = 61$ clients) across six quality-in-use dimensions dictated by the ISO/IEC 25010 standard: Functional Suitability, Usability, Reliability, Performance Efficiency, Security, and Overall Satisfaction. Quantitative evaluation demonstrated exceptional platform affinity across both cohorts, yielding robust grand weighted means of 4.43 for skilled workers and 4.45 for clients, consistently mapping to the "Agree" qualitative descriptor. Notably, System Security emerged as the paramount dimension among consumers ($\text{WM} = 4.49$), wherein 55% of respondents strongly affirmed that the integrated Dual-Path Verification System substantially enhanced transactional and structural platform trust. Instrument validation via the System Usability Scale (SUS) verified cross-cohort accessibility independent of variations in baseline digital literacy, while internal scale consistency was rigorously confirmed by Cronbach's Alpha coefficients exceeding 0.98 for both user groups. Cumulatively, these findings demonstrate that localized, community-grounded, and algorithmically-driven digital architectures can successfully minimize information asymmetry, validate informal skill economies, and accelerate rural digital inclusion, fully converging with the socioeconomic development mandates of the Philippine Innovative Startup Act (RA 11337) and United Nations Sustainable Development Goals (SDGs) 8 and 9. Keywords: digital labor marketplace, gig economy platforms, algorithmic labor matching, dual-path verification, multi-criteria decision-making (MCDM), information asymmetry, ISO/IEC 25010 evaluation, rural digital inclusion, Philippine startup ecosystem, alternative trust architectures.