Pemetaan Masalah Layanan Keimigrasian Melalui Analisis Sentimen Pengaduan: Kajian Systematic Literature Review Dengan Prisma Sebagai Dasar Rekomendasi Kebijakan

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

This study aims to map immigration service problems based on sentiment analysis of public complaints through a systematic literature review using the PRISMA protocol. The review examined studies concerning sentiment analysis in public services, public complaints, e-government, the M-Paspor application, and SP4N-LAPOR!. Literature searches were conducted through Google Scholar on April 1 and 2, 2026, covering publications from 2020 to 2026. Of 1,285 identified articles, the identification, screening, eligibility assessment, and inclusion processes produced 15 articles for analysis. Data from each article were synthesized according to research focus, data source, analytical method, sentiment tendency, and service problem category. The findings indicate that negative sentiment was more dominant than positive sentiment. The most frequent problems involved technical system disruptions, verification and authentication failures, unstable application performance, slow service responses, and weak complaint follow-up. The review also identified administrative and organizational constraints, including complicated procedures, unintuitive interfaces, weak coordination, and limited human resources. Although digital services improve convenience and efficiency, their implementation quality remains influenced by technological reliability and service governance. Regular monitoring supports measurable service improvement priorities. This study concludes that digital immigration service problems are multidimensional. Immigration authorities should improve system stability, simplify verification procedures, strengthen coordination between units, accelerate responses, and develop data-driven complaint management. These findings can support policy recommendations aimed at improving the quality, responsiveness, and sustainability of user-oriented digital immigration services.