Effectiveness of ASN Recruitment Using the CAT System in Deli Serdang Regency, North Sumatra Province

Abstract

Penelitian ini menganalisis efektivitas rekrutmen Aparatur Sipil Negara (ASN) melalui sistem Computer Assisted Test (CAT) di Kabupaten Deli Serdang, Provinsi Sumatera Utara. Metode penelitian deskriptif kualitatif digunakan dengan pendekatan induktif untuk menggambarkan fenomena di lapangan secara sistematis. Hasil penelitian menunjukkan bahwa penerapan sistem CAT meningkatkan efisiensi waktu, transparansi, dan akurasi seleksi. Sistem ini memungkinkan hasil tes ditampilkan secara langsung dan memudahkan pengelolaan data elektronik. Namun, masih terdapat beberapa tantangan, antara lain keterbatasan infrastruktur teknologi, rendahnya literasi teknologi peserta, dan kurang optimalnya koordinasi antar tim. Kendala-kendala ini berdampak pada kelancaran pelaksanaan seleksi, terutama di daerah terpencil. Rekomendasi perbaikan meliputi peningkatan infrastruktur, pelatihan teknologi, dan penguatan koordinasi antar tim. This study analyzes the effectiveness of State Civil Apparatus (ASN) recruitment through the Computer Assisted Test (CAT) system in Deli Serdang Regency, North Sumatra Province. A qualitative descriptive research method was used with an inductive approach to systematically describe the phenomena in the field. The results of the study indicate that the implementation of the CAT system increases time efficiency, transparency, and selection accuracy. This system allows test results to be displayed directly and facilitates electronic data management. However, several challenges remain, including limited technological infrastructure, low technological literacy of participants, and less than optimal coordination between teams. These obstacles affect the smooth implementation of the selection, especially in remote areas. Recommendations for improvement include improving infrastructure, technology training, and strengthening coordination between teams. Wth these steps, the CAT system has the potential to become a more modern and efficient ASN selection model.