INTEGRASI SISTEM INFORMASI BERBASIS A1 UNTUK OPTIMALISASI LAYANAN PUBLIK DI PEMERINTAHAN DAERAH

BENGET PARASIAN LUMBAN RAJA, NPM 2409406015 (2026) INTEGRASI SISTEM INFORMASI BERBASIS A1 UNTUK OPTIMALISASI LAYANAN PUBLIK DI PEMERINTAHAN DAERAH. Tugas_Akhir (Artikel) : Jurnal Sistem Informasi, Teknik Komputer dan Teknologi Pendidikan (JUSTIKPEN) Sinta 5, 5 (2). pp. 25-30. ISSN 2828- 7921 (Online)

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Abstract

Penelitian ini bertujuan untuk mengembangkan dan mengintegrasikan sistem informasi berbasis kecerdasan buatan (A1) guna meningkatkan Layanan publik di pemerintah daerah. Permasalahan utama yang diidentifikasi adalah rendahnya pemanfaatan data secara real time, kurang terintegrasinya basis data antarinstansi, serta lambatnya proses analisis informasi dalam penentuan kebijakan. Metode penelitian menggunakan pendekatan mixed methods yang meliputi analisis kebutuhan sistem, perancangan arsitektur integrasi data, pengembangan model A1 berbasis machine learning, serta pengujian performa menggunakan case study pada instansi pemerintah daerah. Data dikumpulkan melalui wawancara, observasi proses bisnis, serta pengujian sistem menggunakan dataset operasional instansi. Hasil penelitian menunjukkan bahwa integrasi sistem informasi berbasis A1 mampu meningkatkan akurasi analisis data sebesar 28%, mempercepat proses pengambilan keputusan hingga 40%, dan meningkatkan konsistensi rekomendasi kebijakan. Selain itu, model A1 yang diimplementasikan menunjukkan kemampuan prediksi yang stabil dengan tingkat akurasi rata-rata 92% pada berbagai skenario pengujian. Integrasi data antarunit kerja juga terbukti meminimalkan duplikasi informasi dan memperbaiki alur koordinasi kebijakan publik. Simpulan penelitian menyatakan bahwa sistem informasi terintegrasi berbasis A1 memberikan kontribusi signifikan terhadap optimalisasi proses pengambilan keputusan di sektor publik, baik dari Sisi kecepatan, kualitas analisis, maupun efektivitas koordinasi antarinstansi. Implementasi sistem ini direkomendasikan untuk diperluas pada berbagai sektor layanan publik guna mendorong tata kelola pemerintahan yang lebih responsif, efisien, dan berbasis data. Kata Kunci : A1, Sistem Informasi, Integrasi Data, Pengambilan Keputusan, Sektor Publik, Machine Learning ================================================================================= This study aims to develop and integrate an A1-based information system to enhance the effectiveness of decision-making in the public sector. The main issues identified include the limited use of real-time data, the lack of integration among inter-agency databases, and the slow analytical processes involved in policy formulation. The research employs a mixed-methods approach, including system needs analysis, data integration architecture design, development of machine-learning—based A1 models, and performance testing through a case study in a local govemment agency. Data were collected through interviews, business process observations, and system testing using operational datasets from the institution. The findings indicate that the integrated A1-based information system improves data analysis accuracy by 28%, accelerates decision-making processes by up to 40%, and enhances the consistency of policy recommendations. The implemented A1 model demonstrates stable predictive performance with an average accuracy rate of 92% across various testing scenarios. Inter-unit data integration also reduces information duplication and strengthens policy coordination workflows. In conclusion, the integrated A1-based information system contributes significantly to optimizing decision-making in the public sector in terms of speed, analytical quality, and inter-agency coordination. The study recommends broader implementation of the system across various public service domains to support more responsive, efficient, and data-driven governance. Keywords : A1, Information Systems, Data Integration, Decision-Making, Public Sector, Machine Learning

Item Type:	Article
Uncontrolled Keywords:	A1, Sistem Informasi, Integrasi Data, Pengambilan Keputusan, Sektor Publik, Machine Learning ====================================== : A1, Information Systems, Data Integration, Decision-Making, Public Sector, Machine Learning
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	01 Sep 2026 04:23
Last Modified:	01 Sep 2026 04:23
URI:	http://repository.ulb.ac.id/id/eprint/2701

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