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Penerapan Metode Autoregressive (AR) dalam Memprediksi Tren Pertumbuhan Start Up di Kota Medan Syahputra, Mario; Hutapea, Rahmat; Nuryadi, Agung Hidayat; Panjaitan, Rio Anggara; Sari, Rina Widya
Sains Data Jurnal Studi Matematika dan Teknologi Vol 4, No 2: July-December 2026 (In Progress)
Publisher : Sekolah Tinggi Agama Islam Nurul Islam Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52620/sainsdata.v4i2.345

Abstract

The rapid growth of startups in Medan City highlights the need for data-driven approaches to understanding digital entrepreneurship dynamics. This study aims to apply the Autoregressive (AR) model to predict startup growth trends in Medan using historical data from 2016 to 2024. The method employed is time series analysis with a first-order AR(1) model, utilizing secondary data from the Investment and Licensing Agency of North Sumatra Province. The findings indicate a significant increase in startup numbers since 2022, with projections suggesting continued growth to 127 startups by 2030. The AR model proves to offer a simple yet accurate forecasting framework, making it a valuable tool for strategic planning. These results have important implications for policymakers, investors, and entrepreneurs in designing sustainable startup development strategies in urban areas.