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All Journal Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC)
Meyliana Meyliana
Doctor of Computer Science Program, Bina Nusantara University, Jakarta, Indonesia
Computer Science & IT

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Predicting Startup Success, a Literature Review Harjo Baskoro; Harjanto Prabowo; Meyliana Meyliana; Ford Lumban Gaol
Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Vol. 1 No. 1 (2022): Proceeding of International Conference on Information Science and Technology In
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/icostec.v1i1.10

Abstract

The development and growth of startups around the world nowadays have become a global phenomenon. Startups have become an essential element of innovation and economic growth in many countries. But literature shows that the failure rate of a startup is around 90%. Therefore it is crucial for investors, financial advisors, and the government to spot the 10% which eventually will generate higher return rates, bring in greater revenue and ensure economic growth. This research aim is to study what are the critical factors of the startup’s success that can be used to make a predictive model using a machinelearning algorithm to predict the success of a startup.
Co-Authors Ford Lumban Gaol Harjanto Prabowo Harjo Baskoro