Analysis Of The Impact Of The Application Of Artificial Intelligence (Ai) Based Technology And Digital Finance Knowledge In Improving Business Sustainability
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MSMEs are one of the most important sectors in a country's economy. According to the Ministry of Cooperatives and Small and Medium Enterprises (Kemenkop UKM), the total number of MSMEs in Indonesia reached 8.71 million business units in 2022 with a contribution to GDP of 60.5%, and absorbed a workforce of 96.9% of the total national employment. However, MSMEs often face various challenges in maintaining their business continuity, such as low quality of human resources, capital and understanding of the utilization and development of technology (Kusumaastuti & Asih, 2015). Currently, MSMEs must be able to adapt to technology, one of which is Artificial Intelligence (AI) to increase business productivity, such as improving customer service, displaying attractive product descriptions and reviews, and assisting product marketing and sales. AI helps develop sales and marketing strategies that significantly improve business performance so as to maintain business continuity (Palanivelu & Vasanthi, 2020).Digital financial knowledge is a knowledge concept that includes financial knowledge and digital knowledge (Normawati et al., 2021). Business actors who have financial knowledge find it easier to understand matters related to the financial sector and have the knowledge to access the financial sector, and are able to carry out better financial planning (Safitri et al., 2022). By having financial knowledge and skills, business actors can support the sustainability of their business with products produced by financial institutions to facilitate capital development for business actors and ensure financial security in business management (Jayanti & Karnowati, 2023). This study aims to (1) determine the effect of the application of AI-based technology on business sustainable MSMEs, (2) determine the effect of digital financial knowledge on business sustainable MSMEs. The population in this study were MSME actors in Bekasi Regency. The sample collection technique used was accidental sampling technique. The method used is a quantitative method using SEM Smart PLS software as an analytical tool.
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