Perencanaan Business Intelligence untuk Strategi Pengembangan Produk Unggulan Menggunakan Algoritma Support Vector Machine

Oding Herdiana
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Abstract

The government continues to encourage the government to accelerate Small and Medium Enterprises (SMEs) flagship products to enter the digital market, because the current digitalization of SMEs cannot be ignored, SMEs must be able to change their business to the digital realm. The strategy for developing superior SME products needs to be well planned, because a good and measurable strategy is very important for policy making. Development uses an approach that emphasizes that the driving force of development is commodities that are considered to be superior, both at the domestic, national and international levels. Superior products that have quality and are needed by customers require the right selection process, so we need a method to produce this information. Business Intelligence (BI) is a global term for all processes, techniques, and tools that support business decision making based on information technology. The strategy for developing superior products for SME products uses the criteria of production data, income, and SME respondent data in determining the priority list. A good product assessment based on priority can be done by BI using the classification method with the Support Vector Machine (SVM) algorithm. The research method carried out for planning the development of superior products for MSMEs in Tasikmalaya City is a research development research. To complete the classification of the right superior product development strategy, then Support Vector Machine algorithm can be used with test results using the Confusion Matrix with an average accuracy of 97%.
利用支持向量机算法进行产品开发战略的商业智能规划
政府继续鼓励政府加速中小企业(SMEs)旗舰产品进入数字化市场,因为目前中小企业的数字化不容忽视,中小企业必须能够将其业务转变为数字化领域。中小企业优势产品的开发战略需要精心规划,因为一个好的、可衡量的战略对政策制定非常重要。发展所采用的方法强调发展的推动力是在国内、国家和国际各级都被认为是优越的商品。顾客需要的优质产品需要正确的选择过程,所以我们需要一种方法来产生这些信息。商业智能(BI)是支持基于信息技术的业务决策制定的所有流程、技术和工具的总称。为中小企业产品开发优质产品的策略使用生产数据、收入和中小企业受访者数据的标准来确定优先列表。采用支持向量机(SVM)算法的分类方法,可以很好地完成基于优先级的产品评估。为规划Tasikmalaya市中小微企业的优势产品开发而进行的研究方法是一种研究开发研究。为了完成正确的优秀产品开发策略的分类,可以使用支持向量机算法和使用混淆矩阵的测试结果,平均准确率为97%。
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24 weeks
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