Background: Market prediction is an important thing that needs to be analyzed deeply. Business intelligence becomes an important analysis procedure for analyzing the market demand and satisfaction. Since business intelligence needs a deep analysis, sentiment analysis becomes a powerful algorithm for analyzing customer review regarding to the business intelligence analysis.Objective: In this study, we perform a sentiment analysis for identifying the business intelligence analysis in GO-JEK.Methods: We use Twitter posts collected from the Twint library which consists of 3111 tweets. Since the dataset did not provide a ground truth, we perform Microsoft Text Analytic for determining positive, neutral, and negative sentiment. Before applying Microsoft Text Analytic, we conduct a pre-processing step to remove the unwanted data such as duplicate tweets, image, website address, etc.Results: According to the Microsoft Text Analytic, the results are 666 positive sentiment numbers, 2055 neutral sentiment numbers, and 127 negative sentiment numbers.Conclusion:  According to these results, we conclude that most GO-JEK customers are satisfied with the GO-JEK services. In this research, we also develop classification model to predict the sentiment analysis of new data. We use some classifier algorithms such as Decision Tree, Naïve Bayes, Support Vector Machine and Neural Network. In the result, the system shows      that the decision tree provides the best performance.

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Kegiatan pengabdian kepada masyarakat yang akan dilaksanakan berupa edukasi kepada masyarakat melalui kegiatan pelatihan digital marketing untuk UMKM yang masih awam terhadap digital marketing. Digital marketing adalah sesuatu yang sangat mendesak bagi setiap pelaku UMKM gunakan untuk. Oleh karena itu, untuk ikut andil berkontribusi pada hal ini, kami pun menginisiasi pelatihan digital marketing untuk membantu para pelaku UMKM untuk mengerti lebih dalam mengenai apa itu digital marketing dan bagaimana implementasi digital marketing yang paling efektif dan efisien untuk usaha mereka. Manfaat yang didapatkan dari kegiatan Pengabdian Kepada Masyarakat ini adalah membantu UMKM Indonesia tumbuh sehingga target jumlah pengusaha di Indonesia bisa meningkat, yang pada akhirnya mebantu ekonomi Indonesia untuk tumbuh. Community service activities that will be carried out are in the form of educating the community through digital marketing training activities for UMKM who are still unfamiliar with digital marketing. Digital marketing is something that is very urgent for every UMKM actor to use. Therefore, to contribute to this, we also initiated digital marketing training to help UMKM to understand more deeply what digital marketing is and how to implement the most effective and efficient digital marketing for their business. The benefits obtained from this Community Service activity are to help Indonesian UMKM grow so that the target number of entrepreneurs in Indonesia can increase, which in turn helps the Indonesian economy to grow.