Analysis Sentiment Lumajang Square Review using Support Vector Machine

Lumajang Square is one of room the public that becomes center activity community and tourists . Perception public to place This can measured through analysis sentiment to reviews available on digital platforms such as Google Maps. Research This aiming For classify sentiment review the use Support Vector Machine (SVM) method , one of the effective machine learning algorithms For task classification text . Data used in the form of review collected text​ from Google Maps, then through pre- processing data such as cleaning text , tokenization , and deletion stopword . Sentiment label determined manually to be three categories : positive , negative , and neutral . Next , the data is extracted use TF-IDF technique before classified using SVM. Research results show that SVM algorithm is capable of classify sentiment with level high accuracy , making it proper method​ For analysis opinion public based on text . Findings This expected can give input for government area in increase quality services and management room public in Lumajang.