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Rika Yunitarini
Universitas Trunojoyo Madura
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Journal : NERO (Networking Engineering Research Operation)

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IMPLEMENTASI SUPPORT VECTOR MACHINE (SVM) DENGAN QUERY EXPANSION RANKING PADA REVIEW PENGGUNAAN JAMU MADURA Yunitarini, Rika; Fitrianto, Hambali; Ayu Mufarroha, Fifin
Networking Engineering Research Operation Vol 9, No 2 (2024): Nero - November 2024
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v9i2.27785

Abstract

Madura traditional herbal medicine is a traditional herbal medicine made from natural ingredients and is well-known for its efficacy. The popularity of Madura traditional herbal medicine is not only based on the diversity of traditional herbal medicine products and their health benefits, but also on traditional values that have been passed down from generation to generation. One of the most popular Madura traditional herbal medicine is Peluntur traditional herbal medicine. Peluntur traditional herbal medicine is a series of medicinal or herbal products specifically designed as a solution to overcome late menstruation or irregular menstruation, which is often a source of concern for mothers and young women. With the background of the increasing demand for Madura traditional herbal medicine products, a sentiment analysis was conducted on Madura traditional herbal medicine product reviews on the Shopee, Lazada, and Tokopedia applications. This study applies Support Vector Machine and Query Expansion Ranking to achieve the highest accuracy in reviewing the use of Madura traditional herbal medicine. The results obtained for the use of the Support Vector Machine algorithm have an accuracy of 93%, while for the use of the Support Vector Machine and Query Expansion Ranking algorithms at feature selection ratios of 50% and 100% the accuracy increases to 94%.Keywords: Madura traditional herbal medicine, Peluntur traditional herbal medicine, Query Expansion Ranking, Sentiment Analysis, Support Vector Machine
Co-Authors Achmad Jauhari Ajeng Kartiningsih Andharini Dwi Cahyani Aris Eko Priyanto Ayu Mufarroha, Fifin Ayu wulandari Eko Handoyo Ernaning Widiaswanti Fifin Ayu Mufarroha Fika Hastarita R Fitri Agustina Fitrianto, Hambali Gultom , Jhon Filius Heru Nurwarsito Khusnul Fatimah Koeshardianto, Meidya Laylul Musabbichin Maghfiroh, Sobariyah Merlien N. Febriyati Mochammad Kautsar Sophan Muhamad Afif Effindi, Muhamad Afif Mula’ab b Nachnul Ansori Pradita, Dwi Aqilah Prasetyo Adi Pratama Nugroho Purnomo Budi Santoso Rohman, M Habibur Rosida, Illiya Stefany, Evy maya Trisita Novianti Trisita Novianti Yudha Dwi P.N