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All Journal Bulletin of Data Science Jurnal Sains dan Teknologi Informasi
Humaidy, Mohd Irsan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Journal : Bulletin of Data Science

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Penerapan Algoritma Maximum Marginal Relevance Dalam Peringkasan Teks Secara Otomatis Kurniawan, Ade; Humaidy, Mohd Irsan
Bulletin of Data Science Vol 1 No 2 (2022): February 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (498.828 KB) | DOI: 10.47065/bulletinds.v1i2.1358

Abstract

The search engine is a device for searching information from available documents. But the search engine will give you a lot of search results, so to find a document we have to open a meeting. Text summarization allows us to get key information from a document quickly without requiring us to read the contents of the document manually.One of the methods used is Maximum Marginal Relevance (MMR). MMR belongs to the extractive summary category (choosing the sentence in the document as the main sentence of the document content). MMR is done by weighting each sentence in the document.It is hoped that with the application of the Maximum Marginal Relevance Method this automatic summary of text can reduce the level of data redundancy and can help readers understand the meaning of the summary results and provide good information
Co-Authors Ade Kurniawan