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TEXT GENERATION MENGGUNAKAN LSTM PADA WEBSITE LINKEDIN

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Penilaian

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LinkedIn is one of the most popular sites out there to advertise oneself to potential employer. This study aims to create a good enough text generation model that it can generate a text as if it were made by someone who posts on LinkedIn. This study will use a Neural Network layer called Long-Short Term Memory (LSTM) as the main algorithm and the train data consists of actual posts made by users in LinkedIn. LSTM is an algorithm that is created to reduce vanishing and exploding gradient problem in Neural Network. From the result, final accuracy and loss varies. Increasing learning rate from its default value of 0.001, to 0.01, or even 0.1 creates worse model. Meanwhile, increasing dimensions of LSTM will sometimes increases training time or decreases it while not really increasing model performance. In the end, models chosen at the end are models with around 97% of accuracy that has a fairly stable learning graph and predicted output

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000119	T89227	T892272022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T892272022

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer., 2022

Collation

xv, 89 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.678 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Website
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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