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Found 4 from your keywords: subject="Sentiment Analysi"
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Aplikasi Monitoring Pembelajaran Berbasis Proyek Menggunakan Android
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Des SuryaniJerika Mardafora

Advances in information technology are currently increasing rapidly, making it easier for everyone to access the information they need flexibly through digital platforms. In aligning these developments, it is important for human resources to have relevant skills and expertise in that field. Based on researchWorld Economic Forum in the future there will be a great need for workers who are expert…

Edition
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ISBN/ISSN
173510751
Collation
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Series Title
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Call Number
Informatika 005.43 Jer a
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Analisis Sentimen Publik Terhadap Kinerja Pelayanan Pt. Bank Rakyat Indonesia…
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Akmar EfendiIndri Pramadani

Kinerja pelayanan PT. Bank Rakyat Indonesia (Persero) Tbk merupakan salah satu faktor sangat penting dalam menjaga kepuasan dan loyalitas nasabah. Media sosial, seperti platform X, sering digunakan oleh publik untuk menyampaikan opini serta pengalaman mereka terkait pelayanan yang diberikan oleh PT. Bank Rakyat Indonesia (Persero) Tbk. Penelitian ini bertujuan untuk menganalisis sentimen publik…

Edition
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ISBN/ISSN
203510618
Collation
92 Halm. ; 30x21 cm
Series Title
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Call Number
Informatika 005.1 Ind a
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Analisis Sentimen Terhadap Layanan Dana Pada Google Play Menggunakan Naive Ba…
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Rizky WandriTiwi Resti Winda Wibowo

In the current era, technology is widely used and needed by many people, one of which is smartphones. One of the most popular mobile applications in Indonesia is the DANA application, which provides various financial services. DANA is a Financial Technology (Fintech) that provides transaction services with users' smartphones. E-wallet can be interpreted as a digital wallet or you could say elec…

Edition
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ISBN/ISSN
203510023
Collation
i-60 Hlm., 30x21 cm
Series Title
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Call Number
Informatika 664.3 Tiw A
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Analisis Sentimen terhadap Program MBKM Ferienjob pada Twitter/X dengan Mengg…
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Rika Indrina SariRizky Wandri

This study aims to analyze sentiment towards the MBKM Ferienjob program on the Twitter/X platform using three classification methods: Naïve Bayes, Decision Tree, and Convolutional Neural Network (CNN). The analysis involves comparing the performance of these methods in terms of accuracy, precision, recall, and F1-Score to determine the most effective method for user sentiment classification. T…

Edition
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ISBN/ISSN
203510482
Collation
xiii, 158 hlm.; 30 x 21 cm
Series Title
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Call Number
Informatika 006.754 Rik a