Skripsi

PERSEPSI KEMACETAN LALU LINTAS DI KOTA PALEMBANG BERDASARKAN ANALISIS SENTIMEN MEDIA SOSIAL FACEBOOK MENGGUNAKAN ALGORITMA DECISION TREE

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Traffic congestion in Palembang City is a frequent problem that impacts community activities and productivity. This study aims to analyze public perceptions of traffic congestion in Palembang City through sentiment analysis on Facebook social media using the Decision Tree Algorithm. Data were collected through web scraping techniques on public comments related to text data traffic over a 32-month period, then processed through pre-processing stages including case folding, data cleaning, tokenization, stemming, stopword removal, and normalization, then divided into 3 data sets: training data, validation data, and test data, then weighted using the TF-IDF method. The Decision Tree model was used to classify sentiment into three categories: positive, negative, and neutral. The results of this study show a Decision Tree accuracy of 93.77% on training data, 90.40% accuracy on validation data, and 90.42% accuracy on test data. However, the accuracy of manual analysis according to the context of the initial post experienced a significant decrease of 55.82%. This study is expected to provide information and input for related parties in formulating policies to reduce traffic congestion problems.

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Availability

Detail Information

Series Title

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Call Number

T1892832025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 146 hlm.; ilus.; tab, 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

306.460 7

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Budaya Transportasi--Kemacetan

Specific Detail Info

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Statement of Responsibility

MI

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