Skripsi

ANALISIS SENTIMEN DATA INSTAGRAM TERHADAP KONDISI KEPADATAN LALU LINTAS KENDARAAN DIBANDINGKAN DENGAN DATA ETLE (ELECTRONIC TRAFFIC LAW ENFORCEMENT) DI JALAN PROTOKOL KOTA PALEMBANG MENGGUNAKAN ALGORITMA NAÏVE BAYES

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Traffic congestion is a major problem in big cities like Palembang. The Electronic Traffic Law Enforcement (ETLE) system has been implemented to improve traffic discipline through surveillance based on CCTV camera technology. However, the limited coverage of ETLE indicates the need for more dynamic traffic data. In this context, social media such as Instagram with millions of active users offers a more real-time and contextual alternative data source. This research aims to analyze the sentiment of Instagram data related to traffic conditions in Palembang City using the Naïve Bayes algorithm, and compare the results with ETLE data. The results show that negative sentiment dominates people's dissatisfaction with traffic conditions in Palembang. Neutral sentiment reflects informative comments, while positive sentiment is few and generally related to improvement efforts. This research obtained classification accuracy of Instagram text dataof 94% and numeric data of 95.28%. The prediction comparison results between text data and numeric data show a 70.16% agreement.

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Detail Information

Series Title

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Call Number

T1818422025

Publisher

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

Collation

xvi, 74 hlm.; ilus.; tab, 29 cm

Language

Indonesia

ISBN/ISSN

-

Classification

003.307

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

-

Subject(s)

Model dan simulasi komputer
Prodi Sistem Komputer

Specific Detail Info

-

Statement of Responsibility

MURZ

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