Skripsi

ANALISIS HUBUNGAN JUMLAH PENUMPANG DAN BUS SEKOLAH DI KOTA JAKARTA PADA TAHUN 2017 HINGGA 2019 MENGGUNAKAN PENDEKATAN UNSUPERVISED LEARNING

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Penilaian

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This study aims to identify patterns in the relationship between the number of school buses and the number of school passengers in Jakarta during the 2017–2019 period using an unsupervised learning approach. Four clustering algorithms K-Means, Fuzzy C-Means, Gaussian Mixture Model, and Spectral Clustering were applied to group the data, all of which produced two optimal clusters. Among these algorithms, K-Means outperformed the others based on evaluation metrics and was selected as the primary method for analyzing the clustering results. The first cluster represents a high ratio of buses to passengers, while the second shows a lower ratio. These patterns serve as a foundation for more efficient school transportation planning. The clustering results were then used as labels to train a Decision Tree Classifier model, which was applied to data from 2021. The model successfully classified the new data into the two clusters consistent with the previously identified patterns.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003382	T175441	T1754412025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1754412025

Publisher

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

Collation

xiii, 85 hlm., ilus., tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

MI

Other version/related

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