Travel patterns of free-floating e-bike-sharing users before and during COVID-19 pandemic

Choi, Seung Eun; Kim, Jinhee; Seo, Dayoung

doi:10.1016/j.cities.2022.104065

Cited by 11 publications

(3 citation statements)

References 37 publications

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“…Bagian dari proses KDD adalah data mining, dimana pola dan model diekstrak dari data dengan menggunakan algoritma tertentu. Pada penelitian ini tahapan Knowledge Discovery in Database yaitu [13].…”

Section: Teknik Analisis Dataunclassified

Analisis Perbandingan Algoritma Decisioin Tree Dan Naïve Untuk Mengevaluasi Prestasi Belajar Siswa

Sholihin Fauzan,

Irma Purnama Sari,

Ali

2024

jati

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Prestasi belajar siswa merupakan faktor kunci dalam dunia pendidikan. Suatau negara akan maju seiring dengan kemajuan dalam bidang pendidikannya. Prestasi belajar siswa dapat meningkatkan akreditasi sekolah dan merupakan salah satu faktor keberhasilan pendidikan. Analisis data akademik yang tepat dapat membantu mengenai unsur-unsur yang mempengaruhi hasil prestasi belajar siswa. Oleh karena itu, penggunaan algoritma klasifikasi seperti Decision Tree dan Naïve Bayes menjadi penting untuk membantu pengambilan keputusan di lingkungan pendidikan. Penelitian ini mendapatkan sumber data dari SMK Al-Musyawirin Weru Cirebon dengan jumlah data sebesar 202 dengan menggunakan teknik pengumpulan data melakukan observasi dan wawancara langsung. Atribut yang digunakan dalam penelitian ini adalah Nama Siswa, Mata Pelajaran Pendidikan Agama Islam, Pendidikan Kewarganegaraan, Bahasa Indonesia, Bahasa Inggris, Matematika, Sejarah, Seni Budaya, Pendidikan Jasmani Olahraga Kesehatan, Simulasi Digital, Fisika, Kimia dan Bahasa Sunda. Peneliti menerapkan kedua algoritma ini menggunakan teknik data mining. Pada pengujian Cross Validation dengan 5-fold menggunakan metode Naïve Bayes menunjukan hasil keakuratan tertinggi sebesar 85.93%. Sedangkan pengujian menggunakan split data medapatkan keakuratan 95.00%. Pada pengujian Cross Validation dengan 7-fold menggunakan metode Decision Tree menunjukan hasil keakuratan tertinggi sebesar 89,22%. Sedangkan pengujian menggunakan split data medapatkan keakuratan 100.00%. Menurut hasil yang telah diuji dengan menggunakan tools RapidMiner, menyatakan bahwa metode Decision Tree memiliki tingkat akurasi yang lebih tinggi daripada metode Naïve Bayes dalam menentukan prestasi akademik siswa. Dalam hal ini bagian akademik bisa mengantisipasi hasil pembelajaran siswa jika ada yang kurang berprestasi.

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Section: Teknik Analisis Dataunclassified

Analisis Perbandingan Algoritma Decisioin Tree Dan Naïve Untuk Mengevaluasi Prestasi Belajar Siswa

Sholihin Fauzan,

Irma Purnama Sari,

Ali

2024

jati

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“…The usage behavior of these modes shows inconsistent results in each city, probably because the factors of decrease (e.g., decreased numbers of trips and increased working from home) and increase (e.g., effects of short-distance travel shifting from public transit) are mixed together. For example, during the pandemic, bike-sharing use decreased in London (Li et al 2021b;Heydari et al 2021), Lisbon (Teixeira et al 2022), Bangkok (Sangveraphunsiri et al 2022), andSlovakia (Kubal'ák et al 2021), remained moderately stable in Korea (Choi et al 2023), and increased in Singapore (Song et al 2022) and Washington DC (Chen et al 2022b). Ten cities in Germany also showed inconsistent results; the bicycle traffic volume decreased where the ratio of bicycle means was high and increased where the ratio of means was low, while pedestrian traffic decreased with higher local infectiousness and government measures (Mollers et al 2022).…”

Section: Other Impacts: Bicycles Shared Mobility Environment and Traf...mentioning

confidence: 99%

Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility

Lee

Eom

2023

Transportation

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The unprecedented COVID-19 outbreak has significantly influenced our daily life, and COVID-19’s spread is inevitably associated with human mobility. Given the pandemic’s severity and extent of spread, a timely and comprehensive synthesis of the current state of research is needed to understand the pandemic’s impact on human mobility and corresponding government measures. This study examined the relevant literature published to the present (March 2023), identified research trends, and conducted a systematic review of evidence regarding transport’s response to COVID-19. We identified key research agendas and synthesized the results, examining: (1) mobility changes by transport modes analyzed regardless of government policy implementation, using empirical data and survey data; (2) the effect of diverse government interventions to reduce mobility and limit COVID-19 spread, and controversial issues on travel restriction policy effects; and (3) future research issues. The findings showed a strong relationship between the pandemic and mobility, with significant impacts on decreased overall mobility, a remarkable drop in transit ridership, changes in travel behavior, and improved traffic safety. Government implemented various non-pharmaceutical countermeasures, such as city lockdowns, travel restrictions, and social distancing. Many studies showed such interventions were effective. However, some researchers reported inconsistent outcomes. This review provides urban and transport planners with valuable insights to facilitate better preparation for future health emergencies that affect transportation.

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“…Moreover, the demand for public transport in Budapest experienced the greatest reduction (80 %), while cycling (23 %) and bike-sharing (2 %) experienced the lowest; however, private car use increased by 25 % ( Bucsky, 2020 ). According to Choi et al (2023) , citing a report by the Seoul Institute of Technology, there was a reduction of 32 % in public transport movements in Seoul after the outbreak, with a reduction of 27.4 % among subway users. In addition, a Polish survey found a reduction of 66 % in the time spent travelling, regardless of age group and gender ( Borkowski et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Who changed and who maintained their urban bike-sharing mobility after the COVID-19 outbreak? A within-subjects study

Seifert

Pellicer-Chenoll

Antón-González

et al. 2023

Cities

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Travel patterns of free-floating e-bike-sharing users before and during COVID-19 pandemic

Cited by 11 publications

References 37 publications

Analisis Perbandingan Algoritma Decisioin Tree Dan Naïve Untuk Mengevaluasi Prestasi Belajar Siswa

Analisis Perbandingan Algoritma Decisioin Tree Dan Naïve Untuk Mengevaluasi Prestasi Belajar Siswa

Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility

Who changed and who maintained their urban bike-sharing mobility after the COVID-19 outbreak? A within-subjects study

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