Analysis of Corona Virus spread uses the CRISP-DM as a Framework: Predictive Modelling

Rivai, Muhammad Akbar

doi:10.30534/ijatcse/2020/76932020

Cited by 9 publications

(10 citation statements)

References 13 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Metode penelitian yang digunakan dalam penelitian ini mengikuti tahapan model Cross Industry Standard Process for Data Mining (CRISP-DM) [25]- [28]. Framework ini diharapkan mampu untuk menganalisis permasalahan bisnis dan kondisi yang sedang terjadi, memberikan transformasi data yang sesuai hingga memberikan model yang dapat menilai efektivitas dan mendokumentasikan hasil yang didapatkan.…”

Section: Metode Penelitianunclassified

Sistem Pendukung Keputusan Menggunakan Metode FUCOM-MOORA untuk Penentuan Maskapai Favorit

Mahendra¹

2021

SISTEMASI

View full text Add to dashboard Cite

Sejak dikeluarkannya berupa serangkaian langkah deregulasi pada tahun 1999, perkembangan industri jasa udara Indonesia semakin berkembang. Namun masih terdapat fakta bahwa banyak maskapai mengalami berbagai kendala sebelum dan selama penerbangan. Pada tahun 2021 saja, terdapat berbagai permasalahan pada pesawat maskapai mulai dari masalah mesin, kendala teknis, kerusakan ban, gangguan cockpit, hingga masalah tekanan udara. Pelanggan maskapai memiliki pertimbangan serta preferensi pribadi untuk memilih maskapai perjalanannya. Banyaknya pilihan maskapai serta banyaknya pertimbangan seringkali membingungkan pelanggan. Untuk menanggulangi hal tersebut, sistem pendukung keputusan (SPK) dapat dipergunakan untuk memberikan rekomendasi dalam memilih maskapai yang sesuai dengan pilihan pelanggan. Penelitian ini telah berhasil mengimplementasikan FUCOM-MOORA dalam penentuan maskapai favorit di Indonesia berdasarkan narasumber yang dilakukan sampling, dengan menggunakan 8 kriteria dan 6 alternatif yang diujikan. Pada perhitungan pembobotan kriteria menggunakan FUCOM menunjukkan bahwa faktor harga (C5) merupakan faktor yang paling diperhitungkan. Perhitungan menggunakan FUCOM-MOORA menunjukkan bahwa Garuda Indonesia menjadi maskapai favorit di Indonesia dengan nilai preferensi sebesar 0,30204, disusul dengan Citilink menjadi maskapai favorit kedua, Batik Air menempati peringkat ketiga. Pengujian menggunakan analisis konsistensi menunjukkan bahwa Garuda Indonesia tetap stabil menjadi pilihan pertama dengan menempati 15 kali peringkat teratas dari 17 pengujian dengan rata-rata sebaran peringkat sebesar 1,23466.

show abstract

Section: Metode Penelitianunclassified

Sistem Pendukung Keputusan Menggunakan Metode FUCOM-MOORA untuk Penentuan Maskapai Favorit

Mahendra¹

2021

SISTEMASI

View full text Add to dashboard Cite

show abstract

“…Various studies related to virus transmission and its influence factors have been carried out to predict (a) the spread of the virus [29,30,31,32,33]; (b) the person suspected of being infected [34]; (c) new infection areas [35]; (d) the likelihood of the second and third waves of the epidemic [36]; (e) COVID-19 contamination scenario based on people movement [37]; and (f) the increased number of cases [38]. COVID-19 task-force stakeholders can use these epidemiological predictions to prepare the necessary measures and policies.…”

Section: Healthcarementioning

confidence: 99%

“…Optical Character Recognition technology was applied to extract text data from PFT data for classification purposes [47]. To determine suspected cases and areas, cellphone Spatio-temporal data can be processed using a decision tree algorithm for classification [35,32]. An application of artificial intelligence was developed to determine the diagnosis and treatment of the COVID-19 disease for high-risk groups.…”

Section: Classificationmentioning

confidence: 99%

“…Then, chronic disease distribution amongst clusters can be scrutinized [106]. K-means clustering can be employed to allocate infected areas, classify a person's risk in an area using decision tree algorithm [44], and identify the coronavirus spreading [32]. Hierarchical clustering was applied to identify the actual groups of infected COVID-19 [84] and the effects of chloroquine derivatives in patients, based on medical articles [49].…”

Section: Clustering and Topic Modelingmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Big Data Research in Fighting COVID-19: Contributions and Techniques

Riswantini

Nugraheni

Munandar

et al. 2021

Preprint

View full text Add to dashboard Cite

COVID-19 has induced many problems in various sectors of life for humanity around the world. After one year of pandemic, many studies have been carried out in exposing various technology innovations and applications to combat the coronavirus that has killed more people than most. The pandemic has accelerated the use of Big Data technology to mitigate the threats of COVID-19. This survey aims to explore the Big Data research for COVID-19. We collected and analyzed the relevant academic articles to identify how Big Data technology can cover the challenges faced in overcoming the pandemic. In determining the research areas addressed by the past studies, we highlight the technology contributions to five major areas of healthcare, social life, government policy, business and management, and the environment. We discuss how analytical techniques of machine learning, deep learning, statistics, and mathematics can solve pandemic issues. The Big Data research for COVID-19 used a wide variety of data sources available publicly or privately. At the end of the discussion, we present the data source used in the past studies encompassing government official data, institutional service data, IoT generated data, online media data, and open data. We hope that this survey will clarify the role of Big Data technology in enhancing the research for COVID-19.

show abstract

“…Its infections can cause a spectrum of symptoms from common cold to serve pneumonia (pneumonia). CoV also causes various diseases in mammals, birds ranging from enteritis in cattle, pigs, and chickens [1]. As a result, Movement Control Order (MCO) was issued on 18 Mac 2020 as a precautionary measure by the federal government of Malaysia.…”

Section: Introductionmentioning

confidence: 99%

ICT Integration to Support Online Learning During The Covid-19 Outbreaks

Yacob¹

2020

IJATCSE

View full text Add to dashboard Cite

ICT is considered as one of the main elements in transforming the country to the future development. Moreover, ICT is becoming more increasingly important as Coronavirus (CoV) disease or Covid-19 is triggered by the end of 2019. This paper aims to analyze the integration of ICT to support online learning during the covid-19 outbreaks. The methods being used for this research is questionnaire survey, that was response randomly to the total of 118 total of respondents. However, just 114 of the respondents are qualified to be analyzed. The questionnaire was distributed through the google form application. The results indicate that ICT integration has a great effectiveness for both teachers and the students during the Covid-19 outbreaks, with some improvements needed.

show abstract

Analysis of Corona Virus spread uses the CRISP-DM as a Framework: Predictive Modelling

Cited by 9 publications

References 13 publications

Sistem Pendukung Keputusan Menggunakan Metode FUCOM-MOORA untuk Penentuan Maskapai Favorit

Sistem Pendukung Keputusan Menggunakan Metode FUCOM-MOORA untuk Penentuan Maskapai Favorit

A Survey on Big Data Research in Fighting COVID-19: Contributions and Techniques

ICT Integration to Support Online Learning During The Covid-19 Outbreaks

Contact Info

Product

Resources

About