Analisis Sentimen Pengaruh Pembelajaran Daring Terhadap Motivasi Belajar Di Masa Pandemi Menggunakan Naive Bayes Dan SVM

Ariansyah, Ariansyah; Kusmira, Mira

doi:10.30998/faktorexacta.v14i3.10325

Cited by 3 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Classification uses Naive Bayes classification algorithms and supports vector machines by preprocessing data using tokenize, transform case, filtering, and stemming. The highest and best accuracy result is classification algorithm support vector machine with accuracy 97.22%, precision 94.72%, recall 100%, and error 2.78% [4]. Ulasan yang ada cukup banyak dan tidak terstruktur serta mengandung opini dari para pengguna tentang kepuasan mereka terhadap aplikasi tersebut.…”

Section: Pendahuluanmentioning

confidence: 99%

Analisis Sentimen Masyarakat Terhadap Isu Pecat Sri Mulyani Pada Twitter Menggunakan Metode Naive Bayes Dan Support Vector Machine

Berliani,

Lestari

2024

SAINTEK

View full text Add to dashboard Cite

Penelitian ini dilakukan untuk mengetahui pendapat masyarakat terhadap Isu Pecat Sri Mulyani pada media sosial Twitter. Salah satu algoritma yang dapat digunakan untuk melakukan analisis sentimen adalah Naïve Bayes dan Support Vector Machine (SVM), bertujuan Mengetahui Klasifikasi dan Nilai Akurasi Tanggapan masyarakat dengan sisi Positif dan Negatif. Sentimen Analisis yang dilakukan dengan Perbandingan Metode Naïve Bayes dan Support Vector Machine menggunakan datalatih sebanyak 1958 tagar Pecat Sri Mulyani di media sosial Twitter. Hasil akhir dari Perbandingan dengan dua metode pengujian ini, yaitu hasil prediksi Sentimen Masyakarat Terhadap Isu Pecat Sri Mulyani stop bayar pajak berdasarkan data yang didapat dari Twitter dan diimplementasikan dengan metode SVM (Support Vector Machine) menunjukkan nilai akurasi sebesari 95.13%. Dari 596 data uji, terprediksi sebesar 254 data sebagai Sentimen Negatif dan 342 data sebagai Sentimen Positif Untuk hasil prediksi dari Sentimen Negatif, terdapat 596 data terprediksi Negatif dan 2 data yang terprediksi Positif dan Metode Naïve bayes menunjukkan nilai akurasi sebesari 96.14%. Dari 596 data uji, terprediksi sebesar 296 data sebagai Sentimen Negatif dan 302 data sebagai Sentimen Positif Untuk hasil prediksi dari Sentimen Negatif, terdapat 596 data terprediksi Negatif dan 2 data yang terprediksi Positif.

show abstract

Section: Pendahuluanmentioning

confidence: 99%

Analisis Sentimen Masyarakat Terhadap Isu Pecat Sri Mulyani Pada Twitter Menggunakan Metode Naive Bayes Dan Support Vector Machine

Berliani,

Lestari

2024

SAINTEK

View full text Add to dashboard Cite

show abstract

“…The process of changing sentences in a document. The process involves cutting each word into a token so that it can be analyzed [23]. The results obtained are the distribution of words in each row of data.…”

Section: Data Processingmentioning

confidence: 99%

“…Filtering. Procedure for translating and sorting a word that still contains foreign words into a standard word [23]. This stage is also often known as Stopword Removal.…”

Section: Data Processingmentioning

confidence: 99%

See 1 more Smart Citation

The Intersection of Machine Learning, Zakat, and Transportation for a Healthy Society

Asyhari,

Susanti,

Juwari

et al. 2024

Advances in Engineering Research

View full text Add to dashboard Cite

The recent Covid-19 pandemic has shown that transportation has a significant role in creating a healthy society. Human mobility can be tracked and traced to map the spread of infectious diseases using screening, tracing, and tracking methods through policies and applications. This momentum has accelerated the massive application of technology, one of which is using Machine Learning. Zakat also has an essential role during the pandemic quarantine policy. The potential of the combination of Machine Learning, Zakat, and transportation should now be increased to improve the Quality of Life to achieve a healthy society. The intersection of these three topics was researched using data scraping from the web dimension as one of the platforms that accommodates a collection of research publications. Data is limited to abstracts of research results within the last five years. Next, the data obtained was preprocessed, text-processed, and analyzed using the FP-Growth Algorithm for Association Rule. Research published so far shows that there is an intersection between Machine Learning, Zakat, and Transportation to achieve a healthy society, even with varying intersection probability values. Machine learning and transportation have the most potent intersection with health, while zakat is still lower. The results of this research can open up collaborative research topics between these domains. The results of this research can also be used as suggestions for policy-making by stakeholders to explore the existing potentials of various journals that have been published.

show abstract

“…Changes in the pandemic can be seen based on indicators of the comparison of the number of positive cases with the number of tests (positivity rate) and death rates. If the number of tests (positivity rate) and death rates increase, it indicates that the pandemic is out of control (Ariansyah & Kusmira, 2021) . Based on the official report from the Covid-19 Handling Task Force in early 2021 which can be accessed from the official website covid19.go.id , Indonesia's positivity rate occurred on January 31, 2021 which reached 36.18% or more than 7 times the safe limit set.…”

Section: Introductionmentioning

confidence: 99%

Predictor Analysis of Antenatal Care Behavior in the Pandemic Era in the Work Area of the Banyuwangi Kabat Health Center

Raharjo

Purwaningsih²,

Wahyudi³

2022

jqph

View full text Add to dashboard Cite

The spread of COVID-19 caused by the SARS-CoV-2 virus has spread worldwide . On January 30, 2020, WHO declared it a public health emergency (Suryani & Purwodiharjo, 2021). Indonesia is currently expanding across regions, followed by an increase in the number of cases and the number of deaths (Purba, 2021). Overview of the Death Rate from Positive COVID-19 Cases Per 100,000 Population Based on Regency/City, Banyuwangi is ranked 8th at the national level at 396 with the highest number of deaths.ANC is a visit by pregnant women with health workers aimed at monitoring the progress of pregnancy to ensure the health of the mother and baby's growth and development, to recognize any abnormalities or complications that may occur during pregnancy, prepare for childbirth, prepare for the postpartum period and provide exclusive breastfeeding. (Fatkhiyah , d kk, 2020). This type of research is quantitative using observational analytical methods using a cross sectional approach. The variables in this study consisted of independent variables and dependent variables. The independent variable isbehavioral factors (age, occupation, knowledge, and attitude). The dependent variable is ANC (antenatal care) behavior . The number of samples in this study were 30, using total sampling technique. Data collection techniques were carried out by distributing questionnaires. The analysis in this study used Multiple Linear Regression Test consisting of t test and F test.

show abstract

Analisis Sentimen Pengaruh Pembelajaran Daring Terhadap Motivasi Belajar Di Masa Pandemi Menggunakan Naive Bayes Dan SVM

Cited by 3 publications

References 11 publications

Analisis Sentimen Masyarakat Terhadap Isu Pecat Sri Mulyani Pada Twitter Menggunakan Metode Naive Bayes Dan Support Vector Machine

Analisis Sentimen Masyarakat Terhadap Isu Pecat Sri Mulyani Pada Twitter Menggunakan Metode Naive Bayes Dan Support Vector Machine

The Intersection of Machine Learning, Zakat, and Transportation for a Healthy Society

Predictor Analysis of Antenatal Care Behavior in the Pandemic Era in the Work Area of the Banyuwangi Kabat Health Center

Contact Info

Product

Resources

About