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A Confirmation Factor Analysis of Public Compliance in Implementing Health Protocols Post Covid-19 Pandemic Susilawati, Made; Sumarjaya, I Wayan; Octavanny, Made Ayu Dwi; Diva, Made Tresia Pramasta
International Journal of Health and Medicine Vol. 2 No. 1 (2025): January : International Journal of Health and Medicine
Publisher : Asosiasi Riset Ilmu Kesehatan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijhm.v2i1.227

Abstract

The COVID-19 pandemic severely impacted Indonesia, leading to substantial socio-economic disruptions and widespread social anxiety. In response, the government implemented a range of measures, including restrictions and mandatory health protocols, to control the virus. Although the pandemic is officially declared over, the risk of infection remains. Therefore, continued adherence to health protocols is essential. This study aimed to identify the key factors driving public compliance with health protocols in the post-pandemic period within Indonesia, providing valuable insights for policymakers to prevent future outbreaks. The findings revealed that knowledge emerged as the most significant determinant of community adherence to ongoing health protocol implementation. Consequently, the government must consistently emphasize the importance of adhering to health protocols whenever individuals are outside their homes.
Aspect-Based Sentiment Analysis of Reviews for Pandawa Beach Using Naive Bayes and SVM Methods Putri, Made Ayu Asri Oktarini; Sumarjaya, I Wayan; Wijayakusuma, I Gusti Ngurah Lanang
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9083

Abstract

The presence of digital technology, especially online platforms such as Google Maps, has changed the way people search for information about tourist destinations, including reviews and ratings from previous visitors. Aspect-based sentiment analysis becomes a very useful tool to understand people's views and feelings towards a place or product based on the reviews given and identify aspects of interest to tourists visiting Pandawa Beach, by utilizing Naive Bayes and Support Vector Machine (SVM) methods. The main objective of this research is to identify sentiment patterns based on aspects such as attraction, accessibility, amenities, and ancillary. Data was collected and labeled according to sentiment and aspects, then processed using preprocessing techniques, extracted by bag-of-words method, and chi-square feature selection. The model evaluation results showed that SVM produced the highest F1-Score value of 79,625%, while the Naive Bayes method reached 73.29%.
ANALYSIS OF SOCIO-ECONOMIC IMPACTS OF THE COVID-19 PANDEMIC USING FACTOR ANALYSIS Susilawati, Made; Sumarjaya, I Wayan; Srinadi, IGAM; Nilakusmawati, DPE; Suciptawati, NLP
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1235-1244

Abstract

The purpose of this study is to identify the factors that influence the socio-economic impact of the Covid-19 pandemic. This study uses explanatory factor analysis that is an analysis that forms new random factors in which the later formed factors or constructs can be interpreted. The case study was conducted in Sawan Village, Sawan District, Buleleng Bali, with six variables explaining the economic impact, and 16 variables explaining the social impact. The results of the study show that there are three factors that explain the economic impact due to Covid-19. They are the income factor, the purchase of quotas and gadgets, and the expenditure factor with the total variance described being 82,178 percent. Meanwhile, the social impact due to the Covid-19 pandemic is explained by three factors, namely the fear of interacting in public places, the fear factor of doing activities outside the home, and the fear of using public facilities with a total variance that can be explained is 73,609 percent.
Seleksi Fitur Information Gain Untuk Klasifikasi Kualitas Susu Sapi Menggunakan Metode K-Nearest Neighbor Dan Naïve Bayes Ali, Fauzi Wardah; Sumarjaya, I Wayan; Kencana, Eka N.
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i1.17477

Abstract

Kemajuan dalam komputasi modern, khususnya klasifikasi, telah membantu manusia dalam mengklasifikasikan berbagai tugas yang memakan waktu dan komputasi yang mahal, salah satunya adalah klasifikasi kualitas susu sapi. Pengklasifikasian ini penting dilakukan untuk mengurangi kemungkinan beredarnya susu dengan kualitas buruk di masyarakat. Data pada penelitian ini terdiri dari 429 susu kualitas rendah, 374 susu kualitas menengah, dan 256 susu kualitas tinggi. Penelitian ini menguji performa algoritma klarifikasi K-nearest neighbor dan naïve Bayes dengan menggunakan teknik seleksi fitur information gain dan tanpa seleksi fitur information gain. Hasil penelitian ini menunjukkan performa KNN mengalami peningkatan rata-rata akurasi sebesar 1,04 persen dengan perhitungan jarak Euclid dan 0,92 persen dengan perhitungan jarak Manhattan ketika menggunakan lima fitur. Sedangkan performa naïve Bayes mengalami penurunan akurasi sebesar 3,48 persen. Perlakuan yang berbeda tersebut memiliki perbedaan akurasi yang signifikan.
ESTIMASI TAIL VALUE AT RISK SAHAM BLUE CHIPS MENGGUNAKAN COPULA ALI-MIKHAIL-HAQ Candrasuari, Ni Luh Putu Diah Ayu; Sumarjaya, I Wayan; Sari, Kartika
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 5 No. 1 (2024)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v5i1.2142

Abstract

When making investments, investors definitely want high returns with low risk. However, high returns are usually accompanied by high risks and vice versa. Value at Risk (VaR) and other measurement tools help manage risk. VaR measures possible losses. However, VaR has weaknesses, thus Tail Value at Risk (TVaR) can be used to evaluate the likelihood of larger losses than VaR. Copula can be used in risk management because it does not require normal distribution assumptions so it is well applied to financial data. The purpose of this research is to use the Ali-Mikhail-Haq copula to estimate TVaR value of blue chip stock portfolios, including those of BRI, BCA, and Bank Mandiri. Data used is the closing price of daily stocks for the period Jan 1 2021 to Jun 30 2023. The results of calculating TVaR value at the 90%, 95%, and 99% confidence level of the combination of BMRI and BBRI stocks are 0,0574; 0,0668; dan 0,0807. At a confidence level of 90%, 95% and 99% TVaR value of the combination of BMRI and BBCA stocks is 0,0569; 0,0669; dan 0,0886. The combination of BBRI and BBCA stocks resulted in TVaR at 90%, 95% and 99% confidence levels are 0,0238; 0,0283; 0,0376.