A5089350297- Digital Marketing and Social Media
- Sentiment Analysis and Opinion Mining
- COVID-19 Pandemic Impacts
- Recycling and Waste Management Techniques
- Air Quality Monitoring and Forecasting
- Fiscal Policy and Economic Growth
- Extraction and Separation Processes
- Impulse Buying and Technology Impacts
- Energy Load and Power Forecasting
- COVID-19 and Mental Health
- Technology Adoption and User Behaviour
- Taxation and Compliance Studies
- Advanced Battery Technologies Research
- Impact of Light on Environment and Health
- Diverse Aspects of Tourism Research
- COVID-19 epidemiological studies
Bandung Institute of Technology
2022-2023
Bank Indonesia
2023
Purpose This research presents machine learning models for predicting international tourist arrivals in Indonesia during the COVID-19 pandemic using multisource Internet data. Design/methodology/approach To develop prediction models, this utilizes data from TripAdvisor travel forum and Google Trends. Temporal factors, posts comments, search queries index previous records are set as predictors. Four sets of predictors three distinct compositions were utilized training namely artificial neural...
This paper assesses the impact of covid-19 pandemic, measured through work mobility reduction, and e-commerce growth on labour market using data from Indonesian force surveys transaction values. The findings confirm that pandemic adversely affects workers' employment prospects, hours, total earnings, hourly earnings. E-commerce does not counteract adverse as expected, but it plays a role an buffer during crisis, although tends to suppress Our results imply more efforts are needed improve...
Electricity demand has been disrupted in various countries since many governments imposed comprehensive social restriction policies to control the COVID-19 pandemic. Obtaining accurate electricity consumption predictions this highly uncertain period is particularly important for building operators improve corresponding operational planning efficacy. Nevertheless, developing prediction models buildings within context a nontrivial task. Correspondingly, research focuses on incorporating...
The growing utilization of social media platforms enables direct interaction between companies and consumers. However, the expanding range interactions real-world data complexities necessitate development more sophisticated decision models. To address this, current research focuses on constructing machine learning models, namely multinomial logistic regression, tree, k-nearest neighbor, random forest, to forecast engagement level Twitter posts from three prominent e-commerce in Indonesia:...
This study aims to identify the critical factors of shipping success and courier services in Indonesia. The uses a survey questionnaire Indonesia on consumer preferences logistics service consumers, using location Jakarta, Bogor, Depok, Tangerang, Bekasi (Jabodetabek) as locational preferences. consist ease use delivery services; estimated shipments; package location; operational time; availability packaging pricing methods; guarantee; payment method for costs; serving tracking; tracking...
We investigate the effects of COVID-19 lockdowns on frequency online search mental well-being and religiosity-related terms in Indonesia using high-frequency data from Google Trends Bank Consumer Survey January 1st, 2018, to February 28th, 2021. Monthly consumer survey are merged at provincial level, which results a total 131,300 individual observations. Using event analysis instrumental variable approaches, our study suggests that lockdown policy is significantly associated with higher...