Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Business, Economics, and Social Development International Journal of Quantitative Research and Modeling
Mugi Lestari
Master's Program of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor, West Java, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analysis of Economic Growth and Tourism Potential in Tanjung Lesung, Panimbang, Banten as a Creative Economy Destination Rizki Apriva Hidayana; Mugi Lestari
International Journal of Business, Economics, and Social Development Vol. 6 No. 1 (2025): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.879

Abstract

Tanjung Lesung, located in Pandeglang Regency, Banten, has been designated as a Special Economic Zone (SEZ) for Tourism with the aim of encouraging regional economic growth and improving community welfare. This study analyzes the impact of SEZ on the local economy using qualitative and quantitative approaches. Data were obtained through in-depth interviews, surveys, field observations, and documentation studies. The results of the study indicate that the Tanjung Lesung SEZ has contributed positively to increasing community income by 52% and reducing the unemployment rate by 33%. In addition, investment in the tourism sector encourages business growth in the hospitality, culinary, and tourism services sectors. However, the development of SEZ also faces several challenges, such as limited infrastructure, readiness of local workers, and social and environmental impacts. Limited infrastructure, especially transportation access, is an obstacle in supporting the growth of the tourism sector. In addition, many local workers do not yet have the skills needed by the tourism industry. Environmental impacts, such as increasing waste volume and conversion of agricultural land, are also major concerns. Therefore, a comprehensive strategy is needed through improving infrastructure, strengthening human resource capacity, and implementing sustainable environmental management policies. With the right steps, Tanjung Lesung Special Economic Zone can become a successful model for inclusive and sustainable tourism-based economic development in Indonesia.
Negative Binomial Regression with Climatic and Sociodemographic Covariates for Modeling Overdispersed Dengue Hemorrhagic Fever Counts: Evidence from Bandung City, Indonesia Rifki Saefullah; Natasya Tamarysma Putri; Mugi Lestari
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1339

Abstract

Dengue Hemorrhagic Fever (DHF) remains one of the most prevalent vector-borne diseases in Indonesia, with Bandung City consistently reporting high annual incidence. Count regression models have been widely applied in disease epidemiology; however, many studies default to Poisson regression without testing for overdispersion, which violates a fundamental modeling assumption when variance exceeds the mean. This study proposes a Negative Binomial Regression (NBR) framework that jointly incorporates climatic variables (monthly rainfall, mean temperature, relative humidity) and sociodemographic covariates (population density, drainage quality index, vegetation cover) to model weekly DHF case counts across 30 sub-districts of Bandung City from 2019 to 2023. Overdispersion was formally assessed using the Cameron-Trivedi test. Incidence Rate Ratios (IRRs) and 95% confidence intervals were estimated for all predictors. Model selection was performed via AIC, BIC, and likelihood ratio tests against a Poisson baseline. Results demonstrate significant overdispersion (dispersion parameter ), confirming the appropriateness of NBR over Poisson regression. Monthly rainfall (IRR = 1.008, p < 0.001), lagged one-week cases ), and population density emerged as significant positive predictors, while drainage quality index was protective. The NBR model achieved substantially lower AIC (2810 vs 3240) and BIC (2820 vs 3245) compared to Poisson. These findings provide quantitative evidence for spatiotemporal DHF surveillance and can guide targeted vector-control resource allocation in urban West Java
Co-Authors Natasya Tamarysma Putri Rifki Saefullah Rizki Apriva Hidayana