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OPTIMAL STRATEGIES FOR DENGUE CONTROL: WOLBACHIA-INFECTED MOSQUITOES DEPLOYMENT, PUBLIC HEALTH EDUCATION, AND VACCINATION Toni Bakhtiar; Jaharuddin Jaharuddin; Farida Hanum
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1301-1316

Abstract

Wolbachia-infected mosquitoes present a promising method for dengue control by inhibiting viral replication, reducing mosquito reproductive capacity, and shortening the lifespan of Aedes aegypti mosquitoes. This study introduces a novel optimal control model that uniquely integrates two distinct release strategies for Wolbachia-infected mosquitoes—constant and proportional rates. While prior research has explored Wolbachia deployment, our model is the first to directly compare and contrast these two rate types within the same framework to assess their differential impact on dengue transmission dynamics. This provides a more comprehensive understanding of effective release protocols, addressing a critical gap in the literature regarding optimal and adaptive Wolbachia deployment. Based on model simulations for North Kembangan Village, Jakarta, we find that a single-control strategy using Wolbachia mosquito release alone can reduce dengue cases by up to 15%. However, a multiple-control strategy that combines Wolbachia releases with public health education and vaccination is the most effective approach, achieving a substantial reduction of up to 58%. In a cost-effectiveness analysis, the study reveals that the Wolbachia-only strategy (proportional release) is the most cost-effective in terms of cost per infection averted. In terms of release dynamics, the study reveals that a constant release rate provides long-term benefits by establishing a stable Wolbachia-infected mosquito population, whereas a proportional release rate is more effective for achieving a rapid, short-term reduction in dengue cases.
Analysis of Online Marketplace User Satisfaction using SERVQUAL, Quality Function Deployment, and Mixed Integer Linear Programming Nayla Nur Alifah; Toni Bakhtiar; Jaharuddin Jaharuddin
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.30035

Abstract

This study analyzes and optimizes user satisfaction in online marketplaces by integrating SERVQUAL, the Kano Model, Quality Function Deployment (QFD), and Mixed Integer Linear Programming (MILP). Data were collected from 167 Shopee users, with 107 valid responses analyzed. SERVQUAL measured service quality dimensions, the Kano Model derived satisfaction and dissatisfaction parameters, QFD translated user requirements into internal service measures, and MILP selected optimal improvement alternatives under an IDR 90,000,000 budget constraint. The results show that assurance had the highest SERVQUAL weight (0.207), followed by tangibility (0.201), reliability (0.200), empathy (0.198), and responsiveness (0.195). The Pearson correlation-based HoQ approach selected customer service training, automatic delivery update features, and feedback completion incentives, with a total cost of IDR 85,000,000 and a deviation value of 0.191. These findings provide scenario-based decision support to improve the quality of marketplace services.
Optimalitas Rute pada Pengiriman Multiperjalanan dengan Armada Kendaraan Listrik Heterogen Kamilia Salsabilla; Toni Bakhtiar; Farida Hanum
Jambura Journal of Mathematics Vol 6, No 1: February 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i1.23993

Abstract

Electric vehicles are emerging as a key trend in sustainable mobility, mitigating emissions, and reducing dependence on fossil fuels. The challenge in optimizing route modeling lies in some limitations, such as battery range, charging time, and the diversity of electric vehicle types. This article explores the optimality of routes in a multiple-trip distribution system using a heterogeneous fleet of electric vehicles. The electric vehicle routing problem is formulated as a mixed-integer linear programming aiming to find the most cost-efficient optimal route. A notable feature of the model allows electric vehicle fleets to undertake additional travel to complete distribution tasks, i.e., multiple trips. The model is implemented in two illustrative examples involving the delivery of goods using homogeneous and heterogeneous electric vehicle fleets characterized by loading and battery capacities. Each case includes one depot, 8 and 10 customers, and 2 battery swapping stations, solved using the branch-and-bound method through Lingo 18.0. Simulation results indicate that battery capacity and the presence of battery swapping stations significantly influence the routes selection.