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Incidence of malaria is clustered and buffers around plantations: a spatial analysis Yudhi Wibowo; Agung Saprasetya Dwi Laksana; Joko Mulyanto; Madya Ardi Wicaksono; Agus Y Purnomo
Universa Medicina Vol. 34 No. 2 (2015)
Publisher : Faculty of Medicine, Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2015.v34.138-148

Abstract

BackgroundMalaria is re-emerging because of imported cases and the presence of potential vectors that can transmit and spread malaria. Malaria is a health problem in Banyumas District. Mapping the spread of infectious diseases is epidemiologically important. The purpose of this study was to determine the relationship between the variables and the epidemiology of malaria that were spatially modeled using the geographic information system (GIS).MethodsThis was a case-control study with ratio of 1:1. Cases were malaria-positive patients and controls were people without malaria, as diagnosed by microscopic examination. Minimum sample size was 139 per group and total sample size was 282 people. Chi-square was used to test the relationship between the variables, and GIS modeling to determine the spatial distribution of malaria cases.ResultsThere were significant relationships between level of income below minimum wage, not using mosquito nets, not using wire netting, not using insect repellents, habit of going out at night, history of malaria, cattle sheds not located between woods and residential area, history of going to endemic areas, residence at distances <1000 m from plantations, bushes, swamps and puddles, with incidence of confirmed malaria (p<0.001). The group of cases living <1000 meters from plantations numbered 141 (100%).ConclusionsMalaria incidence is clustered and buffers around plantations at <1000 m. Malaria hot spots are displayed as risk maps that are useful for monitoring and spatial targeting of prevention and control measures against the disease.
Lanthanum-doped reduced graphene oxide modified screen-printed carbon electrode for lactic acid sensing Retno Supriyanti; Rafi Satria Dwi Awanda; Wahyu Widanarto; Dina Rahmawati; Madya Ardi Wicaksono; Syafrudin Rais Akhdan; Muhammad Alqaaf
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 3: November 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i3.pp671-682

Abstract

This study develops a high-performance lactic acid sensor by modifying screen-printed carbon electrodes (SPCEs) with lanthanum-doped reduced graphene oxide (La-rGO). To enable portable and wearable applications, the sensor is integrated into an internet of things (IoT) architecture utilizing a micro-power analog front-end (AFE), an ESP32-C6 controller, and a field-programmable gate array (FPGA) coprocessor for dynamic calibration. Electrochemical characterization demonstrated a high sensitivity of 20.36 µA·mM⁻¹·cm⁻², surpassing unmodified SPCEs. Under optimal conditions, the sensor achieved a limit of detection (LOD) of 13.58 mM and a limit of quantification (LOQ) of 45.28 mM. Furthermore, hardware evaluation showed the FPGA executes temperature compensation with an ultra-low latency of 1.80 µs. A hybrid duty-cycling strategy restricts the average current to 1.85 mA, allowing over 172 hours of continuous operation on a 320 mAh battery. These results demonstrate the hardware-accelerated, IoT-enabled La-rGO/SPCE platform's potential for continuous, non-invasive epidermal sweat analysis.