scholarly journals Studi Kasus: Kejadian Bruselosis Pada Sapi Potong Di Kabupaten Barru Provinsi Sulawesi Selatan Tahun 2015-2017

2022 ◽  
Vol 11 (3) ◽  
pp. 321
Author(s):  
Herwin Pisestyani ◽  
Nisa Nurul Fitria ◽  
Ardilasunu Wicaksono
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Beef Cattle ◽  
Incidence Rate ◽  
Control Measure ◽  
Geographic Information ◽  
South Sulawesi ◽  
Medium Risk ◽  
Risk Areas ◽  
Analyze Data

Abstract There is still lack of bruselosis in beef cattle in Barru District, South Sulawesi. The aim of this study was to analyze data about the temporary distribution of disease by measuring spreading speed, and spatial distribution by mapping risk areas for bruselosis over the past three years. The data of this study was collected using the records from Dinas Peternakan and conducting interviews using structured questionnaires. This research was a descriptive study by measuring the incidence rate and describing the risk map using geographic information system (GIS). The results of this study indicate that, based on the incidence rate, the average of distribution rate of bruselosis in beef cattle in Barru is 5 cases per 10 000 heads/year. This incidence rate always decreases every year. There was no sub-district that classified as high risk. There was one area that classified as medium risk namely sub-district of Mallusetasi. Control measure that have been carried out by goverment were successful to reduce the spread of disease. Keywords: Beef cattle; Bruselosis; Incidence rate; Occurrence; Risk.   Abstrak Informasi mengenai penyebaran kejadian penyakit pada sapi potong di Kabupaten Barru Sulawesi selatan masih kurang. Penelitian ini bertujuan menganalisis data distribusi kejadian penyakit secara temporal dengan mengukur kecapatan penyebaran, dan secara spasial dengan memetakan wilayah berisiko bruselosis selama tiga tahun terakhir. Data dalam penelitian ini menggunakan rekapan dari Dinas Peternakan dan wawancara mendalam menggunakan kuesioner terstruktur. Penelitian ini mengunakan metode deskriptif dengan mengukur incidence rate dan menggambarkan peta risiko menggunakan geographic information system. Hasil penelitian ini menunjukkan bahwa berdasarkan incidence rate, kecepatan rata-rata penyebaran bruselosis pada sapi potong di Kabupaten Barru sebesar 5 kasus per 10 000 ekor/tahun. Nilai incidence rate tersebut selalu menurun setiap tahunnya. Kejadian penyakit paling tinggi terjadi di Kecamatan Mallusetasi dengan incidence rate sebesar 35 kasus per 10 000 ekor/tahun. Terdapat satu wilayah yang tergolong ke dalam risiko sedang, yaitu Kecamatan Mallusetasi. Tindakan pengendalian yang telah dilakukan oleh pemerintah setempat dikatakan berhasil dalam menekan tingkat kejadian penyakit. Kata kunci: Bruselosis; Incidence rate; Risiko; Sapi potong; Tingkat kejadian

Kejadian Bruselosis Pada Sapi Potong dan Pemetaan Wilayah Berisiko di Kabupaten Barru Provinsi Sulawesi Selatan Tahun 2015-2017

2020 ◽  
Vol 8 (2) ◽  
pp. 111-120
Author(s):  
Nisa Nurul Fitria ◽  
Herwin Pisestyani ◽  
Ardilasunu Wicaksono
Keyword(s):  
Beef Cattle ◽  
Incidence Rate ◽  
Control Measure ◽  
Descriptive Study ◽  
Risk Map ◽  
The Past ◽  
South Sulawesi ◽  
Medium Risk ◽  
Risk Areas ◽  
Analyze Data

There is still lack of bruselosis in beef cattle in Barru District, South Sulawesi. The aim of this study was to analyze data about the temporary distribution of disease by measuring spreading speed, and spatial distribution by mapping risk areas for bruselosis over the past three years. The data of this study was collected using the records from Dinas Peternakan and conducting interviews using structured questionnaires. This research was a descriptive study by measuring the incidence rate and describing the risk map using geographic information system (GIS). The results of this study indicate that, based on the incidence rate, the average of distribution rate of bruselosis in beef cattle in Barru is 5 cases per 10 000 heads/year. This incidence rate always decreases every year. There was no sub-district that classified as high risk. There was one area that classified as medium risk namely sub-district of Mallusetasi. Control measure that have been carried out by goverment were successful to reduce the spread of disease.

scholarly journals Distribusi Skabies pada Peternakan Sapi Potong di Kabupaten Barru Provinsi Sulawesi Selatan

2020 ◽  
Vol 10 (2) ◽  
pp. 159
Author(s):  
Meisi Nuriski ◽  
Ardilasunu Wicaksono ◽  
Chaerul Basri
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Beef Cattle ◽  
Incidence Rate ◽  
Geographic Information ◽  
Control Measures ◽  
Risk Areas ◽  
Average Distribution ◽  
Cattle Farms ◽  
Cattle Distribution

Abstract  Beef cattle farms in Barru district are susceptible to various diseases, including scabies. This study aims to analyze data about the distribution of disease temporally by measuring the spreading speed, and spatially by mapping risk areas for scabies over the past three years. The data of this study was collected using the records from Dinas Peternakan and conducting interviews using structured questionnaires. This research was a descriptive study by measuring the incidence rate and describing the risk map using geographic information system (GIS). The results of this study indicate that, based on the incidence rate, the average distribution rate of scabies in beef cattle in Barru is 13 cases per 10.000 head/year. This incidence rate always increases every year. Furthermore, the highest incidence of the disease occurs in Mallusetasi with an incidence rate of 35 cases per 10 000 head/year. The three areas that are classified as high risk are Mallusetasi, Tanete Riaja, and Barru. Control measures that have been carried out were not successful to reduce the spread of the disease. Keywords : Beef cattle; Distribution; Incidence rate; Risk; Scabies   Abstrak  Peternakan sapi potong di Kabupaten Barru rentan terhadap berbagai penyakit, termasuk skabies. Penelitian ini bertujuan menganalisis data distribusi kejadian penyakit secara temporal dengan mengukur kecepatan penyebaran, dan secara spasial dengan memetakan wilayah berisiko skabies selama tiga tahun terakhir. Data dalam penelitian ini menggunakan rekapan dari Dinas Peternakan dan wawancara mendalam menggunakan kuesioner terstruktur. Penelitian ini mengunakan metode deskriptif dengan mengukur incidence rate dan menggambarkan peta risiko menggunakan geographic information system (GIS). Hasil penelitian ini menunjukkan bahwa berdasarkan incidence rate, kecepatan rata-rata penyebaran skabies pada sapi potong di Kabupaten Barru sebesar 13 kasus per 10000 ekor—tahun. Nilai incidence rate tersebut selalu meningkat setiap tahunnya. Kejadian penyakit paling tinggi terjadi di kecamatan Mallusetasi dengan incidence rate sebesar 35 kasus per 10000 ekor—tahun. Terdapat 2 wilayah yang tergolong ke dalam risiko tinggi, yaitu Kecamatan Mallusetasi dan Kecamatan Tanete Riaja. Tindakan pengendalian yang telah dilakukan belum berhasil dalam mengurangi kecepatan penyebaran penyakit.  Kata kunci: Sapi potong; Incidence rate; Penyebaran; Risiko; Skabies

scholarly journals Geographic information system based malaria risk analysis and mapping in Erer District eastern Ethiopia

2019 ◽  
Author(s):  
Maereg Teklay A Amare ◽  
Gebrehiwot Gebretsadik kassa ◽  
Esie G/wahid Gebre ◽  
Abadi Abay ◽  
Mekonen yimer ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Analytic Hierarchy Process ◽  
Geographic Information ◽  
Malaria Risk ◽  
Analytic Hierarchy ◽  
Risk Areas ◽  
Hazard And Risk ◽  
Temporal And Spatial ◽  
Hierarchy Process

Abstract Background: Erer is one of the districts in Ethiopia where the first malaria transmission season occurs. Although the focus on malaria research has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria hazard and risk in a temporal and spatial perspective. Objective: To characterize and examine the temporal and spatial malaria trend. The research also aims at producing a predictive model of malaria hazard and risk in Erer district. Methods: In this study a cross sectional research design was used. It was carried out through the collection of both quantitative and qualitative data about the nature of malaria and household’s response towards it. A multi-stage sampling method was used and 136 sample size was determined from the sampling frame of 6203 households. Simple descriptive analysis technique was used to determine the malaria trend of the district. Integration of Geographic information system and analytic hierarchy process was used to determine the weight of each factor pair wise comparison and weighted linear combination was used to aggregate and produce the hazard and malaria risk maps. Results: Results have shown that 19.92%, 27.96%, 32.35%, 18.93% and 0.82% of the district was very high, high, moderate, low and very low malaria risk areas respectively. The malaria trend of the area was found to be variable across time with 2014 the peak year while the minimum case observed was in 2016. Conclusion: It is possible to conclude that risk maps are important for estimating the scale of the risk, and enable detection of high risk areas, thus facilitating decision making and policy formulation for enhanced malaria control interventions. Key words: Analytic Hierarchy Process; Malaria risk; Malaria trend; Weighted overlay

Penilaian Risiko Bencana di Sub DAS Amprong Menggunakan Pendekatan GIS

2020 ◽  
Vol 5 (2) ◽  
pp. 107-121
Author(s):  
Listyo Yudha Irawan ◽  
Nabila Nabila ◽  
Damar Panoto ◽  
Agung Chandra Darmansyah ◽  
Annisa Nur Rasyidah ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Irrigation System ◽  
Geographic Information ◽  
Accurate Solution ◽  
Disaster Mitigation ◽  
Landslide Risk ◽  
Residential Areas ◽  
Risk Levels ◽  
Risk Areas

Abstrak: Sub DAS Amprong secara administrasi masuk pada wilayah Kabupaten Malang dan Kota Malang. Meliputi lima Kecamatan yakni: Kedungkandang, Poncokusumo, Tumpang, Pakis dan Jabung. Risiko bencana longsor tergolong tinggi pada kawasan ini. Maka dari itu, penelitian ini bertujuan untuk melakukan pengurangan risiko bencana longsor mengunakan pendeketaan GIS (Geographic Information System). Menggunakan GIS distribusi tingkat risiko akan dapat diketahui dengan baik, sehingga mampu memberikan solusi yang lebih akurat. Penelitian ini meliputi empat tahapan: 1) pemetaan bahaya longsor, 2) pemetaan kerentanan bencana, 3) pemetaan kapasitas bencana, 4) pemetaan risiko bencana. Hasilnya diketahui bahwa kecamatan Jabung dan Poncokusumo merupakan wialayah dengan tingkat risiko longsor paling tinggi. Upaya yang dapat dilakukan untuk mengurangi tingkat risiko dapat dilakukan melalui mitigasi bencana secara struktural dan nonstruktural. Wilayah dengan risiko tinggi bukan merupakan kawasan pemukiman, namun memiliki aktivitas utama berupa pertanian. Oleh karena itu perlu adanya manajemen risiko bencana longsor dalam usaha longsor seperti: dengan cara: 1) pengaturan sistem irigasi dengan baik, 2) penerapan sistem terasering, dan 3) pemasangan bronjong pada kaki lereng. Abstract: Amprong watershed is administratively included in Malang Regency and Malang City. Includes five districts namely: Kedungkandang, Poncokusumo, Tumpang, Pakis and Jabung. The risk of landslides is classified high in this region. Therefore, this research aims to reduce the risk of landslides using GIS (Geographic Information System). Using GIS the distribution of risk levels will be well known, so as to provide a more accurate solution. This research includes four stages: 1) mapping of landslide hazards, 2) mapping of disaster vulnerability, 3) mapping of disaster capacity, 4) mapping of disaster risk. The results are known that the Jabung and Poncokusumo sub-districts are areas with the highest risk of landslides. Efforts that can be made to reduce the level of risk can be done through structural and nonstructural disaster mitigation. High risk areas are not residential areas, but have major activities in the form of agriculture. Therefore, it is necessary to have landslide risk management, such as: by: 1) regulating the irrigation system properly, 2) applying the terracing system, and 3) installing gabions at the foot of the slope.

scholarly journals Multivariate spatio-temporal approach to identify vulnerable localities in dengue risk areas using Geographic Information System (GIS)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gayan P. Withanage ◽  
Malika Gunawardana ◽  
Sameera D. Viswakula ◽  
Krishantha Samaraweera ◽  
Nilmini S. Gunawardena ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
High Risk ◽  
Sri Lanka ◽  
Risk Model ◽  
Early Warning Systems ◽  
Geographic Information ◽  
Distance Functions ◽  
Public Places ◽  
Risk Areas

AbstractDengue is one of the most important vector-borne infection in Sri Lanka currently leading to vast economic and social burden. Neither a vaccine nor drug is still not being practiced, vector controlling is the best approach to control disease transmission in the country. Therefore, early warning systems are imminent requirement. The aim of the study was to develop Geographic Information System (GIS)-based multivariate analysis model to detect risk hotspots of dengue in the Gampaha District, Sri Lanka to control diseases transmission. A risk model and spatial Poisson point process model were developed using separate layers for patient incidence locations, positive breeding containers, roads, total buildings, public places, land use maps and elevation in four high risk areas in the district. Spatial correlations of each study layer with patient incidences was identified using Kernel density and Euclidean distance functions with minimum allowed distance parameter. Output files of risk model indicate that high risk localities are in close proximity to roads and coincide with vegetation coverage while the Poisson model highlighted the proximity of high intensity localities to public places and possibility of artificial reservoirs of dengue. The latter model further indicate that clustering of dengue cases in a radius of approximately 150 m in high risk areas indicating areas need intensive attention in future vector surveillances.

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