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Journal : Operations Research: International Conference Series

Distribution of Spread and Characteristics of Confirmed Covid-19 based on Spatial Autocorrelation in Manado Pontoh, Sophia Olga; Weku, Winsy; Hatidja, Djoni
Operations Research: International Conference Series Vol. 3 No. 1 (2022): Operations Research International Conference Series (ORICS), March 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i1.128

Abstract

Covid-19 is a collection of viruses that attack the respiratory system. This virus spread quickly and spread to other regions in China and most countries in the world, including Indonesia. North Sulawesi Province, especially Manado City is one of the cities in Indonesia that has been affected by Covid-19. The highest confirmed Covid-19 cases in Manado City are in the Malalayang, Mapanget, and Wanea villages which are geographically not adjacent/neighboring. This study aims to analyze the spatial distribution of Covid-19 cases and their characteristics. This study uses significant data on Covid-19 cases in every village in Manado City, where there are 86 villages (Malayang Satu Barat Village and Malalayang Satu Timur Village combined), and the focus of this research is on the confirmed variables, with the latest data update is October 21, 2021. The effect of covid-19 between observation locations is accomplished using Moran's I, and the weighting matrix used is the Euclidean distance matrix. The Moran's Index provides an overview of the spatial relevance of the Covid-19 case data in every village in Manado City and specifically the spatial attachment of every village will be explained by the Local Moran's I value (LISA). The results of this study found that there is a spatial autocorrelation found using the Euclidean distance matrix. A spatial correlogram of 30 meters is used as the maximum geographical distance limit for being infected with Covid-19. The Moran's Index value of the Covid-19 case in Manado City is 0.348, meaning that there is a positive autocorrelation between the villages. There are thirteen villages that affect the spread of Covid-19 in Manado City, namely Malalayang Satu Timur dan Barat, Malalayang Satu, Winangun Satu, Kleak, Karombasan Utara, Ranotana Weru, Bumi Nyiur, Pakowa, Tinkulu, Taas, Paal Empat, Tikala Baru, and Paniki Dua.
Performance Comparison of Covariance Function to Interpolate Unsampled Points with Simulation Data in Manado City Soleman, Claudya; Weku, Winsy; Salaki, Deiby
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.169

Abstract

The covariance function measures the strength of statistical correlation as a function of distance. This follows Tobler's law which states that everything is usually related to all else but those which are near to each other are more related when compared to those that are further away. The correct weight of the basic covariance structure will produce the optimal kriging predictor. One interesting way to evaluate the strength of a kriging interpolation is to perform a simulation using a spatial structure. The simulation technique is executed in Manado City. The data is then applied to the variogram model using the spherical and matern covariance functions. The type of kriging method used in this simulation is ordinary kriging. The result shows that the suitable model to use is the matern model. Residual results from cross-validation show that the matern model has a lower biased estimation on both data. According to the RMSE and MAE criteria, the matern model outperforms the spherical model on data A and data B. The results of the interpolation are then visualized in the form of a map. Through this research, it can be concluded that the accuracy of the selection of the covariance function in the variogram model will provide a good estimate for the kriging method, and the most appropriate model for this case is the matern model.
Analysis of Changes in Green Land Cover of North Minahasa Gold Mine With Landsat 8 Images using the Normalized Difference Vegetation Index Bahat, Feni; Weku, Winsy; Montolalu, Chriestie
Operations Research: International Conference Series Vol. 2 No. 4 (2021): Operations Research International Conference Series (ORICS), December 2021
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v2i4.182

Abstract

Mining is an activity of extracting non-renewable natural resources, including coal, whose management cannot be separated from the company. In realizing mining activities, they must be managed optimally, so it is necessary to supervise and monitor their activities effectively and efficiently. North Minahasa Mining Toka Tindung is a gold mine that has been operating since 2009, with the first gold production in 2011, and has gold reserves of 122 tons at the end of 2020. Toka Tindung has a mining area of 8,986 hectares (400 thousand square km), or 1.3 percent of the planned contract of work which is 741,000 hectares. This research was conducted by monitoring mining land cover using remote sensing technology based on Landsat 8 satellite imagery. related to vegetation. NDVI has a range of values between -1 to +1, the results of the transformation have different percentages of land use. The greater or positive the NDVI value, the better the vegetation density in the area. This study aims to analyze changes in green land cover in the mining area of North Minahasa in 2013 to 2021 based on variations in the greenness of the vegetation index. The results of the study obtained that Variations in the greenery index of vegetation ranged from 0.0 - 0.4 in 2013 and -0.2 - 0.6 in 2021. Where the mining area environment in 2013 had a vegetation class in the form of rocks, vacant land, meadows, shrubs and dense forests and in 2021 had a vegetation class in the form of rocks, vacant land, grasslands, shrubs, dense forests and water. In 2021 it has a vegetation value of -0.2 whose vegetation class is water due to the loss of Ground Cover Vegetation due to digging too deep to form ponds. on the ground surface. Thus the level of vegetation density in the mining area of North Minahasa has changed from 2013 to 2021. The area without vegetation has generally increased. Replacing the green area and the area with vegetation cover, dense green land cover has decreased.