2 research outputs found

    Analysis of the Timeliness of Graduation of FMIPA College KIP Students at Bengkulu University Using Binary Logistic Regression

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    Previous studies that discuss the timeliness of graduating students are generally more focused on the student population as a whole, without considering the influence of specific scholarship programs such as KIP Kuliah. This study aims to obtain a model of the timeliness of student graduation and obtain factors that affect the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University using the Binary Logistic Regression method. The results of this study are expected to provide valuable information for KIP Kuliah managers of Bengkulu University in improving the effectiveness of the KIP Kuliah scholarship program and helping KIP Kuliah students of FMIPA Bengkulu University to graduate on time. In this study, Binary Logistic Regression method is used because the response variable has a nominal binary scale. Based on the results of the discussion of the research conducted, a Binary Logistic Regression model of the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University is obtained with factors that have a significant influence on the timeliness of graduating KIP Kuliah students of FMIPA Bengkulu University is the origin of the S1-Physics, S1-Biology and S1-Statistics study programs and GPA. Then the classification results using Binary Logistic Regression have a classification accuracy rate of 77.97%. So it can be concluded that the classification of the timeliness of graduating students of FMIPA Bengkulu University in the Binary Logistic Regression model is good enough

    Earthquake Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region: Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region

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    Earthquakes are natural events whose time and place cannot be predicted. Ambon is the largest city in the Maluku Islands region and is the center of development and the capital of Maluku Province. This research will group earthquake events, analyze the characteristics of earthquake events, create earthquake zones and map them using CLARA cluster analysis, and create modeling that will look at the risk of earthquake events in a location based on distance to faults and subduction zones using the Inhomogeneous Neyman-Scott Cox Process. The data used is data on earthquake events in the Ambon region obtained from the United States Geological Survey (USGS) catalog from January 1926 to December 2022, with a depth of ≤360.1 Km and a magnitude of ≥4 Mw. Grouping earthquake events in the Ambon area using CLARA cluster analysis obtained 2 groups of earthquake clusters with an optimal silhouette score of 0.7430. The model obtained in this earthquake research is not good because it is based on the K-function value plot of the original data which is far from the modeling K-function value plot
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