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All Journal Journal La Multiapp Bigint Computing Journal
Sephia, Putri Aisyah
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering

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Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method Sephia, Putri Aisyah; Zufria, Ilka
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1523

Abstract

This research aims to analyze public sentiment towards supporting the DPR's right to inquiry in the 2024 Election fraud issue using the Support Vector Machine (SVM) method. Data was obtained from the social media application X which has a wide user base and is relevant to the issue under study. Comments on the application are classified into positive and negative sentiments after going through the pre-processing stage. The SVM method was chosen because of its high ability in text classification based on appropriate kernels. This research shows how much influence the X application has in identifying public sentiment and the effectiveness of the SVM method in sentiment classification. It is hoped that the research results will provide in-depth insight into public sentiment regarding the issue of fraud in the 2024 elections and support better decision making in the context of politics and democracy in Indonesia.
Development of Image Processing to Visualize Car Dimensions Using Matlab Software Julianti, Miranda; Purba, Ony Hizri Kaifa; Sephia, Putri Aisyah
Bigint Computing Journal Vol 1 No 2 (2023)
Publisher : Ali Institute of Reseach and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/bigint.v1i2.782

Abstract

In an era of increasingly advanced technology, the development of image processing techniques has become important in various fields, including the automotive industry. One important aspect in the automotive industry is understanding and visualizing car dimensions with high accuracy. In this research, we propose the development of image processing techniques using MATLAB software to visualize car dimensions. The proposed method involves a series of image processing steps, including car object segmentation, binary image, and image editing. First, the car image is imported into MATLAB software and converted into a grayscale image. Next, segmentation of the car object is carried out using an appropriate threshold technique. Next, the feature extraction results are used to visualize the dimensions of the car. This visualization can be in the form of a 2D diagram that displays the dimensions of the car proportionally, or a 3D model that shows a three-dimensional view of the car. Through this visualization, users can easily see and understand the dimensions of the car without the need for complicated manual measurements.
Co-Authors Ilka Zufria Julianti, Miranda Purba, Ony Hizri Kaifa