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All Journal Journal of Creative Student Research Student Research Journal Journal of Computer Science Advancements
Willy Pramudia Ananta
Universitas Negeri Medan
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Transportation

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Klasifikasi Tumor Otak Menggunakan Local Binary Pattern dan SVM Classifier Wahyu Ardiantito S; Stacyana Jesika Surianto; Suci Ramadhani; Willy Pramudia Ananta
Student Research Journal Vol. 1 No. 6 (2023): Desember : Student Research Journal
Publisher : Sekolah Tinggi Ilmu Administrasi (STIA) Yappi Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/srjyappi.v1i6.823

Abstract

Brain tumors are abnormal cell growths in brain tissue that can be life-threatening. This study aims to classify brain tumors to help early diagnosis. The method used is to extract features from brain MRI images using Local Binary Pattern (LBP) and then classified with Support Vector Machine (SVM). The data used were 2044 brain MRI images consisting of 3 classes namely meningioma, no tumor, and pituitary. The best results were obtained using LBP with a radius of 1 and the number of neighbors 8, while the best SVM model used the RBF kernel with a C value of 50, resulting in 88% accuracy, 86% precision, and 87% recall. It can be concluded that the combination of LBP and SVM methods is effective enough to classify brain tumor types to support early diagnosis.
Website-Based Employee Attendance Information System (Case Study: PT. Excelindo Karya Abadi) Shabrina Husna Batubara; Willy Pramudia Ananta; Zulfahmi Indra
Journal of Computer Science Advancements Vol. 2 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i3.1106

Abstract

This research aims to develop a web-based employee attendance information system at PT. Excelindo Karya Abadi, overcoming inefficiencies in the manual attendance process. Using the Waterfall method, this research includes the stages of needs analysis, system design, implementation, testing, and maintenance. Data collection is carried out through interviews and direct observation so that it becomes the basis of a system that includes the function of recording attendance via selfie photos, managing employee data, and making reports. The system architecture is designed with front-end and back-end components, using technologies such as HTML, CSS, JavaScript, PHP, and MySQL. Testing involves black box techniques to ensure functionality and user feedback for system improvement. The implemented system demonstrated significant improvements in the accuracy and efficiency of attendance tracking, reducing the potential for data manipulation and errors. The transition to a web-based system allows for greater accessibility and integration with an organization's existing systems, thereby contributing to increased operational efficiency. The findings show that digital attendance systems can simplify administrative processes substantially, offer reliable solutions for employee attendance management, and align with technological advances to support company growth.
Analisis Prediksi Harga Rumah di Bandung Menggunakan Regresi Linear Berganda Rafif Nauval Tuah Siregar; Vijay Sitorus; Willy Pramudia Ananta
Journal of Creative Student Research Vol. 1 No. 6 (2023): Desember : Journal of Creative Student Research
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jcsrpolitama.v1i6.3038

Abstract

This research aims to develop a model for estimating house prices in the Bandung area using the Multiple Linear Regression approach. House prices play a significant role in the decision-making process for purchases. The ability of this model to predict house prices with high accuracy provides significant benefits for potential buyers, sellers, and various stakeholders in the housing industry. Data on house prices and potential variables such as land area, building area, number of bedrooms, nearby facilities, and geographical location were collected for analysis. The use of Multiple Linear Regression allows for a deeper understanding of the relationships between these variables and the value of the house. The analysis results show a strong correlation between these variables and house prices in Bandung. The developed Multiple Linear Regression model can provide satisfactory predictions of house prices. This model can be used as a tool for both homebuyers and sellers to determine fair prices and assist property developers in identifying key factors influencing house prices in the Bandung region.
Co-Authors Rafif Nauval Tuah Siregar Shabrina Husna Batubara Stacyana Jesika Surianto Suci Ramadhani Vijay Sitorus Wahyu Ardiantito S Zulfahmi Indra, Zulfahmi