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All Journal The Indonesian Journal of Computer Science Jurnal Pengabdian Dian Mandala Journal of New Trends in Sciences
Mohamad Sofie
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Public Health

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A Klasifikasi Penyakit Tumor Ginjal Menggunakan SVM dengan Ekstraksi Ciri HOG dan GLCM Affandy, Muhammad Eric; Mohamad Sofie; Muhammad Rofi’i
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4882

Abstract

Early detection of kidney tumors is essential to increase the chances of a patient's recovery. This study aims to develop a classification system for kidney CT scan images to distinguish between normal kidneys and kidneys containing tumors. The classification method used is Support Vector Machine (SVM) with three types of kernels, namely linear, polynomial, and radial basis function (RBF). Previously, feature extraction was performed using two approaches, namely Histogram of Oriented Gradients (HOG) to obtain shape values, and Gray Level Co-occurrence Matrix (GLCM) to obtain texture characteristics of the image. The test results show that SVM with a linear kernel gives the highest accuracy of 90%, followed by polynomial at 85%, while the RBF kernel only reaches 50%. Based on these results, it can be concluded that the combination of HOG and GLCM feature extraction followed by classification using linear kernel SVM is effective for distinguishing normal kidney images and kidney tumors. This research makes a positive contribution to the development of a medical image-based kidney disease diagnosis support system.
Analisis Statistika Multivariat untuk Menilai Keterkaitan Gaya Hidup Digital dengan Tingkat Stres Mahasiswa Rusliadi Rusliadi; Mohamad Sofie
Jurnal Pengabdian Dian Mandala Vol. 3 No. 1 (2025): June : Jurnal Pengabdian Dian Mandala
Publisher : STP Dian Mandala Gunungsitoli Nias Keuskupan Sibolga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62200/jpdm.v3i1.226

Abstract

Digital lifestyle has become an integral part of university students' daily lives, involving the use of social media, digital devices, and digital content consumption. The development of digital technology has positive impacts, facilitating easy access to information and social interactions. However, excessive use can lead to digital stress, which negatively affects students' mental health. This study aims to identify the key factors influencing students' digital lifestyles and analyze their relationship with stress levels. A quantitative approach with a survey method was employed, using a questionnaire to measure digital lifestyle, including social media usage frequency and digital device interaction duration, along with the Perceived Stress Scale (PSS) to measure students' stress levels. The factor analysis results show that social media usage and prolonged interaction with digital devices are significant factors contributing to students' stress. Furthermore, sleep disturbances and social anxiety were identified as other significant factors associated with increased stress. The multivariate regression analysis confirmed that students who spent more time on social media reported higher stress levels, associated with social anxiety and sleep disturbances caused by digital addiction. This study suggests the importance of managing digital device usage and raising students' awareness of the negative impacts of excessive social media use. The findings imply the need for support from universities and mental health organizations to provide interventions that help students manage their digital lifestyles, reduce stress, and improve their mental well-being.
Analisis Statistika Multivariat untuk Menilai Keterkaitan Gaya Hidup Digital dengan Tingkat Stres Mahasiswa Rusliadi Rusliadi; Mohamad Sofie
Journal of New Trends in Sciences Vol. 3 No. 1 (2025): Journal of New Trends in Sciences
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jnts.v3i1.750

Abstract

Digital lifestyle has become an integral part of university students' daily lives, involving the use of social media, digital devices, and digital content consumption. The development of digital technology has positive impacts, facilitating easy access to information and social interactions. However, excessive use can lead to digital stress, which negatively affects students' mental health. This study aims to identify the key factors influencing students' digital lifestyles and analyze their relationship with stress levels. A quantitative approach with a survey method was employed, using a questionnaire to measure digital lifestyle, including social media usage frequency and digital device interaction duration, along with the Perceived Stress Scale (PSS) to measure students' stress levels. The factor analysis results show that social media usage and prolonged interaction with digital devices are significant factors contributing to students' stress. Furthermore, sleep disturbances and social anxiety were identified as other significant factors associated with increased stress. The multivariate regression analysis confirmed that students who spent more time on social media reported higher stress levels, associated with social anxiety and sleep disturbances caused by digital addiction. This study suggests the importance of managing digital device usage and raising students' awareness of the negative impacts of excessive social media use. The findings imply the need for support from universities and mental health organizations to provide interventions that help students manage their digital lifestyles, reduce stress, and improve their mental well-being.
Co-Authors Affandy, Muhammad Eric Muhammad Rofi’i Rusliadi Rusliadi