Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal OKTAL : Jurnal Ilmu Komputer dan Sains AMMA : Jurnal Pengabdian Masyarakat
Alessandro
Unknown Affiliation
Humanities Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Klasifikasi Penyakit Menular Dengan Algoritma Machine Learning Berbasis SVM Alessandro; Alfinsa Pratama; Azzani Nurfadia Rizky; Elyananda Subroto
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 10 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Infectious diseases pose a serious threat to public health, especially with their rapid spread and the difficulty of detecting early symptoms in some cases. Accurate classification of infectious diseases is essential to support early diagnosis and appropriate treatment. In this research, a machine learning algorithm based on Support Vector Machine (SVM) was used to classify types of infectious diseases. This method was chosen because of its ability to handle complex datasets and produce good classification, especially on data with non-linear patterns. This research uses infectious disease datasets from trusted sources which are processed using the Knowledge Discovery in Databases (KDD) method for extracting relevant features. Several SVM kernels, namely linear, radial basis function (RBF), sigmoid, and polynomial, were evaluated to determine the most optimal kernel in increasing classification accuracy. The aim of this research is to identify the most effective method in predicting infectious diseases, so that it can be applied in decision support systems in the health sector. The research results show that the polynomial kernel provides the highest accuracy compared to other kernels, with an accuracy level reaching 75%. With these results, it is hoped that the SVM-based classification model ca be a solution in identifying and treating infectious diseases more efficiently.
Sosialisasi Keamanan Digital: Peningkatan Kesadaran Pemuda Karang Taruna 'Cipta Karya' Terhadap Ancaman Siber Dan Perlindungan Diri Di Dunia Maya Alessandro; Diaz Setyadi, Alvin; Ghani S, Altaf; N E, Fransiskus; Dabit H A, Muhammad; Fauzan Rusby K, Muhamad; Maulana, Noufal; W P, Ryandanu; Alifio, Sadam; Ahda S M, Januardy; Susanto, Riky
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 11 : Desember (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Community Service (PKM) activity with the theme "Digital Security Socialization: Increasing Awareness of Youth of Karang Taruna 'Cipta Karya' towards Cyber ​​Threats and Self-Protection in Cyberspace" was carried out by a team of Pamulang University students in Rancagong Village, Legok District, Tangerang Regency, Banten, on November 10, 2024. This program aims to increase public understanding and awareness, especially Karang Taruna youth, regarding cyber threats and digital protection measures. This activity includes delivering educational materials on types of cyber threats such as hacking, online fraud, and data theft, as well as basic techniques for protecting personal information. In addition to delivering the material, interactive sessions in the form of questions and answers and quizzes were also held to encourage active involvement of participants. The results of this activity showed that participants gained a better understanding of the importance of maintaining digital security and were motivated to apply this knowledge in their daily lives. In closing, souvenirs were given to partners as a form of appreciation for their support for this program. This program is expected to continue in the future to reach more communities, so that the younger generation is better prepared to face the challenges of the digital era wisely and safely.
Co-Authors Ahda S M, Januardy Alfinsa Pratama Alifio, Sadam Azzani Nurfadia Rizky Dabit H A, Muhammad Diaz Setyadi, Alvin Elyananda Subroto Fauzan Rusby K, Muhamad Ghani S, Altaf Maulana, Noufal N E, Fransiskus Riky Susanto, Riky W P, Ryandanu