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All Journal Jurnal Matematika & Sains The Indonesian Journal of Computer Science
Aditya Purwa Santika
Kelompok Keilmuan Aljabar Fakultas Matematika Dan Ilmu Pengetahuan Alam Institut Teknologi Bandung, Bandung
Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics

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Grup Defect pada Grup PSL(2,3) dan PSL(2,5) Aditya Purwa Santika
Jurnal Matematika & Sains Vol 17, No 1 (2012)
Publisher : Institut Teknologi Bandung

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Abstract

Misalkan p bilangan prima, G grup dengan p membagi orde G dan F lapangan dengan karakteristik p. Aljabar grup atas F adalah ruang vektor dengan basis unsur di G dan dinotasikan sebagai FG. Misalkan B adalah blok dari FG, grup defect bagi B merupakan suatu verteks bagi F(G ´ G)-modul B. Dalam tulisan ini, penulis memberikan contoh perhitungan grup defect dari aljabar grup dengan basis grup PSL(2,3) dan PSL(2,5). Kata kunci: Aljabar grup, Blok, grup Defect, Verteks.   Defect Grup on PSL(2,3) and PSL(2,5) Grups Abstract Let p be a prime, G be a group with p divides the order of G and F be a field with characteristic p. Group algebra over F is a vector space with elements in G as its basis and it is denoted by FG. Let B be a block of FG, a  defect group for B is a vertex of F(G ´ G)-module B. In this paper, we give examples of defect group of group algebras with basis PSL(2,3) and PSL(2,5). Keywords: Group algebra, Block, Defect group, Vertex.
Akurasi Metode Mesin Pembelajaran dalam Analisis Variabel Penting Faktor Risiko Sindrom Down Palit, Oscar Oleta; Dhenanta, Rafi Prayoga; Susanto, Agnes Indarwati; Syawly, Adzky Matla; Ivansyah, Atthar Luqman; Santika, Aditya Purwa; Arifyanto, Mochamad Ikbal; Muttaqien, Fahdzi
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): 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.v13i5.4354

Abstract

This study aims to identify risk factors for Down syndrome using machine learning methods. Data were obtained from an epidemiological case-control study conducted at Special Needs Schools in the cities and regencies of Tangerang. Methods used include Random Forest, K-Nearest Neighbors, Support Vector Machine (SVM), Naive Bayes, K-Means, Artificial Neural Network (ANN), and Multi-Layer Perceptron (MLP). The results indicate that maternal age, paternal age, and the time interval of parents' work before the child's birth are the most influential factors in the incidence of Down syndrome. The SVM method achieved the highest accuracy of 76% with data categorized into two groups and using important variables. In addition to SVM, Naive Bayes and Random Forest methods also demonstrated good performance for analyzing epidemiological data with case-control types.
Polinomial Jacobi dan T-Design untuk Kode Linear Susanto, Agnes Indarwati; Santika, Aditya Purwa
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.v14i3.4614

Abstract

This thesis explores the use of Jacobi polynomials and t-design properties in linear codes. The primary goal of the research is to develop a Python and SageMath program to compute the Jacobi polynomial for linear codes with multiple reference vectors. The methodology involves analyzing self-dual codes over various f ields to derive Jacobi polynomials under specific conditions. The results indicate that the analyzed codes do not satisfy the t-design criteria, as different random reference vectors yield varying Jacobi polynomials. The study offers insights into the relationship between linear codes and Jacobi polynomials, with suggestions for further exploration of more complex codes to meet the t-design criteria.
Dogfight dari Sudut Pandang Teori Permainan Rafi Prayoga Dhenanta; Aditya Purwa Santika
The Indonesian Journal of Computer Science Vol. 14 No. 4 (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.v14i4.4902

Abstract

Dogfight is one of many scenarios happening in a battle for air-superiority. This research delves deeper into dogfight, using the perspectives of game theory. The purpose of this research is to model a strategy that can be used in a dogfight. This research models dogfight into game theory’s extensive-form-games and then simulates the model ccompuationally. From the simulation, the model developed in this research increases the winning rate of a certain player significantly.
Co-Authors Arifyanto, Mochamad Ikbal Atthar Luqman Ivansyah Dhenanta, Rafi Prayoga Muttaqien, Fahdzi Palit, Oscar Oleta Rafi Prayoga Dhenanta Susanto, Agnes Indarwati Syawly, Adzky Matla