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Harmanus Batkunde
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Jurusan Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Unversitas Pattimura Jln. Ir. M. Putuhena, Kampus Unpatti, Poka - Ambon 97233, Provinsi Maluku, Indonesia
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Tensor: Pure and Applied Mathematics Journal
Published by Universitas Pattimura
ISSN : 27230325     EISSN : 27230333     DOI : -
Core Subject : Science, Education,
Computer Science & IT Mathematics
Tensor: Pure and Applied Mathematics Journal is an international academic open access journal that gains a foothold in the field of mathematics and its applications which is issued twice a year. The focus is to publish original research and review articles on all aspects of both pure and applied Mathematics. It Publishes original research papers of the highest Algebra Analysis Discrete Mathematics Geometry Number Theory Topology Applied Mathematics Computational Mathematics Probability Theory and Statistics
Arjuna Subject : Matematika - Matematika Terapan
Articles 6 Documents
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Search results for , issue "Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal" : 6 Documents clear
Analisis Stabilitas dan Simulasi Model Penyebaran Penyakit HIV/AIDS Tipe SIA (Susceptible, Infected, Abstained) Zeth Arthur Leleury; Francis Yunito Rumlawang; Alva Grace Naraha
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp31-40

Abstract

HIV/AIDS is a disease that continues to grow and become a global problem that requires special attention. This can be seen from the high number of cases of HIV/AIDS every year. In this study, we discussed an analysis of stability of a point equilibrium and numerical simulation for the spread of HIV/AIDS. The mathematical models that we used is SIA (Susceptibles, Infected, Abstained) model. The model of SIA assumed that sub populations infected will increase because of the influence of the transmission rate sub populations infected to sub population susceptibles. However, mode of transmission of HIV is possible if the transmission of individual of sub populations abstained to individual of sub population susceptibles. The result of the model indicate that population growth rate is determined by theese parameters: birth, death, interaction and isolation. Based on the result of the model simulation showed that the impact of the sub populations abstained would affect so reduced sub population infected.
Fixed Point Theorem in 2-Normed Spaces Francis Yunito Rumlawang
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp41-46

Abstract

In this paper we prove a fixed point theorem in a complete 2-normed Spaces. We define a norm derived from 2-norm. To get the theorem proved we first study some convergent and Cauchy sequences, and contractive mappings in 2-normed spaces.
On H-Irregularity Strength of Grid Graphs Meilin Imelda Tilukay
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp1-6

Abstract

This paper deals with three graph characteristics related to graph covering named the (vertex, edge, and total, resp.) –irregularity strength of a graph admitting -covering. Those are the minimum values of positive integer such that has an -irregular (vertex, edge, and total, resp.) -labeling. The exact values of this three graph characteristics are determined for grid graph admitting grid-covering,
Algoritma Multi-Kelas Twin Bounded SVM Untuk Klasifikasi Pola Berny Pebo Tomasouw; Zeth Arthur Leleury
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp15-24

Abstract

Pattern recognition is a process of recognizing patterns by using machine learning algorithm. Pattern recognition can be defined as a classification of data based on knowledge that already gained or information extracted from patterns. One method that can be used in pattern classification problem is SVM. In this study we introduced Twin Bounded SVM which is refinement of Twin SVM. The discussion begins with the linear Twin Bounded SVM method to solve a two-class classification problem and followed by an algorithm to solve multi-class classification problem
Penyelesaian Numerik Persamaan Diferensial Orde Dua Dengan Metode Runge-Kutta Orde Empat Pada Rangkaian Listrik Seri LC Monalisa E Rijoly; Francis Yunito Rumlawang
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp7-14

Abstract

One alternative to solve second order differential equations by numerical methods, specificallynon-liner differential equations is the Runge-Kutta fourth order method. The Runge-Kutta fourth ordermethod is a numerical method that has high degree of precision and accuracy when compared to othernumerical methods. In this paper we will discuss the numerical solution of second order differentialequations on LC series circuit problem using the Runge-Kutta fourth order method. The numericalsolution generated by the computational calculation using the MATLAB program, the strong current andcharge are obtaind from t = 0 and t =0,5 second and different step size values
Penerapan Jaringan Saraf Tiruan Learning Vector Quantization Untuk Pemetaan Wilayah Berpenduduk Miskin di Provinsi Maluku Dorteus Lodewyik Rahakbauw; Venn Yan Ishak Ilwaru
Tensor: Pure and Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol1iss1pp25-30

Abstract

Badan Pusat Statistik (BPS) stated that the number of poor people in Indonesia reached 28.01 million people based on data as of March 2016. This figure is around 10.86 percent of the national population. Province of Maluku as the third poor contributor of all provinces in Indonesia reached 27.74 percent. Note that, there are 8 of total 11 districts/cities in Maluku which are determined as underdeveloped regions (Kementerian PDT, 2015), Maluku Barat Daya (MBD) is one of them. Based on data from BPS, in 2014 the percentage of poor people in district of MBD reached 28.33 percent being the second highest district in Maluku after Maluku Tenggara Barat (MTB). It is quite difficult make the poverty level of MBD lower, due to a large number of villages in MBD have some economic access isolations because of geographical conditions. Various programs and policies in social and health have been done to solve this poverty problem, but still could not overcome this problem yet. In this paper we have grouped the districts/cities of Maluku based on poverty factors using Learning Vector Quantization (LVQ) method. The results of this research showed that there are 5 poverty clusters in Maluku. Those are: Cluster 1 consists of Maluku Tenggara Barat, Maluku Utara dan Buru; cluster 2 consists of Maluku Tengah; cluster 3 consists of Kep. Aru, Seram Bagian Barat dan Seram Bagian Timur, cluster 4 consists of Maluku Barat Daya dan Buru Selatan; and cluster 5 consists of Ambon and Tual. Each cluster describes the poverty level with respect to its Partition matrix respectively. The results that we obtained also show that cluster 4 has the highest poverty level.

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