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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 2 (2020): Tensor : Pure And Applied Mathematics Journal" : 6 Documents clear
Ideal Dalam Semigrup Ternari Komutatif Noverly Cloren Pattinasarany
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp77-82

Abstract

Algebra is a branch of mathematics that deals with mathematical objects (say, numbers with no known exact value), and uses symbols such as x and y to study them. In algebra, the properties possessed by the operations that can be performed on the object (think addition and multiplication) are studied, and then become "weapons" when we are faced with a problem related to that object. In the structure of algebra, there are many theories such as groups, abelian groups, and semigroups. In semigroups only use binary operations, this makes researchers want to make research on semigroups using ternary surgery, the ideal structure in semigroup commutative ternary. So that we can find out the ideal structure in semigroup commutative fingers.
Neural Network on Tsunami Waves Prediction Detector Tools Using Tectonic Earthquakes Data Meta Kallista
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp47-56

Abstract

On 26 December 2004, tsunami waves were generated by undersea megathrust earthquakes particularly hit the Banda Aceh-Indonesia, also Thailand, Sri Lanka, India. The effect of tsunami waves can be very damaging to the coastal areas even more to the land around the coast. It is very interesting to study the relation between the magnitude of the undersea earthquakes and the tsunami. Therefore, we construct an early warning system using Neural Network to predict the tsunami using data from Indonesian Meteorology, Climatology, and Geophysical Agency that integrated with a hardware tool. The hardware tools will show the prediction result and send a short message.
Prediksi Indeks Harga Konsumen (IHK) Kota Ambon Menggunakan Elman Recurrent Neural Network (ERNN) Jefri Radjabaycolle
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp65-75

Abstract

Indeks Harga Konsumen (IHK) is an economic indicator that can provide information on developments and changes in the prices of goods and services that are predominantly consumed by the public within a certain period of time. In this study the method to be used is the Elman Recurrent Neural Network (ERNN). The research data uses Ambon City IHK data from 2016 to 2019. The data used as research objects are: Food, Beverages, Cigarettes and Tobacco, Housing, Water, Electricity, Gas and Fuel, Clothing, Health, Education, Recreation, and Sport, Transportation, Communication and Financial Services as input variables. The results of training with 5 hidden layers at a maximum epoch of 100,000 obtained the smallest MAPE value of 1.1773. Then the results of testing using the parameters in the experiment on the number of hidden layer neurons 20 obtained the smallest MAPE value of 0.461823.
Pengaruh Ekstrapolasi Richardson Terhadap Keakuratan Solusi Numerik Persamaan Konduksi Panas rofila el maghfiroh
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp57-63

Abstract

The heat conduction equation is a parabolic differential equation and a type of second-order linear partial differential equation. By applying the finite difference scheme in the Crank-Nicolson method, the numerical solution of the heat conduction equation can be calculated. Obtaining numerical solutions with a high level of accuracy, Richardson extrapolation is required. The Crank-Nicolson approach scheme has a high level of accuracy, because the gap between numerical and analytical solutions is very small. Richardson extrapolation greatly influences the accuracy of numerical solutions, because the gap between analytical solution and numerical solutions with Richardson extrapolation is smaller than disparity in numerical solutions without Richardson extrapolation.
Analisis Prediksi Okupansi Jumlah Penumpang Kereta Api dengan Metode Support Vector Regression dan Gaussian Process Regression (Studi Kasus: Kereta Api Argo Parahyangan) Meta Kallista
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp83-92

Abstract

SVR (support vector regression) dan GPR (gaussian process regression) adalah beberapa metode di dalam pembelajaran mesin yang sering digunakan untuk mengakomodasi masalah regresi. SVR dan GPR memiliki keunggulan dibandingkan menggunakan fungsi regresi biasa. Kedua metode ini merupakan model pembelajaran mesin non-deep learning, dimana model pembelajarannya dibangun dengan menggunakan fungsi matematis. Sebagai studi kasus, di dalam makalah diteliti tentang prediksi okupansi penumpang Kereta Api Argo Parahyangan yang dioperasikan oleh PT Kereta Api Indonesia (Persero) untuk melayani lintas kota Bandung–Gambir dan sebaliknya. Penelitian dilakukan dengan menggunakan data berupa jumlah penumpang per hari selama satu tahun pada kelas ekonomi dan kelas eksekutif Kereta Api Argo Parahyangan. Skenario pengujian dilakukan dengan membandingkan antara rata-rata error kuadratik (RMSE) antara prediksi dan target pelatihan dengan metode SVR dan GPR.
Perbandingan Hasil Pengelompokan Menggunakan Metode Self Organizing Maps dan Metode Average Linkage (Studi Kasus: Data PDRB tiap provinsi di Indonesia) Gabriella Haumahu
Tensor: Pure and Applied Mathematics Journal Vol 1 No 2 (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/tensorvol1iss2pp93-99

Abstract

Gross domestic regional product (GDRP) is one of important indicators that can be used to determine economic conditions in some areas. This makes GDRP is very interesting to be studied. In this paper we cluster 33 provinces in Indonesia based on GDRP in 2013. We use self organizing and average linkage method of cluster analysis to investigate it. We also compare the results of both methods. We found that Average linkage method has better performance than self organizing method because it has smaller rasio.

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