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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 3 No 2 (2022): Tensor: Pure and Applied Mathematics Journal" : 6 Documents clear
ICOR Analysis on Inequality in Maluku Development Jefri Tipka
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp57-64

Abstract

The geographical condition of Maluku Province, which is in the form of an archipelago and the uneven distribution of investment, is one of the causes of the development inequality among regions in Maluku Province. Investment as measured by using ICOR can help to see efficiency in investment activities, so this research aims to see the role of investment in relation to equitable development during the 2011-2020 period in Maluku Province. The Linear Regression Method is used to measure how much influence the investment has on the level of unemployment in Maluku Province. The results show that investment is very influential on reducing inequality and helping equality development in Maluku Province. This finding serves as input for the government that until 2020, development inequality still occurs in Maluku Province.
Combined Model Time Series Regression – ARIMA on Stocks Prices Desi Desi; Setyo Wira Rizki; Yundari Yundari
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp65-72

Abstract

Stock price data tend to experience a linear trend and fluctuate over time. So that forecasting is needed to predict stock prices in the next period. The nature of the linear trend can be modeled by linear time series regression and ARIMA. The purpose of this study is to form a combined model time series regression linear – ARIMA and predict stock prices using the combined mode time series regression linear – ARIMA. Combining two models can increase the level of forecasting accuracy compared to using separate models. The data used is the daily closing price of PT Unilever Indonesia Tbk for the period January 4, 2021 to December 30, 2021. The data forms a trend pattern that tends to be linear. The data is divided into in sample and out sample data with a proportion of 80:20. The model time series regression linear is formed by regressing the trend variable and stock closing price variable. From the model time series regression, the residual value is sought that will be used to form the ARIMA model. The model time series regression linear is then combined with the ARIMA model, where the model formed is a combined model time series regression linear – ARIMA (0,1,1) with the MAPE is 1.349906%. The results of PT Unilever Tbk’s stock price forecasting for the period January 3, 2022 to January 21, 2022, continued to decline. The highest forecasting results occurred on January 3, 2022, amounting to 4,091.253. While the lowest forecasting results occurred on January 21, 2022, which amounted to 3,827.192.
Analisis Pendapatan Menggunakan Metode Weighted Least Square (Wls) dengan Fungsi Pembobot Huber Jefri Radjabaycolle; Abraham Z Wattimena; Indriana Umul Mu'minin; Gabriela Haumahu
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp101-110

Abstract

The Weighted Least Square (WLS) method is a development of the OLS method which will provide a more accurate solution than the OLS method when outliers are identified in the data. It is possible that the model generated by the OLS method still contains outliers, while the WLS method minimizes outliers in the data. The income result determined using the OLS method is less than the income result using the WLS method, which means that if a fixed value is given (according to the standard) for each result of the factors that affect the income result in the OLS method, the average fisherman income is IDR 2,225 .220. While the average income of fishermen using the WLS method is Rp. 1,015,840. There were two outliers identified using the OLS method and after using the WLS method there were no outliers.
Grasshopper Optimizaton Algorithm (GOA) untuk Menyelesaikan Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) Anatasia Naomi; Asri Bekti Pratiwi; Herry Suprajitno
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp73-84

Abstract

The purpose of this paper is to solve the Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) using the Grasshopper Optimization Algorithm (GOA). Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) is a problem of forming routes that serve each customer, by delivering and retrieving simultaneously. The purpose of VRPSPD is to minimize the total mileage to serve all customers with the limit that each customer is served exactly once, and the vehicle load does not exceed its maximum capacity. Grasshopper Optimization Algorithm (GOA) is an algorithm inspired by nature by mimicking the living behavior of grasshopper swarms in search of food sources. GOA has several main stages, namely initialization of parameters, determination of target grasshoppers, calculating the coefficient of decline, calculating the distance between grasshoppers, and calculating the new position of the grasshoppers. Implementation of the GOA program to complete VRPSPD using the C++ programming language using 3 types of data, data with 13 customers, 22 customers, and 100 customers. Based on the results of the running program, it can be concluded that the more iterations and the number of populations, the solution obtained tends to be better.
Extension Field Which Are Galois Extensions Novita Dahoklory; Henry Willyam Michel Patty
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp85-92

Abstract

Solusi Numerik Model Sir Dengan Menggunakan Metode Runge-Kutta Orde Empat Dalam Prediksi Penyebaran Virus Covid-19 Di Provinsi Maluku Monalisa Rijoly; Rizki F. Muin; Francis Y. Rumlawang; Berny Pebo Tomasouw
Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): 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/tensorvol3iss2pp93-100

Abstract

Penelitian ini bertujuan untuk memprediksi penyebaran virus Covid-19 di Provinsi Maluku menggunakan metode Runge-Kutta orde empat. Model matematika penyebaran virus Covid-19 berbentuk sistem persamaan diferensial yang mencakup variabel Susceptible (S) yaitu populasi manusia yang rentan terinveksi virus Covid-19, Infectious (I) yaitu populasi manusia yang telah terinveksi virus Covid-19 dan Recovered (R) yaitu populasi manusia yang sudah sembuh atau yang sudah kebal terhadap virus Covid-19, yang digunakan sebagai nilai awal. Nilai sebagai nilai parameter yang diselesaikan secara numerik menggunakan metode Runge-Kutta orde empat yang dilakukan sebanyak 20 iterasi dengan waktu interval bulan menggunakan data dari Dinas Kesehatan Provinsi Maluku dan Polda Maluku tahun 2020 sampai 2021. Berdasarkan data yang diperoleh maka nilai rata-rata dari data tersebut yang digunakan sebagai nilai awal dimana , , . Nilai awal dan nilai parameter disubstitusikan kedalam solusi numerik dan disimulasikan menggunakan dan Matlab sebagai alat bantu. Nilai laju setiap kelas untuk 20 bulan kedepan yaitu untuk laju kelas individu rentan (S) sebesar 69.270 jiwa, untuk laju kelas individu terinfeksi (I) sebesar 19.167 jiwa dan untuk laju kelas individu sembuh (R) sebesar 851 jiwa. Ini berarti bahwa untuk populasi (S) dan (I) akan mengalami penurunan untuk 20 bulan kedepan sedangkan untuk populasi (R) akan mengalami kenaikan pada 20 bulan kedepan.

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