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Harmanus Batkunde
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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 66 Documents
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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.
Proper Inclusion Between Vanishing Morrey Spaces and Morrey Spaces Nicky Kurnia Tumalun
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp1-4

Abstract

In this paper, we give an explicit function which belongs to the Morrey spaces but not in the vanishing Morrey spaces. Therefore, we obtain that the Morrey spaces contain the vanishing Morrey spaces properly.
$P_2\rhd_{o}G$ supermagic labeling of comb product of graphs Ganesha Lapenangga Putra
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp13-18

Abstract

Teorema Titik Tetap Untuk Pemetaan Tipe Hardy-Roger Kontraksi-F_c pada Ruang Metrik Lengkap Bernilai Kompleks Irvandi Gorby Pasangka
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp19-24

Abstract

Dalam tulisan ini, akan dibahas mengenai teorema titik tetap untuk pemetaan tipe Hardy-Roger Kontraksi-F_c pada ruang metrik lengkap bernilai kompleks. Eksistensi titik tetap untuk pemetaan tipe Hardy-Roger Kontraksi-F_c dijamin jika memenuhi 0≾α,β,γ,μ,L, γ≠1, dan α+β+γ+2μ=1. Lebih lanjut, jika α+μ+L≾1, maka T memiliki titik tetap tunggal x^*∈X dan untuk setiap x∈X, barisan {T^n (x)} konvergen ke x^*.
Cuckoo Search Algorithm untuk Menyelesaikan Bi-Objective Permutation Flowshop Scheduling Problem Asri Bekti Pratiwi; Herry Suprajitno; Siti Sarah
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp5-12

Abstract

Tujuan dari penelitian ini adalah menyelesaikan permasalahan Bi-objective Permutation Flowshop Scheduling Problem (BPFSP) menggunakan Cuckoo Search Algorithm (CSA). BPFSP memiliki lebih dari satu fungsi tujuan yaitu meminimalkan makespan dan total tardiness. Program penerapan CSA untuk menyelesaikan BPFSP diimplementasikan dalam kasus dengan tiga jenis data yaitu data kecil dengan 5-pekerjaan 4-mesin, data sedang dengan 20-pekerjaan 10-mesin, dan data besar 50-pekerjaan 20-mesin dengan penggunaan beberapa nilai parameter yang bervariasi diantaranya maksimum iterasi, banyaknya sarang serta probabilitas pergantian sarang. Berdasarkan hasil running pada ketiga jenis data diperoleh bahwa semakin banyak jumlah sarang serta iterasi maka akan memberikan nilai fungsi tujuan BPFSP yang cenderung lebih baik. Sebaliknya, nilai fungsi tujuan BPFSP akan cenderung lebih baik jika nilai probabilitas pergantian sarang semakin kecil.
Analysis of the Changes in 2019-nCov Before and After the Implementation of the "Required Swab PCR-Test for Entry into West Kalimantan via Air Transport" Policy nurainul Miftahul Huda; Nurfitri Imroah
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp33-44

Abstract

Implementing policies during the 2019-nCov pandemic are expected to reduce the number of cases added every day. West Kalimantan is one of the provinces that implements a policy of obliging to include negative results on the PCR-test swab every time they use air transportation to West Kalimantan. In this study, we wanted to know whether there were differences in data behavior before and after implementing the policy. These differences can be analyzed simply by looking at the descriptive statistics of the data. Furthermore, in this study, a time series analysis was also carried out, and the data patterns and the suitable models representing the data. Time series analysis is also needed to predict the next 5 days related to the addition of 2019-nCov cases in West Kalimantan. In modeling, modifications have been made by partitioning the data into two data, namely data before the policy is implemented and the rest is data after the policy is implemented. The result shows that the suitable model for before and after the policy is applied is ARIMA (1,0,0) and ARIMA (7,0,0)(1,0,0)7, respectively. This model shows a better performance in translating problems than using the entire data as input in modeling. The smaller MSE value indicates this than using the ARIMA model (1,0,0) for the entire data (without partition). Therefore, in the prediction stage, a model with partitioned data is used. The results showed that there was a decrease in daily cases in the next five days.
Model Autoregressive Integrated Moving Average (ARIMA) untuk Peramalan Curah Hujan di Kota Surabaya Yonlib Weldri Arnold Nanlohy; Gabriella Haumahu
Tensor: Pure and Applied Mathematics Journal Vol 2 No 1 (2021): 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/tensorvol2iss1pp25-32

Abstract

Surabaya is the largest city in the province of East Java and is also the center of the provincial government. In the city of Surabaya the dry season is from May to October and the rainy season is from November to April. Heavy rain usually occurs between December and January. One of the negative impacts caused by excessive rainfall in the city of Surabaya is flooding. The method is often used to predict rainfall in the city of Surabaya, it is Autoregressive Integrated Moving Average (ARIMA). ARIMA models is forecasting model analysis data of single time series or univariate models. The purpose of this study is to forecast the daily rainfall in the city of Surabaya with a ARIMA model
Maluku Leading Sector Determination Overlay Model Jefri Tipka
Tensor: Pure and Applied Mathematics Journal Vol 2 No 2 (2021): 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/tensorvol2iss2pp59-66

Abstract

The Overlay Model is an analysis in economic development planning used to understand economic development, the Overlay Model is a combination modeling of LQ (Location Quentient), MRP (Growth Ratio Model) and modified SS-EM (Shift Share Estaban Marquillas). This study aims to analyze the leading sectors in Maluku Province and their effects among external and internal areas. The results show that the economic development in Maluku Province during the 2010-2020 period have three leading sectors that are potential in palying the economy. The results of the research can be used as a policy evaluation for the local government and a consideration in future decision making.
Peramalan Jumlah Penduduk Miskin di Provinsi Maluku Tahun 2021 Dengan Menggunakan Metode Arima iksan mule
Tensor: Pure and Applied Mathematics Journal Vol 2 No 2 (2021): 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/tensorvol2iss2pp77-86

Abstract

Studi ini bertujuan untuk meramalan jumlah penduduk miskin di Provinsi Maluku tahun 2021 dengan menggunakan data series tahun 2005-2020 yang bersumber dari website Badan Pusat Statistik Provinsi Maluku. Penelitian serupa masih sangat terbatas di Provinsi Maluku. Metode peramalan yang digunakan dalam penelitian ini adalah metode ARIMA (Autoregresive Integrated Moving Average). ARIMA merupakan metode analisis time series yang baik untuk peramalan jangka pendek. Tahapan penelitian dimulai dari pemeriksaan pola data, pengecekan kestasioneran data, identifikasi model, estimasi parameter, hingga verifikasi model. Setelah melalui tahapan-tahapan tersebut maka model pun dapat digunakan untuk meramalkan data. Dalam pengolahannya menggunakan software Minitab 15 dan SPSS 21. Berdasarkan hasil penelitian, diperoleh model ARIMA(1,0,0) sebagai pilihan terbaik dengan nilai ramalan jumlah penduduk miskin Provinsi Maluku untuk tahun 2021 sebesar 321.094 jiwa. Hal ini menunjukkan terjadi kenaikan sebesar 2.914 jiwa dari tahun 2020. Dengan demikian, penelitian ini diharapkan dapat menjadi pertimbangan bagi pemerintah Provinsi Maluku dalam mengoptimalkan kebijakan pengentasan kemiskinan di seluruh wilayah kepulauan Maluku.

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