cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Harmanus Batkunde
Contact Email
h.batkunde@fmipa.unpatti.ac.id
Phone
+6282397854220
Journal Mail Official
tensormathematics@gmail.com
Editorial Address
Jurusan Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Unversitas Pattimura Jln. Ir. M. Putuhena, Kampus Unpatti, Poka - Ambon 97233, Provinsi Maluku, Indonesia
Location
Kota ambon,
Maluku
INDONESIA
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 12 Documents
 1   2 
Search results for , issue "Vol 6 No 2 (2025): Tensor: Pure and Applied Mathematics Journal" : 12 Documents clear
Analisis Perbandingan Optimasi Stochastic Gradient Descent dan Adaptive Moment Estimation dalam Klasifikasi Emosi dari Audio Menggunakan Convolutional Neural Network Tutuhatunewa, Aldelia Jocelyn; Rahakbauw, Dorteus Lodewyik; Leleury, Zeth Arthur
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp13-22

Abstract

Emotion plays a fundamental role in human life, influencing behavior, social interaction, anddecision-making. Successful communication and understanding between individuals depend greatly on ourability to recognize and express emotions. In this context, sound or audio plays a key role as a medium thatreflects and conveys human emotional expression. In the era of information technology and artificialintelligence, emotion recognition through sound has become a growing focus of research. Machine learningalgorithms, particularly neural networks, can be trained to understand and classify emotions conveyed invarious forms, including text, images, videos, and audio. Among these algorithms, Convolutional NeuralNetwork (CNN) has shown promising performance in emotion classification tasks. In this study, thecomparison between Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (Adam)optimizers in emotion classification from audio using CNN is investigated. The research aims to determinethe optimal optimizer for emotion classification tasks. The results suggest that SGD optimizer outperformsAdam in terms of overall accuracy, with SGD achieving 53% accuracy compared to Adam's 48% accuracy inThe Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset. Therefore, foremotion classification from audio data, Stochastic Gradient Descent (SGD) optimizer is recommended forbetter performance.
Optimization of LSTM Model for Rainfall Prediction in Ambon City: Comparison of Mean Imputation and Interpolation in Time Series Data Prediction Wattimena, Emanuella M. C.; Taihuttu, Pranaya D. M.; Waas, Devi V.; Palembang, Citra F; Pattiradjawane, Victor E.
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp49-56

Abstract

Rainfall prediction is an essential aspect of meteorology, agriculture, and disaster management, particularly in regions like Ambon, where rainfall patterns significantly impact daily life. However, one of the major challenges in developing an accurate predictive model is handling missing values in the dataset. This study aims to optimize the Long Short-Term Memory (LSTM) model for rainfall prediction in Ambon by comparing two missing value handling techniques: mean imputation and interpolation. The dataset used in this study consists of daily rainfall data from 2021 to 2024, with approximately 26.89% missing values. Two experimental scenarios were conducted: the first using mean imputation to fill in missing values with the average rainfall, and the second using linear interpolation. Both scenarios utilized the same LSTM architecture to evaluate their impact on model performance. The evaluation metrics used in this study include Root Mean Square Error (RMSE) and R-squared (R²). The results show that the interpolation-based model achieved a lower RMSE and a slightly higher R² value than the mean imputation-based model, indicating better predictive performance. However, both models struggled to capture extreme values, necessitating further improvements. To address this limitation, a more complex LSTM architecture was implemented in the subsequent experiments, incorporating additional layers and optimized hyperparameters. The findings suggest that choosing an appropriate missing value handling method significantly influences the predictive accuracy of LSTM models for rainfall forecasting. This research contributes to the development of more reliable weather prediction models, which can aid in agricultural planning, flood risk assessment, and climate change adaptation in Ambon.
The Rainbow Vertex Connection Number of Some Amalgamation of Two Cycles Taihuttu, Pranaya D. M.; Tilukay, Meilin I.; Rumlawang, Francis Y.; Wattimena, E. M. C.
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp57-66

Abstract

This paper focuses on rainbow vertex coloring in a graph G, in which, for every two vertices in G, there exists a rainbow vertex path where all internal vertices have distinct colors. The rainbow vertex connection number of G, denoted by rvc(G), is the minimum number of colors required to make G rainbow-vertex connected. In this paper, we determine the rainbow vertex connection number of some amalgamation of two cycles.
Fungsi Trace dan Fungsi Norm Lapangan Perluasan Atas Q Dahoklory, Novita; Patty, Henry Willyam Michel
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp39-48

Abstract

Suppose L/K is an extension field where K⊆L so that L can be viewed as a vector space over K. Moreover, it is known that for every α∈L, we can construct a linear transformation T_α: L→L where T_α (x)=αx for all x∈L so that we have the representation matrix [T_α] of T_α. In this study, the trace and norm functions are discussed which are defined using the trace and determinant of the matrix [T_α]. Furthermore, this study will also discuss the application of the trace and norm functions in the field of an extension field especially Q(∛2) over Q.
Modeling the Spread of Hepatitis B Disease from the SEIR Model in East Java Using RKF 45 Na'malia, Sakinun; Faisol, Faisol; Yulianto, Tony
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp1-12

Abstract

Hepatitis B is an infectious disease that has a major impact on public health, especially in East Java Province with a high prevalence of cases. This study aims to model the spread of Hepatitis B using the SEIR model (Susceptible, Exposed, Infected, Recovered) and solved numerically with the Runge-Kutta Fehlberg method (RKF45). Simulation results for 10 years showed that the susceptible population decreased from to individuals, while the exposed compartment increased from to . The infected population peaked at around individuals in year 2 and decreased to individuals, while the cured population continued to increase until it reached at the end of the period. The SEIR model with the RKF45 method proved effective in describing the dynamics of the spread of Hepatitis B mathematically and can be utilized as a predictive tool in supporting public health policy.
Kajian Basis dan Dimensi pada Ruang Hipervektor Atas Lapangan Kambu, Loisa Genesis; Patty, Henry Willyam Michel; Bakarbessy, Lusye; Dahoklory, Novita
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): 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/tensorvol6iss1pp23-38

Abstract

The concept of algebraic hyperstructure is a generalisation of the concept of algebraic structure. The concept of algebraic hyperstructure discussed in this study is hypervector space. The purpose of this paper is to study the basis and dimension of the hypervector space. In hypervector space there is a strong left distributive property, namely (a+b)∘x=a∘x+b∘x, ∀a,b∈K,∀x∈V. In addition, in a hypervector space that has the K-invertible property, the importance of the strong left distribution property and the invertible property in this hypervector space ensures that each linearly independent set has no more than n elements, where n is the dimension of the hypervector space. Furthermore, the addition of vectors from outside the base will result or not linearly independent. Translated with DeepL.com (free version)
Aplikasi Metode Adams Bashforth Moulton Dalam Memprediksi Pertumbuhan Penduduk Di Kota Ambon Radjab, Fikram; Rumlawang, Francis Yunito
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Vol 6 No 2 (2025): 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/tensorvol6iss2pp121-130

Abstract

The increasing population in Ambon City can cause various problems both social and environmental problems such as lack of residential land, clean water needs, transportation problems to health. This study is to examine the increasing population of Ambon City, this study will also predict the population in Ambon City in the following year using historical data using the fourth-order Adams Bashforth Moulton method approach from Verhulst modeling. This research produces accurate forecasting with a very small relative error value, with an area of 377km2 and a predicted population of 372,725 in 2030. The Adams Bashforth Moulton method as a Verhulst model is very effective for decision making in predicting population growth in Ambon City.
Forecasting Inflastion Rate In Ternate City Using ARIMA Method And ARIMAX Calender Variation Ilu, Riski Noviyanti; Djami, Ronald John; Laamena, Novita Serly
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Vol 6 No 2 (2025): 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/tensorvol6iss2pp111-120

Abstract

Indonesia sebagai negara berkembang sering menghadapi tantangan inflasi, baik nasional maupun daerah, seperti Kota Ternate yang menjadi acuan inflasi di Maluku Utara. Penelitian ini bertujuan untuk meramalkan inflasi di Kota Ternate menggunakan metode ARIMA dan ARIMAX Variasi Kalender berdasarkan data inflasi bulanan tahun 2014–2023 yang diperoleh dari website resmi BPS. ARIMA menangkap pola historis, sedangkan ARIMAX variasi kalender mempertimbangkan faktor musiman dan hari raya. Hasil menunjukkan model ARIMA terbaik adalah ARIMA ([1,4,12,13],0,0) dengan AIC minimum sebesar -184,729 dan tingkat akurasi sebesar 96,71%. Sementara model ARIMAX dengan variabel variasi kalender terbaik adalah ARIMAX ([13],0,[3]) dengan dummy m1 sampai m11 (bulan musiman) dan h2 (bulan hari raya), menghasilkan tingkat akurasi sebesar 97,16%. Dengan demikian, ARIMAX dengan variabel variasi kalender memberikan hasil peramalan yang lebih akurat dan relevan untuk mendukung kebijakan pengendalian inflasi daerah.
Model Predator – Prey Dengan Fungsi Respon Holling Tipe II dengan Adanya Infeksi pada Prey dan Pemanenan pada Predator Amelia, Hilda; Rahakbauw, Dorteus Lodewyik; Leleury, Zeth Arthur
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Vol 6 No 2 (2025): 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/tensorvol6iss2pp95-110

Abstract

Model matematika predator-prey merupakan salah satu pendekatan yang digunakan untuk memahami dinamika populasi dalam ekosistem. Penelitian ini mengembangkan model predator-prey dengan fungsi respon Holling tipe II, di mana prey (mangsa) dapat terinfeksi penyakit dan predator mengalami pemanenan. Tujuan dari penelitian ini adalah untuk membentuk model matematika dari sistem tersebut, menentukan titik kesetimbangan, menganalisis kestabilannya, serta melakukan simulasi guna memahami dinamika populasi. Metode penelitian yang digunakan adalah studi literatur dan pendekatan numerik dengan bantuan perangkat lunak Matlab. Model yang dikembangkan mempertimbangkan tiga sub-populasi mangsa: mangsa sehat, mangsa terinfeksi, dan mangsa yang sedang dalam proses perawatan (treatment). Predator dalam model ini mengalami pemanenan, yang berarti populasinya berkurang akibat eksploitasi manusia. Analisis kestabilan dilakukan dengan mencari titik kesetimbangan sistem serta mengevaluasi kestabilannya menggunakan matriks Jacobian dan nilai eigen. Hasil penelitian menunjukkan bahwa terdapat beberapa titik kesetimbangan dalam sistem, yaitu titik kesetimbangan trivial, semi-trivial, dan non-trivial. Titik kesetimbangan trivial terjadi ketika seluruh populasi punah. Titik kesetimbangan semi-trivial terjadi dalam beberapa skenario, seperti ketika predator punah, mangsa sehat tidak ada, atau mangsa terinfeksi tidak ada. Sementara itu, titik kesetimbangan non-trivial menggambarkan kondisi di mana semua populasi eksis dan berinteraksi dalam keseimbangan dinamis. Simulasi numerik menunjukkan bahwa keberadaan infeksi dan pemanenan dapat mempengaruhi kestabilan sistem dan pola interaksi predator-prey secara signifikan. Kesimpulan dari penelitian ini adalah bahwa faktor infeksi pada prey dan pemanenan pada predator memiliki dampak besar terhadap keseimbangan ekosistem. Pemanenan yang berlebihan dapat menyebabkan kepunahan predator, yang selanjutnya dapat menyebabkan ledakan populasi mangsa atau ketidakseimbangan ekosistem. Berdasarkan hasil penelitian, disarankan agar dilakukan studi lebih lanjut dengan mempertimbangkan faktor lingkungan lainnya, seperti variasi tingkat infeksi dan kebijakan pengelolaan pemanenan predator, untuk menjaga keseimbangan ekosistem secara lebih realistis.
Clustering of Regencies/Cities in Maluku Province Based on Tuberculosis Cases Using the K-Medoids Algorithm Wattimena, Meyriska; Noya Van Delsen, Marlon Stivo; Salhuteru, Rosalina; Lewaherilla, Norisca
Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Vol 6 No 2 (2025): 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/tensorvol6iss2pp67-74

Abstract

Tuberkulosis (TBC) merupakan penyakit menular yang masih menjadi permasalahan kesehatan serius di Indonesia, termasuk di Provinsi Maluku. Penanganan TBC yang efektif memerlukan pemahaman terhadap karakteristik wilayah berdasarkan tingkat kasus TBC. Penelitian ini bertujuan untuk mengelompokkan kabupaten/kota di Provinsi Maluku berdasarkan jumlah kasus TBC periode 2021–2023 menggunakan algoritma K-Medoids, serta menentukan jumlah cluster optimal dengan Metode Elbow dan Silhouette Coefficient. Data yang digunakan diperoleh dari Badan Pusat Statistik Provinsi Maluku. Hasil analisis menunjukkan bahwa jumlah cluster optimal adalah tiga, yaitu: Cluster 0 (kategori rendah) terdiri dari 8 kabupaten/kota, Cluster 1 (kategori sedang) terdiri dari 2 kabupaten/kota, dan Cluster 2 (kategori tinggi) hanya terdiri dari Kota Ambon. Validasi menggunakan Silhouette Coefficient pada k = 3 menunjukkan nilai sebesar 0,641 yang berada pada kategori struktur sedang. Pengelompokan ini diharapkan dapat membantu pemerintah dalam merancang strategi penanggulangan TBC yang lebih terfokus dan sesuai dengan tingkat risiko di masing-masing wilayah.

Page 1 of 2 | Total Record : 12

 1   2 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol 6 No 2 (2025): Vol 6 No 2 (2025): Tensor: Pure and Applied Mathematics Journal Vol 6 No 2 (2025): Tensor: Pure and Applied Mathematics Journal Vol 5 No 2 (2024): Tensor: Pure and Applied Mathematics Journal Vol 5 No 1 (2024): Tensor: Pure and Applied Mathematics Journal Vol 4 No 2 (2023): Tensor: Pure and Applied Mathematics Journal Vol 4 No 1 (2023): Tensor: Pure and Applied Mathematics Journal Vol 3 No 2 (2022): Tensor: Pure and Applied Mathematics Journal Vol 3 No 1 (2022): Tensor: Pure and Applied Mathematics Journal Vol 2 No 2 (2021): Tensor : Pure and Applied Mathematics Journal Vol 2 No 1 (2021): Tensor : Pure And Applied Mathematics Journal Vol 1 No 2 (2020): Tensor : Pure And Applied Mathematics Journal Vol 1 No 1 (2020): Tensor : Pure And Applied Mathematics Journal More Issue