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Jurnal Matematika
Published by Universitas Udayana
ISSN : 16931394     EISSN : 26550016     DOI : https://doi.org/10.24843/JMAT
Core Subject : Education,
Mathematics
Jurnal Matematika (p-ISSN: 1693-1394 |e-ISSN: 2655-0016| DOI: 10.24843/JMAT ) is an open access journal which publishes the scientific works for researchers. The articles of this journal are published every six months, that is on June and December.
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Articles 9 Documents
 1 
Search results for , issue "Vol 14 No 1 (2024)" : 9 Documents clear
Implementasi Numerik Berbagai Kondisi Batas pada Persamaan Air Dangkal Menggunakan Metode Elemen Hingga Terbaru Konformal dan Non-Konformal Swastika, Pt Veri; Sulvianuri, Rani; Gautama, I Putu Winada
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p168

Abstract

In this paper, we extend the capability of a newly developed numerical scheme based on our preceding linear conformal and non-conformal finite element methods (FEM) to study 2D shallow water equations (SWE) with various boundaries. Unlike usual approach, we approximate the unknown in a staggered grid due to the use of linear alternating basis. Here, the free surface is approximated using a conformal while the velocity potential is approximated using a non-conformal linear basis. As a result, the varational problem must be reformulated. The resulting scheme is a ODE system which is easy to solve by any time integration method. Therefore, our method is staggered in space, explicit, flexible and simple to implement. The simulation results show that the flexibility of the scheme can be interpreted as the successful use of various boundary conditions. Keywords: 2D SWE, staggered finite element, non-conformal basis, influx boundary
A New Type of Extended Soft Set Operation: Complementary Extended Intersection Operation Sezgin, Aslihan; Sarialioglu, Murat; Aygün, Emin
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p173

Abstract

Soft set theory is seen as an effective mathematical tool in solving problems involving uncertainty, and has been applied in many theoretical and practical areas since its introduction. The basic concept of the theory is soft set operations. In this context, in this paper, a new kind of soft set operations called complementary extended soft set operation is defined in order to contribute to the theory. The properties of the operation are examined in detail together with its distributions over other soft set operations in order to obtain the relationship between complementary extended intersection operation and the others. We demonstrate that the collection of soft sets over with a fixed parameter set, along with the complementary extended intersection operation and other certain types of soft sets, form many well-known and important algebraic structures in classical algebra, including semiring, hemiring, Boolean ring, Boolean Algebra, De Morgan Algebra, Kleene Algebra, and Stone Algebra.
A Comparative Analysis of Deep Autoregressive, Deep State Space, Simple Feed Forward, and Seasonal Naive in Forecasting Indonesia’s Inflation Rate Sumarjaya, I Wayan; Susilawati, Made
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p170

Abstract

Information about inflation plays important role in economic policy. The government of the Republic Indonesia has put a great deal of effort to control inflation rate. The aims of this research are to forecast Indonesia’s inflation rate using deep auto-regressive networks and to compare it with other models such as deep state space, simple feed forward, and naïve seasonal. In this study we compare eighteen deep au-toregressive networks. Each model differs only in its hyperparameters settings such as the number of epochs, the number of layers, the number of cells, and the number of batch sizes. In order to check for consistency each model is replicated ten times. In total there are 180 runs for each of configuration including the replication. The results show that the deep autoregressive model with 50 epochs, 4 layers, 40 cells, 32 batch sizes produces the smallest root mean squared error at 0.218565. This root mean squared error also the smallest among the other models such as deep state space (0.28734), simple feed forward (0.350449), and naïve seasonal (0.336056). In conclusion, the median forecasts fluctuates but below 1 percent.
Prediksi Jumlah Pengiriman Paket Menggunakan Metode Auto Regressive Integrated Moving Average Sholikah, Layla Hidayatus; Chandra, Novita Eka; Rohmaniah, Siti Alfiatur; Rohmah, Awawin Mustana
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p174

Abstract

This research aims to predict the number of postal office package deliveries using the ARIMA method. The data used is delivery data at the Lamongan Post Office from January 2018 to December 2022. The results of this research are the best model for predicting delivery data, namely ARIMA (2,2,0) with an RMSE value of 2333.897 and a MAPE value of 8,83%. Prediction results for the full year in 2023 have increased every month. Keywords: prediction, delivery, ARIMA
Prediksi Volume Weighted Average Price Saham INDF Menggunakan Algoritma Genetika Firdaus, Liony Putri; Ahmad, Defri
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p169

Abstract

In the era of industrial revolution 4.0, investors in almost all countries are interested in investing in stocks. The wrong investment decision in deciding when it is the right time to buy and sell shares can cause big losses for investors. Therefore, technical analysis is required. One of the technical indicators used in intraday trading is the volume-weighted average price (VWAP). To predict the VWAP accurately in stock trading transactions, a genetic algorithm is used. The stocks that are suitable to be selected for conducting stock trading transactions are PT. Indofood Sukses Makmur Tbk. This research is applied research that uses secondary data from the website of PT. Indofood Sukses Makmur Tbk. The results showed that the predictive results of the VWAP testing data for PT. Indofood Sukses Makmur Tbk are close to actual data, which means that the genetic algorithm has good predictive abilities with an accuracy rate of 99.7% (very high method accuracy).
Kekuatan Ketakteraturan Sisi Modular Pada Graf Rantai C(nCm) Budayana, I Nyoman; Sariyasa, Sariyasa
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p175

Abstract

Modular edge irregular labeling of graph G is an vertex labeling f from V(G) to {1,2,3,…,k} which is induced a bijection w from E(G) to Zn , where w(xy) = f(x) + f(y). Modular edge irregularity strength of graph G, mes(G), is the minimum number k such that f is a modular edge irregular labeling on G. In this paper, we discuss the modular edge irregularity strength of chain graph C(nCm), for m = 4,6,and 8.
Algoritma Djikstra : Rute Pengungsian Terpendek Daerah Rawan Bencana di Desa Canggu Arimbawa K., Ida Bagus Kade Puja
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p171

Abstract

Canggu Village, located in North Kuta, Badung Regency, Bali, Indonesia, is a popular tourist area with a population density of 1,305 people per square kilometer. This region offers an attractive combination of natural beauty, rich Balinese culture, and modern lifestyle, yet it also faces high risks of natural disasters such as floods, tsunamis, and coastal erosion due to its coastal location. The coastal geography of Canggu necessitates awareness and preparedness for disasters. This study focuses on formulating and implementing evacuation routes using the Dijkstra algorithm to find the shortest and safest evacuation path from disaster-prone areas to safe zones. The results indicate that the Dijkstra algorithm is effective in establishing evacuation routes from the most vulnerable points, such as Batu Bolong Beach, to safe zones with varying distances, allowing residents to leave high-risk areas quickly and safely. These recommendations are expected to be used by local governments in disaster planning and management.
Implementasi Algoritma Dijkstra Menggunakan Adjacency Matrix Ismawati, Iis; Maulani, Alfi
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p167

Abstract

Abstract: Dijkstra's algorithm is an algorithm that can support finding the fastest route by mapping alternative trajectories in finding travel routes. The aim of this research is to find alternative travel routes by implementing the Dijkstra Algorithm using the Adjacency Matrix to pick up goods from the PT Drop Center Warehouse. Cisoka Express Technology Jet. Survey data in the form of customer names and addresses from two sub-districts was used. The results obtained with the Dijkstra Algorithm using the adjacency matrix obtained 4 routes in searching for the shortest path to pick up goods in Cisoka sub-district with the first route totaling 5 points with a distance of 9.35 km, the second route totaling 5 points with a distance of 9 km, the third route totaling 3 points with a distance of 3.95 km and the fourth route consists of 2 points with a distance of 3.6 km. and for Solear sub-district there are 3 routes, the first route is 7 points 14.9 km away, the second route is 9 points 14.72 km away and the third route is 2 points 5.85 km away. . Keywords: Dijkstra's Algorithm, Matrix, Shortest Path
Penerapan Metode K-means Pada Klasterisasi Provinsi di Indonesia Berdasarkan Indikator Indeks Kebahagiaan Damayanthi, Ni Wayan Rita; Suciptawati, Ni Luh Putu; Jayanegara, Ketut; Sukarsa, I Komang Gde; Kencana, Eka N.; Wijayakusuma, I Gusti Ngurah Lanang
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p172

Abstract

The happiness index is a measure that reflects individual well-being, thus playing an important role in the development of a region. The level of happiness in Indonesia is still significantly lower compared to other ASEAN countries. In relation to efforts to improve the happiness index in Indonesia, this study applies the K-means method to cluster the 34 provinces of Indonesia based on the indicators of the happiness index for the year 2021. The data used is sourced from publications by the Indonesian Central Bureau of Statistics with seven happiness index indicators and employing the Minkowski distance. The clustering results of the 34 provinces using the K-means method obtained four clusters with a cluster accuracy value of 71 percent. Cluster 1 consists of seven provinces with a fairly high average of seven attributes, cluster 2 consists of seven provinces is a cluster with a low average level of internal and external satisfaction, cluster 3 consists of four provinces with a high average of seven attributes, and cluster 4 consists of 16 provinces is a cluster with provinces with a fairly high average level of external satisfaction, but a low level of internal satisfaction.

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