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E-Jurnal Matematika
Published by Universitas Udayana
ISSN : -     EISSN : 23031751     DOI : https://doi.org/10.24843/MTK
Core Subject : Education,
Mathematics
The scope of the E-Jurnal Matematika includes analysis, algebra, topology, graphics, numerical simulation approaches or what is known as numerical analysis, optimal control, queuing problems, optimization, finance, biomathematics, industrial mathematics, financial mathematics, and others.
Arjuna Subject : Matematika - Matematika Terapan
Articles 39 Documents
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ANALISIS SENTIMEN PROGRAM MAKAN BERGIZI GRATIS MENGGUNAKAN SVM DAN KNN DENGAN TF-IDF DAN TF-ABS SEVIRA HUKMAN MAJIDAH; PUTRIAJI HENDIKAWATI
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p496

Abstract

The Free Nutritious Meal Program, initiated by the government to improve child and maternal health, has generated varied public responses on social media. This study aims to classify public sentiment toward the program by applying machine learning models to social media text data. The dataset used consists of 9000 tweets from Platform X that have been manually labeled into positive, negative, and neutral categories. Classification was performed using Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms combined with two term weighting techniques Term Frequency-Inverse Document Frequency (TF-IDF) and Term Frequency-Absolute (TF-ABS). The performance of each model was evaluated using accuracy, precision, recall, and F1-score. The results show that SVM model with TF-ABS achieved the best performance with 99.69% accuracy, precision 99.69%, recall 99.68%, and F1-score 99.68%. The KNN model with TF-ABS also performed well, reaching 95.55% accuracy. In contrast, models employing TF-IDF demonstrated noticeably lower performance, with the SVM achieving an accuracy of [75,53%] and the KNN reaching [70,89%], indicating a clear performance gap compared to the TF-ABS weighting scheme. This research provides insights into suitable machine learning models and term weighting methods for sentiment analysis of public opinion on government programs using social media data.
PEMODELAN MATEMATIKA KEKERASAN DALAM RUMAH TANGGA (KDRT) TERHADAP PEREMPUAN DI INDONESIA DENGAN MENGGUNAKAN SOLUSI NUMERIK RUNGE-KUTTA ORDE EMPAT MAMLUATUL AULIYAK; AMALIYATUL HASANAH
E-Jurnal Matematika Vol. 14 No. 4 (2025)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2025.v14.i04.p495

Abstract

The high number of domestic violence cases in Indonesia indicates the need for a scientific approach to understand the dynamics of the spread and more systematic control efforts. In this study, model is developed into six compartments, namely ShIRSvHC. In the model, the equilibrium point and stability of the equilibrium point are sought, as well as numerical simulations using the fourth order Runge-Kutta method and the simulation results are compared with actual data for 2020-2024. Evaluation of model accuracy is done by calculating the relative error. The simulation results show that the sub population has decreased every time with a population of about 268,030 women. The I population experienced an increase at the beginning of the period and experienced a significant decrease in the following year, the R population experienced an increase at the beginning to the middle of the period and for the and H, C populations experienced an increase every time.
ANALISIS PREFERENSI PELAKU UMKM DALAM MEMILIH BANK DENGAN PENERAPAN TEORI PERMAINAN IRENE NAKISOMA; NI KETUT TARI TASTRAWATI; KARTIKA SARI
E-Jurnal Matematika Vol. 14 No. 4 (2025)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2025.v14.i04.p494

Abstract

Business actors require banking services that effectively support their financial activities. The variety of available banks requires institutions to understand customer preferences in order to develop competitive strategies. This study aims to determine the optimal strategy that banks may implement based on the preferences of micro, small, and medium business actors using game theory. The research employed a two-stage data collection process. The first stage involved 30 respondents to identify the two most preferred banks, namely Bank A and Bank B. The second stage involved 108 respondents, determined through the Yamane formula, to evaluate eight strategic banking attributes. Payoff values were calculated using the difference in preference probabilities for each attribute. Game theory analysis used a two-person zero-sum game with pure strategies. The results indicate that Bank A optimal strategy is ATM availability, while Bank B optimal strategy is loan interest rates. These findings may assist banks in enhancing their services according to business actors’ preferences.
METODE REGRESI MULTILEVEL UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR LAMA MASA STUDI MAHASISWA FMIPA UNIVERSITAS UDAYANA DEWA AYU MADE SRI WIJAYATI UTAMI; MADE SUSILAWATI; I KOMANG GDE SUKARSA
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p497

Abstract

Hierarchical data is data that has a multilevel structure, where individuals belong to certain groups and variables are measured at different levels. Analysis of hierarchical data without considering group membership may result in bias due to violation of the independence assumption. Multilevel regression analysis is a statistical method to overcome this problem by modeling the data structure at several levels. This study aims to apply three-level multilevel regression analysis to identify factors that affect the study duration of undergraduate students at FMIPA Udayana University. In this data structure, students are at the first level, grouped into classes at the second level, and the classes are in study programs at the third level. The model uses random intercepts as well as exploring random slopes to assess differences in the influence of independent variables between study programs.
ANALISIS DINAMIK MODEL PENYEBARAN PENYAKIT DEMAM BERDARAH DENGUE (DBD) DENGAN PENGARUH TERAPI YESINTA KHARISMA NINGTIAS; M. NUR HAQQUL QOMARUDIN; RACHMADANIA AKBARITA; RIZKA RIZQY ROBBY
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p498

Abstract

Dengue Hemorrhagic Fever (DHF) is a viral infectious disease transmitted through the bite of the Aedes aegypti mosquito. This study analyzes the equilibrium effect of therapy in controlling the spread of DHF. A mathematical modeling approach is used to predict the dynamics of the spread of DHF by considering the intervention of therapy use. This model describes the interaction between human population and the effectiveness of therapy. The results of the analysis with a disease-free equilibrium . While the endemic equilibrium point is  with . Stability is achieved when the eigenvalue is less than zero. Disease-free stability is said to be stable when the value of  and endemic stability is said to be stable when the value of . The results of the traveling wave in the model have a minimum speed with . In this case, with the existence of this minimum speed, the wave of spread in the future can occur again needs to be watched out for properly. By carrying out therapy, it is hoped that it can help infected individuals.
PENERAPAN MODEL PROSES RENEWAL DALAM MANAJEMEN PERSEDIAAN BAHAN PANGAN DI HOTEL MERCURE RESORT SANUR, BALI DIVA FELIZIA BAGINDO; MADE IREINA DWIANDRA DIVAYANTI; NARISKA DESWITA WINANDI; CHRISTIAN MELANIA LEU; MADE AYU DWI OCTAVANNY
E-Jurnal Matematika Vol. 15 No. 2 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i02.p503

Abstract

The daily operation of a hotel kitchen relies heavily on the consistent availability of staple goods. This study analyzes the inventory management of key staples such as rice, cooking oil, milk, and eggs at Mercure Resort Sanur Bali. The research aims to determine optimal safety stock levels and reorder points to handle uncertain demand and market fluctuations. Using a renewal process model, the study analyzes the hotel’s inventory patterns based on usage and restocking data. The results show that Rice C4 should be reordered when stock reaches 40 kg, with a safety stock of 7 kg. Cooking Oil (18 LT) should be replenished at 2 jars, with 1 jar as safety stock. Milk UHT full cream should be reordered at 43 liters remaining, with an 8 liters safety stock. Chicken Eggs should be reordered at 30 kg, with a 6 kg safety stock. These findings demonstrate that applying a renewal process helps maintain the availability of essential food items and supports smooth, continuous kitchen operations at the resort.
ESTIMASI KEDATANGAN PELANGGAN DAN TRANSAKSI PESANAN RUMAH MAKAN MAHIRA MENGGUNAKAN RENEWAL-REWARD PROCESS PIONITA MARETTI BR AMBARITA; KETUT GITA SEKARINI; TASSYA MURNI PASARIBU; WIRA PRANATA T. TAMBUN; MADE AYU DWI OCTAVANNY
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p499

Abstract

Random fluctuations in customer arrivals at restaurants often result in suboptimal operational planning based on subjective estimates. This study aims to estimate customer arrival patterns and transaction values at Mahira Jimbaran Restaurant using the renewal-reward process approach, as well as to calculate long-term revenue rates. The methods used include collecting primary data for 4 hours on Saturday, November 8, 2025 (1:00 p.m. to 5:00 p.m. Wita) by recording the time between arrivals and the transaction value per customer. The analysis was conducted by calculating the expected transaction value (E[R]), expected inter-arrival time (E[X]), and long-term reward rate using the Wald Equation. The results show an average transaction of IDR 23,808.99 per customer, an average inter-arrival time of 2.013 minutes, and a revenue rate of IDR 11,828.67 per minute. These quantitative estimates can be used as a basis for operational decision-making related to workforce scheduling, queue management, and raw material planning.
ANALISIS SISTEM ANTREAN PADA SPBU 54.803.16 ULUWATU UNTUK MENGUKUR EFISIENSI PELAYANAN RAGAH NIHAN RAZANDO; NOVIA NURROHMAH; NI MADE ARI PUAN KAMINI; I GEDE DARMA YUDA UDAYANA; MADE AYU DWI OCTAVANNY
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p501

Abstract

This study aims to analyze the queuing characteristics of motorcycles refueling pertalite at SPBU 54.803.16 Uluwatu and to determine the most appropriate queueing model to represent the performance of its service system. Data were collected through direct observation on Monday and Saturday to examine the patterns of vehicle arrivals and service times. The analysis was carried out using queueing theory, applying the M/G/1 and G/G/1 models along with distribution tests to identify the suitability of arrival and service patterns. The results indicate that the distribution of arrivals on both observation days is not entirely uniform, with noticeable variations at specific time intervals. Based on the data analysis, the G/G/1 model provides a more accurate representation of the queueing conditions, as both arrival and service processes exhibit randomness without following a specific theoretical distribution. System performance evaluation shows that the server utilization rate is relatively high, leading to increased waiting times and longer queues during peak hours. These findings suggest the need for operational adjustments, particularly during high-demand periods, to improve service efficiency and reduce traffic congestion around the fuel station.
PENERAPAN BIRTH-AND-DEATH PROCESS PADA KASUS TERINFEKSI DAN KEMATIAN COVID-19 KALIMANTAN TIMUR JANUARI 2021 WINA CHRISTIANI PARHUSIP; NI KOMANG KHARINA GAYATRI; DEWA AYU RATIH ISAKA PUTRI; GINA CORNELIA BR TARIGAN; MADE AYU DWI OCTAVANNY
E-Jurnal Matematika Vol. 15 No. 2 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i02.p504

Abstract

The birth and death process is a powerful Markov process for modeling population changes due to two events: births and deaths. In this study, the birth and death events are described as the number of new infections and deaths due to the Covid-19 virus in East Kalimantan for the period 1–31 January 2021. In this study, the birth and death processes are used to analyze the data with a focus on estimating the parameters of the birth rate and death rate and observing the ratio between the two parameters. The results show that the estimated parameter values ​​for the birth (λ) and death (µ) are 0.0139132 and 0.00024230, respectively, and the ratio of the two parameters is 57.42. This indicates that the birth and death rates in this case are still in the supercritical category. This means that without significant external interventions such as emergency PPKM (restrictions on community activities), mass vaccination, or drastic increases in testing and tracing capacity, the number of active cases is likely to increase indefinitely in the long term.
PREDIKSI TINGKAT CURAH HUJAN KOTA MATARAM MENGGUNAKAN LONG SHORT-TERM MEMORY DIMAS ANGGRAWAN HADINATA; IRENE RAINBOW KEWA SOMI; LULUK KARTIKA; TRI MARYONO RUSADI; SISKA APRILIA HARDIYANTI
E-Jurnal Matematika Vol. 15 No. 1 (2026)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2026.v15.i01.p500

Abstract

Rainfall is an important weather parameter that significantly influences the agricultural sector and regional planning. The City of Mataram, as the center of social and economic activities in West Nusa Tenggara Province, requires an accurate rainfall prediction method. This study aims to predict daily rainfall in Mataram City using a multivariate long short-term memory (LSTM) approach. The data used consist of daily observations from BMKG, with input variables including average temperature, average humidity, average wind speed, and average air pressure. The dataset is structured as a time series using a sliding window approach with a 7-day lookback period and is divided into 80% training data and 20% testing data. The LSTM model is constructed with two LSTM layers containing 64 and 32 units, respectively, complemented by a 0,2 drop out layer and a Dense layer as the output for prediction. Evaluation using MAE and RMSE indicates that a configuration of 100 epochs and a batch size of 16 provides the best performance, achieving MAE of 4,020 mm and RMSE of 7,915 mm on the testing data, demonstrating the model’s capability to predict daily rainfall in a stable manner.

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