cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Desak Putu Eka Nilakusmawati
Contact Email
nilakusmawati@unud.ac.id
Phone
+62895600630316
Journal Mail Official
ejurnal_matematika@unud.ac.id
Editorial Address
https://ejournal3.unud.ac.id/index.php/mtk/about/editorialTeam Mathematics Department, Faculty of Mathematics and Natural Science, Udayana University. Bukit Jimbaran, Badung-Bali.
Location
Kota denpasar,
Bali
INDONESIA
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 3 Documents
 1 
Search results for , issue "Vol. 15 No. 1 (2026)" : 3 Documents clear
ANALISIS SENTIMEN PROGRAM MAKAN BERGIZI GRATIS MENGGUNAKAN SVM DAN KNN DENGAN TF-IDF DAN TF-ABS MAJIDAH, SEVIRA HUKMAN; HENDIKAWATI, PUTRIAJI
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.
METODE REGRESI MULTILEVEL UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR LAMA MASA STUDI MAHASISWA FMIPA UNIVERSITAS UDAYANA UTAMI, DEWA AYU MADE SRI WIJAYATI; SUSILAWATI, MADE; SUKARSA, I KOMANG GDE
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 NINGTIAS, YESINTA KHARISMA; QOMARUDIN, M. NUR HAQQUL; AKBARITA, RACHMADANIA; ROBBY, RIZKA RIZQY
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.

Page 1 of 1 | Total Record : 3

 1 

Filter by Year

2026 2026


Reset
Filter By Issues
All Issue Vol. 15 No. 1 (2026) Vol. 14 No. 4 (2025) Vol. 14 No. 3 (2025)