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All Journal Jurnal Matematika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JOURNAL SCIENTIFIC OF MANDALIKA (JSM)
I Putu Winada Gautama
Universitas Udayana
Humanities Computer Science & IT Languange, Linguistic, Communication & Media Mathematics Other

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Penentuan Rute Terpendek dengan Menggunakan Algoritma Dijkstra pada Jalur Bus Sekolah I Putu Winada Gautama; Koko Hermanto
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p128

Abstract

Peran angkutan umum atau bus sekolah sangat vital dalam mengurangi pelanggaran lalu lintas bagi pengendara di bawah umur. Alat transportasi bus sekolah mulai populer di Bali. Khususnya di kota Denpasar, dinas perhubungan Kota Denpasar sudah beroperasi pada bulan September 2017. Salah satu optimasi yang dapat dilakukan adalah menentukan jarak terpendek dari rute bus sekolah. Semakin pendek jarak yang dilalui tentunya berdampak pada biaya dan waktu. Biaya yang dikeluarkan dapat diminimalkan dan waktu tempuh lebih efisien. Berdasarkan hasil yang diperoleh bahwa biaya bahan bakar yang dihabiskan bus sekolah shift pagi adalah Rp 70.132,-. Hasil ini dapat memberikan gambaran untuk Dinas Perhubungan kota Denpasar mengenai terapan matematika dalam menentukan rute yang dapat mengoptimalkan pengeluaran biaya bahan bakar
Analisis Sensitivitas Pada Model Matematika Penyebaran Penyakit Demam Dengue dengan Laju Insidensi NonLinier I Putu Winada Gautama; Ni Kadek Nova Anggarani; I Made Eka Dwipayana; Putu Veri Swastika
Jurnal Matematika Vol 12 No 2 (2022)
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.2022.v12.i02.p155

Abstract

Abstract: Dengue fever is a disease that can be fatal if not treated seriously. This disease is transmitted to humans through the Aedes Aegypti mosquito. Mathematical modeling is a tool used to understand the dynamics of dengue fever. Incomplete data creates uncertainty in the parameter values of the mathematical model. Uncertainty analysis to determine these parameters using sensitivity analysis. This study found that the bite rate of susceptible and infected mosquitoes and the mosquito death rate have a large influence on changes in the value of . Human recovery rate (r), mosquito mortality rate , and human mortality rate have a major influence on infected human individuals . The bite rate of susceptible and infected mosquitoes has the most positive influence on the number of infected mosquitoes . The mortality rate of mosquitoes had the most negative relationship with the number of mosquitoes infected with . Numerical simulations are carried out to determine the dynamics that occur when parameter values are increased or decreased. Keywords: Sensitivity Analysis, Dengue Fever, Mathematical Modeling
Named Entity Recognition for Medical Records of Heart Failure Using a Pre-trained BERT Model Manurung, Mikael Triartama; I Gusti Ngurah Lanang Wijayakusuma; I Putu Winada Gautama
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9170

Abstract

This study aims to develop a Named Entity Recognition (NER) model based on a pre-trained BERT model for medical records of heart failure patients. The focus of this research is to classify essential medical entities from unstructured medical record texts. The classification covers four categories: objective data (patient identity, laboratory test results, and objective examination data), subjective data (patient complaints), prescriptions, and diagnoses (diagnosis codes and descriptions). The methodology employs Natural Language Processing (NLP) techniques using Transformer-based architectures, such as Bidirectional Encoder Representation from Transformers (BERT). The developed model is evaluated based on entity label prediction accuracy and medical entity classification performance. The results indicate that the BERT-based NER model performs well, achieving an entity prediction accuracy of 84.82%. Furthermore, the model effectively classifies medical entities from input texts in alignment with expected medical entities. This research is expected to contribute significantly to medical data management, assist healthcare professionals in clinical decision-making, and serve as a reference for the development of AI-based healthcare technology in Indonesia.
Pengelompokan Provinsi Di Indonesia Berdasarkan Indikator Kesehatan Balita Menggunakan Metode Agglomerative Clustering Ana Fikria; I Komang Gede Sukarsa; I Putu Winada Gautama; Made Ayu Dwi Octavanny; Anggun Yuliarum Qur’ani; Desak Putu Eka Nilakusmawati
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 7 No. 1 (2026)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol7iss1pp71-80

Abstract

Child Health is a crucial indicator in assessing the overall health of a population. However, there are disparities between provinces in terms of healthcare access, immunization coverage, and child nutrition status. Therefore, this study aims to cluster 38 provinces in Indonesia based on infant health indicators using the Agglomerative Hierarchical Clustering method. The data used is sourced from the 2023 Indonesian Health Profile Report, with variables including neonatal visit coverage, complete basic immunization, infant weighing, and the prevalence of infants with severe underweight, stunting, and malnutrition. The five agglomerative methods applied in this study are Single Linkage, Complete Linkage, Average Linkage, Centroid, and Ward. The results indicate disparities in child health conditions across provinces, with clusters representing regions with good, moderate, and poor conditions. These findings can serve as a reference for the implementation of the Free Nutritious Meal Program (MBG) in 2025 to better target areas with high vulnerability, in order to reduce stunting rates and improve overall child nutritional status.
Co-Authors Ana Fikria Anggun Yuliarum Qur’ani Desak Putu Eka Nilakusmawati FARREL WILLIEARDAN Hermanto, Koko I GUSTI NGURAH SENTANA PUTRA I Komang Gede Sukarsa I Made Eka Dwipayana I Nyoman Widana I Putu Eka Nila Kencana MADE AYU DWI OCTAVANNY Made Susilawati Manurung, Mikael Triartama Ni Kadek Nova Anggarani Ni Luh Putu Suciptawati Putu Veri Swastika Wijayakusuma, I Gusti Ngurah Lanang