Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Matematika E-Jurnal Matematika
Tjokorda Bagus Oka
Faculty Of Mathematics And Natural Sciences, Udayana University
Mathematics

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 18 Documents
Search

 1   2 
MODEL SIR (SUSCEPTIBLE, INFECTIOUS, RECOVERED) UNTUK PENYEBARAN PENYAKIT TUBERKULOSIS K. QUEENA FREDLINA; TJOKORDA BAGUS OKA; I MADE EKA DWIPAYANA
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
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.2012.v01.i01.p009

Abstract

Tuberkulosis (TB) merupakan salah satu penyakit penyebab kematian di negara berkembang. Oleh karena itu, perlu dilakukan analisis yang dapat diterima secara ilmiah terhadap peristiwa penyebaran penyakit tuberkulosis. Salah satunya dapat dipandang dalam bentuk model matematika. Model penyebaran penyakit TB yang disusun menghasilkan persamaan model yang menggambarkan penyebaran penyakit TB pada kelas susceptible, infectious dan recovered. Model yang terbentuk perlu dianalisis dengan mencari titik kritis, nilai eigen dan basic reproduction ratio. Kemudian dilakukan simulasi menggunakan metode Runge-Kutta orde 4 untuk menguji analisis parameter. Dari hasil analisis akan didapat parameter yang paling berpengaruh dalam penyebaran tuberkulosis adalah laju penularan dan laju kesembuhan. Dengan demikian penyebaran tuberkulosis dapat dikendalikan dari kejadian epidemi dengan membuat   atau menurunkan laju penularan dan meningkatkan laju kesembuhan.
PENERAPAN METODE PENDUGAAN AREA KECIL (SMALL AREA ESTIMATION) PADA PENENTUAN PROPORSI RUMAH TANGGA MISKIN DI KABUPATEN KLUNGKUNG PUTU EKA ARIWIJAYANTHI; I WAYAN SUMARJAYA; TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 2 No 3 (2013)
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.2013.v02.i03.p046

Abstract

Small area is an area with insufficient sample for direct estimation. Limited survey objects, cause direct estimation can not produce better parameter estimates. Based on this, an indirect estimation method called empirical Bayes is used to obtain a better estimate. This study will compare means squared error by  direct estimation method and empirical Bayes method to find a better method on a small area. Jackknife is used to get the means squared error in the empirical Bayes. The results is, empirical Bayes methods give a better parameters based on mean squared errors. Empirical Bayes can produce a smaller mean squared error more than direct estimation in small area.
ANALISIS KUNJUNGAN ULANG WISATAWAN NUSANTARA DENGAN MODEL KONSTRUK BERHIERARKI DWI HERAYANTHI W.; KOMANG GDE SUKARSA; TJOKORDA BAGUS OKA; EKA N. KENCANA
E-Jurnal Matematika Vol 5 No 4 (2016)
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.2016.v05.i04.p140

Abstract

This research is aimed to analyze the effect of domestic tourists’ satisfaction towards their intention to revisit destinations at Badung Regency, Province of Bali by using hierarchical construct modeling. Data from 75 local tourists were collected in July through December 2015 and were used to model this causal relationship.  In our model, destination attributes, tourist’s facilities, and destination accessibilities were positioned as the second-order constructs and proposed have effect on tourists’ satisfaction.  Futhermore, satisfaction – in turns – is proposed affects tourist intention to revisit.  We found destination attributes significantly affect tourist satisfaction with its causal value is 0.410 and this satisfaction significantly affects their intention to revisit tourism destinations at Badung Regency with path value as much as 0.764.
PENERAPAN STATIC HEDGE DALAM PENGELOLAAN RISIKO PADA OPSI TIPE BARRIER NI MADE NITA ASTUTI; KOMANG DHARMAWAN; TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 7 No 4 (2018)
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.2018.v07.i04.p225

Abstract

The barrier option is an option whose payoff depends on whether the underlying asset touches the barrier or not during the lifetime of the option. The determination of the barrier option requires a numerical approach, one of which is the Binomial Tree model. The purpose of this study is to determine barrier option type down and out call on a static hedging using the Binomial Tree model and compare it with the analytic value. The results show that the increases in strike price would decrease the option value. Moreover, values from 80 periods using the Binomial Tree model for the four strike prices are close to analytic with error less than or equal to 0.00182.
PENENTUAN CADANGAN PREMI DENGAN METODE NEW JERSEY PADA ASURANSI JOINT LIFE JENNE LALI TEWO; I NYOMAN WIDANA; TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 7 No 3 (2018)
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.2018.v07.i03.p207

Abstract

Joint Life insurance is an insurance that covered two individuals in one policy. The purpose of this research is to determine and to compare the reserve value of Joint Life insurance using New Jersey method and Prospective method with and without New Jersey method. The method that used in this research are New Jersey method, the participants of this assurance is a couple of husband and wife between 45 and 40 years old with 30 years period, interest levels at 6,5%. The results of this represent reserve value with New Jersey method always smaller, and the reserve value in the 30 years period have the same result using New Jersey method and Prospective method.
KAJIAN TERHADAP TINGKAT PEMERATAAN PENDIDIKAN MENGGUNAKAN ANALISIS BIPLOT KLASIK DAN BIPLOT KEKAR NI LUH ARDILA KUSUMAYANTI; I KOMANG GDE SUKARSA; TJOKORDA BAGUS OKA; I PUTU EKA N. KENCANA
E-Jurnal Matematika Vol 4 No 2 (2015)
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.2015.v04.i02.p086

Abstract

The aim of this research is to find the better from classical and robust biplot in determine dominant indicators of educational equity in Bali, NTB and NTT Provinces. This research based on secondary data obtain from Central Bureau of Statistics for year 2012/2013. Educational equity was portraited by Classical and Robust Biplot. The results of this research showed Robust Biplot is better method which goodness of fit is 90,64% meanwhile Classical Biplot as much as 83,62%. The Robust Biplot showed Students- Junior or Islamic Middle School Ratio and Students-Senior or Islamic High School were dominant indicators to educational equity in Bali,  NTB and NTT Provinces.
ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI WAKTU KELULUSAN MAHASISWA DENGAN MENGGUNAKAN METODE GOMPIT (Studi Kasus: Mahasiswa Fakultas MIPA Universitas Udayana) NI KOMANG DEBY ARIANI; I WAYAN SUMARJAYA; TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 2 No 3 (2013)
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.2013.v02.i03.p047

Abstract

The aims of this research analyzed the factors affecting the period of the students’ graduation based on GPA at Faculty of Mathematics and Natural Science, Udayana University by using gompit regression. This data strongly indicates unbalanced between students who graduated on time and students who graduated not on time. The result of this study indicates that the graduation of the students based on the GPA categorization satisfied all of the independent variables was not significant. Meanwhile, for the graduation of the students based on the GPA categorization was highly satisfied. There are four dependent variables which are significant, such as: gender, study program, region, and the final assignment accomplishment period. Moreover, for the students’ graduation based on the GPA categorization with praises, there were two independent variables which were significant: region and the final assignment accomplishment period.
ANALISIS SENTIMEN MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER DENGAN SELEKSI FITUR CHI SQUARE JUEN LING; I PUTU EKA N. KENCANA; TJOKORDA BAGUS OKA
E-Jurnal Matematika Vol 3 No 3 (2014)
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.2014.v03.i03.p070

Abstract

Sentiment analysis is the computational study of opinions, sentiments, and emotions expressed in texts. The basic task of sentiment analysis is to classify the polarity of the existing texts in documents, sentences, or opinions. Polarity has meaning if there is text in the document, sentence, or the opinion has a positive or negative aspect. In this study, classification of the polarity in sentiment analysis using machine learning techniques, that is Naïve Bayes classifier. Criteria for text classification decisions, learned automatically from learning the data. The need for manual classification is still required because training the data derived from manually labeling, the label (feature) refers to the process of adding a description of each data according to its category. In the process of labeling, feature selection is used and performed by chi-square feature selection, to reduce the disturbance (noise) in the classification. The results showed that the frequency of occurrences of the expected features in the true category and in the false category have an important role in the chi-square feature selection. Then classification breaking news by Naïve Bayes classifier obtained an accuracy of 83% and a harmonic average of 90.713%.
Co-Authors Ahmad Fitri Ahmad Fitri AMI HILDA AGUSTIN DWI HERAYANTHI W. EKA N. KENCANA Eka N. Kencana G. K. GANDHIADI I Gede Oka Artawan I GUSTI AYU MITA ERMIA SARI I KOMANG GDE SUKARSA I MADE EKA DWIPAYANA I Nyoman Widana I Putu Eka Nila Kencana I Wayan Sumarjaya JENNE LALI TEWO JUEN LING Ketut Queena Fredlina Komang Dharmawan LUH PUTU IDA HARINI MELINDA HERMANTO NI KADEK SUMARWATI NI KOMANG DEBY ARIANI NI LUH ARDILA KUSUMAYANTI NI MADE NITA ASTUTI PUTU EKA ARIWIJAYANTHI