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All Journal Jurnal Ilmu Dasar Jurnal Gaussian KADIKMA BERKALA SAINSTEK Tadris: Jurnal keguruan dan Ilmu Tarbiyah Prosiding Seminar Matematika dan Pendidikan Matematik Jurnas Nasional Teknologi dan Sistem Informasi UNEJ e-Proceeding Indonesian Journal of Applied Statistics International Conference on Mathematics and Science Education of Universitas Pendidikan Indonesia Majalah Ilmiah Matematika dan Statistika (MIMS) JURNAL BIOSHELL Jurnal Ilmiah Matematika Pancaran Pendidikan JPMA Jurnal Statistika dan Komputasi (STATKOM) Jurnal Hasil Pengabdian Kepada Masyarakat Universitas Jember
I Made Tirta
Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Jember
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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PENERAPAN MODEL LEAST SQUARE SUPPORT VECTOR MACHINE (LSSVM) UNTUK PERAMALAN KASUS COVID-19 DI INDONESIA Lutfi Ardining Tyas; I Made Tirta; Yuliani Setia Dewi
Jurnal Gaussian Vol 12, No 2 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.2.304-313

Abstract

Forecasting is about predicting the future based on historical data and any information that might affects the forecasts. This article applies the LSSVM model to forecast Covid-19 cases in Indonesia. The purpose of this study is to find out how the LSSVM model applied and the model performances for forecasting Covid-19 cases in Indonesia, using time series data and the factors that influence it, as input features. The factor data used in this study are mobility data and daily fully vaccinated data. The research has three main objectives; first, calculate the correlation between confirmed cases data and past data (lag) of mobility and vaccination. Second, is the selection of input features based on the highest correlation coefficient value of each variable. Third, do LSSVM modeling and Covid-19 case forecasting with the optimal model. RBF kernel and grid-search algorithm with 10-fold cross-validation are used to tune model parameters. The results show that the LSSVM model provides good performance for Covid-19 forecasting and the optimal LSSVM model for forecasting Covid-19 cases in Indonesia is using time lag 14 for the mobility factor and time lag 24 for the vaccination factor.
Analysis of the Death Risk of Covid-19 Patients Using Extended Cox model Romarizka, Cyndy; Fatekurohman, Mohamat; Tirta, I Made
Jurnal ILMU DASAR Vol 24 No 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v24i1.33074

Abstract

Globally, in 2021, there were 170,051,718 COVID-19 cases and 3,540,437 patients who died. The high mortality rate of patients infected with COVID-19 gives an idea to research the analysis of the factors that influence the death of Covid-19 patients. The data used in this study is data on Covid-19 patients obtained from the Mexican Government, with response variables namely time and status and predictor variables, namely patient laboratory results in the form of a history of illness that has been suffered by Covid-19 patients so that they adopt the extended model to evaluate the data. The data in this study are heterogeneous and large in number so that data clustering is carried out into 3 clusters, namely low emergency clusters, medium emergency clusters and high emergency clusters using K-means clustering. Because the study could not find the factors that influence the death of Covid-19 patients, two clusters were chosen, namely the medium emergency cluster and the high emergency cluster. So that the factors that influence the death of Covid-19 patients in the medium emergency cluster are sorted by the highest hazard ratio, namely pneumonia, old age, renal chronic, diabetes, Chronic Obstructive Pulmonary Disease (COPD), immune system, hypertension, cardiovascular, obesity, gender, and asthma. In the high emergency cluster, sorted by the highest hazard ratio is the immune system, renal chronic, cardiovascular, COPD, tobacco, hypertension, obesity, gender, and pneumonia.
PERAMALAN PERTUMBUHAN PENDUDUK KABUPATEN SITUBONDO DENGAN MODEL ARIMA, DERET ARITMATIK, DERET GEOMETRI DAN DERET EKSPONENSIAL “THE FORECASTING GROWTH OF THE POPULATION IN SITUBONDO BY USING ARIMA, ARITMATICS, GEOMETRICS AND EXPONENTIAL” As’ad, A; Tirta, I Made; Dewi, Yuliani Setia
Kadikma Vol 4 No 1 (2013): April 2013
Publisher : Department of Mathematics Education , University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/kdma.v4i1.1123

Abstract

Abstract. ARIMA models as the population forecasting in Situbondo is a model of ARIMA(3, 3, 3) and mathematically, it is stated as; =2,445–1,6632–0,148+0,9732–1,0746+ 0,4676+– 1,0635. Forecasting the population in Situbondo is 667646 people in 2012 and in 2013 is 677852 people. Some other approaches in determining the population is the Arithmetic growth formula, the result of forecasting in 2012 is 657540 people and in 2013 is 661626 people, Based on Geometric growth formula, the result of forecasting in 2012 is 19696459 people and in 2013 is 35211214 people and Based on Exponential growth formula the result of forecasting in 2012 is 657611 people and in 2013 is 661799 people. If we compare the data of the forecasted result of ARIMA model with the Aritmatics growth formula and Exponential growth formula, show that the data of the population with the last ten actual data is relatively similiar.The closed last ten actual data forecasting of population is the aritmatics growth formula, whereas the data of the population result for next two year based on the Geometric growth formula got the forecasted result which is different from the forecasted result of ARIMA model, Aritmatics growth formula and Exponential growth formula. Key Words:forecasting, arima models, arithmetic, geometric, exponential
POLA-POLA JALUR PADA PATH ANALISYS UNTUK ANALISIS FAKTOR-FAKTOR YANG BERPENGARUH TERHADAP NILAI UN SMA DI KABUPATEN LUMAJANG Isdarmawan, Agus; Tirta, I Made; Dewi, Yuliani Setia
Kadikma Vol 4 No 1 (2013): April 2013
Publisher : Department of Mathematics Education , University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/kdma.v4i1.1118

Abstract

Abstract. Path analysis is a technique to analyze the effect of free and bound variables in which every variable correlates or associates with cause and effect directly or indirectly. This study was conducted to determine some factors which influenced National Examination at Senior High School in Lumajang. The Data were analyzed using path analysis. The results of the study were explained as follows: 1. The correlation of variables in path analysis followed the pattern of direct, indirect and mixed. 2. Path analysis could be applied to the analysis of the relationship between exogenous variables (Practical Training (X1), Assignment (X2), and Daily Test (X3)) with endogenous variables (Mid-Term Test (Y1), Final-Term Test (Y2), and National Examination (Z)). Daily Test (X3) contributed directly to Mid-Term Test (Y1). On the other hand, Practical Training (X1) and Daily Test (X3) did not contribute significantly to the Final-Term Test (Y2). 3. Assignment (X2) has direct and indirect influence on National Examination (Z) through Final-Term Test (Y2). 4. Daily Test (X3) did not have a direct influence to Final-Term Test (Y2) but it had a direct impact either through National (Z or through Mid-Term Test (Y1) and Final-Term Test (Y2) which contributed 19.6% of the total site. The direct contribution of Mid-Term Test (Y1) to National Examination (Z) was the highest direct contribution in this study with 40% of the total site. While, the contribution of Practical Training (X1), Assignment (X2), Daily Test (X3), Mid-Term Test (Y1), and Final-Term Test (Y2) simultaneously influenced National Examination (Z) with 93.5% . Abaut 6.5% was influenced by the other factors which could not be described in this study. Key Words : National Examination, Path Analysis, Variable Exogenous, endogenous variables
Application of Black Scholes Method in Determining Agricultural Insurance Premium Based On Climate Index Using Historical Burn Analysis Method Sholiha, Aminatus; Fatekurohman, Mohamat; Tirta, I Made
BERKALA SAINSTEK Vol 9 No 3 (2021)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v9i3.22920

Abstract

Climate index insurance is an insurance that provides reimbursement for losses due to decreased harvest rates or crop failures caused by weather. The use of Historical Burn Analysis (HBA) method in determining climate index based on rainfall resulted in a concept of the agricultural insurance payment in Pasuruan Regency. The application of The Black Scholes method in determining agricultural insurance premiums is obtained when rainfall more than 17 mm the premium is Rp 221,234. If the rainfall are 13 mm ≥ RR < 17 mm, the nominal premium paid by farmers to the insurance party is Rp 147,489. Respondents in the study were farmers who owned rice fields. Instrument quality testing (questionnaire) using validity test and reliability test using the help of SPSS statistical software. It can be concluded that the questionnaire is valid and reliable. Based on the results of the questionnaire, farmers considered that the nominal agricultural insurance premiums are in accordance with farmers' income.
Comparison of Online and Offline Learning During The COVID-19 Pandemic using Naïve Bayes Method and C4.5 Aulia, Andini Cahya; Fatekurohman, Mohamat; Tirta, I Made
BERKALA SAINSTEK Vol 11 No 3 (2023)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v11i3.31737

Abstract

Learning is a process of interaction between educators and students who meet the elements of learning carried out in an educational environment, so that learning can develop student’s abilities, interests and talents optimally. In today's era learning is done online and inversely with offline. The purpose of this study is to analyze the comparison of percentages and classification results as well as the results of learning evaluations using the Naïve Bayes method and C4.5. This test is carried out with 4 variables and a comparison of the two methods. The results showed that the accuracy of Naïve Bayes was 74.07% and C4.5. of 77.77% so that the comparison results show that the level of accuracy of the C4.5 method is better than Naïve Bayes. The resulting importance variables are time and effectiveness as well as the results of the classification of learning decisions, namely the offline category as many as 16 data on the Naïve Bayes method and 19 data on the Decision Tree algorithm C4.5 method from 27 input testing data.
ANALISIS REGRESI KELAS LATEN UNTUK DATA KATEGORIK DENGAN SATU KOVARIAT Haeruddin, Haeruddin; Tirta, I Made; Dewi, Yuliani Setia
BERKALA SAINSTEK Vol 1 No 1 (2013)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Analisis regresi kelas laten merupakan analisis multivariat untuk data kategorik. Estimasi parameter pada analisis regresi kelas laten menggunakan algoritma EM (ekspektasi-maksimisasi) yang dilanjutkan dengan metode Newton-Raphson. Dalam penelitian ini, analisis regresi kelas laten digunakan untuk mengklasifikasikan responden berdasarkan persepsinya terhadap peluang (opportunity) dan ancaman (treath) bagi distributor produk Unilever, PT. Panahmas Dwitama Distrindo Regional Jember. Lamanya responden berlangganan terhadap distributor ini dijadikan sebagai kovariat. Hasil analisis menunjukkan bahwa berdasarkan persepsinya terhadap opportunity, responden dikelompokkan menjadi tiga kelompok, sedangkan terhadap treath dikelompokkan menjadi dua kelompok.
Klasifikasi penyakit Demam Berdarah Dengue (DBD) menggunakan algoritma C5.0 berbasis Binary Particle Swarm Optimization (BPSO) Ani Rimadani; Agustina Pradjaningsih; I Made Tirta
Jurnal Ilmiah Matematika Vol. 9 No. 2 (2022)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/konvergensi.v9i2.26089

Abstract

Dengue Hemorrhagic Fever, or DHF, is an infectious disease caused by the dengue virus. Diseases that are dangerous and at risk of death must be treated quickly and precisely. The determination that someone is suffering from DHF or not can be done with the classification technology, namely the decision tree method, the C5.0 algorithm. Over time, the number of features in the classification increases. Feature reduction is needed for a good model, namely the Binary Particle Swarm Optimization (BPSO) algorithm. This research used 13 features consisting of 12 independent features and one bound feature with two classes: Positive and Negative. The better model in this study is the classification C5.0 algorithm based on BPSO, which can reduce features from 12 to 9 features with an accuracy of 86% compared to classification with the C5.0 algorithm alone, which produces an accuracy of 71%.
Analisis Ketahanan Hidup Pasien COVID-19 Menggunakan Pendekatan Multivariate Adaptive Regression Spline (MARS) Khoirunnisa, Wilda; Fatekurohman, Mohamat; Tirta, I Made
Jurnal Statistika dan Komputasi Vol. 3 No. 1 (2024): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/statkom.v3i1.2700

Abstract

Latar   Belakang: Tahun 2019 dunia digemparkan dengan terjadinya penyebaran penyakit baru yaitu Coronavirus Disease 19 (COVID-19) yang merupakan penyakit menular disebabkan oleh jenis corona virus bernama Severe Acute Repiratory Syndrome Coronavirus 2 (SARS-CoV-2). Virus ini menyebabkan gangguan pada sistem pernapasan, infeksi paru-paru, pneumonia akut, bahkan kematian, sehingga dilakukan analisis ketahanan hidup pasien COVID-19. Tujuan: Mendapatkan model dan mengetahui faktor paling mempengaruhi ketahanan hidup pasien COVID-19 di RSD dr. Soebandi Jember berdasarkan variabel prediktor yang digunakan. Metode: Penelitian ini menggunakan metode pendekatan MARS untuk menganalisis data. Data yang digunakan yaitu data rekam medis pasien COVID-19 tahun 2020 – 2021 di RSD dr. Soebandi Jember. Hasil: Model MARS terbaik berdasarkan kombinasi Basis Function (BF), Maximum Interaction (MI), dan Minimum Observation (MO) yang bernilai masing-masing 24, 3, dan 0 dengan nilai Generalized Cross Validation (GCV) terkecil yaitu 0,135. Berdasarkan model MARS yang diperoleh, 7 dari 12 variabel prediktor yang digunakan berpengaruh pada ketahanan hidup pasien COVID-19 yaitu usia, jenis kelamin, status gagal napas, status hipertensi, status pneumonia, status koagulopati, dan status penyakit lainnya. Kesimpulan: Variabel yang paling mempengaruhi ketahanan hidup pasien COVID-19 di RSD dr. Soebandi menggunakan pendekatan MARS berdasarkan variabel prediktor yang digunakan adalah status gagal napas.  
Enhancing Students' Combinatorial Thinking for Graceful Coloring Problem: A STEM-Based, Research-Informed Approach in ATM Placement Adawiyah, Robiatul; Kristiana, Arika Indah; Dafik, Dafik; Asy’ari, Muhammad Lutfi; Tirta, I Made; Ridlo, Zainur Rasyid; Kurniawati, Elsa Yuli
Tadris: Jurnal Keguruan dan Ilmu Tarbiyah Vol 8 No 1 (2023): Tadris: Jurnal Keguruan dan Ilmu Tarbiyah
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/tadris.v8i1.15176

Abstract

Combinatorial generalization thinking, a component of higher-order thinking skills, encompasses perception (pattern identification), expressions (pattern illustration), symbolic expressions (pattern formulation), and manipulation (combinatorial results application). Implementing a research-based learning (RBL) model with a Science, Technology, Engineering, and Mathematics (STEM) approach can effectively transform students' learning processes, promoting experiential learning through the integration of STEM elements. This study employs a mixed-method research design, combining quantitative and qualitative methodologies, to evaluate the impact of this RBL-STEM model on students' ability to solve graceful coloring problems, hence developing their combinatorial thinking skills. Two distinct classes, one experimental and one control, were analyzed for statistical homogeneity, normality, and independent t-test comparisons. Results indicated a significant post-test t-score difference between the two groups. Consequently, we conclude that the RBL model with a STEM approach significantly enhances students' combinatorial generalization thinking skills in solving graceful coloring problems. As this research provides empirical evidence of the effectiveness of a STEM-based RBL model, educators, and curriculum developers are encouraged to incorporate this approach into their instructional strategies for enhancing combinatorial thinking skills. Future research should consider various contexts and diverse student populations to further validate and generalize these findings.
Co-Authors A As’ad Agus Isdarmawan Agustina Pradjaningsih Alfian Futuhul Hadi Anak Agung Gede Sugianthara Andina Ishmah Almira, Andina Ishmah Ani Rimadani Anisa Fitri Anjani Anjani, Anisa Fitri Arika Indah Kristiana Asy’ari, Muhammad Lutfi As’ad, A Aulia, Andini Cahya Budi Lestari Budi Lestari D. Dafik Dian Anggraeni Dian Anggraeni Dian Anggraeni Elsa Yuli Kurniawati Erfan Syahuri Habibi, Azwar Haeruddin Haeruddin Haeruddin Haeruddin Holipah, Holipah Ikhsanul Halikin, Ikhsanul Indriasih Yanuwijaya Istiqomah, Fikriana Nur Kasmuri Kasmuri Kasmuri Kasmuri, Kasmuri Khoirunnisa, Wilda Kurniawati, Elsa Yuli Kusbudiono Kusbudiono, Kusbudiono Lutfi Ardining Tyas M Fatekurrahman M. Isnaini Marino Marino, Marino Maulidani, Noor Dyah Miftahul Ulum Mohamad Fatekurohman Muhammad Lutfi Asy’ari Mutiarasari, Yusna Nawal Ika Susanti, Nawal Ika Paramitha, Luckyta Citra Ayu Ridlo, Zainur Rasyid Rizka Dwi Hidayati Robiatul Adawiyah Robiatul Adawiyah Romarizka, Cyndy Sholiha, Aminatus T C P Utama Tika Clarinta Putri Utama Wilujeng, Dian Tri Yeni Rismawati Yuliani Setia Dewi Zainur Rasyid Ridlo