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DISTRIBUTED LAG MODEL PENGARUH JUMLAH UANG BEREDAR TERHADAP NILAI TUKAR RUPIAH MENGGUNAKAN METODE KOYCK DAN ALMON SRIRAPI H LIHAWA; RESMAWAN RESMAWAN; DEWI RAHMAWATY ISA; LA ODE NASHAR
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.11805

Abstract

A regression model that contains the dependent variable which is influenced by the current independent variable, and is also influenced by the independent variable at the previous time is called a distributed lag model. Distributed lag model is a dynamic model in econometrics that is useful in empirical econometrics because it makes a static economic theory dynamic by taking into account the role of time explicitly. There are two distributed lag models, namely the infinite lag model and the finite lag model using the Koyck method and the Almon method in determining the estimated Distributed lag model. This study aims to determine the Distributed lag model for the effect of the money supply on the rupiah exchange rate and determine the best model based on the Koyck method and the Almon method. From the results of selecting the best model based on the SIC value and judging by the more precise R2 of the Koyck method, the resulting model ist  = 7958 + 0.0002Xt + 0.000177Xt-1+ 0.000157Xt-2+ 0.000139Xt-3 + 0.0000123Xt-4
ESTIMASI PARAMETER COX SEMIPARAMETRIC HAZARDS MODEL DENGAN METODE EFRON PADA DATA TERSENSOR KANAN TEDY MACHMUD; LA ODE NASHAR; DINA FAKHRIYANA; LA ODE SABRAN
Jurnal Matematika UNAND Vol 10, No 3 (2021)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.10.3.394-405.2021

Abstract

Salah satu kendala yang sering dihadapi pada penelitian survival adalah adanya data tersensor. Jika data tersensor dihilangkan, maka akan terjadi bias. Pengolahan data tersensor dapat dilakukan dengan Cox Semiparametric Hazards model. Pada penelitian ini, digunakan data tersensor kanan yang dianalisis dengan Cox semiparametric hazards model, yang parameternya diestimasi dengan metode Efron. Pada penelitian ini dilakukan studi kasus dengan menganalisis Hazard rasio terjadinya diabetik retinopati pada pasien diabetes tipe juvenile dan tipe adult. Setelah melakukan stratifikasi jenis mata yang dilakukan treatment, diperoleh risiko terjadinya retinopati pada penderita diabetes tipe adult 0.678 kali dari penderita diabetes tipe juvenile. Artinya, risiko terjadinya diabetik retinopati pada penderita diabetes tipe adult 0.322 kali lebih besar dari penderita diabetes tipe juvenile.Kata Kunci: Cox Semiparametric Hazards model, Data tersensor Kanan, Metode Efron
Bilangan Terhubung Titik Pelangi Kuat Graf Octa-Chain (OCm) Nisky Imansyah Yahya; Karina Anselia Mamonto; Nurwan Nurwan; Lailany Yahya; Djihad Wungguli; La Ode Nashar
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 10 Issue 1 June 2022
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/euler.v10i1.15177

Abstract

An Octa-Chain graph (OCm) is a graph formed by modifying the cycle graph C8 by adding an edge connecting the midpoints in C8. The minimum number of colors used to color the vertices in a graph so that every two vertices have a rainbow path is called the rainbow vertex-connected number denoted by rvc (G). While the minimum number of colors used to color the vertices in a graph so that every two vertices are always connected by a rainbow path is called a strong rainbow vertex connected number and is denoted by srvc (G). This study aims to determine the rainbow vertex-connected number (rvc) and the strong rainbow-vertex-connected number (srvc) in the Octa-Chain graph (OCm). The results obtained from this research are the rainbow vertex-connected number rvc (OCm)=2m and the strong rainbow-vertex-connected number srvc (OCm)=2m.
Teorema Titik Tetap untuk Kontraksi Reich Siklik pada Ruang Kuasi αb-Metrik Asriadi Asriadi; NURWAN NURWAN; LA ODE NASHAR
Jurnal Matematika UNAND Vol 11, No 2 (2022)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.11.2.133-140.2022

Abstract

Pemetaan kontraksi Reich siklik pada ruang kuasi αB-metrik akan diperkenalkan dalam tulisan ini. Akan ditunjukkan bahwa setiap pemetaan kontraksi Reich siklik memiliki titik tetap yang tunggal. Selain itu, diberikan pula contoh fungsi yang memenuhi kontraksi Reich siklik.
Analisis Data Tersensor Kanan dengan Metode Cox Proportional Hazard Model La Ode Nashar; Asriadi Asriadi; Dewi Rahmawaty Isa
Journal of Science and Technology Vol 2, No 2: September 2022
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v2i2.4434

Abstract

In time series data research, it is often encountered the problem of lack of available time and budget. So often found the presence of censored data. Censored data can be analyzed using the partial likelihood method. However, other obstacles will arise if the processed data contains ties. So it is necessary to use other methods that can overcome the co-occurrence. In this study, the Breslow method is used to estimate the censored data due to joint events. This method is applied to the case of patients with burns. The variables used are the method of treatment, gender, race and type of burn. The results of the analysis showed that race did not give a significant difference to the incidence of cutting burned organs. While the other three variables showed significant differences at the 95% confidence level. The results of the analysis using the Cox proportional hazard method showed that patients treated with the body cleansing method had 17% greater risk of cutting than those treated with the body routhine bathing. 
IMPLEMENTASI IMRPOVED CHI-SQUARE AUTOMATIC INTERACTION DETECTION PADA KLASIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI LITERASI INFORMASI GENERASI MUDA Zian Bula; Resmawan Resmawan; La Ode Nashar; Salmun K. Nasib
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06207

Abstract

Information Literacy skills are needed to find quality sources and manage and sort information so that it can be used to improve the quality of life and community empowerment. The number of factors that affect information literacy causes the need for classification. The method used is Improved Chi-Square Automatic Interaction Detection (Improved CHAID), which aims to classify influencing factors with Information Literacy abilities. This study uses primary data, namely 237 Mananggu Young Generation (15-24 years), with Information Literacy as the dependent variable. The independent variables consist of reading interest, reading habits, gender, digital literacy, information needs, critical thinking, and information-seeking behavior. Based on the Improved CHAID analysis, the factors that significantly affect information literacy are Reading Habits (83%), Information Needs (89%), and Critical Thinking (94%). The classification performance of Testing Data is 40%, with a classification accuracy of 77% or from 95 samples, there are 73 samples that are properly classified. The sensitivity of 78% shows that the classification results are able to predict samples that have information literacy, 74% specificity indicates that the classification results are able to predict samples that do not have information literacy, and Press's Q 27.38 indicates a stable classification or statistically significant.
Optimasi Portofolio Saham Syariah Menggunakan Model Indeks Tunggal dan VaR Berbasis GUI Matlab Lindrawati Abdjul; Resmawan Resmawan; Agusyarif Rezka Nuha; Nurwan Nurwan; Djihad Wungguli; La Ode Nashar
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i1.18570

Abstract

Sharia-based investment is an investment by the community to obtain profits in accordance with Islamic principles and law. This study aims to calculate the optimal portfolio return value using the Single Index Model, calculate risk with VaR (Value at Risk), and then implement it with Matlab’s GUI (Graphical User Interface). The data used is closing stock price data on the JII (Jakarta Islamic Index) using 30 stocks for two consecutive years. Furthermore, these stocks are selected which have a positive average return value. The study results show that 14 stocks are candidates for optimal portfolios with positive return values, namely: ACES, ADRO, ANTM, BRPT, BTPS, CTRA, EXCL, INCO, MDKA, MNCN, SCMA, TPIA, UNTR, and WIKA. Then the optimal portfolio of the 14 stocks is determined using the Single Index Model considering the ERB (Excess Return to Beta) value ≥ cut-off point value (C*). Based on the value, 4 shares were obtained that belong to the optimal portfolio, namely: MDKA, BRPT, BTPS, and ANTM. Furthermore, VaR calculations are performed on the 4 optimal portfolios to obtain optimum VaR consistency values with 500 repetitions. The VaR calculation results with a 95% confidence level show that the average VaR result is in the range of -0.14704 to -0.3420 so that when investors invest in 4 optimal stocks, the losses experienced by investors are no more than 34%.
Perbandingan Metode Efron dan Breslow pada Regresi Cox Propotional Hazard yang Mengandung Ties Sugito Mahendra Imran; La Ode Nashar; Nurwan Nurwan; Agusyarif Rezka Nuha
JOSTECH Journal of Science and Technology Vol 3, No 1: Maret 2023
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v3i1.5589

Abstract

This study concerned to apply the Cox proportional hazard regression model to the incidence of ties using two approaches, namely the Efron approach and the Breslow approach, and find out its application in cases of dengue hemorrhagic fever at Dr. Hasri Ainun Habibie Hospital, Gorontalo Regency. Dengue hemorrhagic fever data was taken from Dr. Hasri Ainun Habibie Hospital, Gorontalo Regency. There were seven variables considered in this study, namely age, sex, Hemoglobin, Erythrocytes, Leukocytes, Platelets, and type of treatment. Then tested the proportional hazard assumption, all variables met the proportional hazard assumption and were included in the model. After testing the Cox best model, the two approaches used gave different results where there was one significant variable, namely, leukocytes in the Efron approach, while there was no single variable. significant based on the Breslow approach
Comparison of Feature Selection Based on Computation Time and Classification Accuracy Using Support Vector Machine Salmun K Nasib; Fadilah Istiqomah Pammus; Nurwan; La Ode Nashar
Indonesian Journal of Applied Research (IJAR) Vol. 4 No. 1 (2023): Indonesian Journal of Applied Research (IJAR)
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/ijar.v4i1.252

Abstract

The goal of this research to compare Chi-Square feature selection with Mutual Information feature selection based on computation time and classification accuracy. In this research, people's comments on Twitter are classified based on positive, negative, and neutral sentiments using the Support Vector Machine method. Sentiment classification has the disadvantage that it has many features that are used, therefore feature selection is needed to optimize a sentiment classification performance. Chi-square feature selection and mutual information feature selection are feature selections that both can improve the accuracy of sentiment classification. How to collect the data on twitter taken using the IDE application from python. The results of this study indicate that sentiment classification using Chi-Square feature selection produces a computation time of 0.4375 seconds with an accuracy of 78% while sentiment classification using Mutual Information feature selection produces an accuracy of 80% with a required computation time of 252.75 seconds. So that the conclusion are obtained based on the computational time aspect, the Chi-Square feature selection is superior to the Mutual Information feature selection, while based on the classification accuracy aspect, the Mutual Information feature selection is more accurate than the Chi-Square feature selection. The recommendations for further research can use mutual information feature selection to get high accuracy results on sentiment classification
Analisis Regresi Logistik Multinomial dengan Metode Bayes untuk Identifikasi Faktor-Faktor Terjadinya Diabetes Melitus Sartika Sari Dewi; Resmawan Resmawan; La Ode Nashar
Journal of Mathematics: Theory and Applications Vol 5 No 2 (2023): Volume 5, Nomor 2, 2023
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v5i2.2520

Abstract

Diabetes Melitus merupakan salah satu penyebab kematian terbesar di dunia dimana pada tahun 2020 Indonesia dinyatakan berada pada peringkat ke-7 di dunia dengan 10,7 juta penderita diabetes. Provinsi Gorontalo termasuk kedalam 5 besar penderita diabetes melitus. Terdapat beberapa tipe diabetes melitus yang umumnya terdiri dari DM tipe 1, DM tipe 2, dan DM tipe lainnya yang dapat disebabkan oleh dua faktor yaitu faktor yang tidak bisa diubah dan yang bisa diubah. Model regresi logistik multinomial digunakan untuk meneliti faktor tersebut karena variabel dependen memiliki lebih dari 2 kategori. Untuk mengestimasi parameter model regresi logistik multinomial digunakan metode Bayes. Metode Bayes merupakan metode estimasi parameter yang menghubungkan antara distribusi prior dengan fungsi likelihood sehingga menghasilkan distribusi posterior. Penyelesaian metode Bayes menerapkan simulasi Markov Chain Monte Carlo (MCMC) dengan algoritma Gibbs Sampler. Data yang digunakan adalah penderita diabetes melitus di Rumah Sakit Toto Kabupaten Bone Bolango Tahun 2021 dengan variabel dependen DM tipe 1, DM tipe 2, dan DM tipe lain. Variabel Independen teridiri dari Usia, Jenis Kelamin, Tingkat Pendidikan, Pekerjaan, dan Hipertensi. Hasil pemodelan menunjukkan bahwa variabel yang berpengaruh secara signifikan terhadap penyebab terjadinya diabetes melitus adalah Tingkat Pendidikan Menengah dan Hipertensi. Berdasarkan model yang didapatkan menghasilkan kesalahan klasifikasi sebesar 0,1885% dengan nilai ketepatan klasifikasi sebesar 99,8115%.