Browsing by Author "Adnan, Arisman"
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Item ALGORITMA K-PROTOTYPES DALAM MELAKUKAN KLASTERISASI WILAYAH DI INDONESIA BERDASARKAN INDIKATOR PEMBANGUNAN EKONOMI(Elfitra, 2023-05) Ramadhani, Savira; Adnan, ArismanUnequal economic development is one of the causes of economic inequality. It is necessary to formulate appropriate policies as an effort to equalize economic development. This study aims to classify districts/cities based on indicators of economic development using the K-prototypes method in order to assist the government in formulating policies. The study shows that grouping 5 clusters is the optimal number of clusters with a silhouette value of 0.3027283. Clusters 1 to 5 have 192, 11, 210, 80 and 12 members respectively. The results of the mean difference test between clusters showed that only the HDI development variable was not significantly different between the 5 clusters.Item ANALISIS JALUR FAKTOR YANG MEMPENGARUHI SUKU BUNGA SERTA IMPLIKASINYA TERHADAP INFLASI PROVINSI RIAU(2021-01) Aresta, Fujha Sri Aknella; Adnan, ArismanThe purpose of this study is to analyze the influence of US dollar exchange rate, money supply and imports toward BI rates and their implication to the inflation in Riau Province. Path analysis and trimming methods were applied to study the direct and indirect effects by using AMOS 25. The study shows that US dollar and import have a significant and positive effect on BI rate, while the amount of money has a significant effect and negative to the BI rate. Furthermore, US dollar has a significant and negative effect on inflation, the BI rate has a significant and positive effect on inflation while import does not have significantly influence on inflation. Indirectly, the US dollar affects the inflation through the BI rate, while import does not have a significant effect on inflation through the BI rate.Item ANALISIS KLASTER HIERARKI TERHADAP DATA KESEJAHTERAAN SOSIAL EKONOMI DI SUMATERA BAGIAN UTARA(Elfitra, 2022-05) Gamal, Mohammad Haidar; Adnan, ArismanDetermining the characteristics of each region before carrying out development is a step or strategy that can be applied. The characteristics are based on indicators of the public welfare of regencies and cities in the northern area of Sumatra. This study discusses the grouping of regencies and cities using cluster analysis with the average linkage method. The variables used in this study are population density, open unemployment rate, PDRB, percentage of poverty, percentage of households that do not have a toilet, life expectancy, elementary school gross enrollment rate, and number of health centers. This study recommends that regencies and cities in the northern area of Sumatra can be clustered into 3 clusters based on the level of walfare. The results obtained from this study are that there are 3 clusters. Cluster 1, consisting of 88 regencies and cities, is a cluster with a low level of welfare, cluster 2 that consists of 5 regencies and cities is a cluster with a high level of welfare, and cluster 3 that consists of 1 city is a cluster with a moderate level of welfare.Item ANALISIS MODEL INTERVENSI PANDEMI COVID-19 TERHADAP JUMLAH WISATAWAN MANCANEGARA DI INDONESIA(Elfitra, 2022-05) Natasya, Fanny; Adnan, ArismanThe Indonesian government made a policy to reduce the spread of the coronavirus by restricting entry/exit to Indonesian territory. As a result, there is a decrease in the number of foreign tourist visits to Indonesia. The decrease in the data pattern was studied using the ARIMA Intervention method. The ARIMA Intervention method is used to see how big and duration of the impact of entry/exit restrictions due to the Covid-19 pandemic on the number of foreign tourists in Indonesia. Forecasting results for August 2020 until May 2021 were obtained with a MAPE value of 9.74%. ARIMA Intervention is classified as very good in predicting the number of foreign tourists in Indonesia because it produces a MAPE value of less than 10%.Item ANALISIS PENGARUH OUTLIER DATA PADA RANCANGAN BUJUR SANGKAR YOUDEN(Elfitra, 2023-03) Nadia, Nadia; Adnan, ArismanLatin Square Design is a square design where the number of treatments is the same as the number of rows or columns. If there are more treatments than the number of rows and columns, the Latin Square Design cannot be used, the Youden Square Design is the correct design. In the experimental design there are several things that can make a data outlier, namely the failure of an observation in one of the experimental units or errors in data collection which can have a separate impact on the analysis process. If there are outliers, the data must be estimated or repeated trials. In this study, outliers were overcome by estimating the data and replacing it with new data by removing the outlier values in the experimental data and treating them as missing data. Then, analysis of variance was carried out again and the study shows that there is a significant effect of the treatment observed.Item ANALISIS REGRESI SPASIAL DAN POLA PERSENTASE KESEMBUHAN TUBERCULOSIS DI PROVINSI RIAU(Elfitra, 2022-11) Sirait, Tesa Theresia; Adnan, ArismanSpatial regression analysis is a statistical method that is useful for analyzing spatial data. Spatial analysis assumes the presence of spatial dependencies. One way to find out if there is a spatial dependency is to do a spatial autocorrelation test. Spatial autocorrelation is used to analyze the similarity of values at observation locations with neighboring locations on the same variable. There are several spatial models, including the Spatial Autoregressive Model (SAR) and Spatial Error Model (SEM). The purpose of this study was to determine the best spatial regression model to model the percentage of tuberculosis cures in Riau Province and to determine the factors that influence it, by examining spatial autocorrelation using the Moran Index. Based on the results of the analysis by testing the Moran Index hypothesis, it was found that there was positive spatial autocorrelation and on examining spatial dependence, it was found that there was a lag dependence on the dependent variable, which means that the modeling was done with SAR. Based on the results of the SAR analysis, it was found that there were three independent variables that significantly influenced the percentage of TB cures, including the percentage of households with proper drinking water (𝑋1), the number of medical personnel at the puskesmas health facility (𝑋3) and the total number of public places (TTU) that met the requirements health (𝑋5).Item IMPLEMENTASI JARINGAN SARAF KONVOLUSI TERHADAP ANALISIS SENTIMEN TENTANG KULIAH ONLINE PADA MASA COVID-19(Elfitra, 2022-03) Pratama, Putra Agung; Adnan, ArismanThis paper discusses online course that use the internet network to stay connected during the activity. This study aims to see the impact of online course based on someone's opinion. One of the appropriate methods for this research is sentiment analysis. For this reason, there are 7000 tweets is analyzed from media social twitter April 2020–April 2021 which convey opinions about online course. Sentiment analysis uses a convolution neural network (one directional convolution) which classifies data in the form of text documents. Convolutional neural network is trained using keras programming with 100 epoch. The convolutional neural network trains using 5600 tweets and predicts 1400 different tweets. The training results from the convolution neural network give a neutral sentiment as the most dominant sentiment with amount 76.5% accuracy level.Item MENENTUKAN KOEFISIEN REGRESI EKSPONENSIAL DENGAN METODE KUADRAT TERKECIL SEDERHANA DAN METODE KUADRAT TERKECIL BERBOBOT(2013-07-12) Pahlevi, Riza; Adnan, Arisman; Sugiarto, SigitRelation between two variables x and y are not always linear, but also non-linear. Scatter diagram from non-linear relationship will show a pattern of data points that can be approximated by an exponential curve. The process of determining an exponential curve that best fits a data set called an exponential regression. In order to get the best an exponential regression curve was used a standard least square method with logarithm transformation. However, using this logarithm causes error change from error in the variable y to the error in the variable ln y. To overcome this problem, Glaister Internat. J. Math. Ed. Sci. Tech.. 38 (2007): 422-427 proposes a least square method that is based on applying a weighting in the standard least square method that is based on the error in the logarithm of a variable. This method is called a weighted least square method that we discuss in this article. By comparing these two methods in the case of an exponential data, the performance of the weighted least square method is better than that of the standard least square method.Item METODE ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK KLASIFIKASI TINGKAT KESEJAHTERAAN KESEHATAN MASYARAKAT PEKANBARU(perpustakaan UR, 2021-06) Anggraini, Mila; Adnan, ArismanThe level of public health welfare in a country can determine the quality and circumstances of the country. The purpose of this study is to classify the level of public health welfare of Pekanbaru City in 2019. The study used C4.5 and Naïve Bayes algorithms with k-fold cross validation to predict the accuracy of classification and performance evaluation measure as evaluation of both models. Performance evaluation measure results with k-fold cross validation show that models with Naïve Bayes have better classification results than C4.5 algorithm models. This is because Naïve Bayes' accuracy, precision, sensitivity and specificity are greater than the C4.5 algorithm by 100%. This is also because Naïve Bayes obtained the result from the probability value of each attribute being free of each other.Item METODE PRINCIPAL COMPONENT ANALYSIS PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN PULAU SUMATERA(Elfitra, 2022-04) Rizalde, Fadlika Arsy; Adnan, ArismanSumatera Island is the sixth largest island in the world, located in Indonesia, consisting of 154 regencies/cities. Sumatra Island is ranked fourth in the Indonesia for having the highest percentage of poor people, with 5,8 million in 2020. The factors that influence poverty can be viewed from the fields of population, employment, health, education, and the economy. The number of these factors can be reduced by using one of the methods in multivariate analysis, namely Principal Component Analysis (PCA). PCA aims to reduce data consisting of many variables that are interrelated with one another but still maintain the largest possible variance from the original data. The variables used to consist of 7 variables, namely, Open Unemployment Rate (𝑋1), Average Length of Schooling (𝑋2), Expenditure Per Capita (𝑋3), Population Density(𝑋4), Total Population (𝑋5), Gross Regional Domestic Product (𝑋6), and Life Expectancy(𝑋7). By using the correlation matrix in PCA analysis, three principal components are obtained with a cumulative proportion of variance of 77,8% in explaining the diversity of the original variable.Item METODE REGRESI LOGISTIK LASSO UNTUK ANALISIS GIZI BURUK PADA BALITA DI SUMATERA TENGAH(perpustakaan UR, 2021-06) Hidayah, Innaka; Adnan, ArismanThe nutritional status of toddlers can be classified into two variables, namely normal nutrition and malnutrition. The emergence of nutritional problems in toddlers can be influenced by several things such as unbalanced nutrition, infectious diseases and malnutrition. In this article, a selection is made of the factors that have an influence on cases of toddlers malnutrition in 49 districts and cities in Middle Sumatera. The study is conducted using the logistic regression method of LASSO. The dependent variable is a variable with 2 categories of cases in each region, namely above and below the average. This study results in three variables that influence cases of toddlers malnutrition in Middle Sumatera, namely the number of poor people, provincial minimum wage and the total populationItem MODIFIKASI PENAKSIR UNTUK RASIO PADA SAMPLING BERPERINGKAT(2013-03-25) Erwin, Devani; Adnan, Arisman; Efendi, RustamRatio estimator discussed are two proposed by Samawi Muttlak [4], for ratio estimator rank set sampling (RSS) and ratio estimator using regression coefficients has been reviewed, each estimator is a biased estimator. so as to determine an efficient estimator by comparing Mean Square Error (MSE) of each estimatorItem PEMODELAN JUMLAH PENDUDUK MISKIN DI INDONESIA MENGGUNAKAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION(2021-01) Natashia, Puji; Adnan, ArismanPoverty is a condition of an individual’s inability to meet his basic needs. The number of poor people in Indonesia in September 2019 was 24,79 million people or around 9,22%. This study uses a geographically weighted negative binomial regression model to determine the factors that affect the amount of poverty in Indonesia in 2019. Modeling the number of poor people in Indonesia using Poisson regression is overdispersed, so to overcome it using geographically weighted negative binomial regression. Based on the regression model used, the results show that the significant variables are the open unemployment rate, the percentage of households that occupy non-private houses, the percentage of illiteracy, and gross regional domestic product at current prices per capita.Item PEMODELAN REGRESI LOGISTIK BINER DENGAN PENDEKATAN BAYESIAN MARKOV CHAIN MONTE CARLO : KASUS INDEKS KEDALAMAN KEMISKINAN DI SUMATERA TAHUN 2021(Elfitra, 2023-05) Savira, Husna; Adnan, ArismanThe Poverty Gap Index (PGI) is the average expenditure gap of each poor population towards the poverty line. This study aims to model PGI data using binary logistic regression with a classical approach using the Maximum Likelihood Estimation (MLE) method and a Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. MCMC is a popular method for obtaining information about the distribution, especially for estimating the posterior distribution in Bayesian inference with the Metropolis-Hasting algorithm. Factors that have a significant influence on the IKK in Sumatera using the Bayesian approach and the classical approach are the same, namely Life Expectancy and per capita expenditure. Based on the results of the classification with training data of 80% and test data of 20% a classification accuracy of 62,50%.Item PEMODELAN REGRESI PROBIT ORDINAL PADA STATUS KETAHANAN PANGAN DI PULAU SUMATERA(perpustakaan UR, 2021-07) Aufa, Yaumil Rahmatul; Adnan, ArismanFood is a basic need of an individual so that the fulfillment of food is something that is very important in order to have the better generation. The purpose of this study is to model the food security of Sumatera Island in 2018. The response variables used are three levels, namely food insecurity, vulnerable to food insecurity and food security with 10 predictor variables using ordinal probit regression. From the analysis that has been carried out, it is found that four predictor variables have an effect on the model, namely the rice production, the percentage of illiterate women, stunting toddlers and the average length of schooling variable where the significant variable is explained by pseudo-R2 NagelkerkeItem PENAKSIR PRODUK YANG EFISIEN UNTUK RATA-RATA POPULASI PADA SAMPLING ACAK SEDERHANA DAN SAMPLING BERPERINGKAT(2014-03-25) Andini, Dwi; Firdaus; Adnan, ArismanThis paper discusses two product estimators for the population mean in the random sampling, those are the product estimator in simple random sampling and product estimator in ranked set sampling using the auxiliary variable quartiles given by Al- Omari [International Journal of Human and Social Sciences., 4 (2009), pp. 1181-1185]. The two estimators are biased estimators. The most efficient estimator is the estimator that has the smallest mean square error obtained by comparing the mean square error of each estimator.Item PENAKSIR RASIO UNTUK RATA-RATA POPULASI PADA SAMPLING ACAK SEDERHANA MENGGUNAKAN KOEFISIEN VARIASI DAN MEDIAN(2014-03-25) Rahmadani, Riski; Adnan, Arisman; Sirait, HaposanThis paper discusses three ratio estimators for the population mean in simple random sampling using coefficient of variation and median of an auxiliary variable, which is a review from the article of Subramani and Kumarapandiyan. All estimators are biased, then their mean square errors (MSE) are determined. Furthermore, the mean square errors are compared to show which estimator is the most efficient estimator. This paper reveals that the estimator using coefficient of variation and the median has the smallest mean square error (MSE)Item PENAKSIR RASIO UNTUK RATA-RATA POPULASI MENGGUNAKAN SAMPLING ACAK SEDERHANA DAN SAMPLING BERPERINGKAT(2013-03-16) Suroso, Ryan Ariesta Ramli; Adnan, Arisman; Efendi, RustamRatio estimators of the population mean using simple random sampling and ranked set sampling that suggested here are two ratio estimators involving the first and the third quartiles parameters. These estimators are biased estimators, so that the Mean Square Error is calculated for each estimators to obtain the efficient estimators. Therefore, the simulation using the first and third quartiles parameters is carried out. The simulation showed that the first quartiles parameters are more efficient than the third quartileItem PENAKSIR RASIO UNTUK VARIANSI POPULASI MENGGUNAKAN KOEFISIEN VARIASI DAN KURTOSIS PADA SAMPLING ACAK SEDERHANA(2016-05-23) Gusnawan, Erpan; Adnan, Arisman; Sirait, HaposanThis paper is a review of Kadilar and Chingi [Journal of Modern Applied Statistical Method, 35 (2006), 111{115] which discusses three estimators of ratio population variances ^ S2 KC1, ^ S2 K C2 and ^ S2 K C3 of the population of variables Y using known aux- iliary variables X on simple random sampling. The three estimators ^ S2 K C1, ^ S2 K C2 and ^ S2 K C3 are the modi ed of ratio variances estimator using coe cien of variation and kurtosis. Bias and mean square error (MSE) of the three estimators are obtained by MacLaurin series approximation. Furthermore, the MSE of each esti- mator is compared. This comparison shows that the estimator having the smallest MSE is the most e cient estimator.Item PENAKSIR RASIO UNTUK VARIANSI POPULASI MENGGUNAKAN KUARTIL DARI KARAKTER TAMBAHAN PADA SAMPLING ACAK SEDERHANA(2014-03-25) Elvita, Asri; Adnan, Arisman; Sirait, HaposanThis paper discusses three ratio estimators for population variance in simple random sampling using quartiles of the auxiliary variable given by Subramani and Kumarapandiyan [International Journal of Statistics and Applications., 2(5): 67-72]. The estimators discussed are the ratio estimator using the first quartile, the third quartile and the inter-quartile range. These three estimators discussed are biased estimators. Furthermore, their mean square errors are compared to show which one is the most efficient estimator. This comparison shows that the ratio estimator using inter-quartile range is the most efficient estimator.