J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika
This journal publishes scientific articles in the form of research results, case studies, or literature reviews on various aspects related to the field of statistics, scientific data and their applications. Such as Computing, Time Series, Multivariate, Data Mining, Biostatistics, Survival Analysis, Econometrics, Spatial Analysis, Actuarial, Quality Control, Bayesian Analysis, Development Research in Statistics, Natural Language Processing, Applied Mathematics, Applied Statistics. However, the editorial team does not rule out other topics in the fields of statistics and scientific data.
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278 Documents
<![CDATA[Forecasting PT Triputra Agro Persada Tbk (TAPG) Share Prices Using Multivariate Time Series Analysis ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 16 No 2 (2023): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol16.no2.a8344
<![CDATA[An increase in the price of crude palm oil (CPO) positively affects the share prices of companies engaged in the palm oil industry. PT Triputra Agro Persada Tbk (TAPG) 2021 was recorded as one of the companies with the CPO business that received the most significant capital gain. Prediction or forecasting of stock prices in the future is crucial for investors as a consideration before deciding to invest. Many kinds of research on stock price prediction have been carried out previously using univariate methods. Univariate modeling cannot represent the influence of other variables on stock prices. Forecasting with the influence of other variables can be done with multivariate time series analysis. This study aims to analyze the multivariate time series of TAPG stock prices and the factors that influence them. Based on the research results, data on TAPG stock prices and CPO prices are cointegrated, so the multivariate time series model used is the vector error correction model (VECM). In the VECM model, the optimum lag used is lag 11. In the long run, CPO prices significantly affect TAPG stock prices.]]>
<![CDATA[Identifying Factors that Influence Life Expectancy in Central Java Using Spatial Regression Models ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 16 No 2 (2023): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol16.no2.a8375
<![CDATA[Life Expectancy is an average calculated over several years, assuming that mortality remains constant as age increases. It serves as a metric to gauge the success of population health development at the urban level and overall well-being, particularly in terms of health. Various indicators, including socioeconomic conditions, environmental factors, and health indicators, influence the highs and lows of life expectancy. This study in Central Java Province's 35 districts and cities aims to identify crucial components impacting life expectancy through a process-oriented spatial regression analysis. Additionally, the research endeavors to determine the optimal spatial regression equation for modeling life expectancy in the province. Spatial regression, a linear regression development method falling under the point element model, is employed. Utilizing two independent variables selected from seven, the study explores spatial regression equations using SAR, SEM, and SARMA area approaches. Data sourced from BPS in 2020 reveals that the SAR model, with a p-value of 0.02183, is apt for identifying spatial effects on Central Java's life expectancy. The Open Unemployment Rate (X4) and the Percentage of Poor Population (X6) emerge as significant spatial factors influencing life expectancy in Central Java.]]>
<![CDATA[Analysis of Public Perception of Dynastic Politics in the 2024 Presidential and Vice Presidential Elections in Indonesia with a Chi-Square Approach ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 2 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no2.a8562
<![CDATA[The phenomenon of dynastic politics in the 2024 Presidential and Vice Presidential Elections has become a hot issue in Indonesia. Dynastic politics is the inheritance of power in the family to maintain political influence, which has the potential to threaten democracy and state development. This study aims to identify the relationship between public perceptions of dynastic politics based on the characteristics of respondents, in line with SDGs point 16, namely, peace, justice and resilient institutions, if dynastic politics is not transparent it can hinder good governance. Data was obtained through questionnaires distributed to 210 respondents, then analyzed using the Chi-Square test to measure the relationship between public perceptions of dynastic politics and the characteristics of gender, profession, and region of residence. The results of the analysis show that public perception does not have a significant relationship with gender, but is significantly related to profession and region of residence on one of the statements, namely agreeing that the existence of political dynasties has a negative impact on Indonesian democracy.]]>
<![CDATA[Analysis of Environmental and Productivity Factors with the Number of Dengue Hemorrhagic Fever and Obesity Cases in Indonesia ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 2 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no2.a8737
<![CDATA[Dengue Hemorrhagic Fever (DHF) is a frequently occurring disease in tropical regions. This is due to the disease vector being the Aedes aegypti mosquito, whose habitat is in tropical environments. Obesity has become a global issue worldwide. Patients with obesity have a stronger immune response due to increased inflammation in circulation. As a result, blood vessels may become wider than usual. This triggers plasma leakage and exacerbates DHF, potentially leading to Severe Dengue Syndrome (SDS). Both of these diseases have various triggering factors such as environmental and productivity-related aspects. In this study, multivariate linear regression analysis will be employed to identify which factors are significant for both diseases. The linear regression analysis will use simultaneous and partial Wilks' Lambda tests. Based on the research findings, it is stated that there are four predictor variables significant for the levels of DHF and obesity, namely, Air Quality Index (), productivity (), poverty rate ( ), and the number of health centers ().]]>
<![CDATA[Binary Logistic Regression Analysis on the Spread of Dengue Fever in Bali Province ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a8955
<![CDATA[The spread of dengue fever involves a complex cycle between humans as hosts and mosquitoes as vectors. Symptoms of dengue fever can vary from a mild fever to a severe form that can be life-threatening. One of the areas that has the highest spread of dengue fever in Bali Province is the Denpasar area. Research continues to be carried out to understand the factors that influence the spread of dengue fever using the binary logistic regression method. Binary logistic regression is a regression model that is often used in modeling categorical data, where the dependent variable in this study is the distribution of dengue fever cases with the number of cases spreading in each region being assigned a category of zero for a low number of cases and one for a high number of cases. So in this research a more effective strategy was developed in controlling this disease as well as the best model for data on the spread of dengue fever in Bali Province. The results obtained from this research were a test of the influence of the independent variable on the dependent variable, showing that the variable number of adequate sanitation facilities (X5) had a significant influence on the number of dengue fever sufferers in Bali Province, namely 0.081.]]>
<![CDATA[Association of Poverty Categories, Educational Characteristics, and Area of Residence in Indonesia Using a Three-Way Log-Linear Model ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a9054
<![CDATA[Contingency tables are one way to present data with all categorical variables. The analysis used to model the contingency table is a log-linear model. The log-linear model is also used to estimate parameters and see the association between variables. This research aims to utilize the three-way log-linear model to model and see the association between poverty category variables, educational characteristics (level of education and reading and writing ability) of the head of the household, and area of residence in Indonesia in 2023. Research is done by forming a saturated and homogeneous log-linear model first, then comparing the difference in deviance values from the two models with the table chi-square value or choosing the smallest AIC value to determine the best model. The results obtained are a significant saturated model. This means that there is an association between the poverty category variable, the education level of the head of the household, and the area of residence. There is also an association between the poverty category variable, the reading and writing ability of the head of the household, and the area of residence. In addition, there is a greater tendency for poverty for heads of households who have a primary school education or less and cannot read and write.]]>
<![CDATA[Factors Affecting the Resilience Index Food in Papua Province and West Papua Province Using a Spatial Model Approach ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a9087
<![CDATA[The Food Security Index is a measure of indicators to produce a composite value that reflects the status of food security in a region. Food security plays an important role in sustainable development, including food availability, environmental preservation and economic balance, as well as being the basis for economic growth, preventing poverty and inequality. In Indonesia, with an estimated population growth of 430 million people in 2050, the challenge of meeting food needs is increasing. Indonesia's commitment to the Sustainable Development Goals (SDGs) includes efforts to end hunger and promote sustainable agriculture. This research aims to apply spatial regression analysis to the Provinces of Papua and West Papua to determine the best model and significant factors that influence the Food Security Index in the region in order to identify the challenges faced by the region in calculating the food availability of its people as well as assist in developing efforts to overcome them. Five predictor variables were used with the assumption that they have a significant influence on the Food Security Index. This research examines the spatial regression equation using the SAR, SEM and SARMA regional approaches. The results obtained showed that the selected SEM model with a p-value of 0.0082581 was appropriate for identifying the dependence of spatial effects on Food Security Index in Papua Province and West Papua Province. Life Expectancy at Birth, Prevalence of Stunting Toddlers, Percentage of Poor Population, Open Unemployment Rate, and Average Length of Life are significant factors that influence the Food Security Index in Papua Province and West Papua spatially.]]>
<![CDATA[Sentiment Analysis Of Public Opinion On Handling Stunting In Indonesia Using Random Forest ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a9088
<![CDATA[The problem of stunting is important to solve, as it has the potential to disrupt human resource potential and is linked to health outcomes and even child mortality. The Indonesian government targets the stunting rate to drop to 14 percent by 2024 through an accelerated stunting reduction program as an effort to improve the nutritional status of the community and also reduce the prevalence of stunting or short toddlers. Understanding public sentiment towards stunting initiatives is essential for policy makers and stakeholders to design effective interventions and allocate resources efficiently. In this research, classification of positive and negative sentiment is carried out using the random forest algorithm. The data used is comment data on one of the social media pages, namely Twitter, regarding public sentiment towards handling stunting cases in Indonesia. The first stage in this research after obtaining a data is data preprocessing. The data preprocessing stage in sentiment analysis is useful for cleaning and normalizing text, removing irrelevant words, and preparing data so that algorithms can analyze sentiment more accurately and efficiently. Furthermore, the results of the preprocessed data are labeled 0 for positive and 1 for negative labels. The classification of positive and negative sentiment was done using random forest and resulted in an accuracy value of 97.5%. This model is good, but we suggest trying other algorithms in future research.]]>
<![CDATA[Accelerating SIREKAP Digital Transformation in the 2020 Natuna Regency Election ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a9174
<![CDATA[The aim of this research is to analyze the implementation of digital transformation in the use of Sirekap in Pilkada 2020 district of Natuna. This type of research is qualitative, using a single case study research strategy, which involves an individual in one company or office, namely the Natuna Regency KPU office. The research design used is qualitative research. The acceleration of digital transformation is essential in the operational process of acquisition and as a support tool while minimizing risks from the early stages of the elections, the election day, and the post-election period. (post-election). The over-implementation of the Sirekap in the election of the head of the Bupati district and the Deputy Bupati District of Natuna district in 2022 increases transparency and accountability to increase public confidence in the results of the election calculations. The Sirekap application makes the working time of the KPU more effective than manual calculations. The KPU, with the presence of the Sireap application, also makes the information disseminated to the public no less rapidly than the survey agency because the region can monitor the data entered in the place of direct voting. The Sirekap application also has a high level of rigor and minimizes the error rate of voting calculation]]>
<![CDATA[Forecasting Average Rice Prices at Milling Level According to Quality Using Support Vector Regression ]]>
<![CDATA[ J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 17 No 1 (2024): Jurnal Ilmiah Teori dan Aplikasi Statistika ]]>
Publisher : <![CDATA[Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya ]]>
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DOI: 10.36456/jstat.vol17.no1.a9245
<![CDATA[Indonesia is an agricultural country where the majority of the population work as farmers and one of the humongous commodities produced is rice. Rice is a very important commodity for the Indonesian people, because it is the main food of them. This is why rice production in Indonesia is the big concern to the government, including of the average rice prices at milling level. The fluctuative of the rice prices will be affect to the purchasing power of the people. One of the efforts that can be made to prepare a policy to increase people's purchasing power of the rice is by forecasting. This study used SVR to modeling the average rice prices using 114 datasets obtained from January 2013 to June 2023, then evaluating its performance using Mean Absoute Percetage Error (MAPE). The best model formed from a linear kernel with parameters ε = 0.078 and C = 3.1. The model produced the smallest MAPE value of 2.32% in testing data and 1.2% in training data which also less than 10% meaning that the performance of the model to forecast the average price of rice is very high.]]>
