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Parameter: Journal of Statistics
Published by Universitas Tadulako
ISSN : -     EISSN : 27765660     DOI : https://doi.org/10.22487/27765660.2021.v1.i2
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 66 Documents
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ADAPTIVE SYNTHETIC IMPLEMENTATION ON RANDOM FOREST IN ARCHIPELAGIC FISHING PORT OF PEMANGKAT NESSYANA DEBATARAJA, NAOMI; Kusnandar, Dadan; Anugrahnu, Joannes Fregis Philosovio
Parameter: Journal of Statistics Vol. 4 No. 2 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i2.17279

Abstract

Random Forest is one of the classification methods employed in data mining. One of the problems in data mining classification is the problem of unbalanced class data This phenomenon arises when the data classes utilized do not have identical instances. Imbalance class data causes the classification results to be biased towards the majority class. Adaptive Synthetic (ADASYN) can be used to deal with this problem. ADASYN generates synthetic data by assigning different importance of minority class samples and then producing synthetic data with similar characteristics. The implementation of ADASYN is suitable for fishery production data, which will experience the problem of unbalanced class data. Fish production is part of the measured fishery. This study aims to classify the value of measured fishery production at PPN Pemangkat through Random Forest Classification using ADASYN to handle the imbalance class data problem and compare the results with those without ADASYN implementation. This study uses four predictor variables which include fishing gear types (), number of trip days (), number of crew (), and the total weight of fish () with production value as response variable (). Accuracy, precision, recall, specificity, and G-mean are the model performance indicators used. The results showed that ADASYN successfully handles the problem of unbalanced class data in Random Forest classification. Accuracy is increased from to , Specificity is increased from to , Precision from to , and G-Mean from to . The decrease in recall is negligible due to the small amount, so the Random Forest classification with ADASYN is better than without ADASYN
FORECASTING TOTAL ASSETS OF PT. BPD KALTIM KALTARA USING THE SINGLE EXPONENTIAL SMOOTHING METHOD Nurmayanti, Wiwit Pura; Ningsih, Eva Lestari; Arif, Zainul; Fathurahman, M; Hasanah, Siti Hadijah
Parameter: Journal of Statistics Vol. 4 No. 2 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i2.17473

Abstract

PT. BPD Kaltim Kaltara is one of the regional development banks that plays a crucial role in supporting regional economic development in East Kalimantan and North Kalimantan. The company's total assets reflect significant financial stability and growth, making it an interesting topic to analyze in the context of strategic financial planning. The purpose of this study is to use the Single Exponential Smoothing (SES) approach to forecast PT. BPD Kaltim Kaltara's total assets. In the forecasting process, alpha 0,3, alpha 0,6, alpha 0,7, and alpha 0,8 are tested to determine the best value that gives the most accurate results. Based on the forecasting accuracy analysis, the SES method with alpha = 0,7 proved to be the most optimal in predicting the company's total assets, achieving MAE = 1454272,737, MSE = 4764920751283, and MAPE = 4,0433% (excellent forecasting ability). The forecasting results show an upward trend in assets, with total assets in September 2024 estimated to reach IDR 48.440.683,75. This method provides valuable guidance in thecompany's financial strategic planning, helping to anticipate future asset developments more precisely.These forecasting results also emphasize the importance of selecting the right parameters in the forecasting model to improve prediction accuracy.
SPATIAL AUTOREGRESSIVE MODEL (SAR) AND SPATIAL ERROR MODEL (SEM) MODELING ON LIFE EXPECTANCY DATA IN SOUTH SULAWESI PROVINCE 2022 Ayu Pebriyanti; Hafid, Hardianti; Sudarmin
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17397

Abstract

Spatial regression is a development of classical linear regression which takes into account the spatial or spatial effects of the data being analyzed. The Spatial Autoregressive Model (SAR) and Spatial Error Model (SEM) methods include spatial regression models show that spatial effects on response variables and predictor variables. This research aims to model the factors that influence life expectancy in South Sulawesi Province in 2022. The analysis method used in this research is the SAR and SEM methods. The results show that based on the Lagrange Multiplier test values, there are lag and error dependencies. Based on the research results, it was found that the SAR and SEM models each had Akaike’s Information Criterion (AIC) values of 94.0069 and 90.6410, so the best model for analyzing the influence life expectancy value was the SEM model because the smallest had Akaike’s Information Criterion (AIC) value was obtained. The factors that have a significant influence on life expectancy are average years of schooling and gross regional domestic product which have a positive effect. Then, the percentage of poor population and per capita expenditure have a negative effect.
CLUSTER ANALYSIS OF HIGHEST EDUCATION COMPLETED IN EAST JAVA PROVINCE WITH SPHERICAL K-MEANS METHOD Purnama, Mohammad Dian
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17440

Abstract

One of the key pillars of development that greatly aids in the social and economic advancement of civilization is education. The purpose of this study is to use the Spherical K-Means Clustering method to evaluate the distribution and degree of educational attainment in districts/cities in East Java Province. This approach was selected because it can group vector-based data according to directional similarity, making it appropriate for multidimensional data. Based on education-related variables, including never attending school, not graduating from primary school, graduating from primary school, graduating from junior high school, graduating from senior high school, and graduating from university, this analysis groups regions. Based on the clustering results, several significant clusters were found. Areas with strong secondary and tertiary education levels make up Cluster 1. There is a more equitable distribution of schooling between primary and secondary education in Cluster 2. Regions with a higher percentage of basic education and lower secondary education levels are included in Cluster 3. The results can help stakeholders create more focused and efficient education policies by offering significant insights into the differences in educational attainment in East Java.
ROBUST PERMUTATION TEST FOR SPEARMAN CORRELATION AND ITS APPLICATION TO TESTING THE RELATIONSHIP BETWEEN OPEN UNEMPLOYMENT RATE AND NUMBER OF CRIMES Indriyani, Indriyani; Suliadi, Suliadi
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17444

Abstract

Pearson correlation coefficient is often unreliable for data that is not bivariate normally distributed or outliers are present, which affects the accuracy of measuring the strength of the linear relationship. Alternatively, Spearman correlation coefficient can be used to measure monotonic relationships without the assumption of normal distribution and can overcome the presence of outliers. Although the t-test approach to Spearman correlation is commonly used in theory, it is not always appropriate and can result in a Type I error when data are not normal or the sample size is small. To overcome these limitations, Yu & Hutson in 2022 proposed a robust permutation test method on the Spearman correlation coefficient using studentized statistics designed to overcome deviations from bivariate normality and small sample sizes, providing better control of Type I error. This research discusses the application of that method to analyze data of the open unemployment rate and the number of reported crimes in Indonesia. Using the permutation test, it was obtained the value of =0.2437 with a p-value <0.05, indicating a significant correlation between the two variables. The findings of this study are expected to provide a basis for effective policy recommendations in reducing crime rates by considering unemployment factors.
FRIEDMAN'S ANALYSIS OF THE READING LITERACY PROGRAM IN IMPROVING STUDENT'S READING SKILLS Pitri, Rizka Pitri; Alvionita, Elisya
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17483

Abstract

The School Literacy Movement (GLS) is an effort to cultivate character through reading activities. GLS becomes the foundation of the learning process through the establishment of a school culture as a comfortable learning environment and leads to increased literacy skills in students. One of the School Literacy Movement is the 15-minute reading program before learning begins which is implemented in education units. However, the GLS program has not been comprehensively based on the GLS guidelines from MoEC-Ristek. The intensity of GLS activities is still lacking because it is only done twice a week. Based on this fact, the researcher conducted a 15-minute reading program before learning begins four times a week. This study aims to evaluate the implementation of the reading literacy program in improving reading skills. The samples in this study were early grades I and II of MIN 3 Bandar Lampung. This study used quantitative methods by applying Friedman and Effect Size analysis. This study found that there is a difference in the level of reading skills before and after the implementation of the 15-minute reading program before learning begins, in other words, the program has effectiveness in improving reading skills. The effectiveness of the 15-minute reading literacy program before learning begins on improving the reading skills of early grade students is 0.7 or equivalent to 76% effectiveness.
CLUSTERING OF REGENCIES/CITIES IN WEST JAVA PROVINCE BASED ON INDICATORS THAT AFFECT AIR QUALITY USING PRINCIPAL COMPONENT ANALYSIS AND K-MEANS CLUSTERING Suriawan, Jasmine Angelia; Ahnaf, Muhammad Fairuz
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17489

Abstract

Air quality in Indonesia has significantly declined over the past two decades, transforming from one of the cleanest countries in 1998 to one of the twenty most polluted by 2016 due to a 171% increase in air particulate pollution concentrations. This study examines factors affecting air quality in West Java Province, one of Indonesia’s most populous regions, using Principal Component Analysis (PCA) and K-Means Clustering. The analysis includes 14 variables, such as population density, forest area, road length, and vehicle numbers. PCA was used to reduce data dimensions while retaining essential characteristics, identifying two principal components: population mobility and land infrastructure. The cluster analysis revealed two distinct groups: Cluster 1 includes 18 regencies/cities with lower population mobility and land infrastructure, indicating better air quality, while Cluster 2 consists of 9 regencies/cities with higher population mobility and land infrastructure, potentially reflecting worse air quality. Areas in Cluster 2 are concentrated near DKI Jakarta, Bandung, and the eastern border with Central Java, suggesting the influence of urbanization, industrial activities, and cross-border emissions. This study provides a spatial grouping of regencies/cities in West Java based on air quality indicators, offering insights for policymakers to target interventions more effectively. The findings emphasize the need for sustainable urban planning and stricter environmental regulations to address the growing air pollution challenge.
CATEGORICAL ANALYSIS OF STUDENT ENTHUSIASM RELATED TO THE 2024 INDONESIAN ELECTION WITH CHI-SQUARE INDEPENDENCE TEST Fitriana Nur Afifa; Ilham Darussalam; Evi WIjayawati; M. Syahrie Khamdani
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17551

Abstract

General elections in Indonesia are crucial for democracy, enabling citizens to directly choose their leaders. But the abstention or the "whites" in Indonesian elections is growing due to perceived political bias in the state apparatus operating under bureaucratic democracy principles. KPU RI has designated the National Permanent Voter List for the 2024 election, with 52% being young voters consisting of students. Ranging in age from 17 to 22 years old, the students will make a major contribution to the number of votes and the number of abstinences. In this study, a chi-square independence test was conducted to analyze the factors that are thought to influence student enthusiasm regarding the 2024 Indonesian elections. The results of this study indicate that social media intensity has a significant effect on student enthusiasm regarding the 2024 Indonesian elections, while gender and regional origin have no significant effect.
RAINFALL PREDICTION IN BALIKPAPAN CITY USING SUPPORT VECTOR REGRESSION Nur Rahmayanthi, Annida; M, Fathurahman; Wahyuningsih, Sri
Parameter: Journal of Statistics Vol. 5 No. 1 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i1.17640

Abstract

Support Vector Regression (SVR) is one of the machine learning methods. The concept of SVR is to maximize the hyperplane to obtain support vector data. In machine learning, there is an overfitting problem, namely the behavior of the data during the training phase produces almost perfect accuracy. The advantage of the SVR method is that it can produce good predictions because it is able to solve the overfitting problem. The Central Statistics Agency stated that Balikpapan City experienced natural disasters such as landslides and floods due to high rainfall. This study aims to obtain the best SVR model with a linear kernel in predicting rainfall in Balikpapan City. The data for this study are monthly data on rainfall in Balikpapan City from January 2014 to December 2023. The proportion of training data and testing data used is 60:40, 70:30, 80:20, and 90:10. The results of the study indicate that the best SVR model with a linear kernel is a model with a proportion of training data and testing data of 90:10 where the parameters used are ε = 0,9 and C = 128 with a support vector of 24 points and a bias value of 0.02818046. The results of the Balikpapan City rainfall prediction are quite good, indicated by the RMSE value of the training data of 0.159 and the RMSE value of the testing data of 0.150.
FORECASTING MODEL FOR THE DYNAMICS OF THE CONSUMER PRICE INDEX IN THE HEALTH SECTOR IN EAST JAVA USING THE ARIMA-GARCH MODEL Banat, Imamatul Banat; Ira Yudistira; Wintan Konitania; Kuzairi
Parameter: Journal of Statistics Vol. 5 No. 2 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i2.17627

Abstract

The Consumer Price Index (CPI) is a measure of development success and inflation rates in a country. The CPI is often used to assess the general rate of increase in the prices of goods and services and as a consideration in adjusting salaries, wages, pensions, and other contracts. Therefore, forecasting the CPI is very useful for formulating future policies, including in the health sector. This study aims to create a CPI forecasting model for the health sector in East Java using the ARIMA-GARCH model, namely the integration of the ARIMA model with the GARCH model. The data used were monthly CPI data from January 2020 to December 2023 obtained from the Central Statistics Agency (BPS). The ARIMA model is used to capture long-term trends, while the GARCH model is applied to handle residual heteroscedasticity. The identification results showed that the best ARIMA model is ARIMA(2, 2, 2) with all coefficients statistically significant but heteroscedasticity occurs in the therefore, GARCH modeling is applied to the residuals. Based on the lowest Akaike Information Criterion (AIC) value of 8.342491, the GARCH(1,0) model was selected as the best model. The combined ARIMA(2,2,2)–GARCH(1,0) model produced an AIC value of 18.583 and an RMSE of 0.251383. Residual diagnostic tests indicated that the resulting model meets the assumptions of normal distribution and homogeneity, and there is no significant autocorrelation. The results of this study are expected to contribute to providing predictive information that can be used by the government as a reference in formulating health sector policies, particularly regarding managing the prices of goods and services to maintain economic stability in East Java.

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