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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 5 Documents
 1 
Search results for , issue "Vol. 3 No. 2 (2023)" : 5 Documents clear
IMPLEMENTATION OF THE K-MEDOIDS METHOD IN CLUSTERING HUMAN DEVELOPMENT INDEXES IN INDONESIA Erda, Gustriza; Usdika, Radhiatul Khaira; Pitri, Rizka; Erda, Zulya
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16906

Abstract

The Human Development Index (HDI), which takes into account three fundamental aspects of human existence, a long and healthy life, knowledge, and a reasonable level of living, is one tool used to assess the effectiveness of human progress. Clustering provinces based on the human development index is important so that development disparities can be identified and help identify provinces with high, medium or low levels of development. The purpose of this study was to use the k-medoids approach to perform a cluster analysis of HDI in Indonesia based on life expectancy, average years of schooling, expected years of schooling, and expenditure per capita adjusted for 2022. The analysis indicate that two clusters were created: cluster 1 had a high human development index, while cluster 2 had a low human development index. More provinces belonged to cluster 1 than cluster 2 suggesting that human development index in Indonesia in 2022 was largely in the high category
MODELING PNEUMONIA CASES IN TODDLERS IN INDONESIA USING GENERALIZED ADDITIVE MODEL FOR LOCATION, SCALE, AND SHAPE (GAMLSS) WITH LOESS SMOOTHING Syahar, Sofya; Tazliqoh, Agustifa Zea; Harison
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16918

Abstract

Pneumonia is an acute respiratory infectious disease that is the primary death cause due to infection in children worldwide, including Indonesia. Pneumonia case modeling is necessary to predict the incidence, especially pneumonia in toddlers. In this study, case modeling using the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) method with LOESS smoothing to determine the model form and the factors influencing pneumonia cases in toddlers in Indonesia in 2021. The research results obtained indicate that with the Inverse Gaussian distribution, the model form for the location parameter is 9,719 + 0,013 + 0,001 + 0,031 and for the scale parameter is -10,897 + 0,125. The resulting model is accurate and suitable for use because the model residuals follow a normal distribution. Along with factors that influence pneumonia cases in toddlers in Indonesia are the percentage of babies receiving exclusive breastfeeding (), population density (), and the percentage of toddlers receiving measles immunization ().
SENTIMENT ANALYSIS OF REVIEW DATA OF THE RUANGGURU ONLINE LEARNING APPLICATION USING THE C5.0 ALGORITHM Izzah, Nurul; Nur'eni; Pitri, Rizka
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16919

Abstract

Sentiment analysis is process to determine the sentiment of a person that is manifested in the form of text. Internet users write their opinions and everything that concerns them in the google play store review column. Moreover, when the world of education could not carry out face-to-face learning due to the covid-19 pandemic, learning turned to e-learning applications. Through this innovation, many pros and cons flow from the community with the existence of Ruangguru online learning application in the world of education. This research was conducted with the aim of determining word cloud visualization and the accuracy of the results of sentiment analysis of review data on the Ruangguru application using the C5.0 algorithm. The word cloud visualization results are dominated by word such as “paham”, “bagus”, “mudah”, “suka”, “langganan”, “seru”, “nyaman”, “senang”, “menarik”, “keren”, “lancar”, “sukses”. This shows that Ruangguru Application is a good application because it is dominated by positive sentiment words which means that users find it helpful and easy to understand the learning material in Ruangguru. The results of the Confusion Matrix show that the model successfully classifies 0.8557 or 85.57% of the data correctly from all test data
FORECASTING INDONESIAN ISLAMIC BANK (BSI) SHARE PRICES USING THE FUZZY TIME SERIES CHENG METHOD Nurfitra; Sofia, Ayu
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16920

Abstract

Shares were one of the most popular financial market instruments. In Indonesia, stock market activity continued to increase so that stock investment was in great demand by the public, especially in the banking sector. Indonesia had a majority Muslim population. Based on this, Indonesia had good potential in the field of Islamic finance, especially Islamic banking. One of the Islamic banks that had achieved positive performance was Bank Syariah Indonesia (BSI). BSI's stock price every day from February 1, 2021, to January 11, 2023, tended to experience a downward trend and fluctuated, making it difficult for investors to see the prospects of a company in the future. For this reason, a forecasting technique was needed. A good forecasting method used for data with trend patterns both down and up was Cheng's Fuzzy Time Series (FTS) method. So, this study used Cheng's FTS method to predict BSI's share price in the future. The calculation of the accuracy of the prediction results in this study used Mean Absolute Percentage Error (MAPE). The results showed that the forecasted value of BSI's share price for the period January 12, 2023, to January 31, 2023, was constant at 1,353.267 million with a MAPE value of 3.09%.
REGRESSION ANALYSIS OF ROBUST ESTIMATION-S WITH TUKEY BISQUARE WEIGHTING ON POVERTY LEVEL ON SULAWESI ISLAND Saputri, Sandra; Nur'eni; Masyitah Meliyana R, Sitti
Parameter: Journal of Statistics Vol. 3 No. 2 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i2.16923

Abstract

Poverty is a situation where a person experiences difficulty in meeting basic needs. There are several factors that influence poverty, including population, unemployment, gross regional domestic product, human development index, average years of schooling and labor force participation rate. Therefore, it is necessary to carry out regression analysis to determine the relationship between one variable and other variables. One method for estimating regression parameters is the least squares method. Some classic assumptions are not met because there are outlier data. Outliers are data that do not follow the overall distribution pattern, so a method is used that can overcome outliers, namely the S-estimation robust regression method with the Tukey bisquare weighting function. The results of the research show that the best model was obtained from robust S-estimation regression with Tukey bisquare weighting, namely factors that influence the level of poverty on the island of Sulawesi, namely Population Number ), Human Development Index ( ), Average Years of Schooling ( ) and, Force Participation Level. Work .

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