1,720,957 research outputs found
Perbandingan Fungsi Pembobot Kernel pada Geographically Weighted Logistic Regression dalam Memodelkan Kasus Kemiskinan di Indonesia
Get PDFIndonesia is a developing country that is facing poverty. The percentage of the poor population in Indonesia in 2020 increased by 0.97 percent from 2019. A suitable analysis to overcome poverty in Indonesia is the regional effect, namely Geographically Weighted Logistic Regression (GWLR). This study aimed to compare the weighting functions of the Fixed Gaussian Kernel, Fixed Tricube Kernel, and Fixed Bisquare Kernel in the GWLR model in modeling poverty in Indonesia in 2020. The best model can determine significant factors that affected poverty in Indonesia in 2020. This study used the percentage data of poor population and the factors affecting it, namely the Open Unemployment Rate , Human Development Index , and Total Population in 34 Provinces in Indonesia. This study indicates that the GWLR model with the Fixed Gaussian Kernel weighting function is the best in modeling poverty in Indonesia in 2020 based on the smallest Akaike Information Criterion Corrected (AlCc) value. The GWLR model with the Fixed Gaussian Kernel weighting function shows the Open Unemployment Rate as a significant factor affecting poverty in Indonesia in 2020 in 10 provinces in Indonesia, namely Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, DKI Jakarta, and Banten.
Indonesia merupakan negara berkembang yang dihadapkan pada masalah kemiskinan. Persentase penduduk miskin di Indonesia tahun 2020 meningkat 0.97 persen dari tahun 2019. Analisis yang cocok untuk mengatasi kemiskinan di Indonesia ini dengan menggunakan efek kewilayaan yaitu Geographically Weighted Logistic Regression (GWLR). Penelitian ini bertujuan untuk membandingkan fungsi pembobot Fixed Gaussian Kernel, Fixed Tricube Kernel dan Fixed Bisquare Kernel pada model GWLR dalam memodelkan kasus kemiskinan di Indonesia tahun 2020. Pada model terbaik dapat diketahui faktor signifikan yang mempengaruhi kemiskinan di Indonesia tahun 2020. Penelitian ini menggunakan data Persentase Penduduk Miskin dan faktor-faktor yang mempengaruhinya, yaitu Tingkat Pengangguran Terbuka , Indeks Pembangunan Manusia dan Jumlah Penduduk pada 34 Provinsi di Indonesia. Hasil penelitian ini yaitu model GWLR dengan fungsi pembobot Fixed Gaussian Kernel merupakan model terbaik dalam memodelkan kasus kemiskinan di Indonesia pada tahun 2020 yang diperoleh berdasarkan nilai Akeike Information Criterion Corrected (AICc) terkecil. Model GWLR dengan fungsi pembobot Fixed Gaussian Kernel menghasilkan Tingkat Pengangguran Terbuka merupakan faktor signifikan yang mempengaruhi kemiskinan di Indonesia tahun 2020 pada 10 Provinsi di Indonesia yaitu Provinsi Aceh, Sumatera Utara, Sumatera Barat, Riau, Jambi, Sumatera Selatan, Bengkulu, Lampung, DKI Jakarta dan Banten
Comparison of Ordinal Logistic Regression and Geographically Weighted Ordinal Logistic Regression (GWOLR) in Predicting Stunting Prevalence among Indonesian Toddlers
Get PDFOrdinal logistic regression is a type of logistic regression used for response variables with an ordinal scale, containing two or more categories with levels between them. This method is an extension of logistic regression where the observed response variable is ordinal with a clear order. It addresses spatial effects that can cause variance heterogeneity and improve parameter estimation accuracy compared to logistic regression. Geographically Weighted Regression (GWR) is a statistical analysis technique designed to account for spatial heterogeneity. GWOLR is an extension of OLS and GWR models that incorporates spatial elements into regression with categorical variables. This study compares the effectiveness of OLR and GWOLR in analyzing stunting prevalence in toddlers. Comparing OLR and GWOLR can help assess the spatial impact on stunting prevalence. This analysis could reveal that certain regions have a higher tendency for stunting prevalence, while others might have lower tendencies, thus helping in understanding regional disparities. Toddler height is a key indicator of health and nutrition in early growth. The prevalence of stunting for toddlers, according to WHO, is categorized into four levels: low, moderate, high, and very high. The Ordinal Logistic Regression model is better suited for modeling toddler stunting prevalence in Indonesia than the GWORL model. The Ordinal Logistic Regression model and the GWOLR both have a classification accuracy of 85.7%, but the OLR model has a lower AIC value. The GWOLR model is not suitable for analyzing stunting prevalence among Indonesian toddlers due to the lack of spatial variability in the data. The Breusch-Pagan test results indicate that there is no spatial heterogeneity in the data on stunting prevalence among Indonesian toddlers, as the p-value is less than the significance level of 0.05. The prevalence of undernourished toddlers is the main factor influencing stunting among Indonesian toddlers
Pemodelan Stunting dan Gizi Kurang di Kabupaten Bone Bolango menggunakan Regresi Poisson Generalized
Get PDFTujuan penelitian ini adalah untuk menentukan model kasus Stunting dan Gizi Kurang dengan Regresi Poisson Generalized dan faktor-faktor yang berpengaruh terhadap kejadian tersebut. Analisis Data menggunakan Regresi Poisson Generalized karena untuk menangani masalah overdispersi pada data. Hasil yang diperoleh yaitu variabel yang berpengaruh signifikan terhadap kejadian Stunting 2018 adalah Jumlah penduduk miskin dan untuk kejadian Stunting 2019 adalah Persentase balita diberi ASI eksklusif dan Jumlah penduduk miskin. Variabel yang berpengaruh signifikan terhadap kejadian Gizi Kurang 2018 adalah Persentase balita diberi ASI eksklusif dan Jumlah bayi mendapatkan vitamin A dan untuk Gizi Kurang tahun 2019 adalah variabel Persentase balita diberi ASI eksklusif dan Persentase berat badan lahir rendah
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI STUNTING PADA BALITA DI KOTA GORONTALO MENGGUNAKAN REGRESI BINOMIAL NEGATIF
Get PDFThis study aims to model stunting cases in children under five in Gorontalo city in 2018. In this model, it can be seen that the significant factors that affect stunting cases in children under five in Gorontalo city in 2018. This study uses data on stunting cases in 9 (nine) districts in the city of Gorontalo and the factors that influence it. The research data were obtained from the Public Health in Gorontalo city. This study used one response variable, namely the number of cases of stunting and four predictor variables, namely number of toddlers who received exclusive breastfeeding, the percentage of low birth weight (LBW), the percentage toddlers who received complete basic immunization, and number of proper sanitation. The results obtained were the variables of number of toddlers who received exclusive breastfeeding and the percentage toddlers who received complete basic immunization which had a significant effect on stunting cases in children under five in the city of Gorontalo in 2018. This was indicated by the P-value of the variable for number of toddlers who received exclusive breastfeeding of 0.00283 and P-value of variable the percentage toddlers who get complete basic immunization is 0.06564.
Association of Poverty Categories, Educational Characteristics, and Area of Residence in Indonesia Using a Three-Way Log-Linear Model
Get PDFContingency 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
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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