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Perbandingan Geographically Weighted Regression dengan Mixed Geographically Weighted Regression: Studi Kasus Prevalensi Stunting di Indonesia Fahmi Cholid
Statistika Vol. 23 No. 2 (2023): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v23i2.1700

Abstract

ABSTRACT Infants who suffer from chronic malnutrition, or stunting, have a very small height compared to other children their age. Slow-growing children have a higher risk of contracting diseases and growing up with degenerative conditions. Indonesia has the second highest stunting rate among children under five in ASEAN. In 2015, 36.4% of Indonesian children less than five years old were stunted. Indonesia has the second highest stunting rate in Southeast Asia, after Laos (43.8%). The child nutritional status study found that 29.6% of children under five years old were stunted (PSG, 2017). The number increased from 2017 to 2018. Stunting rates vary from province to province in Indonesia. Therefore, research linking stunting to the characteristics of the province is needed to address its prevalence. Therefore, there is a need for research that correlates stunting with relevant provincial characteristics to address its prevalence. By comparing the Geographically Weighted Regression (GWR) method and the Mixed Geographically Weighted Regression (MGWR) method, this study aims to identify the factors that influence the prevalence of stunting among under-fives in Indonesia by considering regional aspects in the province. The average incidence of stunting in Indonesia is 30.59. The study found that East Nusa Tenggara Province has the highest prevalence of stunting in Indonesia. In Indonesia, the success rate of children receiving all recommended vaccine doses (X1) was a significant predictor of stunting prevalence. The GWR model is superior to the MGWR model because the optimal AIC and R2 values are 167.6841 and 0.828, respectively, as shown by the comparison of global regression models.  ABSTRAK Bayi yang menderita kekurangan gizi kronis, atau stunting, memiliki tinggi badan yang sangat kecil dibandingkan anak-anak lain seusianya. Anak-anak yang tumbuh lambat mempunyai risiko lebih tinggi tertular penyakit dan tumbuh dengan kondisi degeneratif. Indonesia merupakan negara dengan tingkat stunting tertinggi kedua di antara balita di ASEAN. Pada tahun 2015, 36,4% anak Indonesia berusia kurang dari lima tahun mengalami stunting. Indonesia merupakan negara dengan angka stunting tertinggi kedua di Asia Tenggara, setelah Laos (43,8%). Penelitian status gizi anak menemukan bahwa 29,6% balita mengalami stunting (PSG, 2017). Jumlah tersebut meningkat dari tahun 2017 ke tahun 2018. Tingkat stunting bervariasi dari satu provinsi ke provinsi lain di Indonesia. Oleh karena itu, diperlukan penelitian yang menghubungkan stunting dengan karakteristik provinsi terkait untuk mengatasi prevalensinya. Dengan membandingkan metode Geographically Weighted Regression (GWR) dan metode Mixed Geographically Weighted Regression (MGWR), penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang mempengaruhi prevalensi stunting pada balita di Indonesia dengan mempertimbangkan aspek regional di provinsi tersebut. Rata-rata kejadian stunting di Indonesia adalah 30,59. Penelitian ini menemukan bahwa provinsi Nusa Tenggara Timur memiliki prevalensi stunting tertinggi di Indonesia. Di Indonesia, tingkat keberhasilan anak mendapatkan seluruh dosis vaksin yang dianjurkan (X1) merupakan prediktor signifikan terhadap prevalensi stunting. Model GWR lebih unggul dibandingkan model MGWR karena nilai AIC dan R2 optimalnya masing-masing sebesar 167.6841 dan 0.828 yang ditunjukkan oleh hasil perbandingan model regresi global.
ANALYSIS OF TWITTER USER SENTIMENTS ON INDEPENDENT CURRICULUM INDONESIA Fahmi Cholid; Suparman; Ngatma’in; Insani Wahyu Mubarok
Didaktis: Jurnal Pendidikan dan Ilmu Pengetahuan Vol 24 No 3 (2024): Didaktis
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/didaktis.v24i3.24330

Abstract

Education is a very important aspect in various lives, this cannot be separated from the magnitude of the role and positive impact caused by the advancement of an education system. The world of education is an effort to improve the quality of human resources in terms of thought and expertise. Education is the main key for a country to excel in global competition. Education is always related to the curriculum. The curriculum is a tool used to achieve educational goals so that it can be said that the curriculum is a reference in the process of organizing education in Indonesia. The Indonesian education curriculum has been changed or revised at least 10 times, namely in 1952, 1964, 1968, 1975, 1984, 1994, 2004, 2006, 2013. The latest curriculum in Indonesia, the independent curriculum is a time when teachers and students can or have freedom in thinking and also free in the burden of thought so that they can develop their educational potential. This research aims to classify the sentiment of Twitter users towards government policies regarding the independent curriculum into positive sentiment and negative sentiment. The method used by the Naïve Bayes Classifier (NBC) and Support Vector Machines (SVM). The Result shows that the percentage of positive sentiment is 47% or 451 tweets while the negative sentiment is 53% or 264 tweets.