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ANALISIS PERBANDINGAN KINERJA CART KONVENSIONAL, BAGGING DAN RANDOM FOREST PADA KLASIFIKASI OBJEK: HASIL DARI DUA SIMULASI Yogo Aryo Jatmiko; Septiadi Padmadisastra; Anna Chadidjah
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.528 KB) | DOI: 10.14710/medstat.12.1.1-12

Abstract

The conventional CART method is a nonparametric classification method built on categorical response data. Bagging is one of the popular ensemble methods whereas, Random Forests (RF) is one of the relatively new ensemble methods in the decision tree that is the development of the Bagging method. Unlike Bagging, Random Forest was developed with the idea of adding layers to the random resampling process in bagging. Therefore, not only randomly sampled sample data to form a classification tree, but also independent variables are randomly selected and newly selected as the best divider when determining the sorting of trees, which is expected to produce more accurate predictions. Based on the above, the authors are interested to study the three methods by comparing the accuracy of classification on binary and non-binary simulation data to understand the effect of the number of sample sizes, the correlation between independent variables, the presence or absence of certain distribution patterns to the accuracy generated classification method. Results of the research on simulation data show that the Random Forest ensemble method can improve the accuracy of classification.
DETERMINAN FERTILITAS DI INDONESIA HASIL SDKI 2017 Yogo Aryo Jatmiko; Sri Wahyuni
Euclid Vol 6, No 1 (2019): Edisi Januari
Publisher : Universitas Swadaya Gunung Jati.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (735.221 KB) | DOI: 10.33603/e.v6i1.1516

Abstract

Penurunan fertilitas menjadi 2,4 anak belum mampu memenuhi target RPJMN pada angka 2,1 anak pada tahun 2015 sehingga upaya menurunkan angka kelahiran masih menjadi pekerjaan rumah bagi pemerintah dan seluruh masyarakat Indonesia. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi fertilitas. Data yang digunakan adalah data dari Survei Demografi dan Kesehatan Indonesia (SDKI). Dalam studi ini, data yang digunakan adalah data cross-sectional untuk survei tahun 2017 di wilayah Indonesia. Model yang digunakan adalah analisis regresi logistik biner untuk memprediksi keterlibatan faktor-faktor variabel bebas dengan fertilitas Wanita Usia Subur (WUS) berumur 15-49 tahun yang pernah melahirkan. Hasil analisis menunjukkan bahwa dengan tingkat kesalahan 5%, umur, tingkat pendidikan, status bekerja, status kekayaan, jumlah anak yang meninggal, penggunaan kontrasepsi dan umur melahirkan anak pertama berpengaruh secara signifikan terhadap fertilitas.
PARTISIPASI KERJA LANSIA PADA RUMAH TANGGA TUNGGAL DI INDONESIA Diane Putri Prahastiwi; Yogo Aryo Jatmiko
Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Vol 7 No 1 (2023): Vol. 7 No. 1, Mei 2023
Publisher : Badan Perencanaan Pembangunan, Riset dan Inovasi Daerah Kabupaten Sragen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32630/sukowati.v7i1.391

Abstract

The phenomenon of an aging population has occurred in many countries, including Indonesia. The addition of the percentage of elderly people is expected to have a positive impact on the country's economy by becoming an active elderly person. The scope and unit of analysis used in this study are residents aged 60 years and over throughout Indonesia, both working and not working. This study aims to see the effect of living status with the elderly on the work participation of the elderly in Indonesia using the August 2021 Sakernas data. Descriptive statistics and binary logistic regression are used as analytical tools. The results showed that the tendency for the work participation of the elderly in single households was greater than that of the elderly in non-single households. Therefore, policies to improve the welfare of the elderly in single households need to be of concern to the government, both in terms of improving elderly health services, elderly-friendly employment opportunities, or more equitable social security.
Pemodelan Tingkat Kerawanan Pangan Rumah Tangga di Indonesia Tahun 2021 dengan Pendekatan Regresi Logistik Ordinal Tasya Aguilera; Yogo Aryo Jatmiko
Indonesian Journal of Applied Statistics Vol 5, No 2 (2022)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v5i2.65141

Abstract

Until 2021, Indonesia has succeeded in reducing the prevalence rate of the population with moderate or severe food insecurity. But on the other hand, Indonesia's Global Food Security Index (GFSI) score which has declined in the last three years shows that Indonesia's food security is getting weaker in various aspects. The condition of food security that begins to weaken can trigger food insecurity. Food insecurity that can have an impact on health, nutrition and health system problems is a national health problem that needs attention. Therefore, this study aims to examine the level of household food insecurity and the variables that influence it. This study uses The National Socioeconomic Survey (Susenas) March 2021 data which was analyzed using partial proportional odds model (PPOM) ordinal logistics regression method. In general, the results show that variables area of residence, gender, age, education, business field, number of household members, residence ownership status, and per capita expenditure affect the level of household food insecurity in Indonesia in 2021.Keywords: food insecurity; ordinal logistic regression; PPOM