Judul: Analisis Faktor-Faktor yang Memengaruhi Anemia Wanita usia 10-54 Tahun pada Data Riskesdas 2018 dengan Metode PLSSEM.
Abstrak: Anemia adalah suatu kondisi ketika kadar hemoglobin dalam sel darah merah kurang dari normal, yaitu kurang dari 12 g/dL untuk wanita tidak hamil dan 11 g/dL untuk wanita hamil (Anggraini et al. 2018). Menurut WHO tahun 2019 prevalensi anemia pada anak usia 6 bulan sampai 5 tahun sebesar 40% dan pada ibu hamil sebesar 37%. Sedangkan di Indonesia menurut Riskesdas 2018 prevalensi anemia pada remaja sebesar 32% dan pada ibu hamil sebesar 48%. Tujuan penelitian ini adalah melakukan evaluasi model PLS-SEM baik outer model maupun inner model serta melakukan uji hipotesis untuk mengetahui peubah yang signifikan terhadap anemia pada wanita usia 10-54. Data yang digunakan merupakan data Riskesdas 2018 dengan menggunakan metode PLS-SEM. Hasil penelitian menunjukkan terdapat 6 indikator yang dinyatakan valid dan reliabel yaitu indikator anemia, geografi, pendidikan, ISPA, Pneumonia, dan status kehamilan. Peubah laten yang signifikan berpengaruh terhadap anemia adalah peubah laten sosial perilaku lingkungan dan biologis. Peubah laten yang signifikan berpengaruh terhadap penyakit adalah sosial perilaku lingkungan dan biologis., Anemia is a condition when the hemoglobin level in red blood cells is less than normal, namely less than 12 g/dL for non-pregnant women and 11 g/dL for pregnant women (Anggraini et al. 2018). According to WHO, in 2019 the prevalence of anemia in children aged 6 months to 5 years was 40% and in pregnant women it was 37%. Meanwhile, in Indonesia, according to Riskesdas 2018, the prevalence of anemia in teenagers is 32% and in pregnant women it is 48%. The aim of this research is to evaluate the PLS-SEM model, both outer model and inner model, and to carry out hypothesis testing to determine significant variables on anemia in women aged 10-54. The data used is 2018 Riskesdas data using the PLS SEM method. The research results showed that there were 6 indicators that were declared valid and reliable, namely anemia, geography, education, ISPA, pneumonia and pregnancy status. Latent variables that significantly influence anemia are social, environmental and biological behavioral latent variables. Latent variables that significantly influence disease are social, environmental and behavior also biological.
Keyword: anemia, PLS-SEM, remaja, WUS

Judul: Factors Influencing Anemia and Iron Deficiency of Pregnant Women in Indonesia
Abstrak: Wanita hamil berisiko tinggi mengalami anemia, defisiensi besi (DB), dan anemia defisiensi besi (ADB). Selama kehamilan, hal itu dikaitkan dengan berat badan lahir rendah, kelahiran prematur, dan peningkatan risiko kematian perinatal. Kondisi anemia, DB, ADB, dapat diprediksi dengan menggunakan metode regresi logistik multinomial. Namun, metode klasifikasi rentan terhadap data yang tidak seimbang. Salah satu metode yang dapat digunakan untuk mengatasi masalah ketidakseimbangan data adalah Random Over Sampling (ROS). Hasil metode regresi logistik multinomial menunjukkan bahwa faktor yang memengaruhi anemia dan defisiensi besi secara signifikan adalah usia kehamilan, status gizi, riwayat penyakit malaria, pendidikan, frekuensi konsumsi buah, dan frekuensi konsumsi sayuran. Model regresi logistik multinomial memberikan akurasi klasifikasi sebesar 44,559%. Penelitian ini juga menunjukkan bahwa tingkat ketepatan klasifikasi keempat kategori lebih seimbang setelah dilakukan Random Over Sampling., Pregnant women are at high risk of anemia, iron deficiency (ID), and iron deficiency anemia (IDA). During pregnancy, it has been associated with low birth weight, premature delivery, and increased risk of perinatal mortality. Anemia, ID, IDA conditions can be predicted using multinomial logistic regression method. However, the classification method is prone to data imbalance. One method that can be used to overcome the problem of data imbalanced is Random Over Sampling (ROS). The results of multinomial logistic regression method indicated that outcome variable were significantly influanced by gestational age, nutritional status, malaria, education, frequency of fruit and vegetable consumption. Multinomial logistic regression model provided classification accuracy of 44,559%. This study also shows that the accuracy of the classification of the four categories is more balanced after Random Over Sampling.
Keyword: anemia, iron deficiency, multinomial logistic regression, pregnant women, random oversampling

Judul: Codiaeum Malesia
Abstrak: The Malesian genus Codiaeum has been revised based on the morphological character using available herbarium collections in Herbarium Bogor iense and loan specimens from Rijksherbarium Leiden. The study is based on the observation of 350 specimens. Eleven species have been recognized, namely Codiaeum variegatum, C. luzonicum, C. palawanense, C. trichocalyx, C. megalanthum, C. cilliatum, C. affine, C. tenerifolium dan C. hirsutum, C. macgregorii, C. ludovicianum. number of species is found in the Philippines The highest (8 species), Two species (C. tenerifolium and C. ludovicianum) endemic in Lousiade Archipelago of the New Guinea and C. affine endemic in Banguey Island. C. variegatum is widespread by nature or in cultivation almost in all of Malesian region. C. cillia tum is a species in the earliest level among the other species according to 20 selected characters.
Keyword: Codiaeum, Malesia