Judul: Variable Importance Analysis Based on The Extra-Trees Model for Identification of The Characterizing Variables of Food-Insecure Households in West Java
Abstrak: Sekitar 2,3 miliar orang di dunia mengalami kerawanan pangan. Kerawanan pangan dapat memiliki konsekuensi serius bagi kesehatan dan kesejahteraan. Pengentasan kerawanan pangan menjadi salah satu isu krusial dalam mewujudkan tujuan kedua pembangunan berkelanjutan, yaitu tanpa kelaparan. Penelitian ini bertujuan untuk mengidentifikasi peubah penting yang mencirikan kerawanan pangan rumah tangga di Jawa Barat. Penelitian akan dibagi menjadi dua subpopulasi yaitu rumah tangga perdesan dan perkotaan. Data yang digunakan dalam penelitian ini adalah data Survei Sosial Ekonomi Nasional tahun 2021. Algoritma yang digunakan untuk melakukan pemodelan klasifikasi kejadian rawan pangan adalah Extremely Randomized Trees (Extra-Trees) dengan penanganan data tidak seimbang menggunakan oversampling ADASYN dan pembobotan kelas peubah respon. Peubah penting yang mencirikan kerawanan pangan diidentifikasi menggunakan SHapley Additive exPlanations (SHAP). Model dengan penanganan menggunakan pembobotan kelas menghasilkan kinerja yang lebih baik dibanding tanpa penanganan dan dengan penanganan ketidakseimbangan data menggunakan ADASYN. Hasil evaluasi menunjukan balanced accuracy model perdesaan sebesar 60,76% dan model perkotaan sebesar 64,08%. Jenis lantai, kepemilikan aset tanah, Bantuan Pangan Non-Tunai (BPNT), bantuan Pemda, jenis dinding, banyaknya penabung, pendidikan KRT, Penerima Bantuan Iuran (PBI) BPJS, bahan bakar masak, dan jenis kelamin KRT merupakan peubah penting yang mencirikan kejadian rumah tangga rawan pangan perdesaan. Banyaknya penabung, PBI BPJS, kepemilikan aset tanah, jenis lantai, pendidikan KRT, BPNT, bantuan Pemda, Program Keluarga Harapan (PKH), sanitasi layak, dan jumlah perokok merupakan peubah penting yang mencirikan kejadian rumah tangga rawan pangan perkotaan., Approximately 2,3 billion people in the world have experienced food insecurity. Food insecurity can have serious consequences for health and well-being. Alleviation of food insecurity is one of the crucial issues in realizing the second goal of the Sustainable Development Goals, zero hunger. This study aims to identify important variables that characterize household food insecurity in West Java Province. This study will be divided into two subpopulations, rural and urban households. The data used in this study is the 2021 National Social and Economic Survey. The algorithm used to classify the incidence of household food insecurity is Extremely Randomized Trees (Extra-Trees) with imbalanced data handling using ADASYN and class weight of response variables. Important variables that characterize food insecurity are identified using SHapley Additive exPlanations (SHAP). Models that handle by using class weights produce better performance than without handling imbalanced data and with handling by using ADASYN. The evaluation results show that the balanced accuracy of the rural model is 60,76%, and the urban model is 64,08%. Floor type, land assets ownership, Non-Cash Food Assistance (BPNT), local government assistance, wall type, number of savers, education of household head, Premium Assistance Beneficiaries (PBI) BPJS, cooking fuel, and gender of household head are important variables that characterize the incidence of food insecurity in rural households. The number of savers, PBI BPJS, land assets ownership, floor type, education of household head, BPNT, local government assistance, Keluarga Harapan Program (PKH), decent sanitation, and number of smokers are important variables that characterize food insecurity in urban households.
Keyword: Extra-Trees, food insecurity, imbalanced data, SHAP, West Java

Judul: Identifikasi Faktor yang Memengaruhi Status Rawan Pangan Rumah Tangga di Provinsi Jawa Barat
Abstrak: Kesejahteraan bagi suatu rumah tangga ditandai dengan terpenuhinya kebutuhan standar hidup salah satunya adalah pangan. Negara berkewajiban dalam memenuhi kebutuhan pangan tertuang dalam UU No.18 Tahun 2012. Perwujudan ketahanan pangan perlu dimulai dari terpenuhinya kebutuhan pangan pada skala terkecil (rumah tangga). Jawa Barat merupakan provinsi dengan jumlah penduduk terbanyak di Indonesia. Ketersediaan pangan akan terancam dengan semakin meningkatnya jumlah penduduk, dikhawatirkan dapat mengancam ketahanan pangan di Jawa Barat hingga ke skala rumah tangga. Penelitian ini membangun model klasifikasi status rawan pangan rumah tangga serta mengkaji faktor yang memengaruhinya dengan pendekatan metode multivariate adaptive regression splines (MARS). Model MARS terpilih pada penelitian ini terbentuk berdasarkan kombinasi basis function (BF) = 28, maximum interaction (MI) = 2, dan minimum observation (MO) = 1, model menghasilkan generalized cross validation (GCV) minimum sebesar 0.1604912. Terdapat 8 dari 14 peubah penjelas berpengaruh signifikan berdasarkan tingkat kepentingan terhadap model klasifikasi status rawan pangan rumah tangga di provinsi Jawa Barat. Evaluasi model dilakukan pada data uji dihasilkan nilai akurasi sebesar 64.66% dan apparent error rate (APER) sebesar 35.34%. Pada keseluruhan data dihasilkan nilai akurasi sebesar 64.9% dengan APER sebesar 35.1%. Statistik Uji Press’s Q menunjukan hasil klasifikasi sudah stabil dan konsisten secara statistik pada taraf nyata 5%., Welfare for a household is characterized by the fulfilling living standard needs, one of which is food. The state is obliged to meet the food needs contained in Law No.18 of 2012. The realization of food security needs to start from the fulfilling food needs on the smallest scale (household). West Java is the province with the largest population in Indonesia. The increasing population will threaten food availability, feared to threaten food security in West Java to the scale of households. This study builds a classification model of household food insecurity status and examines the factors that influence it using multivariate adaptive regression splines (MARS) methods. The MARS model selected in the study was formed based on a combination of base functions (BF) = 28, maximum interaction (MI) = 2, and minimum observation (MO) = 1, the model produced a minimum generalized cross-validation (GCV) of 0.1604912. There are 8 out of 14 significant influences based on the level of importance to the classification model of household food insecurity status in West Java province. The evaluation of the model conducted on the test data resulted in an accuracy value of 64.66% and an apparent error rate (APER) of 35.34%. Overall data generated an accuracy value of 64.9% with an APER of 35.1%. Press's Q Test statistics show the classification results are stable and statistically consistent at a real level of 5%.
Keyword: Klasifikasi, MARS, Peubah, Rawan Pangan, Rumah Tangga

Judul: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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