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: 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: Elektrodeposisi Film Tipis Semikonduktor Cu2ZnSnS4 (CZTS) pada Substrat Kaca ITO
Abstrak: Semiconductor Cu2ZnSnS4 (CZTS) thin film that can be used as absorber layers on solar cell module was made via electrodeposition method. CZTS thin film was electrodeposited on the surface of a silicate glass coated with a thin layer of indium tin oxide (ITO). Deposition process was done using potentiostatic mode at room temperature with a potential of 1.05 V for 30, 45, and 60 minutes, followed with annealing the film at 2 different temperatures, 500 ºC using furnace and 180 ºC using hot plate, both treatments for 45 minutes in N2/H2S atmosphere. The X-ray difractograms were analyzed using Match 2 program and showed that the CZTS thin films had kesterit crystalline structure, with a low percentage of CZTS phase. The thin film also contained secondary phases such as Cu2S, ZnS, and SnS. The obtained CZTS thin films had a thickness between 1.039 and 1.676 μm. Absorption study showed that the band gap energy of CZTS thin films which was annealed using furnace ranged from 1.50 to 1.52 eV, whereas that annealed using the hot plate was not observed. The band gap energy value showed that CZTS thin films can be used as sunlight absorber layers on solar cell. The formation of CZTS crystal film on this investigation was effectively performed using furnace annealing process at a temperature of 500 ºC with deposition time of 45 minutes.
Keyword: Thin film, Electrodeposition, Cu2ZnSnS4