Purpose The purpose of this paper is to clarify the socioeconomic determinants of household food insecurity in Indonesia using individual household data obtained from the 2015 nationwide household socioeconomic and expenditure survey called Survei Sosial Ekonomi Nasional. Design/methodology/approach A stereotype logistic regression model is applied to detect factors determining household food security. Findings The results from the cross-analysis between calorie consumption and share of food expenditure to total household expenditure (Engel coefficient) indicate that 20.8 percent of households were in the “food insecure” category, 21.5 percent in the “lack of food” category, 26.6 percent in the “vulnerable” category and the remaining 31.2 percent in the “food secure” category. Research limitations/implications The main limitation relates to the data set because the collection was conducted in March 2015. Furthermore, the analysis is restricted because of the limited availability of information on socioeconomic factors of respondents. Further research based on the latest data set with more detailed information on respondents is necessary to deepen the discussion. Originality/value Researchers have not specifically discussed the factors determining household food security in Indonesia using reliable nationwide household survey data. The estimation results clearly indicate that a household fulfilling one or more of the following conditions is more likely to be in the “food insecure” category: many members, low education level of household head, divorced household head, household head is a smoker, household head engages in agriculture or construction work and residence is in rural or backward regions.

<strong>English</strong><br />Direct cash transfer is widely used to strengthen food security and reduce household vulnerability to poverty. In Indonesia, direct cash transfer (BLT) has lasted several decades. However, there are still problems in its implementation. This study aims to analyze the effect of BLT on the food security of household-recipients. The data source used was Susenas March 2015, with a total sample of 285,908 households, comprising 55,238 BLT recipients and 230,670 non-recipients. PSM and IPWRA estimators were used to estimate the ATET indicator of food security. The analysis results showed that BLT positively impacted recipient households in terms of calorie and protein intake per capita/day. BLT also has a positive effect on per capita food expenditure and the share of food expenditure. Besides, BLT impacts a change in the percentage of food expenditure; there is a shift in food consumption from the root crops, animal food, fruit, and vegetables to grains, processed food and beverages, and cigarettes. There has been a change in food consumption patterns in recipient households to become more consumptive. However, providing BLT alone is not enough. It should be combined with other social safety net programs to increase the food security of poor households. <br /><br /><br /><strong>Indonesian</strong><br />Bantuan langsung semakin banyak digunakan untuk memperkuat ketahanan pangan dan mengurangi kerentanan kemiskinan. Di Indonesia, Bantuan Langsung Tunai (BLT) telah berlangsung beberapa dekade. Akan tetapi, dalam pelaksanaannya terdapat beberapa permasalahan, di antaranya ketidaktepatan sasaran. Penelitian ini bertujuan menganalisis dampak program BLT terhadap ketahanan pangan penerima. Sumber data adalah Susenas Maret 2015, dengan sampel 285.908 rumah tangga, terdiri dari 55.238 penerima BLT dan 230.670 bukan penerima. Metode PSM dan IPWRA digunakan untuk menduga ATET indikator ketahanan pangan. Hasil analisis menunjukkan bahwa pemberian BLT memberikan dampak positif bagi rumah tangga penerima dalam aspek asupan kalori dan protein per kapita/hari. BLT juga berdampak positif terhadap pengeluaran pangan per kapita dan pangsa pengeluaran pangan. Selain itu, BLT berdampak pada perubahan pangsa pengeluaran pangan yang ditunjukkan oleh terjadinya pergeseran konsumsi pangan dari kelompok pangan umbi-umbian, pangan hewani, buah dan sayur menuju kelompok padi-padian, makanan dan minuman jadi, serta rokok. Terjadi perubahan pola konsumsi pangan pada rumah tangga penerima menjadi lebih konsumtif. Secara keseluruhan, BLT mampu memberikan dampak positif terhadap beberapa indikator ketahanan pangan. Pemberian BLT saja tidak cukup untuk memberikan makanan yang cukup dan bergizi bagi rumah tangga penerima. Perlu ada kombinasi antara bantuan langsung tunai dengan program jaring pengaman sosial lainnya yang bertujuan untuk meningkatkan ketahanan pangan rumah tangga miskin.

This paper aims to identify factors affecting farmers' negative perception on utilizing rice transplanters and combine harvesters. To this end, data obtained from interview survey in the westernmost part of Java Island, Banten Province was analyzed, where agricultural labor wages increase at a faster pace as compared to other regions and a rapid diffusion of agricultural mechanization is anticipated. The estimation results of multiple regression models clearly show that majority of coefficients of three independent variables: farm size extension, and farming experience, are statistically significant and take negative values. Therefore, it can be concluded that the larger the farm size, the more training provided by the government extension office, and the longer farming experience, the lesser the negative perception on the use of transplanters and combine harvesters. Educational background (formal human capital formation), the number of family members (within-household labor endowment), and yield per hectare are not found to significantly affect farmers' negative perception. Considering the above estimation results, it seems that the government agricultural extension service plays a significant role in lessening farmers' negative perceptions on transplanters and combine harvesters and thereby facilitates agricultural mechanization to cope with the rapid rise in agricultural labor wages.

<strong>English</strong><br />Combined Harvester (CH) aid is part of the Indonesian government policy instrument for accelerating rice production and increasing farmers’ income. In addition to reducing harvesting cost and time, CH may also reduce harvest loss. This study intends to quantify rice yield loss reduction if CH is used for harvesting. The study was conducted in Banten Province in 2014 using primary data collected from 119 CH user farmers and 116 non-user farmers selected purposively. Preliminary analysis was conducted using regression which was estimated with the Ordinary Least Square (OLS) method. Since OLS estimated regression is prone to sample selection bias, subsequent analysis is conducted using the Propensity Score Matching (PSM) estimator with a logistic regression. The PSM analysis support the regression analysis that CH reduces harvest loss. Based on the Stratification Matching, it was found that the CH reduces harvest loss by up to 200.39 kg per hectare or around 3.52% of total yield. It is recommended that the Government facilitates provision of technical assistance and training for CH operator farmers or farmers’ groups particularly the first users aid recipients. The harvest reduction advantage is an additional reason for supporting feasibility of CH scaling out policy in Indonesia.<br /><br /><br /><strong>Indonesian</strong><br />Bantuan combined harvester (CH) padi adalah salah satu instrumen kebijakan pemerintah Indonesia untuk mendorong peningkatan produksi dan pendapatan petani padi. Walau manfaat utamanya adalah untuk menghemat ongkos dan mempercepat panen, CH juga dapat mengurangi kehilangan panen. Penelitian ini bertujuan untuk menghitung kuantitas pengurangan kehilangan hasil usaha tani padi jika panen dilakukan dengan CH. Penelitian dilakukan menggunakan data primer dari 119 petani pengguna dan 116 petani nonpengguna CH yang dipilih sengaja di Provinsi Banten pada tahun 2014. Analisis awal dilakukan dengan regresi yang diduga dengan kwadrat terkecil biasa (OLS). Untuk mengatasi potensi bias sampel pada analisis regresi OLS, selanjutnya digunakan penduga Propensity Score Matching (PSM) dengan mempergunakan regresi logistik. Hasil analisis PSM memverifikasi efek positif penggunaan CH terhadap kehilangan hasil berdasarkan analisis regresi OLS. Berdasarkan Stratification Matching didapatkan bahwa penggunan CH dapat menekan kehilangan hasil sebesar 200,39 kg per hektare atau sekitar 3,52% dari total hasil. Disarankan agar pemerintah memfasilitasi pendampingan dan pelatihan teknis kepada petani atau kelompok tani operator, utamanya pengguna pertama penerima bantuan. Manfaat mengurangi kehilangan panen memperkuat kelayakan kebijakan perluasan penggunaan CH di Indonesia.

This study aims to evaluate the effects of an urban and peri-urban agriculture program called Sustainable Home-Yard Food Garden (KRPL, Kawasan Rumah Pangan Lestari) on participants' household income and identify factors affecting the extent to which a participant is actively involved in the program. Many varieties of fresh vegetables, such as chilies, celery, mustard, kai lan (Chinese broccoli), eggplants, tomatoes, cauliflower, lettuce, packoy (Chinese cabbage), cabbage, long beans, and spinach, are harvested from plastic pots, suggesting the program contributes to dietary diversification. In addition, participating in the KRPL program results in cutting back on expenditure on fresh vegetables and/or increasing household income to a certain extent. The estimation results of the OLS regression model using the interview survey data indicate that a KRPL participant who has a larger number of pots and/or grows more varieties of vegetables tends to exhibit the following characteristics: (1) she likes gardening and/or spending time in nature, (2) she is not motivated by a passive reason for participating in the KRPL program, (3) she grows vegetables for the purpose of selling them, (4) the largest proportion of products is sold to someone or given to her friends/neighbors/relatives, and (5) she resides in the more developed northern part of Banten, which is directly connected to the capital city by the Jakarta-Merak toll road.