Judul: IDENTIFICATION OF AGRICULTURAL DROUGHT AREAS USING NDDI AND TVDI METHODS IN CIRANJANG SUB-DISTRICT, CIANJUR REGENCY
Abstrak: Kekeringan merupakan salah satu jenis bencana alam hidrometeorologis. Kecamatan Ciranjang, Kabupaten Cianjur mengalami kekeringan puncak musim kemarau yang berdampak pada ketersediaan air untuk keperluan domestik dan pengairan lahan pertanian. Penelitian ini bertujuan menganalisis persebaran wilayah yang mengalami kekeringan lahan pertanian menggunakan metode Normalized Difference Drought Index (NDDI) dan Temperature Vegetation Dryness Index (TVDI) di Kecamatan Ciranjang, Kabupaten Cianjur pada tahun 2015 dan 2019. NDDI berfokus pada perubahan vegetasi dan kehilangan air tanaman sebagai indikator kekeringan. TVDI dalam mengindikasikan kekeringan berfokus pada perbedaan suhu permukaan tanah dan vegetasi. Kelembaban tanah sawah irigasi dan tadah hujan memiliki tren positif terhadap ketinggian lahan yang berkaitan dengan kedekatan sumber air. Wilayah kekeringan pertanian di Kecamatan Ciranjang pada kategori kering metode NDDI dan TVDI adalah sawah tadah hujan yang berada di Desa Kertajaya, Gunungsari, dan Sindangsari pada ketinggian lahan di atas 250 mdpl. Kejadian kekeringan di Kecamatan Ciranjang dipengaruhi oleh topografi, wilayah yang lebih tinggi cenderung lebih kering saat kondisi curah hujan tidak mencukupi. Kekeringan lahan pertanian di Kecamatan Ciranjang pada tahun 2015 dan 2019 menurunkan luas panen padi sekitar 15%. Pemetaan area persawahan yang berpotensi kering merupakan strategi awal untuk menentukan area prioritas penanganan kekeringan guna meminimalisir kerugian., Drought is one type of hydrometeorological natural disaster. Ciranjang Sub-district, Cianjur Regency had a peak dry season drought that affected the availability of water for domestic use and irrigation of agricultural land. This study aims to analyze the distribution of areas experiencing agricultural land drought using the Normalized Difference Drought Index (NDDI) and Temperature Vegetation Dryness Index (TVDI) methods in Ciranjang District, Cianjur Regency in 2015 and 2019. NDDI focuses on changes in vegetation and plant water loss as indicators of drought. TVDI indicates drought by focusing on differences in soil surface temperature and vegetation. Soil moisture of irrigated and rainfed rice fields has a positive trend towards land elevation related to the nearness of water sources. Agricultural drought areas in Ciranjang Sub-district in the dry category of NDDI and TVDI methods are rainfed rice fields located in Kertajaya, Gunungsari, and Sindangsari Villages at land elevations above 250 meters above sea level. Drought events in Ciranjang Sub-district is influenced by topography; higher areas tend to be drier when there is insufficient rainfall. Drought in Ciranjang sub-district in 2015 and 2019 reduced the rice harvest area by around 15%. Mapping of potentially dry rice fields is an initial strategy to determine priority areas for drought management to minimize losses.
Keyword: drought, NDDI, paddy field, soil moisture, TVDI

Judul: Identifikasi lahan pertanian rawan kekeringan dengan metode sistem informasi geografis
Abstrak: Drought is an event where rainfall is very low for long time period. Drought is a common natural phenomenon in Indonesia. It affects a wide variety of events, one of which is crop failure. This study aims to determine the drought prone of an area in Indramayu using GIS methods based on several bio-physic parameters, to determine the distribution and characteristics of drought prone area in Indramayu district, and to see the difference in the distribution of drought prone area by using different or the equal weights of parameter in annual rainfall or monthly rainfall (dry season). The study consists of several phases namely preparation, collection of base maps and create thematic map, satellite imagery interpretation, analysis and making drought-vulnerable, and presentation of research results. The bio-physic parameters used in this study were rainfall, landforms, land cover, drainage, slope, and stream buffers. All parameters are combined in a GIS analysis using different weighting and equal weighting with annual rainfall and dry season rainfall. The most influential parameter will get the highest value of weight and parameters with small influence will be given a low weight value. Modeling bio-physic parameter with different weights to the annual rainfall resulted in two vulnerable classes, less vulnerable 77.24%, and vulnerable 22.76%, while for the dry season rainfall resulted three classes including not vulnerable 0.74%, less vulnerable 85.20%, and vulnerable 14.06%. Maps with the equal weighting parameters for the annual rainfall resulted in four classes including not vulnerable 0.07%, less vulnerable 76.26%, vulnerable 23.56% and very vulnerable 0.11%. For the dry season rainfall also resulted in four classes: not vulnerable 0.47%, less vulnerable 84.12%, and vulnerable 15.28%, and the very vulnerable classes 0.12%. The subdistrict that potentially effected by drought prone area are Trisi subdistrict and Gantar subdistrict.
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Judul: Karakteristik Emulsifier dari otak sapi yang diekstrak dengan menggunakan pelarut yangberbeda
Abstrak: Brain is an animal by-product which has the highest phospholipids a ~cdho lesterol content. Phospholipids in brain consist of a polar head (phosphate acid) and nonpolar tail (lipid). Therefore, phospholipids can be used as an emulsifier in emulsion products such as cosmetics and pharmaceutical.
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