Judul: Pemodelan Decision Network untuk Menentukan Pola Tanam Pertanian Dinamis
Abstrak: Plants require different climatic conditions to grow well. The knowledge of optimum climate for plant to grow is essentially needed. The El Nino and La Nina phenomena affect the climate changes variability in Indonesia. El Nino causes a decrease in agricultural productivity due to the reduction in availability of water for crops. However, the La Nina phenomenon increases agricultural productivity due to the abundant availability of water. The strategy that can be done to solve the problem of climate change are to adjust the shape of cropping patterns and to forecast the season by using a Decision Network. Based on the Decision Network, the decision to select established cropping patterns is done using climate information and other obtained information before the decision is made. In this study, there are four information to be used. They are SOI index in August which can be used as an early possible indicator of rainy season changes, the length of rainy season, the rainfall in dry season, and the land area affected by drought. The objective of this research was to build the information model for agricultural cropping pattern by decision network. The data in this research were from 1965 to 2010. Cropping pattern can be used to produce a proper and accurate decision regarding to possibility of drought in areas. It also can be used to predict the possibility of loss amount that may arise. This study is conducted Indramayu District. The decisions are based on cropping patterns in Indramayu. The result showed that the model accuracy was 61.9% based on the relationship between the possibility of drought and drought data record in Indramayu from 1989 until 2009.
Keyword: 

Judul: Development of semi dynamic cropping calendar for Indramayu using Pacific sea surface temperature
Abstrak: Agriculture is a very important sector in Indramayu’s economy. Approximately 53.52% of Indramayu residents are involved in agriculture. Indramayu has 119.752 Ha (58% of the total area) cultivated as rice fields which generates the majority of the district’s income. Most of the farmers use a traditional cropping method called Pranata Mangsa, which is based on periodic natural events and Primbon, but not climate variability. Climate variability has become a major obstacle to achieving a successful harvest, because it can affect the timing of planting and length of the growing season, which leads to drought and flood vulnerability. The planting date and growing season can be predicted using monthly sea surface temperature (SST) anomalies in Nino 3.4. The August SST anomalies can describe the planting date better than the growing season, which are demonstrated best in Lohbener with R-Sq = 45% with forecast skill reach = 84% and 92% for advanced and delayed planting date. Knowing the planting date and growing season length produces a more efficient cropping calendar, which includes details such as when to prepare the land, plant seeds, and harvest. This cropping calendar is expected to reduce the impacts of climate variability by providing a more efficient cropping pattern and avoiding potential harvest failures.
Keyword: 

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
Keyword: