Judul: "SMART" AGROLOGISTIK: Sistem Pendukung Keputusan Spasial Cerdas untuk Pengembangan Logistik Agroindustri Kentang Berkelanjutan
Abstrak: Potato (Solanum tuberosum L.) is an essential horticultural food after wheat, rice, and corn. Indonesia is the world's 10th producer and the largest in Southeast Asia, with a growth rate of 8.4% per year and an average production of 1.3 million tons/year. The most significant production in Indonesia is Central Java, which is 277,702 tons. In Indonesia, potato is a strategic horticultural commodity that prioritizes diversified food consumption and supports national sustainable food security. Trends in global food security, the complexity, uncertainty of decision-making, and demands for environmental sustainability have given birth to adaptive technology, including modern logistics. Agro-industry logistics (agro logistics) is a modern logistics related to processing food horticultural raw materials. The main problem is the product characteristics with high vulnerability, complexity, and uncertainty. The perishable nature of commodities, sensitivity to climate change, and high price fluctuations cause this. Quality declines rapidly after harvest, resulting in potential losses of up to 40%. In addition, the spatial conditions affect the supply capability, while standard mathematical calculations cannot solve this problem. Therefore, a Decision Support System (DSS) is needed to improve sustainable food security that considers the characteristics of food horticultural products with a spatial perspective. This study developed "SMART" AGROLOGISTICS, a prototype application of an intelligent spatial decision-making system for sustainable potato agro logistics development. This prototype supports the SMART framework, a reliable and integrated simulation model that is adaptive and integrated. This prototype has determined the most suitable location for the development of potatoes as sustainable food horticulture. This prototype can integrate the IoT, namely SHT15 sensors for humidity and temperature and rain gauge sensors for rainfall. Spatial analysis of three physical factors: altitude, soil texture, slope percentage, and three factors: climate, temperature, humidity, and rainfall. The development of this prototype is an effort to increase productivity which is currently low, which is 16.99 tons/ha, and the target of meeting industrial needs, has only reached 85.93%. The prototype implementation level in Wonosobo, Central Java, shows that the average research sample with very suitable sustainability is 11.05%. Good condition with several inhibiting factors is 62.01%, and moderately sustainable condition is 22.9%. Meanwhile, we did not record 4.04%. Sustainability areas are in Kejajar (P1), Garung (P2), Mojotengah (P3), Kalikajar (P5), and Kepil (P13), so we recommend prioritizing these locations to meet industry needs. This study modifies the multi-thresholding method with overlay and geoprocessing techniques to predict the amount of harvest. The development of a prototype with a modification of this method attempts to balance supply and demand. The current demand for raw materials for the potato industry in Central Java is 117,000 tons/year. This prototype integrates IoT, namely remote sensing using DJI quadcopters drones to balance supply and demand. The prototype implementation shows that the average total harvest is 13.79 tons/ha, with the accuracy rate of 89.35%. The predicted total industrial potato production is 72,765 tons/year. So there is still a shortage of production of 44,235 tons/year. Decision-makers can use this method to meet the needs of potato raw materials for industry. The modification of this model can recommend an increase in
Keyword: food security, IoT, ISDSS, logistics transparency, spatial Dijkstra, sustainable potato agro-industry

Judul: Aplikasi model simulasi untuk prediksi dampak perubahan iklim terhadap produktivitas tanaman kentang (Solanum tuberosum L.) di Indonesia
Abstrak: Potato is an important horticulture crop in Indonesia in terms of planted area more than 55.000 ha and its production 864.000 ton. The crop is commonly grown in upland areas above 800 m where runoff and erosion often cause environmental problem whereas the yield is relatively low due to various reasons. The crop growth depends on climatic variables particularly rainfall, solar radiation and temperature. Climate change, particularly temperature increase and rainfall decrease, is expected to adversely impact potato growth with the results of even lower yield of the crop compared to the current yield. In order to develop potato crop simulation model, field experiment at Pacet and Galudra (West Java Province) and Kerinci (Jambi Province) were conducted to derive parameters that are required for model building and validation. The experiments were conducted from December 2009 to September 2011. The model being constructed consists of (1) crop-development submodel, (2) crop-growth submodel, and (3) water-balance submodel. Model was calibrated using data collected from three field experiments. The application includes determining potential yield of potato crop under different climates, both under current condition and under different climate change scenarios. The model was also run at different planting dates to find the maximum yield from which optimum planting date was determined. Result showed that in general validation results using paired t-test suggest that model predictions are not significantly different (P > 0,05) with field measurements at Galudra and Kerinci for variables of periods of developmental phases, biomass of root, stem, leaf and tuber, leaf area index, and soil water content (Granola cultivar) and biomass of stem, tuber and soil water content (Atlantic cultivar). However, graphical test of the relationships between model predictions and field measurements have coefficients of determination (R2) higher than 0,80 for all of variables being tested. The simulation model of development, growth and waterbalance of potato crop could predict climate change impact on potato productivity in several potato production centers in Indonesia (Minahasa, Alahan Panjang, Pangalengan, Pasuruan, Wonosobo, and Deli Serdang). Predicted potato yields in the six potato production centers using three scenarios of increasing temperature and decreasing rainfall for the year 2020, 2050, and 2080 based on climate change projection in Indonesia for the future (SRES A1) were in the range of 13% – 31%, 25% – 47% and 37% – 63%, respectively. Potato production center in Pangalengan was predicted to experience the biggest decline in yield for all scenarios. Predicted yield of Atlantic variety was 25 ton ha-1, which was higher than Granola variety of 16 ton ha-1. Climate change adaptation options based on simulation of the model are: optimal planting time, use of superior potato varieties that have higher value of RUE, and select application of suitable potato varieties that are more tolerant to high temperatures.
Keyword: 

Judul: Konstruksi Hukum Grup Kurva Eliptik Atas F3m
Abstrak: Elliptic curves upon F3m can be divided in two cases, i.e. supersingular and nonsupersingular case. Based on group laws on elliptic curves, a new arithmetic upon F3m can be formulated as an addition process of two random points on the curve. This addition process can then be applied to the ElGamal algorithm.
Keyword: