Warta Informatika Pertanian : Volume 17 No. 2, 2008

TIM PENYUSUN

Penanggung Jawab :

DR. HARYONO SOEPARNO

Dewan Redaksi :

DR. MARHENDRO

Anggota :

Dr. Wayan R. Susila ; Dr. L. Hardi Prasetyo ; Drs. Iwa Sungkawa, M.S ; 

Dra. Siti Nurjayanti, M.Sc ; Ir. Erlita Andriani, M.Sc ; Dhani Gartina, S.Komp.

Redaksi Pelaksana :

Mimbarsono ; Ir. Sri Arini Daryati ; Mohammad Maulana, Amd.

    

Yiyi Sulaeman dan Rizatus Shofiyati, Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian - Bogor.

Results of soil data from soil research activity may be useful for other purposes if they are stored in digitalized database and analyzed using the appropriate approach and tool. The data mining approach provides a superior and speedy means in problem solving, presentation of the results, data assumption and research goals. Such an approach has not been fully used in national soil research. This paper aims to discuss the potential contribution of data mining and the challenges to apply it in national soil research, as well as to propose a framework in its application. Data mining provides techniques for discovering data pattern(s) and building models using large soil dataset. Data pattern(s) and models are used to formulate hypothesis and develop tools for soil and land management. The proposed framework being tailored to national condition covers soil digital database development, dataset selection, algorithm application, and presentation and interpretation of the results. Examples of decision tree and rule model are provided. Yet, to fully take advantage of these opportunities, national soil scientists are challenged to find ways on how: (i) to develop good soil digital database; (ii) to understand data mining algorithms, and (iii) to increase their capability in operating available software. Hopefully, studies benefiting from data mining approach may increase in near future.

Keyword : data mining, soil database, data mining framework.

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Chandra Indrawanto, Pusat Penelitian dan Pengembangan Perkebunan - Bogor.

As the largest coconut producing area, coconuts in Lampung Selatan Regency have not provided a good income  to the farmers. Developing a coconut agro-industry at the farmers group level is a way to increase the farmers’ income. For that reason, it is important to determine the most economically suitable type of coconut agro-industry and its financial feasibility. This research uses a system approach in its analysis. Analytical Hierarchy Process (AHP) method has been applied to decide the most suitable type of coconut agroindustry to be developed. Acquisition of expert judgement has been done by intensive interview and Focus Group Discussion (FGD) for five coconut experts. For financial analysis, the data was collected from 55 coconut farmers and 4 coconut agroindustry entrepreneurs. The analysis shows that the market for the coconut agroindustry products is the most important determinant factor in developing a coconut agroindustry. This factor is very dependent on the performance of the government in building a good relation between the agroindustry with the downstream industry, which uses the agroindustry products as raw materials. This condition placed the government as the most important actor in developing the coconut agroindustry. From the five types of alternative coconut agroindustry examined, the fibre and coco-peat agro-industry is the best industry to be developed in Lampung Selatan Regency. Financial analysis shows that this type of agro-industry is feasible to be developed. However, the agro-industry has to be supported by sufficient raw materials. Fibre and coco-peat agroindustry with 1,500 fibres per day capacity has to be supported with raw materials from 75 ha of coconut trees. The government of Lampung Selatan Regency can be a leader in developing this fibre and coco-peat agroindustry by creating clusters of the fibre and coco-peat agroindustry at a level that meets with the area’s ability to supply the raw materials and building a good relation between the agroindustry with the downstream industry, which uses the agroindustry products as raw materials.

Key words : Cocos nucifera, agro industry, feasibility, AHP.

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Wayan R. Susila1 dan Ernawati Munadi2, 1. Lembaga Riset Perkebunan Indonesia - Bogor & 2. Dosen Universitas Wijaya Kusuma - Surabaya.

The development of CPO-based biodiesel has been perceived to create a dilemma regarding the poverty alleviation in Indonesia. On one hand, the development will reduce the incidence of poverty in the palm oil producing center. On the other hand, the production of biodiesel will induce the CPO price to increase, which will lead to cooking oil price increase. This will lift the poverty line leading to an increase in the number of the poor. The objective of this study is to assess the net impact of the CPO-based development on poverty alleviation. A simulation model that integrates CPO market, cooking oil market, biodiesel production, and poverty alleviation is applied to assess the impact. The results of the study indicate that the development of biodiesel will reduce the number of the poor. Therefore, the development of the biodiesel should be accelerated through (i) assign government owned companies operating on CPO industry and energy to be the trigger of the industry; (ii) provide tax incentives to the industry; and (iii) provide price subsidy to the industry.       

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Wieta B. Komalasari, Statistisi pada Pusat Data dan Informasi Pertanian - Jakarta. 

Soybean plays an important role to fulfill the requirement of plant protein for Indonesia. The most recognized soybean product is tempe. Indonesia represents the biggest producing country of tempe and thus the biggest soybean market in Asia. To meet its demand, soybeans still have to be imported. The Government continues to make an effort to increase soybean production by making soybean as a primary commodity such as paddy in the food crops sub-sector. The objective of this paper is to perform a prediction on soybean’s supply and demand situation for 2 (two) years ahead with time series data analysis. This paper is expected to supply or make available information for users to construct a planning model in agricultural development for soybean. According to the BPS Statistics Bureau, Indonesia, in 2008 the area harvested for soybean is 579.59 thousand hectares, with an average yield of 13.13 kw/ha and total production of 761.21 thousand tons. Globally, Indonesia’s soybean production is the 9th largest production.  For the 2 (two) years ahead, based on the analytical results of this study, soybean production will increase by about 2.60%. As the institution responsible for the foodcrop industry, the Directorate General of Food Crops has set a very optimistic target compare to the prediction in this paper. The study result shows that in 2009 and 2010, Indonesia will suffer an insufficient supply of soybean of about 771 thousand ton and 705 thousand ton respectively.

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Roch Widaningsih, Statistisi pada Pusat Data dan Informasi Pertanian - Jakarta. 

Survey sampling is one of the tools which can be used to estimate the parameter of a population. The best survey sampling technique can produce the highest reliability, validity and accuracy of a population estimation. This research studied the various survey sampling techniques (i.e. simple random sampling, systematic random sampling, stratified random sampling and two-stage cluster sampling) to estimate cattle population by making a simulation of population estimate and its variance. The simulation was conducted for 100 times with the numbers of samples n1=300, n2=400, and n3=500, and then they were compared to determine which technique produced the best estimate. They were then compared to the agriculture survey sampling. The result shows that stratified random sampling with n=500 has the highest level of reliability, validity and accuracy. The simple random sampling, systematic random sampling and stratified random sampling give a higher estimate level than the agricultural survey sampling, and the two-stage cluster sampling a lower level.

Key words : Survey Sampling, Reliability, Validity, Accuracy.

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