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Influence of Social Capital on the Development of Agricultural Areas on Highland Peatlands in Humbang Hasundutan Regency Sipahutar, Tumpal; Nasution, Zulkifli; Purwoko, Agus; Simatupang, Sortha
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.3526

Abstract

The objectives of this study are (1) There are several social capitals owned by farmer groups in supporting the development of highland peatland agricultural areas in Dolok Sanggul District. (2) Measuring the level of social capital of farmer groups on highland peatlands in Dolok Sanggul District. (3) Analyzing the relationship between social capital and the development of agricultural areas in the Upland Peatlands in Dolok Sanggul District. The research method used is the interpretation of the logistic regression model to explain the functional relationship between the dependent variable and the independent variable and to define the unit of change in the dependent variable caused by the independent variable. The results of the research obtained that social capital for farmers who manage agricultural land in Dolok Sanggul District includes two interrelated categories, namely the structural category which includes social relations and solidarity, and the cognitive category which includes health, norms, trust and cooperation. Overall the average level of social capital of farmers in the peatlands of Dolok Sanggul District is 70.45% or moderate (>50-75%), where the level of social capital for social relations (75.9%), solidarity (76.1% ), and cooperation (76.5%) included in the high level of social capital (75-100%), while the level of social capital for health (74.3%), norms (64.2%) and trust (55.7%) ) is included in the moderate level of social capital (50-75%). The results of the analysis show that the relationship variable has a significant effect on increasing farmers' income on peatlands in Dolok Sanggul District. Likewise with social relations, the better the social relations between farmers, the higher the opportunity to increase farmers' income.
Estimated Shallot Yield Area Using the Rapid Classification of Croplands Method Santoso, Agung Budi; Sipahutar, Tumpal; Purba, Tommy; Lumbantobing, Sarman Paul; Hidayat, Shabil; Girsang, Moral Abadi; Haloho, Lermansius
Jurnal Ilmu Pertanian Indonesia Vol. 30 No. 1 (2025): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18343/jipi.30.1.108

Abstract

Shallots are one of the horticultural commodities that have fluctuating prices. Market integration occurs horizontally but not vertically due to poor information systems at the producer and consumer levels. This study aimed to estimate the area of shallot land quickly using the rapid classification of croplands method. The research was conducted in Merek District, Karo Regency, North Sumatra. Primary data obtained from survey activities were processed using the Google Earth Engine platform. Classification and regression trees (CART) and random forest (RF) algorithms were used to classify land cover as onion and non-onion classes. The shallot land area based on this method was 74.4 hectares, with an area accuracy of 95% (RF) and 24% (CART) and a location accuracy of 92% (CART and RF). The rapid classification of croplands method can estimate land area quickly. It helps stakeholders who need information on shallot production projections and can be developed to improve the vertical market integration information system (market integration between producers and consumers). Some areas for improvement of this method are limited access and resolution, inability to describe up to the level of garden bunds, and the condition of the area covered by clouds, which will affect the accuracy of the results. Keywords: shallots, production estimation, google earth engine, remote sensing