Identifying Potential Positive Deviants (PDs) Across Rice Producing Areas in Indonesia: An Application of Big Data Analytics and Approaches

Rice growing areas across Indonesia (2014), including both wetland and dryland production.
Among the 15 distinct HE identified, the table shows the number of villages within each.
Outlier identification is an integral part of the proposed method. We experimented with multiple approaches for outlier identification, and only those outliers that were found across more than one outlier method were termed as “True Outliers”. Mapped (in dark blue) here are “True Outlier” villages of Cipeundeuy, Sobang, Kubangkampil, Sukaresmi Pagelaran, Rangkasbitung, Tanara, Cigelam, Pontang identified in the province of Banteng.
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Data Powered Positive Deviance DPPD

Data Powered Positive Deviance DPPD

We are an international collective that is dedicated to utilizing big data to find effective locally developed solutions to complex problems.

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