Penggunaan Systematic Point Sample sebagai Area Master Frame dalam Mengestimasi Luas Panen Padi - Hazanul Zikra; Widyo Pura Buana (Program Studi Statistika FMIPA UNJ, 2022)
Food data plays an important role in planning for national economic recovery. Therefore, Statistic Indonesia (BPS) developed the Area Frame Survey (AFS) in estimating paddy harvested area. AFS is an method for collecting harvested area data which was previously carried out using eye estimate. Eventhough objective sampling has been applied with a two-stage non-stratified point sampling design (point clustered by square segment), the use of a square segment 300 meters × 300 meters has the potential to generate bias due to the potential for observation points to fall outside the target population (paddy field). This study aims to analyze an alternative AFS using the EUROSTAT recommended design, namely two-phase unclustered point sampling (systematic point sampling frame). The method used is a sampling simulation using rice field population map of East Denpasar in February 2019. The simulation results show that the use of point sample frame provides a better level of accuracy and efficiency than segment sample frame.