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All Journal HAYATI Journal of Biosciences Jurnal Ilmu Pertanian Indonesia Jurnal Fitopatologi Indonesia Buletin Penelitian Tanaman Rempah dan Obat Jurnal Perlindungan Tanaman Indonesia ZOO INDONESIA JURNAL HAMA DAN PENYAKIT TUMBUHAN TROPIKA Jurnal Penelitian Pertanian Tanaman Pangan Jurnal Entomologi Indonesia Buletin Penelitian Tanaman Rempah dan Obat Zoo Indonesia Biodiversitas Journal of Biological Diversity
I Wayan Winasa
Department Of Plant Protection, Faculty Of Agriculture, IPB University, Jl. Meranti, Kampus IPB Dramaga, Bogor, West Java, Indonesia, 16680
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Earth & Planetary Sciences Medicine & Pharmacology Other

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Applying Small Area Estimation to Optimize Sample Size for Brown Planthopper (Nilaparvata lugens Stal.) Density Farhan Alfian Nur; Ali Nurmansyah; I Wayan Winasa; Yeni Herdiyeni
Jurnal Perlindungan Tanaman Indonesia Vol 30, No 1 (2026)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jpti.108155

Abstract

The brown planthopper (BPH), Nilaparvata lugens Stål, is an important rice pest requiring consistent monitoring to prevent population outbreaks. However, conventional monitoring relying on large sample sizes is labor-intensive and susceptible to non-sampling errors. This study aimed to evaluate the estimation precision of the Kernel-based Small Area Estimation (SAE) method for BPH population density under significantly reduced sample size conditions. The research utilized observation data from 81 paddy fields in Subang Regency, combined with synthetic data generated via Monte Carlo simulation and variance estimation using Taylor’s Power Law. Altitude was selected as the auxiliary variable for the Kernel-based SAE model based on Spearman’s correlation analysis. The estimation quality was evaluated by comparing Relative Efficiency (RE) and Coefficient of Variation (CV) against the direct estimation method. The results showed that the Kernel-based SAE method with a 20% sample size produced reliable estimates with an RE value of less than one. Statistical tests confirmed no significant difference between the SAE method at 20% sampling and direct estimation at 100% sampling, yet the SAE method demonstrated significantly higher precision with a lower average CV (3.03%) compared to direct estimation (12.72%). In conclusion, the Kernel-based SAE method allows for an 80% reduction in sample size while delivering unbiased and more precise BPH density estimates than conventional methods.
Co-Authors Abdul Munif Akhmad Rizali Ali Nurmansyah Amelia Feryna Bulan Dini Ciptadi Achmad Yusup Dadan Hindayana Dadang Dadang DAMAYANTI BUCHORI Dede Maryana Dewi Sartiami DIAN AGUNG SANORA LAIA ELI ZULKATRI Endang Sri Ratna Farhan Alfian Nur Gusti Indriati HAMDAN MARULI SIREGAR Hamdan Maruli Siregar HERMANU TRIWIDODO HERMANU TRIWIDODO Hermanu Triwidodo Herni Dwinta Pebrianti, Herni Dwinta Hery Widyanto Kurniawan Effendi Kurniawan Effendi Kusumah , Yayi Munara Kusumah, Yayi Munara Manuwoto, Syafrida Mayasari, Astrid Mihwan Sataral Monica, Dheya Cintya Muhammad Rifqi Shafari NFN Rohimatun Nila Wardani Nina Maryana Nurdaaniyah, Andi Prayogo Probo Asmoro PUDJIANTO PUDJIANTO Pudjianto Pudjianto PURNAMA HIDAYAT Rahmini, Rahmini RAUF, AUNU SAKINAH AMANINA SISKA EFENDI Siska Efendi SRI HENDRASTUTI HIDAYAT Sri Yuliani Sugeng Santoso Tawakkal, Muhammad Iqbal TRI YANINTA GINTING TRI YANINTA GINTING Yeni Herdiyeni