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All Journal Jurnal Kajian Informasi & Perpustakaan ZIRAA'AH MAJALAH ILMIAH PERTANIAN Educative Sportive LIBRIA: Library of UIN Ar-Raniry Journal of Correctional Issues (JCI) Informatio: Journal of Library and Information Science Shautuna: Jurnal Ilmiah Mahasiswa Perbandingan Mazhab Dulang: Jurnal Pengabdian Kepada Masyarakat Journal of Engineering, Technology and Computing (JETCom) Nanggroe: Journal Of Scholarly Service Nanggroe: Journal of Scholarly Service JRIIN :Jurnal Riset Informatika dan Inovasi
Saputra, Dandi
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PRODUCTION ANALYSIS OF SMALLHOLDER OIL PALM ON PEATLAND AND DRYLAND IN RAWA BANGUN VILLAGE Saputra, Dandi; Yuristia, Rahmi; Cahyadinata, Indra; Hayati, Nur Qomarian
ZIRAA'AH MAJALAH ILMIAH PERTANIAN Vol 50, No 2 (2025)
Publisher : Pusat Publikasi Jurnal Universitas Islam Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/zmip.v50i2.18888

Abstract

Oil palm is one of the commodities that plays a vital role in the Indonesian economy, especially in Bengkulu Province. Mukomuko District, Rawa Bangun Village, has oil palm plantations on peatland and dryland. This study aims to analyze production, productivity, and factors affecting smallholder oil palm production on peatland and dryland. Respondents totalled 84 oil palm farmers, determined by the Slovin method and Proportionate Stratified Random Sampling to divide peatland and dryland respondents. Production factors were analyzed using the Cobb-Douglas model. The results showed that the average production was 65,038 kg per year, and the average productivity was 21,967 kg per hectare per year in dryland, higher than in peatland. Factors of oil palm production show that land area, number of plants, and fertilizer significantly positively affect oil palm production in both types of land. Meanwhile, labour, pesticides, and plant age have no significant effect and tend to hurt oil palm production in both types of land.
Klasifikasi Tingkat Kerentanan Website Berdasarkan Hasil Vulnerability Assessment Menggunakan Algoritma K-Means Clustering Saputra, Dandi; Dhika, Harry; Fuadah, Siti
Jurnal Riset Informatika dan Inovasi Vol 3 No 8 (2026): JRIIN : Jurnal Riset Informatika dan Inovasi (INPRESS)
Publisher : shofanah Media Berkah

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Abstract

Tujuan dari penelitian ini adalah untuk merancang dan membangun sistem pendukung keputusan (SPK) yang mampu mengklasifikasikan tingkat kerentanan website berdasarkan hasil vulnerability assessment menggunakan algoritma K-Means Clustering. Sistem ini bertujuan untuk mengelompokkan kerentanan website menjadi beberapa kategori risiko yang dapat digunakan untuk memprioritaskan tindakan mitigasi. Algoritma K-Means Clustering digunakan untuk mengelompokkan data hasil assessment yang mencakup jenis kerentanan, tingkat keparahan (severity), dan skoring CVSS. Sistem ini dibangun menggunakan bahasa pemrograman Java (NetBeans) dan basis data MySQL, serta menghasilkan keluaran berupa kategori tingkat kerentanan yang memudahkan tim keamanan dalam mengambil keputusan. Hasil penelitian menunjukkan bahwa sistem ini mampu memberikan klasifikasi tingkat kerentanan secara efisien dan objektif, yang dapat membantu dalam pengelolaan risiko dan pemilihan prioritas perbaikan kerentanan website secara lebih tepat sasaran
Co-Authors Agus Rusmana Alwi, Muhammmad Ahkam Ashabul Kahfi, Ashabul Azizul Rahman Baiti, Nur Bintal Amin Cahyani, A. Intan Cahyani, Veola Resti Edwin Rizal Erwanto Fuadah, Siti Gobel, Sry Ade Muhtya Gunawan Sudarsono, Bernadus Harry Dhika, Harry Hayati, Nur Qomarian Hidayatul Fitria Ilfajri, Ilfajri Indra Cahyadinata, Indra Juwita Juwita, Juwita Kurniawan, Hendy Lestari, Sindi Martiani Martiani, Martiani Naurah Lisnarini Nazirah, Aulia Nur Akmal Pradana, Fauzi Ardika Sharyanto, Sharyanto Subiyanti, Subiyanti Sukanto Sukanto Yanti Setianti Yuristia, Rahmi