Jurnal Sapta Agrica

ANALISIS KEKERABATAN GENETIK BERBASIS KARAKTER FENOTIPE PADA BEBERAPA GALUR HARAPAN BUNGA MATAHARI (Helianthus annuus L.)

Mukhammad Irwan Kurniadi — 2026-05-26

The sunflower plant (Helianthus annuus L.) is widely known as a source of vegetable oil with an oil content reaching 40-50%. This research was conducted to analyze the genetic relationships of several promising sunflower lines based on their phenotypic characters. The research was carried out in Srigading Village, Bantul Regency, Special Region of Yogyakarta, from December 2025 to March 2026. The study used a Randomized Block Design (RBD) with 9 promising lines and 3 replications, resulting in 27 experimental units. The observed characters consisted of 11 quantitative and 5 qualitative characters. The data were analyzed using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) based on Gower’s General Similarity Coefficient, as well as Principal Component Analysis (PCA). The results from the 9 lines using PCA were divided into two Principal Components with a cumulative diversity value of 83.03%, and the cluster analysis showed that the 9 promising lines formed 3 main clusters.

INTEGRATION OF SCIENCE (NATURAL SCIENCES), REMOTE SENSING, AND NIAS LOCAL WISDOM IN MODELING FOOD CROP PRODUCTIVITY

Darmawan Harefa — 2026-05-27

This study aims to develop an integrated model for food crop productivity by combining natural sciences, remote sensing technology, and Nias local wisdom in South Nias Regency, Indonesia. The agricultural sector in this region faces challenges such as low productivity, soil fertility variability, and limited access to modern agricultural monitoring systems. To address these issues, a mixed-methods approach was applied, integrating quantitative geospatial analysis and qualitative ethnographic data. Remote sensing data from Sentinel-2 and Landsat satellites were used to extract vegetation indices (NDVI) for assessing crop health and spatial productivity patterns. Soil parameters and climatic variables from natural sciences were incorporated to explain biophysical factors influencing crop growth. In addition, local wisdom practices such as organic farming, mixed cropping, and traditional planting systems were quantified into a Local Wisdom Index (LWI). The data were analyzed using Geographic Information Systems and machine learning models to generate a predictive productivity map. The results show that the integrated model significantly improves prediction accuracy compared to single-source approaches, with strong spatial consistency between vegetation health, soil fertility, and traditional farming practices. This study demonstrates that combining scientific data, geospatial technology, and indigenous knowledge provides a more holistic and sustainable framework for agricultural productivity modeling in tropical rural regions.

PENERAPAN SIKLUS PDCA PADA PEMBIBITAN KELAPA SAWIT (Elaeis guineensis Jacq) DI PEMBIBITAN UTAMA PT PERKEBUNAN NUSANTARA IV REGIONAL III KECAMATAN BUKIT KAPUR KOTA DUMAI

Arman Maulana — 2026-06-23

Oil palm (Elaeis guineensis Jacq.) is a strategic plantation commodity that contributes significantly to national foreign exchange earnings. The main nursery stage is a crucial phase in ensuring the availability of high-quality seedlings before field planting. This study aimed to examine the implementation of the PDCA (Plan, Do, Check, Action) cycle in improving the quality of oil palm seedlings, identify the challenges encountered, and formulate solutions to address these challenges at PT Perkebunan Nusantara IV Regional III, Bukit Kapur District, Dumai City. The study employed a descriptive qualitative approach, with data collected through interviews, field observations, and documentation studies. The results showed that the implementation of the PDCA cycle had been carried out systematically, with an activity implementation rate of 83.33%. The main challenges included delays in the procurement of production inputs, high rainfall, and labor shortages. The solutions implemented consisted of enhanced coordination, drainage improvement, and intensive supervision. The application of the PDCA cycle proved effective in improving operational efficiency and the quality of oil palm seedlings in the main nursery.