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All Journal Jurnal Biogenerasi Journal Of Agriculture Sciences (Agrosci)
Rhamadaningtyas, Nabila Aulia
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Analisis Komparatif Keragaman Serangga Tanah Diurnal pada Perkebunan Kopi Berdasarkan Prediksi AI dan Eksplorasi Lapangan Afandi, Aril; Winarno, Winarno; Suhada, Suhada; Maharani, Annisa Lidya; Safitri, Anggi; Saputri, Nur Ayu; Rhamadaningtyas, Nabila Aulia; Soegiharto, Yolande Cathleya; Apriani, Vivin; Fitrisyah, Asyifa Zahara; Pratama, M. Idris Afta; Vega, Cindy Ameliya; Pawaka, Arrahmaan Syah; Saputra, Rama Arsalta Bara; Amrullah, Syarif Hidayat; Parabi, M. Iqbal; Rustiati, Elly Lestari; Pratami, Gina Dania; Permatasari, Nindy; Priyambodo, Priyambodo
Jurnal Biogenerasi Vol. 10 No. 4 (2025): Volume 10 nomor 4 tahun 2025 Terbit Oktober-Desember 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/biogenerasi.v10i4.7121

Abstract

Soil insects play a crucial role in maintaining ecosystem balance and supporting soil fertility, particularly within coffee plantation ecosystems. This study aims to analyze the diversity of soil insects by comparing results from artificial intelligence (AI)-based predictions and field explorations to obtain a comprehensive understanding of community structure. The research was conducted in a smallholder coffee plantation located in Wiyono Village, Pesawaran Regency, Lampung. Field data were collected using the pitfall trap method, while AI-based predictions were generated utilizing a dataset derived from 14 relevant scientific publications. Data analysis employed the Shannon-Wiener diversity index (H′) to evaluate differences between predicted and observed results. The findings revealed that the AI-based prediction estimated an H′ value of 1.787 (moderate diversity), whereas the field exploration yielded an H′ value of 0.428 (low diversity). This discrepancy is influenced by dataset limitations, species dominance, and selectivity inherent in the sampling method. The results highlight the importance of integrating AI-based predictive approaches with field validation to enhance the accuracy of biodiversity assessments. This study contributes to the development of AI-driven prediction models and supports sustainable management of coffee plantation ecosystems.
Oral Swab-Based DNA Extraction Of Cynopterus Brachyotis: An Initial Step For Species Confirmation Rhamadaningtyas, Nabila Aulia; Rustiati, Elly Lestari; Priyambodo, Priyambodo; Srihanto, Eko Agus; Saswiyanti, Enny; Pratiwi, Dian Neli; Susanto, Alvin Wiwiet
Jurnal Agrosci Vol 3 No 3 (2026): Vol 3 No 3 January 2026
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/agrosci.v3i3.1025

Abstract

Background. Identifying bat species based on morphological characteristics often faces challenges due to character overlap among species, especially within cryptic species groups. Cynopterus brachyotis is one of the fruit bats with high genetic diversity but relatively uniform morphology. Aims. Therefore, a molecular approach is needed to support accurate species confirmation. Under the HETI Research Grant of Innovation and Collaboration Batch 3- II Year 2025, this study aims to obtain genomic DNA from C. brachyotis bats caught at the Lampung Disease Investigation Center as the initial step of molecular species confirmation. Methods. Samples were obtained by taking oral swabs on bat individuals caught using mist nets. DNA extraction is performed using silica membrane-based methods with commercial kits. Quantitative evaluation of DNA was performed using a Qubit Fluorometer, while qualitative evaluation was performed by agarose gel electrophoresis. Conclusion. The results showed that the DNA concentration was in the low range (0.1–0.7 ng/μL), with a DNA band appearing very thin on electrophoresis. Implementation. Nevertheless, the quantification results confirm that DNA was successfully extracted and remains suitable for advanced molecular analysis, with optimization at the DNA amplification stage.
Co-Authors Afandi, Aril Apriani, Vivin Eko Agus Srihanto, Eko Agus Elly Lestari Rustiati Fitrisyah, Asyifa Zahara Gina Dania Pratami, Gina Dania Maharani, Annisa Lidya Parabi, M. Iqbal Pawaka, Arrahmaan Syah Permatasari, Nindy Pratama, M. Idris Afta Pratiwi, Dian Neli Priyambodo Priyambodo Safitri, Anggi Saputra, Rama Arsalta Bara Saputri, Nur Ayu Saswiyanti, Enny Soegiharto, Yolande Cathleya Suhada Suhada, Suhada Susanto, Alvin Wiwiet Syarif Hidayat Amrullah Vega, Cindy Ameliya Winarno Winarno