Analisis Komparatif Keragaman Serangga Tanah Diurnal pada Perkebunan Kopi Berdasarkan Prediksi AI dan Eksplorasi Lapangan

Authors

  • Aril Afandi Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Winarno Winarno Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Suhada Suhada Jurusan Budidaya Tanaman Perkebunan, Politeknik Negeri Lampung
  • Annisa Lidya Maharani Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Anggi Safitri Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Nur Ayu Saputri Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Nabila Aulia Rhamadaningtyas Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Yolande Cathleya Soegiharto Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Vivin Apriani Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Asyifa Zahara Fitrisyah Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • M. Idris Afta Pratama Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Cindy Ameliya Vega Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Arrahmaan Syah Pawaka Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Rama Arsalta Bara Saputra Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Syarif Hidayat Amrullah Jurusan Biologi, FST, UIN Alauddin Makassar
  • M. Iqbal Parabi Jurusan Ilmu Komputer, Fakultas MIPA, Universitas Lampung
  • Elly Lestari Rustiati Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Gina Dania Pratami Jurusan Biologi, Fakultas MIPA, Universitas Lampung
  • Nindy Permatasari Jurusan Budidaya Tanaman Perkebunan, Politeknik Negeri Lampung
  • Priyambodo Priyambodo Jurusan Biologi, Fakultas MIPA, Universitas Lampung

DOI:

https://doi.org/10.30605/biogenerasi.v10i4.7121

Keywords:

artificial intelligence, coffee plantations, pitfall trap, soil insect diversity

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.

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References

1. Amanda S, Rosiana N. Analisis daya saing kopi Indonesia dalam menghadapi perdagangan kopi dunia. InForum Agribisnis: Agribusiness Forum 2023 Mar 30 (Vol. 13, No. 1, pp. 1-11). https://doi.org/10.29244/fagb.13.1.1-11

2. Tamimi C, Ayundasari L. Perubahan sosial ekonomi masyarakat Desa Bangelan 1901-2020: Analisis terhadap peran industri kopi PTPN XII Kebun Bangelan dalam peningkatan ekonomi masyarakat. Jurnal Integrasi dan Harmoni Inovatif Ilmu-Ilmu Sosial. 2022 Mar 20;2(3):282-90. https://doi.org/10.17977/um063v2i3p282-290

3. Sari RR, Ishaq RM, Purnamasari E, Saputra DD. Fungsi Ganda Agroforestri Kopi: Konservasi Cadangan Karbon dan Keanekaragaman Vegetasi. Jurnal Tanah dan Sumberdaya Lahan. 2025 Jan 1;12(1):159-69. https://doi.org/10.21776/ub.jtsl.2025.012.1.16

4. Ibnu M, Rosanti N. Tren produksi dan perdagangan negara-negara produsen kopi terbesar di dunia dan implikasinya bagi Indonesia. Buletin Ilmiah Litbang Perdagangan. 2022 Dec 30;16(2). https://doi.org/10.55981/bilp.2022.5

5. Ali FY, Nugroho SA, Fatimah T, Asmono SL, Rosdiana E, Pratita DG, Firgiyanto R. Pengembangan Produk Kopi Herbal Berbasis Rempah Lokal Sebagai Strategi Peningkatan Daya Saing Usaha Mikro di Kabupaten Jember. Jurnal Hasil Pengabdian Masyarakat (JURIBMAS). 2025 Jul 11;4(1):122-30. https://doi.org/10.62712/juribmas.v4i1.430

6. Hidayat YA, Siregar LS, Kurniani K. Pengaruh Orientasi Kewirausahaan dan Inovasi Produk Pada Kinerja Bisnis UMKM Kopi Temanggung. Jurnal Agribisnis Indonesia (Journal of Indonesian Agribusiness). 2023 Jun 26;11(1):190-204. https://doi.org/10.29244/jai.2023.11.1.190-204

7. Selvi S, Ningrum L. Gaya Hidup Minum Kopi dalam Pengambilan Keputusan Pembelian Kopi (Studi Kasus Pada Kopi Kenangan Gandaria City-Jakarta). Kepariwisataan: Jurnal Ilmiah. 2021 Nov 5;14(1):23-30. http://dx.doi.org/10.47256/kji.v14i1.43

8. Evizal R, Tohari T, Prijambada ID, Widada J, Prasmatiwi FE, Afandi A. Pengaruh tipe agroekosistem terhadap produktivitas dan keberlanjutan usahatani kopi. Jurnal Agrotropika. 2020 Jul 28;15(1). https://doi.org/10.23960/ja.v15i1.4243

9. Fajar A, Fariyanti A, Priatna WB. Status Keberlanjutan Perkebunan Kopi Bersertifikasi CAFE Practices. Jurnal Agribisnis Indonesia (Journal of Indonesian Agribusiness). 2023 Jun 26;11(1):1-6. https://doi.org/10.29244/jai.2023.11.1.1-16

10. Martin E, Suharjito D, Darusman D, Sunito S, Winarno B. Etika subsistensi petani kopi: Memahami dinamika pengembangan agroforestri di dataran tinggi Sumatera Selatan. Sodality J. Sosiol. Pedesaan. 2016 Apr;4:92-102.

11. Rachmanita RE, Febriani SD, Anggriani S, Siswadi E, Firgiyanto R, Apriadana MI. Penerapan Alat Penjebak Serangga Otomatis Tenaga Surya Di Kelompok Tani Dusun Rayap Desa Kemuning Lor. InProsiding Seminar Nasional Terapan Riset Inovatif (SENTRINOV) 2021 Nov 30 (Vol. 7, No. 3, pp. 150-157). https://proceeding.isas.or.id/index.php/sentrinov/article/view/1087

12. Samsiyah MB. Keanekaragaman dan kepadatan serangga tanah di Agroforestri Kopi Sederhana dan kompleks Desa Tambaksari Kecamatan Purwodadi Kabupaten Pasuruan Jawa Timur (Doctoral dissertation, Universitas Islam Negeri Maulana Malik Ibrahim). http://etheses.uin-malang.ac.id/43682/

13. Prasetyo D, Evizal R, Septiana LM. Struktur Komunitas Mesofauna sebagai Bioindikator Kualitas Tanah pada Sistem Budidaya Kakao Konvensional dan Berbasis Biochar di Sidomulyo, Tanggamus. Jurnal Agrotek Tropika. 2025 May 12;13(2):494-503. https://doi.org/10.23960/jat.v13i2.10203

14. Aderele MO, Srivastava AK, Butterbach-Bahl K, Rahimi J. Integrating machine learning with agroecosystem modelling: Current state and future challenges. European Journal of Agronomy. 2025 Jul 1;168:127610. https://doi.org/10.1016/j.eja.2025.127610

15. Waseem M, Raza A, Malik A. AI-Driven Crop Yield Prediction and Disease Detection in Agroecosystems. InMaintaining a Sustainable World in the Nexus of Environmental Science and AI 2024 (pp. 229-258). IGI Global. DOI:10.4018/979-8-3693-6336-2.ch009

16. Peixoto PG, Nascimento VF, de Lacerda LB, Siansi FL, de Matos GF, de Souza JM, Ramalho DG, De Bortoli SA. Attractiveness of Pitfall Traps with Baits for Harvestmen in a Sugarcane Agroecosystem. Sugar Tech. 2024 Jun;26(3):731-40. https://doi.org/10.1007/s12355-024-01390-4

17. Delgado S, Calvo MV, Duarte F, Borges A, Scatoni IB. Food attractants for mass trapping of fruit flies (Diptera: Tephritidae) and its selectivity for beneficial arthropods. Florida Entomologist. 2022 Oct;105(3):185-93. https://doi.org/10.1653/024.105.0302

18. Jaya AS, Widayat W. Pengaruh umpan terhadap keefektifan pitfall trap untuk mendukung praktikum ekologi hewan di Laboratorium Ekologi FMIPA Unsyiah. Jurnal Bioleuser. 2018;2(3).

19. Borror DJ, DeLong DM. An introduction to the study of insects.

20. Kalshoven LG. Pests of crops in Indonesia.

21. Lilies C. Kunci determinasi serangga. Kanisius. Yogyakarta. 1991;223.

22. Baeza JL, Cerrone D, Männigo K. Comparing two methods for urban complexity calculation using the Shannon-Wiener Index. WIT Trans. Ecol. Environ. 2017 Jun;226:369-78. doi:10.2495/sdp170321

23. Usnaddinovich TJ, Abatovna JA. Insecta: ecology of coleoptera. American Journal of Agriculture and Horticulture Innovations. 2025 Mar 17;5(03):14-6. https://doi.org/10.37547/ajahi/Volume05Issue03-04

24. Escobar‐González D, Landaverde‐González P, Casiá‐Ajché QB, Morales‐Siná J, Cardona E, Mejía‐Coroy A, Enríquez E. Fruit production in coffee (Coffea arabica L.) crops is enhanced by the behaviour of wild bees (Hymenoptera: Apidae). Austral Entomology. 2024 Feb;63(1):82-94. https://doi.org/10.1111/aen.12673

25. Girsang W, Purba R, Rudiyantono R. Intensitas serangan hama penggerek buah kopi (Hipothenemus hampei Ferr.) pada tingkat umur tanaman yang berbeda dan upaya pengendalian memanfaatkan atraktan. Journal TABARO Agriculture Science. 2020 Jun 4;4(1):27-34. https://doi.org/10.35914/tabaro.v4i1.358

26. Kinasih ID, Cahyanto TR, Widiana AN, KURNIA DN, Julita U, PUTRA RE. Soil invertebrate diversity in coffee-pine agroforestry system at Sumedang, West Java. Biodiversitas Journal of Biological Diversity. 2016 Jun 9;17(2). https://doi.org/10.13057/biodiv/d170211

27. Moreira CC, Celestino D, Guerra Sobrinho T, Cardoso IM, Elliot SL. Agroforestry coffee soils increase the insect‐suppressive potential offered by entomopathogenic fungi over full‐sun soils: A case proposing a “bait survival technique”. Ecology and Evolution. 2019 Sep;9(18):10777-87. https://doi.org/10.1002/ece3.5598

28. Nestel D, Dickschen F, Altieri MA. Diversity patterns of soil macro-Coleoptera in Mexican shaded and unshaded coffee agroecosystems: an indication of habitat perturbation. Biodiversity & Conservation. 1993 Feb;2(1):70-8. https://doi.org/10.1007/BF00055104

29. Santos JB, Ramos AC, Azevedo Júnior R, Oliveira Filho LC, Baretta D, Cardoso EJ. Soil macrofauna in organic and conventional coffee plantations in Brazil. Biota Neotropica. 2018 Apr 23;18:e20180515. https://doi.org/10.1590/1676-0611-BN-2018-0515

30. Hohbein RR, Conway CJ. Pitfall traps: A review of methods for estimating arthropod abundance. Wildlife Society Bulletin. 2018 Dec;42(4):597-606. https://doi.org/10.1002/wsb.928

31. Costa-Silva V, Grella MD, Thyssen PJ. Optimized pitfall trap design for collecting terrestrial insects (Arthropoda: Insecta) in biodiversity studies. Neotropical Entomology. 2019 Feb 1;48(1):50-6. https://doi.org/10.1007/s13744-018-0613-8

32. Quque M, Bles O. Lasius. InEncyclopedia of Social Insects 2020 (pp. 1-4). Springer, Cham. https://doi.org/10.1007/978-3-319-90306-4_169-1

33. Perfecto I, Vandermeer J. The assembly and importance of a novel ecosystem: the ant community of coffee farms in Puerto Rico. Ecology and Evolution. 2020 Dec;10(23):12650-62. https://doi.org/10.1002/ece3.6785

34. Strong WL. Biased richness and evenness relationships within Shannon–Wiener index values. Ecological indicators. 2016 Aug 1;67:703-13. https://doi.org/10.1016/j.ecolind.2016.03.043

35. Omayio D, Mzungu E, Kakamega K. Modification of shannon-wiener diversity index towards quantitative estimation of environmental wellness and biodiversity levels under a non-comparative Scenario. Journal of Environment and Earth Science. 2019 Sep 30;9(9):46-57. DOI: 10.7176/JEES

36. Verdugo Morales EG, Yáñez Díaz MI, Alanís Rodríguez E, González Rodríguez H, Garza Ocañas F, Rodríguez Larramendi LA. Tree richness, structure, and diversity in an altitudinal gradient in coffee plantations in Chiapas. Revista mexicana de ciencias forestales. 2025 Apr;16(88):148-73. https://doi.org/10.29298/rmcf.v16i88.1506

37. Kurniawan YD, Faizah M, Nasiruddin M. Keanekaragaman Serangga pada Tanaman Jeruk Kawasan Dataran Rendah di Desa Mejoyolosari Jombang. Al-Furqan: Jurnal Agama, Sosial, dan Budaya. 2024 Aug 22;3(4):2108-20.

38. Supit MM, Pinaria BA, Rimbing J. Keanekaragaman serangga pada beberapa varietas kelapa (Cocos nucifera L.) dan kelapa sawit (Elaeis guenenssis Jacq). Sam Ratulangi Journal of Entomology Review. 2020 Oct 2;1(1).

39. Rohyani IS. The effect of microhabitat diversity on the similarity of soil insect types at Lombok Island, Indonesia. Jurnal Penelitian Pendidikan IPA. 2021 Oct 16;7(4):738-45.

40. Boetzl FA, Ries E, Schneider G, Krauss J. It’sa matter of design—how pitfall trap design affects trap samples and possible predictions. PeerJ. 2018 Jun 25;6:e5078. https://doi.org/10.7717/peerj.5078

41. Giczy AV, Pairolero NA, Toole AA. Identifying artificial intelligence (AI) invention: A novel AI patent dataset. The Journal of Technology Transfer. 2022 Apr;47(2):476-505. https://doi.org/10.1007/s10961-021-09900-2

42. Polizzi A, Quinzi V, Lo Giudice A, Marzo G, Leonardi R, Isola G. Accuracy of artificial intelligence models in the prediction of periodontitis: a systematic review. JDR Clinical & Translational Research. 2024 Oct;9(4):312-24. https://doi.org/10.1177/2380084424123231

43. Ghaffar Nia N, Kaplanoglu E, Nasab A. Evaluation of artificial intelligence techniques in disease diagnosis and prediction. Discover Artificial Intelligence. 2023 Jan 30;3(1):5.

44. Corti C, Cobanaj M, Marian F, Dee EC, Lloyd MR, Marcu S, Dombrovschi A, Biondetti GP, Batalini F, Celi LA, Curigliano G. Artificial intelligence for prediction of treatment outcomes in breast cancer: Systematic review of design, reporting standards, and bias. Cancer treatment reviews. 2022 Jul 1;108:102410.

45. Nazer LH, Zatarah R, Waldrip S, Ke JX, Moukheiber M, Khanna AK, Hicklen RS, Moukheiber L, Moukheiber D, Ma H, Mathur P. Bias in artificial intelligence algorithms and recommendations for mitigation. PLOS digital health. 2023 Jun 22;2(6).

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Published

2025-11-04

How to Cite

Afandi, A., Winarno, W., Suhada, S., Maharani, A. L., Safitri, A., Saputri, N. A., … Priyambodo, P. (2025). Analisis Komparatif Keragaman Serangga Tanah Diurnal pada Perkebunan Kopi Berdasarkan Prediksi AI dan Eksplorasi Lapangan. Jurnal Biogenerasi, 10(4), 2096–2108. https://doi.org/10.30605/biogenerasi.v10i4.7121

Issue

Vol. 10 No. 4 (2025): Volume 10 nomor 4 tahun 2025 Terbit Oktober-Desember 2025

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Articles

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Copyright (c) 2025 Aril Afandi, Winarno Winarno, Suhada Suhada, Annisa Lidya Maharani, Anggi Safitri, Nur Ayu Saputri, Nabila Aulia Rhamadaningtyas, Yolande Cathleya Soegiharto, Vivin Apriani, Asyifa Zahara Fitrisyah, M. Idris Afta Pratama, Cindy Ameliya Vega, Arrahmaan Syah Pawaka, Rama Arsalta Bara Saputra, Syarif Hidayat Amrullah, M. Iqbal Parabi, Elly Lestari Rustiati, Gina Dania Pratami, Nindy Permatasari, Priyambodo Priyambodo

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