Geospatial API Architecture with Laravel for Agricultural Land Suitability Detection System

Yerymia Alfa Susetyo

Abstract


Identification of agricultural land suitability involves a variety of variables that are heterogeneous. The heterogeneity of spatially-based climate and physiographic data is in fact quite complex to solve. Therefore, a spatial-based system architecture that meets the criteria of inclusiveness, collaboration, capacity development, and quick request-response is needed. The research aims to build an API geospatial architecture with Laravel for Agricultural Land Suitability Detection Systems. The geospatial API architecture in this study was built using RESTFul Web services on the Laravel Framework. Simulation architecture involves five nodes as a server and one node as a client. Six main API were produced in this study. Four services are derived from four severs, where services are services related to spatial data (area, altitude, slope, and rainfall). Meanwhile, two other services, relating to conventional information zoning of agricultural land suitability generated by Server 5. The service generated by the last server was successfully implemented on the client-based web-based interactive map application.

Full Text:

PDF

References


A. Nurkholis and I. S. Sitanggang, “Optimization for prediction model of palm oil land suitability using spatial decision tree algorithm,” Jurnal Teknologi dan Sistem Komputer, vol. 8, no. 3, pp. 192–200, Jul. 2020, doi: 10.14710/jtsiskom.2020.13657.

Kementerian Pertanian, Outlook komoditas pertanian tanaman pangan ubi kayu. Jakarta: Pusat Data Dan Sistem Informasi Pertanian Kementrian Pertanian, 2016.

BBSDLP, Atlas peta kesesuaian lahan dan arahan komoditas pertanian pertanian, Kabupaten Bogor, Provinsi Jawa Barat, 2nd ed. Bogor: Badan Penelitian dan Pengembangan Pertanian Kementerian Pertanian, 2016.

F. R. Fauzi, S. H. Abdullah, and A. Priyati, “Evaluasi Kesesuaian Lahan untuk Komoditas Padi dengan Memanfaatkan Aplikasi Sistem Informasi Geografis (SIG) di Kabupaten Lombok Tengah,” Jurnal Ilmiah Rekayasa Pertanian dan Biosistem, vol. 6, no. 2, pp. 131–140, Sep. 2018, doi: 10.29303/jrpb.v6i2.87.

J. B. Ahmed and S. Mansor, “Overview of the application of geospatial technology to groundwater potential mapping in Nigeria,” Arabian Journal of Geosciences, vol. 11, no. 17. Springer Verlag, Sep. 01, 2018. doi: 10.1007/s12517-018-3852-4.

S. Kramer, T. Amos, S. Lazarus, and M. Seedat, “The Philosophical Assumptions, Utility and Challenges of Asset Mapping Approaches to Community Engagement,” Journal of Psychology in Africa, vol. 22, no. 4, pp. 537–544, Jan. 2012, doi: 10.1080/14330237.2012.10820565.

Siti Rochimah and Bintang Nuralamsyah, “Decomposing Monolithic to Microservices: Keyword Extraction and BFS Combination Method to Cluster Monolithic’s Classes,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 7, no. 2, pp. 263–270, Mar. 2023, doi: 10.29207/resti.v7i2.4866.

B. P. Putra and Y. A. Susetyo, “Implementasi API Master Store Menggunakan Flask, REST, dan ORM di PT XYZ,” Jurnal Sistemasi, vol. 9, no. 3, p. 543, Sep. 2020, doi: 10.32520/stmsi.v9i3.899.

X. Chen, Z. Ji, Y. Fan, and Y. Zhan, “Restful API Architecture Based on Laravel Framework,” in Journal of Physics: Conference Series, Institute of Physics Publishing, Nov. 2017. doi: 10.1088/1742-6596/910/1/012016.

A. Pratama, A. Adiyatma Wicaksana, and A. Razi, “Analisa Kesesuaian Lahan Tanah untuk Tanaman Padi (Oryza sativa L.) dengan Metode Decision Tree Berbasis Web (Studi Kasus: Kabupaten Aceh Utara),” JIK, vol. 6, no. 1, 2022.

T. Horbiński and D. Lorek, “The use of Leaflet and GeoJSON files for creating the interactive web map of the preindustrial state of the natural environment,” Journal of Spatial Science, vol. 67, no. 1. Mapping Sciences Institute Australia, pp. 61–77, 2022. doi: 10.1080/14498596.2020.1713237.

O. M. A. AL-atraqchi, “A Proposed Model for Build a Secure Restful API to Connect between Server Side and Mobile Application Using Laravel Framework with Flutter Toolkits,” Cihan University-Erbil Scientific Journal, vol. 6, no. 2, pp. 28–35, Aug. 2022, doi: 10.24086/cuesj.v6n2y2022.pp28-35.

S. J. Kim et al., “Developing spatial agricultural drought risk index with controllable geo-spatial indicators: A case study for South Korea and Kazakhstan,” International Journal of Disaster Risk Reduction, vol. 54, Feb. 2021, doi: 10.1016/j.ijdrr.2021.102056.

U. P. Jawang et al., “Evaluasi Zona Agroekologi Kabupaten Sumba Tengah Berbasis Sistem Informasi Geografis”, Konser Karya Ilmiah Magister Ilmu Pertanian UKSW,” 2017.

Y. W. Baly Woda, I. Hermadi, and M. Marimin, “Sistem Pendukung Keputusan Cerdas Kesesuaian Lahan dengan Jenis Tanaman Pangan: Studi Kasus Kabupaten Sikka,” Jurnal Teknologi Industri Pertanian, vol. 29, no. 1, pp. 62–71, Apr. 2019, doi: 10.24961/j.tek.ind.pert.2019.29.1.62.

R. Ariyanto et al., “A web and mobile GIS for identifying areas within the radius affected by natural disasters based on openstreetmap data,” International journal of online and biomedical engineering, vol. 15, no. 15, pp. 80–95, 2019, doi: 10.3991/ijoe.v15i15.11507.

R. G. Donohue, C. M. Sack, and R. E. Roth, “Time Series Proportional Symbol Maps with Leaflet and jQuery,” Cartographic Perspectives, no. 76, pp. 43–66, Oct. 2014, doi: 10.14714/CP76.1248.

R. Pu, “A special issue of geosciences: Mapping and assessing natural disasters using geospatial technologies,” Geosciences (Switzerland), vol. 7, no. 1. MDPI AG, Mar. 01, 2017. doi: 10.3390/geosciences7010004.

D. A. Morales et al., “Designing of an enterprise resource planning for the optimal management of agricultural plots regarding quality and environmental requirements,” Agronomy, vol. 10, no. 9, Sep. 2020, doi: 10.3390/agronomy10091352.

O. Dwi Arianto and Y. A. Susetyo, “Penerapan RESTful Web Service dengan Framework Laravel untuk Pembangunan Sistem Informasi Manajemen Sumber Daya Manusia.”

R. Sturm, C. Pollard, and J. Craig, in Application Performance Management (APM) in the Digital Enterprise, Chapter 11—Application Programming Interfaces and Connected Systems. Boston, MA, USA, 2019.

R. G. Donohue, C. M. Sack, and R. E. Roth, “Time series proportional symbol maps with Leaflet and jQuery,” Cartographic Perspectives, vol. 76, pp. 43–65, 2013.




DOI: https://doi.org/10.32520/stmsi.v12i3.2844

Article Metrics

Abstract view : 237 times
PDF - 138 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
https://learning.modernland.co.id/api/toto/http://himatikauny.org/wp-includes/mahjong-ways-3/https://www.jst.hvu.edu.vn/akun-pro-kamboja/https://section.iaesonline.com/akun-pro-kamboja/https://journals.uol.edu.pk/sugar-rush/http://mysimpeg.gowakab.go.id/mysimpeg/aset/https://jurnal.jsa.ikippgriptk.ac.id/plugins/https://ppid.cimahikota.go.id/assets/demo/https://journals.zetech.ac.ke/scatter-hitam/https://silasa.sarolangunkab.go.id/swal/https://sipirus.sukabumikab.go.id/storage/uploads/-/sthai/https://sipirus.sukabumikab.go.id/storage/uploads/-/stoto/https://alwasilahlilhasanah.ac.id/starlight-princess-1000/https://www.remap.ugto.mx/pages/slot-luar-negeri-winrate-tertinggi/https://waper.serdangbedagaikab.go.id/storage/sgacor/https://waper.serdangbedagaikab.go.id/public/images/qrcode/slot-dana/https://siipbang.katingankab.go.id/storage_old/maxwin/https://waper.serdangbedagaikab.go.id/public/img/cover/10k/