Land Suitability for Mustard Plants Using Multi-Objective Optimization by Ratio Analysis Method

Heliza Rahmania Hatta - Mulawarman University, Samarinda, Indonesia
Riska Ariani - Mulawarman University, Samarinda, Indonesia
Dyna Marisa Khairina - Mulawarman University, Samarinda, Indonesia
Septya Maharani - Mulawarman University, Samarinda, Indonesia
Vina Zahrotun Kamila - Mulawarman University, Samarinda, Indonesia
Arini Wijayanti - University of California Santa Cruz, USA


Citation Format:



DOI: http://dx.doi.org/10.62527/joiv.7.4.1290

Abstract


Sawi dapat dikembangkan atau dikembangkan dari sudut pandang finansial dan bisnis untuk memenuhi permintaan pembeli dan menangkap peluang pasar yang signifikan. Sawi merupakan tanaman hortikultura yang mempunyai daya adaptasi tinggi dan waktu panen yang relatif singkat. Sawi ini menawarkan banyak keuntungan bagi petani. Misalnya saja banyak petani yang menanam sawi di Samarinda, Kalimantan Timur, Indonesia. Meskipun sangat mudah beradaptasi, beberapa spesies sawi tidak tumbuh subur di tanah tertentu. Tanah yang baik sangat penting untuk hasil optimal saat menanam sawi. Sawi yang ditanam dapat diseleksi dengan menggunakan pendukung keputusan berdasarkan kriteria lahan untuk mendapatkan hasil terbaik. Tujuan dari penelitian ini adalah untuk merekomendasikan tanaman sawi yang cocok berdasarkan kebutuhan luas dengan menggunakan pendekatan multi-objective optimize by ratio analysis (MOORA). MOORA merupakan suatu metode pengambilan keputusan yang membantu dalam memilih alternatif terbaik dari beberapa pilihan atau alternatif berdasarkan beberapa kriteria atau tujuan. Pengamatan ini menggunakan lima kriteria yaitu jenis tanah, pH tanah, curah hujan, suhu, ketinggian lokasi, dan enam alternatif sawi. Berdasarkan uji lahan, sawi yang direkomendasikan metode MOORA adalah Sawi Sendok atau Pak Choy dengan nilai Yi sebesar 7,6698. Jadi yang dipilih sebagai sawi yang ditanam di lahan tersebut adalah Sawi Sendok atau Pak Choy. Untuk penelitian selanjutnya perlu dilakukan penambahan atau penyesuaian kriteria dan sensor baru secara real-time yang dapat diterapkan untuk meningkatkan efisiensi sawi menuju smart farming yang fokus pada hasil yang lebih baik dengan tetap menjaga keseimbangan alam.

Keywords


Mustard; land; suitability; decision support system; MOORA method

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References


L. Kang et al., “Genomic insights into the origin, domestication and diversification of Brassica juncea,” Nature Genetics, vol. 53, no. 9, pp. 1392–1402, Sep. 2021, doi: 10.1038/s41588-021-00922-y.

Q. Xie, F. Yan, Z. Hu, S. Wei, J. Lai, and G. Chen, “Accumulation of Anthocyanin and Its Associated Gene Expression in Purple Tumorous Stem Mustard (Brassica juncea var. tumida Tsen et Lee) Sprouts When Exposed to Light, Dark, Sugar, and Methyl Jasmonate,” Journal of Agricultural and Food Chemistry, vol. 67, no. 3, pp. 856–866, Dec. 2018, doi: 10.1021/acs.jafc.8b04706.

U. Riaz et al., “Genomics of Mustard Crops,” Oil Crop Genomics, pp. 271–290, 2021, doi: 10.1007/978-3-030-70420-9_12.

A. N. Ignatov, A. M. Artemyeva, and K. Hida, “Origin and Expansion of Cultivated Brassica Rapa in Eurasia: Linguistic Facts,” Acta Horticulturae, no. 867, pp. 81–88, Jun. 2010, doi:10.17660/actahortic.2010.867.9.

M. E. Cartea, M. Francisco, P. Soengas, and P. Velasco, “Phenolic Compounds in Brassica Vegetables,” Molecules, vol. 16, no. 1, pp. 251–280, Dec. 2010, doi: 10.3390/molecules16010251.

L.-Z. Lin and J. M. Harnly, “Phenolic Component Profiles of Mustard Greens, Yu Choy, and 15 Other Brassica Vegetables,” Journal of Agricultural and Food Chemistry, vol. 58, no. 11, pp. 6850–6857, May 2010, doi: 10.1021/jf1004786.

J. Hong and N. S. Gruda, “The Potential of Introduction of Asian Vegetables in Europe,” Horticulturae, vol. 6, no. 3, p. 38, Jul. 2020, doi: 10.3390/horticulturae6030038.

I. B. Pratama, U. Hapsari, Y. D. Prasetyatama, and L. Soetiarso, “The Effect of Fertilizer Variations from Organic Waste on the Growth of Mustard Plants (Brassica juncea L.) in Integration Farming System,” Advances in Biological Sciences Research, 2022, doi:10.2991/absr.k.220305.029.

S. R. Patra and M. K. Bhowmick, “System of Assured Rice Production in Kharif: A Resource-Conserving and Climate-Resilient Methodology for Higher Productivity and Profitability,” New Frontiers in Stress Management for Durable Agriculture, pp. 645–660, 2020, doi: 10.1007/978-981-15-1322-0_31.

G. Donchyts, F. Baart, H. Winsemius, N. Gorelick, J. Kwadijk, and N. van de Giesen, “Earth’s surface water change over the past 30 years,” Nature Climate Change, vol. 6, no. 9, pp. 810–813, Aug. 2016, doi:10.1038/nclimate3111.

P. Passalacqua et al., “Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review,” Earth-Science Reviews, vol. 148, pp. 174–193, Sep. 2015, doi: 10.1016/j.earscirev.2015.05.012.

P. Tarolli and G. Sofia, “Human topographic signatures and derived geomorphic processes across landscapes,” Geomorphology, vol. 255, pp. 140–161, Feb. 2016, doi: 10.1016/j.geomorph.2015.12.007.

H. Han, C. Yang, and J. Song, “Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China,” Sustainability, vol. 7, no. 4, pp. 4260–4279, Apr. 2015, doi: 10.3390/su7044260.

H. Briassoulis, “Analysis of Land Use Change: Theoretical and Modeling Approaches,” Wholbk, 2000.

D. M. J. S. Bowman, C. A. Kolden, J. T. Abatzoglou, F. H. Johnston, G. R. van der Werf, and M. Flannigan, “Vegetation fires in the Anthropocene,” Nature Reviews Earth & Environment, vol. 1, no. 10, pp. 500–515, Aug. 2020, doi: 10.1038/s43017-020-0085-3.

P. Borrelli et al., “Land use and climate change impacts on global soil erosion by water (2015-2070),” Proceedings of the National Academy of Sciences, vol. 117, no. 36, pp. 21994–22001, Aug. 2020, doi:10.1073/pnas.2001403117.

M. Chairul, B. Umanailo, N. Handayani, A. Masniati, S. H. Makatita, and S. Lisaholit, “The Urbanization And Diversification Of Farmland Namlea Village,” Article in International Journal of Scientific & Technology Research, vol. 8, p. 8, 2019.

R. Sholeh, F. Agus, H. R. Hatta, and T. Munawwarah, “Analytical hierarchy process for land suitability analysis,” 2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering, Nov. 2014, doi:10.1109/icitacee.2014.7065728.

H. Rahmania Hatta, R. Muhammad Akhyar, D. Marisa Khairina, S. Maharani, H. Haviluddin, and P. Purnawansyah, “Decision Making of Banana Varieties Based On Land in Samarinda Using Electre Method,” Proceedings of the 2017 International Conference on Education and Technology (2017 ICEduTech), 2018, doi: 10.2991/icedutech-17.2018.5.

R. O. Abach and M. M. Ngigi, “Land suitability study for rice growing in Kisumu county,” International Journal of Geomatics and Geosciences, vol. 7, no. 1, pp. 33–42, 2016, [Online]. Available: https://www.indianjournals.com/ijor.aspx?target=ijor:ijggs&volume=7&issue=1&article=004

Ş. Bilaşco et al., “Identification of Land Suitability for Agricultural Use by Applying Morphometric and Risk Parameters Based on GIS Spatial Analysis,” Notulae Botanicae Horti Agrobotanici Cluj-Napoca, vol. 44, no. 1, pp. 302–312, Jun. 2016, doi: 10.15835/nbha44110289.

S. Sengupta, Sk. Mohinuddin, M. Arif, B. Sengupta, and W. Zhang, “Assessment of agricultural land suitability using GIS and fuzzy analytical hierarchy process approach in Ranchi District, India,” Geocarto International, vol. 37, no. 26, pp. 13337–13368, May 2022, doi: 10.1080/10106049.2022.2076925.

Rukhsana and S. H. Molla, “Investigating the Suitability for Rice Cultivation Using Multi-Criteria Land Evaluation in the Sundarban Region of South 24 Parganas District, West Bengal, India,” Journal of the Indian Society of Remote Sensing, vol. 50, no. 2, pp. 359–372, Nov. 2021, doi: 10.1007/s12524-021-01441-3.

R. A. Purnamasari, R. Noguchi, and T. Ahamed, “Land Suitability Assessment for Cassava Production in Indonesia Using GIS, Remote Sensing, and Multi-Criteria Analysis,” Remote Sensing Application, pp. 99–132, 2022, doi: 10.1007/978-981-19-0213-0_4.

S. Mohammed et al., “Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support- Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria),” Geocarto International, vol. 37, no. 6, pp. 1645–1663, Jul. 2020, doi: 10.1080/10106049.2020.1790674.

H. Rahmania Hatta, R. Muhammad Akhyar, D. Marisa Khairina, S. Maharani, H. Haviluddin, and P. Purnawansyah, “Decision Making Of Banana Varieties Based On Land in Samarinda Using Electre Method,” Proceedings of the 2017 International Conference on Education and Technology (2017 ICEduTech), 2018, doi: 10.2991/icedutech-17.2018.5.

F. Agus, R. Sholeh, H. R. Hatta, and T. Munawwarah, “Fuzzy Analytical Hierarchy Process for Land Suitability Analysis Compared to Analytical Hierarchy Process,” in Science and Technology for Sustainability Proceeding, 2014.

[28] R. Attri and S. Grover, “Decision making over the production system life cycle: MOORA method,” International Journal of System Assurance Engineering and Management, vol. 5, no. 3, pp. 320–328, Jun. 2013, doi: 10.1007/s13198-013-0169-2.

S. Singh, S. P. Upadhyay, and S. Powar, “Developing an integrated social, economic, environmental, and technical analysis model for sustainable development using hybrid multi-criteria decision making methods,” Appl Energy, vol. 308, p. 118235, Feb. 2022, doi: 10.1016/j.apenergy.2021.118235.

U. Mandal and B. Sarkar, “Selection of Best Intelligent Manufacturing System (IMS) Under Fuzzy Moora Conflicting MCDM Environment,” Citeseer, vol. 2, no. 9, pp. 301–310, 2012.

D. Hanifatulqolbi, I. E. Ismail, J. Hammad, and M. H. Al-Hooti, “Decision support system for considering the best teacher performance using MOORA method,” J Phys Conf Ser, vol. 1193, no. 1, p. 012018, Apr. 2019, doi: 10.1088/1742-6596/1193/1/012018.

V. Marudut et al., “Decision support system for selection technique using MOORA method,” IOP Conf Ser Mater Sci Eng, vol. 1088, no. 1, p. 012022, Feb. 2021, doi: 10.1088/1757-899X/1088/1/012022.

B. Ceballos, M. T. Lamata, and D. A. Pelta, “A comparative analysis of multi-criteria decision-making methods,” Progress in Artificial Intelligence 2016 5:4, vol. 5, no. 4, pp. 315–322, Apr. 2016, doi:10.1007/S13748-016-0093-1.

I. Petrov, “Multi-criteria Evaluation of Students’ Performance Based on Hybrid AHP-Entropy Approach with TOPSIS, MOORA and WPM,” Communications in Computer and Information Science, vol. 1521 CCIS, pp. 68–84, 2022, doi: 10.1007/978-3-031-04206-5_6/cover/.

J. George, P. Badoniya, and J. F. Xavier, “Comparative Analysis of Supplier Selection Based on ARAS, COPRAS, and MOORA Methods Integrated with Fuzzy AHP in Supply Chain Management,” Lecture Notes in Mechanical Engineering, pp. 141–156, 2022, doi:10.1007/978-981-16-7059-6_13/COVER/.

A. I. Lubis, P. Sihombing, and E. B. Nababan, “Comparison SAW and MOORA Methods with Attribute Weighting Using Rank Order Centroid in Decision Making,” MECnIT 2020 - International Conference on Mechanical, Electronics, Computer, and Industrial Technology, pp. 127–131, Jun. 2020, doi:10.1109/MECNIT48290.2020.9166640.

W. K. Brauers and E. K. Zavadskas, “The MOORA method and its application to privatization in a transition economy,” Control and Cybernetics, vol. 35, no. 2, pp. 445–469, 2006.