Integrasi smart agriculture technology map dan model objective matrix untuk analisis key performance indicators (KPI) pengelolaan greenhouse

Dani Yudiastono, Nafis Khuriyanti, Mohammad Affan Fajar Falah

Abstract

Key Performance Indicators (KPI) for Agriculture is a guide to assessing performance in agriculture using 5 work indicators: efficiency, quality, capacity index, work environment, and maintenance. The purpose of this study is to identify the level of technology application in greenhouses based on the Smart Agriculture Kaizen Level (SAKL) technology mapping, determine a systematic performance appraisal method in greenhouses, and evaluate the operational performance of Greenhouse Pandanaran, Gunung Kidul Regency. The use of technology and utilization of production data is very important to support the level of productivity of an agricultural system. Moreover, in the transition process from traditional agriculture to agriculture based on smart agriculture, actual research is needed to support its performance against Agricultural KPIs. Through this research, the relationship between the level of technology application and agricultural KPIs in greenhouse production will be obtained Initial research was carried out by identifying the level of technology application in several greenhouse samples and then performing a performance assessment based on Agricultural KPIs. In the performance appraisal based on KPI Agriculture conducted in the greenhouse, the productivity value is obtained from the Objective Matrix (OMAX) method. The use of OMAX includes calculating 3 (three) indicators: efficiency, quality, and capacity index. The study results show that the Pandanaran Greenhouse performance assessment uses the OMAX method from May 2021 to November 2022 (19 months). 11 months are equal to or above standard productivity. The highest overall productivity was achieved in November 2022, whereby the cultivation method implemented in November 2022. From this research, it was found that the best results in aquaponic cultivation were obtained by using fish as the main product and vegetables as a side product.

Keywords

Aquaponics; Key Performance Indicators (KPI); OMAX; Productivity; Smart Agriculture

References

Chen, Y., Zhang, X., Yuan, Y., and Cui, Z. 2019. An integrated key performance indicator evaluation framework for evaluating sustainable greenhouse crop production. Journal of Cleaner Production, 234, 56-68.

Egea, G., Font, R., and Sánchez, B. 2020. Greenhouse key performance indicators for sustainable agriculture. Acta Horticulturae, 1270, 63-68.

Fereira, S, F. J. G. Silva, R. B. Casais, M. T. Pereira, L. P. Ferreira. 2019. KPI development and obsolescence management in industrial maintenance. 29th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2019), June 24-28, 2019, Limerick, Ireland. Published by Elsevier B.V.

Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M. 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660.

Liu, X., Gao, Y., Li, J., and Ma, J. 2018. Evaluation of key performance indicators for greenhouse production. Energy Procedia, 153, 294-299.

Mahmudi, B. Surarso, and A. Subagio. 2014. Kombinasi Balanced Scorecard dan Objective Matrix Untuk Penilaian Kinerja Perguruan Tinggi. J. Sist. Inf. Bisnis, vol. 4, no. 1, pp. 1–10, 2014, https://doi.org/10.21456/vol4iss1pp01-10

Mishra, P., Tripathi, S., Sivakumar, R., Prakash, R., and Kim, K. H. 2019. Internet of Things (IoT)-enabled smart farming: A potential solution

Nurmaydha, A. 2017. Analisis Produktivitas Pada Bagian Produksi Gondorukem dan Terpenting Menggunakan Metode Objective Matrix (Omax) (Studi Kasus Di Pgt Sukun Ponorogo Kesatuan Bisnis Mandiri Industri Non Kayu (KBM-INK) Perum Perhutani Unit II Jawa Timur). Agroindustrial Technology Journal, 1(1), 43–55. Retrieved from https://ejournal.unida.gontor.ac.id/index.php/atj/article/view/1839.

Setiadi, I. 2014. Analisis Produktivitas Sektor Kebun PT. Perkebunan Nusantara XII (Persero) Wonosari Lawang Malang Dengan Menggunakan Craig-Harris Productivity Model. Jurnal Universitas Brawijaya.

Utomo, T.S, Trisakti, B, Sunyoto, A, Sugiono, T, Masykuri, AM. 2021. Development of Smart Agriculture Keizen Level (SAKL) for Precision Farming in Indonesia. The International Journal of Agricultural and Biological Engineering.

https://doi.org/10.25165/j.ijabe.20171204.2811

Washizu, A and Nakano, S. 2022. Exploring the characteristics of smart agricultural development in Japan: Analysis using a smart agricultural kaizen level technology map. Published by Elsevier B.V. https://doi.org/10.1016/j.compag.2022.107001

DOI

https://doi.org/10.21107/agrointek.v18i3.20451

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