ABSTRACT
According to data from the World Food and Agriculture Organization (FAO), Indonesia produced the fourth-most coffee in the world in 2017 and 2018. Gayo, Robusta Dampit, and Toraja coffees are only a few well-known coffee varieties Indonesian growers produce. This research aims to create an app that can identify the type of coffee and serve as a coffee-related educational tool. A single case study was the research methodology used. By employing the EfficienNet-Lite architecture for transfer learning, a model for categorizing coffee beans is created. Users can get information through the photographs they submit with the help of the type of application development that uses deep learning to do categorization based on image data of coffee bean types. The coffee bean classification feature was built using transfer learning with the EfficientNet architecture. A training accuracy of 87% and a validation accuracy of 81% were achieved using the EfficientNet-Lite 0 architecture.
Supplemental Material
- J. Kath, V. Mittahalli Byrareddy, S. Mushtaq, A. Craparo, and M. Porcel, “Temperature and rainfall impacts on robusta coffee bean characteristics,” Clim. Risk Manag., vol. 32, p. 100281, 2021, doi: 10.1016/j.crm.2021.100281.Google ScholarCross Ref
- I. A. Koelemeijer, A. J. M. Tack, B. Zewdie, S. Nemomissa, and K. Hylander, “Management intensity and landscape configuration affect the potential for woody plant regeneration in coffee agroforestry,” Agric. Ecosyst. Environ., vol. 313, p. 107384, Jun. 2021, doi: 10.1016/j.agee.2021.107384.Google ScholarCross Ref
- A. Nugroho, “The Impact of Food Safety Standard on Indonesia's Coffee Exports,” Procedia Environ. Sci., vol. 20, pp. 425–433, 2014, doi: 10.1016/j.proenv.2014.03.054.Google ScholarCross Ref
- M. Zhu , “Fast determination of lipid and protein content in green coffee beans from different origins using NIR spectroscopy and chemometrics,” J. Food Compos. Anal., vol. 102, p. 104055, Sep. 2021, doi: 10.1016/j.jfca.2021.104055.Google ScholarCross Ref
- F. Fitriani, B. Arifin, and H. Ismono, “Indonesian coffee exports and its relation to global market integration,” J. Socioecon. Dev., vol. 4, no. 1, p. 120, Apr. 2021, doi: 10.31328/jsed.v4i1.2115.Google ScholarCross Ref
- M. Muzaifa and D. Hasni, “Exploration Study of Gayo Specialty Coffee (Coffea arabica L.): Chemical Compounds, Sensory Profile and Physical Appearance,” Pakistan J. Nutr., vol. 15, no. 5, pp. 486–491, Apr. 2016, doi: 10.3923/pjn.2016.486.491.Google ScholarCross Ref
- S. H. Sinaga and E. Julianti, “Physical characteristics of Gayo arabica coffee with semi-washed processing,” IOP Conf. Ser. Earth Environ. Sci., vol. 782, no. 3, p. 032093, Jun. 2021, doi: 10.1088/1755-1315/782/3/032093.Google ScholarCross Ref
- Sake Juli Martina, P. A. P. Govindan, and A. S. Wahyuni, “The Difference in Effect of Arabica Coffee Gayo Beans and Leaf (Coffea Arabica Gayo) Extract on Decreasing Blood Sugar Levels in Healthy Mice,” Open Access Maced. J. Med. Sci., vol. 7, no. 20, pp. 3363–3365, Oct. 2019, doi: 10.3889/oamjms.2019.423.Google ScholarCross Ref
- M. A. Rahmawati and K. Fibrianto, “Karakterisasi Sensori Kopi Robusta Dampit: Kajian Pustaka,” J. Pangan dan Agroindustri, vol. 6, no. 1, pp. 75–79, Jan. 2018, doi: 10.21776/ub.jpa.2018.006.01.9.Google ScholarCross Ref
- D. N. Priminingtyas, “The Development Strategy of Dampit Coffee Ecotourism To Improve the Rural Economy (A Case Study in Amadanom Village, Malang Regency, East Java, Indonesia),” IOP Conf. Ser. Earth Environ. Sci., vol. 709, no. 1, p. 012049, Mar. 2021, doi: 10.1088/1755-1315/709/1/012049.Google ScholarCross Ref
- M. Salam, N. M. Viantika, A. Amiruddin, F. M. Pinontoan, and R. A. Rahmatullah, “Value chain analysis of Toraja coffee,” IOP Conf. Ser. Earth Environ. Sci., vol. 681, no. 1, p. 012115, Mar. 2021, doi: 10.1088/1755-1315/681/1/012115.Google ScholarCross Ref
- A. Michael and M. Garonga, “Classification model of ‘Toraja’ arabica coffee fruit ripeness levels using convolution neural network approach,” Ilk. J. Ilmiah; Vol 13, No 3 Press, vol. 13, no. 3, pp. 226–234, 2021.Google Scholar
- M. Muzaifa, D. Hasni, F. Rahmi, and Syarifudin, “What is kopi luwak? A literature review on production, quality and problems,” IOP Conf. Ser. Earth Environ. Sci., vol. 365, no. 1, p. 012041, Oct. 2019, doi: 10.1088/1755-1315/365/1/012041.Google ScholarCross Ref
- D. P. Thana, R. Darma, and R. Kadir, “The Priority of Marketing Strategy of Coffee in Tana Toraja,” Int. J. Sci. Res., vol. 6, no. 11, pp. 953–958, 2017.Google Scholar
- K. Hidayah and I. Nasyi'ah, “Potensi Pendaftaran Indikasi Geografis Kopi Lereng Semeru oleh Pemerintah Daerah dalam Menghadapi ASEAN Economic Community,” Kertha Patrika, vol. 42, no. 2, p. 132, 2020, doi: 10.24843/kp.2020.v42.i02.p03.Google ScholarCross Ref
Index Terms
- Discoffery: a Coffee Types Detection Apps using an EfficienNet-Lite Architecture
Recommendations
Identifying potential areas of understorey coffee in Ethiopia’s highlands using predictive modelling
Coffee production is one of the main economic activities in Ethiopia, representing about 40% of the country’s economy. Coffee is particularly important in the Ethiopian highlands, where appropriate climate allows higher productivity and quality. The ...
Identifying potential areas of understorey coffee in Ethiopia’s highlands using predictive modelling
Coffee production is one of the main economic activities in Ethiopia, representing about 40% of the country’s economy. Coffee is particularly important in the Ethiopian highlands, where appropriate climate allows higher productivity and quality. The ...
Identifying potential areas of understorey coffee in Ethiopia’s highlands using predictive modelling
Coffee production is one of the main economic activities in Ethiopia, representing about 40% of the country’s economy. Coffee is particularly important in the Ethiopian highlands, where appropriate climate allows higher productivity and quality. The ...
Comments