1
Adegbeye, M. J., Reddy, P. R. K., Obaisi, A. I., Elghandour, M. M. M. Y., Oyebamiji, K. J., Salem, A. Z. M., ... & Camacho-DÃaz, L. M. (2020). Sustainable agriculture options for production, greenhouse gasses and pollution alleviation, and nutrient recycling in emerging and transitional nations-An overview. Journal of Cleaner Production, 242, 118319.
2
Rusliyadi, M., Jamil, A. B. H. M., Othman, M., & Kumalasari, R. T. (2018). Agricultural extension policy, agricultural growth and poverty reduction in Indonesia. International Journal of Engineering & Technology, 7(4), 5539-5550.
3
Septiani, Y., & Iskandar, D. D. (2024). Determinants Of Food Security Among Indonesian Farming Households. Jurnal REP (Riset Ekonomi Pembangunan), 9(2), 208-213.
4
Valerio, E., Hilmiati, N., Prior, J., & Dahlanuddin, D. (2022). Analysis of the agricultural innovation system in Indonesia: A case study of the beef sector in Nusa Tenggara Barat. Agricultural Systems, 203, 103529.
5
Riptanti, E. W., Masyhuri, M., Irham, I., Suryantini, A., & Mujiyo, M. (2018). The development of leading food commodities based on local wisdom in food-insecure area in East Nusa Tenggara Province, Indonesia. Applied Ecology & Environmental Research, 16(6).
6
Rozi, F., Elisabeth, D. A. A., Krisdiana, R., Adri, A., Yardha, Y., & Rina, Y. (2022). Prospects of cassava development in Indonesia in supporting global food availability in future. In Advances in Root Vegetables Research. IntechOpen.
7
Gocht, A., & Röder, N. (2014). Using a Bayesian estimator to combine information from a cluster analysis and remote sensing data to estimate high-resolution data for agricultural production in Germany. International Journal of Geographical Information Science, 28(9), 1744-1764.
8
Zhang, H., Zhang, J., & Song, J. (2022). Analysis of the threshold effect of agricultural industrial agglomeration and industrial structure upgrading on sustainable agricultural development in China. Journal of Cleaner Production, 341, 130818.
9
Elkhateeb, E., Soliman, H., Atwan, A., Elmogy, M., Kwak, K. S., & Mekky, N. (2021). A novel coarse-to-Fine Sea-land segmentation technique based on Superpixel fuzzy C-means clustering and modified Chan-Vese model. IEEE Access, 9, 53902-53919.
10
Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & geosciences, 10(2-3), 191-203.
11
Chuang, K. S., Tzeng, H. L., Chen, S., Wu, J., & Chen, T. J. (2006). Fuzzy c-means clustering with spatial information for image segmentation. computerized medical imaging and graphics, 30(1), 9-15.
12
Amri, F. U. (2018). Implementasi Segmentasi Spatial Fuzzy C-Means Pada Identifikasi Citra Daging Sapi dan Babi. In Seminar Nasional Teknologi Informasi Komunikasi dan Industri (pp. 206-214).
13
Xie, X. L., & Beni, G. (1991). A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis & Machine Intelligence, 13(08), 841-847.
14
Isnaini, S. A., Indah, P. N., & Laily, D. W. (2024). The Analysis of Factors Influencing Rice Imports in Indonesia. Buletin Penelitian Sosial Ekonomi Pertanian Fakultas Pertanian Universitas Haluoleo, 26(2), 105-115.
15
Sujianto, Gunawan, E., Saptana, Syahyuti, Darwis, V., Ashari, ... & Marhendro. (2022). Farmers’ perception, awareness, and constraints of organic rice farming in Indonesia. Open Agriculture, 7(1), 284-299.
16
Lybbert, T. J., & Sumner, D. A. (2012). Agricultural technologies for climate change in developing countries: Policy options for innovation and technology diffusion. Food policy, 37(1), 114-123.
17
Peterman, A., Behrman, J. A., & Quisumbing, A. R. (2014). A review of empirical evidence on gender differences in nonland agricultural inputs, technology, and services in developing countries (pp. 145-186). Springer Netherlands.
18
Gwambene, B., Liwenga, E., & Mung’ong’o, C. (2023). Climate change and variability impacts on agricultural production and food security for the smallholder farmers in Rungwe, Tanzania. Environmental Management, 71(1), 3-14.
19
Bekhit, A. E. D. A., Riley, W. W., & Hussain, M. A. (Eds.). (2022). Alternative Proteins: Safety and Food Security Considerations. CRC Press.
20
Rob, V. O. S., & Cattaneo, A. (2021). Poverty reduction through the development of inclusive food value chains. Journal of Integrative Agriculture, 20(4), 964-978.
21
Sreevalsan-Nair, J. (2022). Fuzzy C-Means Clustering. In Encyclopedia of mathematical geosciences (pp. 1-3). Cham: Springer International Publishing.
22
Antoine, V., Guerrero, J. A., & Romero, G. (2022). Possibilistic fuzzy c-means with partial supervision. Fuzzy Sets and Systems, 449, 162-186.
23
Wang, H. Y., Wang, J. S., & Wang, G. (2022). A survey of fuzzy clustering validity evaluation methods. Information Sciences, 618, 270-297.
24
Cheon, J. H., Kim, D., & Park, J. H. (2019, August). Towards a practical cluster analysis over encrypted data. In International Conference on Selected Areas in Cryptography (pp. 227-249). Cham: Springer International Publishing.
25
Bui, Q. T., Vo, B., Snasel, V., Pedrycz, W., Hong, T. P., Nguyen, N. T., & Chen, M. Y. (2020). SFCM: A fuzzy clustering algorithm of extracting the shape information of data. IEEE Transactions on Fuzzy Systems, 29(1), 75-89.
26
Safouan, S., El Moutaouakil, K., & Patriciu, A. M. (2024). Fractional Derivative to Symmetrically Extend the Memory of Fuzzy C-Means. Symmetry, 16(10), 1353.
27
Klimczuk, A., & Klimczuk-Kochańska, M. (2023). Core-periphery model. In The palgrave encyclopedia of global security studies (pp. 239-245). Cham: Springer International Publishing.
28
Shepley, S., & Wilmot, J. (1995). Core vs. periphery. Behind the myth of European Union, 51-82.
29
Pawlak, K., & Kołodziejczak, M. (2020). The role of agriculture in ensuring food security in developing countries: Considerations in the context of the problem of sustainable food production. Sustainability, 12(13), 5488.
30
Hatab, A. A., Cavinato, M. E. R., Lindemer, A., & Lagerkvist, C. J. (2019). Urban sprawl, food security and agricultural systems in developing countries: A systematic review of the literature. Cities, 94, 129-142.
