Implementation of Fuzzy Logic in Stabilizing Temperature and Humidity in Freeze Dryers for Dried Apple
DOI:
https://doi.org/10.62535/3bjxym42Keywords:
dried apple, freeze drying, fuzzy logicAbstract
Freeze drying is a process to remove water from a material by sublimation, in the form of ice under low pressure. This process is used to stabilize food, and pharmaceutical products. During the process, the dried product maintains its quality, including biological, nutritional, and sensory properties, because freezing the water within the material before lyophilization prevents chemical, biochemical, and microbiological reactions. The aim of this research is to determine the optimal temperature and time to produce good products in the freeze drying process. The method used for this article is the literature study and observation method. This research uses manual calculations which are then implemented in a control system using a fuzzy logic algorithm in the Matlab application. In conclusion, both the manual calculation results and the matlab calculations that have been conducted are the same, which confirms the accuracy and validity of the preceding calculations.
References
Adrial, R. (2018). Fuzzy logic modeling metode sugeno pada penentuan tipe Diabetes Melitus Menggunakan MATLAB. Jurnal Ilmiah Informatika, 6(1), 62–68. https://ejournal.upbatam.ac.id/index.php/jif/article/view/423.
Alhafiz, A. (2020). Implementasi metode fuzzy logic pada intensitas lampu di laboratorium berbasis arduino. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika Dan Komputer), 19(2), 36–45. https://doi.org/10.53513/jis.v19i2.2422.
Bezděk, V. (2014). Using fuzzy logic in business. Procedia - Social and Behavioral Sciences, 124, 371–380. https://doi.org/10.1016/j.sbspro.2014.02.498
D, I. L. H., Sofwan, A., Rosnelly, R., Wardoyo, R., Rogério dos Santos Alves; Alex Soares de Souza, et all, SUCIANTINI, S., Degei, F. M., Tanaamah, A. R., Wowor, A. D., Informasi, F. T., Kristen, U., Wacana, S., & Diponegoro, J. (2015). Penerapan fuzzy logic pada sistem pengaturan jumlah air berdasarkan suhu dan kelembaban. Seminar Nasional Informatika (Semnas IF 2011), 3(April), 358–365. http://biodiversitas.mipa.uns.ac.id/M/M0102/M010232.pdf
Dimuro, G. P., Bedregal, B., Bustince, H., Jurio, A., Baczyński, M., & Miś, K. (2017). QL operations and QL-implication functions constructed from tuples (O,G,N) and the generation of fuzzy subsethood and entropy measures. International Journal of Approximate Reasoning, 82(2017), 170–192. https://doi.org/10.1016/j.ijar.2016.12.013
Fatkhurrozi, B., & Setiawan, H. T. (2024). Implementasi logika fuzzy pada sistem kendali suhu dan kelembaban udara ruangan pengering biji kopi berbasis mikrokontroller. Journal of Telecommunication Electronics and Control Engineering (JTECE), 6(1), 50–59. https://doi.org/10.20895/jtece.v6i1.1319
Gilda, K. S., & Satarkar, S. L. (2020). Analytical overview of defuzzification methods. International Journal of Advance Research, Ideas and Innovations in Technology, 6(2), 359-365. www.IJARIIT.com
Hantosa, S. H., & Hidayat, A. P. (2019). Model penentuan jumlah pesanan pada aktifitas supply chain telur ayam menggunakan fuzzy logic. Jurnal Ilmiah Teknik Industri, 18(2), 224–235. https://doi.org/10.23917/jiti.v18i2.8486
Hofmann, P. (2016). Defuzzification strategies for fuzzy classifications of remote sensing data. Remote Sensing, 8(6), 1–23. https://doi.org/10.3390/rs8060467
Improta, G., Mazzella, V., Vecchione, D., Santini, S., & Triassi, M. (2020). Fuzzy logic–based clinical decision support system for the evaluation of renal function in post-Transplant Patients. Journal of Evaluation in Clinical Practice, 26(4), 1224–1234. https://doi.org/10.1111/jep.13302
Jane, J. B., & Ganesh, E. N. (2019). A review on big data with machine learning and fuzzy logic for better decision making. International Journal of Scientific and Technology Research, 8(10), 1221–1225.
Makkar, R. (2018). Application of fuzzy logic: A literature review. International Journal of Statistics Applied Mathematics, 3(1), 357–359. https://www.mathsjournal.com/pdf/2018/vol3issue1/PartE/3-1-73-380.pdf
Nakagawa, K., Horie, A., Nakabayashi, M., Nishimura, K., & Yasunobu, T. (2021). Influence of processing conditions of atmospheric freeze-drying/low-temperature drying on the drying kinetics of sliced fruits and their vitamin C retention. Journal of Agriculture and Food Research, 6(2021), 1–8. https://doi.org/10.1016/j.jafr.2021.100231
Nowak, D., & Jakubczyk, E. (2020). The freeze-drying of foods the characteristic of the process course and the effect of its parameters on the physical properties of food materials. Foods, 9(1488), 1–27. https://doi.org/10.3390/foods9101488
Oyinloye, T. M., & Yoon, W. B. (2020). Effect of freeze-drying on quality and grinding process of food produce: A review. Processes, 8(3), 1–23. https://doi.org/10.3390/PR8030354
P, S., D.N, S., & B, P. (2014). Temperature control using fuzzy logic. International Journal of Instrumentation and Control Systems, 4(1), 1–10. https://doi.org/10.5121/ijics.2014.4101
Palmkron, S. B., Gustavsson, L., Wahlgren, M., Bergensthål, B., & Fureby, A. M. (2022). Temperature and heat transfer control during freeze drying effect of vial holders and influence pressure. Pharmaceutical Research, 39(10), 2597–2606. https://doi.org/10.1007/s11095-022-03353-4
Papageorgiou, E. I., Aggelopoulou, K., Gemtos, T. A., & Nanos, G. D. (2018). Development and evaluation of a fuzzy inference system and a neuro-fuzzy inference system for grading apple quality. Applied Artificial Intelligence, 32(3), 253–280. https://doi.org/10.1080/08839514.2018.1448072
Sabbaghi, H., Ziaiifar, A. M., & Kashaninejad, M. (2021). Simulation of fuzzy temperature controller during infrared dry blanching and dehydration of apple slices by intermittent heating method. Iranian Food Science and Technology Research Journal , 16(6), 133–150. https://doi.org/10.22067/ifstrj.v16i6.86368
Santosa, S. H., Hidayat, A. P., & Siskandar, R. (2021). Safea application design on determining the optimal order quantity of chicken eggs based on fuzzy logic. IAES International Journal of Artificial Intelligence, 10(4), 858–871. https://doi.org/10.11591/ijai.v10.i4.pp858-871
Santosa, S. H., Hidayat, A. P., & Siskandar, R. (2022). Raw material planning for tapioca flour production based on fuzzy logic approach: a case study. Jurnal Sistem Dan Manajemen Industri, 6(1), 67–76. http://dx.doi.org/10.30656/jsmi.v6i1.4594
Santosa, S. H., Sulaeman, S., Hidayat, A. P., & Ardani, I. (2020). Fuzzy Logic approach to determine the optimum nugget production capacity. Jurnal Ilmiah Teknik Industri, 19(1), 70-83. https://doi.org/10.23917/jiti.v19i1.10295
Sharma, S., & Obaid, A. J. (2020). Mathematical modelling, analysis and design of fuzzy logic controller for the control of ventilation systems using MATLAB fuzzy logic toolbox. Journal of Interdisciplinary Mathematics, 23(4), 843–849. https://doi.org/10.1080/09720502.2020.1727611
Shiau, J. K., Wei, Y. C., & Chen, B. C. (2015). A study on the fuzzy-logic-based solar power MPPT algorithms using different fuzzy input variables. Algorithms, 8(2), 100–127. https://doi.org/10.3390/a8020100
Suganthi, L., Iniyan, S., & Samuel, A. A. (2015). Applications of fuzzy logic in renewable energy systems - A review. Renewable and Sustainable Energy Reviews, 48, 585–607. https://doi.org/10.1016/j.rser.2015.04.037
Sun, Q., Zhang, M., & Mujumdar, A. S. (2019). Recent developments of artificial intelligence in drying of fresh food: A review. Critical Reviews in Food Science and Nutrition, 59(14), 2258-2275. https://doi.org/10.1080/10408398.2018.1446900
Tepe, T. K. (2024). Convective drying of golden delicious apple enhancement : drying characteristics , artificial neural network modeling , chemical and ATR ‑ FTIR analysis of quality parameters. Biomass Conversion and Biorefinery, 0123456789. https://doi.org/10.1007/s13399-024-05562-w
Wantoro, A., Muludi, K., & Sukisno. (2019). Penerapan logika fuzzy pada sistem pendukung keputusan penentuan kelayakan kualitas telur bebek. JUTIS, 7(1), 1–6. http://repository.lppm.unila.ac.id/34953/1/agus wantoro 140-321-1-SM.pdf
Xu, W., Yuan, J., Tian, J., Li, G., Sun, X., E, S., Zhu, G., Xia, Z., Wang, D., Wang, T., Wu, J., & Xiao, Z. (2020). Aroma and quality of carrot dried using a microwave-convective drying system as affect by temperature gradient. International Journal of Food Properties, 23(1), 63-79. https://doi.org/10.1080/10942912.2019.1709497
Yanti, N., Nur, T., & Randis, R. (2022). Implementation of fuzzy logic in fish dryer design. ILKOM Jurnal Ilmiah, 14(1), 39–51. https://doi.org/10.33096/ilkom.v14i1.1092.39-51




