MULTI-CRITERIA RECOMMENDER SYSTEM BERBASIS METODE WEIGHTED SUM DAN PARETO FRONT UNTUK MANAJEMEN SUMBER DAYA AIR

Astrid Novita Putri

Abstract


Abstract

Clean water is used daily to meet individual needs such as cooking, drinking, bathing, and more. Clean water is essential to support human metabolism, which impacts health. However, obtaining clean water has become increasingly difficult due to high population growth and rising demand, coupled with limited availability.This study develops a multi-criteria recommender system model that considers various criteria or attributes to provide valuable recommendations, facilitating better decision-making based on suitable recommendations regarding water production and consumption. Using the Pareto front and weighted sum methods, this model balances trade-offs among criteria. The results of this study offer an optimal solution for both consumers and water resource management in Semarang City to achieve balance, with W1 minimizing water consumption and W2 maximizing production. The recommended optimal solution is W1 = 0.5 and W2 = 0.5, yielding water consumption of 1,064,910.4 m³/ha and production yield of 14,933,601 tons/ha. Other findings include W1 = 0.1 and W2 = 0.9, yielding water consumption of 11,115,920 m³/ha and production yield of 16,341,636 tons/ha. W1 = 0.4 and W2 = 0.6, yielding water consumption of 11,115,920 m³/ha and production yield of 16,341,636 tons/ha, W1 = 0.7 and W2 = 0.3, yielding water consumption of 10,649,104 m³/ha and production yield of 14,933,601 tons/ha.These outcomes indicate optimal solutions based on different weighting balances between consumption and production criteria.

Keywords: Multi-criteria recommender system, pareto front, water resource management


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C. Diaz Ardianzah, C. Darujati, and A. Bimo Gumelar, “Analisa Perhitungan Performance Maintenance Head Truck Menggunakan Metode Total Productive Maintenance (TPM) Head Truck Performance Calculation Analysis Using Total Productive Maintenance (TPM) Method,” 2023.

Badan Pusat Statistik Provinsi Jawa Tengah, “Statistik air bersih provinsi jawa tengah 2022,” no. 2407–3407, 2022.

I Gede Made Yudi Antara, “Pemanfaatan Teknologi Informasi dalam Pengelolaan Sumber Daya Air Berbasis Kearifan Lokal,” Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI), vol. 4, no. 2, Dec. 2021.

W. Wijiharta, S. Tinggi, E. Islam, and H. Yogyakarta, “Pendekatan Environmental Scanning Manajemen Strategi dalam Pemetaan Permasalahan Pengelolaan Sumberdaya Air,” Youth & islamic economic journal, Jan. 2023, doi: 10.5281/zenodo.13770003.

A. Marianti, “Indonesian Journal of Conservation i j Integrasi Smart Water Management Berbasis Kearifan Lokal Sebagai Upaya Konservasi Sumber Daya Air di Indonesia,” Indonesian Journal of Conservation, vol. 10, no. 1, pp. 67–108, 2021, doi: 10.15294/ijc.v10i1.31036.

M. Davtalab-Olyaie, M. A.-E. J. of Operational, and undefined 2021, “On Pareto-optimality in the cross-efficiency evaluation,” Elsevier, Accessed: Apr. 03, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0377221720304860

T. P. Bagchi, “Pareto-optimal solutions for multi-objective production scheduling problems,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1993, pp. 458–471, 2001, doi: 10.1007/3-540-44719-9_32.

A. N. Putri, M. Hariadi, and R. F. Rachmadi, “Multi-objective Optimization of Production Using Simplex , Goal Programming , and Pareto Front Models,” vol. 16, no. 2, pp. 63–73, 2023, doi: 10.22094/JOIE.2023.1985816.2062.

Q. Shambour, “A deep learning based algorithm for multi-criteria recommender systems,” Knowl Based Syst, vol. 211, Jan. 2021, doi: 10.1016/j.knosys.2020.106545.

M. Li, S. Yang, and X. Liu, “Diversity comparison of Pareto front approximations in many-objective optimization,” IEEE Trans Cybern, vol. 44, no. 12, pp. 2568–2584, Dec. 2014, doi: 10.1109/TCYB.2014.2310651.

Z. Wang and G. P. Rangaiah, “Application and Analysis of Methods for Selecting an Optimal Solution from the Pareto-Optimal Front obtained by Multiobjective Optimization,” Ind Eng Chem Res, vol. 56, no. 2, pp. 560–574, Jan. 2017, doi: 10.1021/acs.iecr.6b03453.

B. Du, S. Guo, X. Huang, Y. Li, and J. Guo, “A Pareto supplier selection algorithm for minimum the life cycle cost of complex product system,” Expert Syst Appl, vol. 42, no. 9, pp. 4253–4264, Jun. 2015, doi: 10.1016/j.eswa.2015.01.056.

T. Mitra and K. Ozbek, “Ranking by weighted sum,” Econ Theory, vol. 72, no. 2, pp. 511–532, 2021, doi: 10.1007/s00199-020-01305-w.

W. Jakob and C. Blume, “Pareto optimization or cascaded weighted sum: A comparison of concepts,” Algorithms, vol. 7, no. 1, pp. 166–185, 2014, doi: 10.3390/a7010166.

N. Gunantara, “A review of multi-objective optimization: Methods and its applications,” Cogent Eng, vol. 5, no. 1, pp. 1–16, 2018, doi: 10.1080/23311916.2018.1502242.

“Gunantara, N.(2018).Teknik Optimasi - Google Scholar.” Accessed: Apr. 03, 2023. [Online]. Available: https://scholar.google.co.id/scholar?hl=id&as_sdt=0%2C5&q=Gunantara%2C+N.%282018%29.Teknik+Optimasi&btnG=

A. Navon, A. Shamsian, G. Chechik, E. F. preprint arXiv, and undefined 2020, “Learning the pareto front with hypernetworks,” arxiv.org, Accessed: Mar. 20, 2023. [Online]. Available: https://arxiv.org/abs/2010.04104

N. Idris, T. Sin, S. Ibrahim, M. F.-… of S. 2020, and undefined 2021, “A case study of coffee sachets production defect analysis using pareto analysis, P-control chart and Ishikawa diagram,” Springer, pp. 1295–1305, 2021, doi: 10.1007/978-981-16-0866-7_115.

A. K. Adisusilo, M. Hariadi, E. M. Yuniarno, and B. Purwantana, “Optimizing player engagement in an immersive serious game for soil tillage base on Pareto optimal strategies,” Heliyon, vol. 6, no. 3, p. e03613, Mar. 2020, doi: 10.1016/J.HELIYON.2020.E03613.

M. Nazar Yuniar, “Klasifikasi Kualitas Air Bersih Menggunakan Metode Naïve baiyes,” Jurnal Sains dan Teknologi, vol. 5, no. 1, pp. 243–246, 2023, doi: 10.55338/saintek.v5i1.1383.

Yadi, “Prediksi Nasabah Kredit Usaha Rakyat Menggunakan Algoritma C4.5 Prediction People’s Kredit Usaha Rakyat Using C4.5 Algorithm Yadi 1),” Sep. 2024.




DOI: https://doi.org/10.21107/nero.v9i2.27840

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