Applying the Fuzzy Tsukamoto Method to Determine Eligibility for Village Fund BLT (Direct Cash Assistance)

  • Farid Fitriyadi Universitas Sahid Surakarta
  • Firdhaus Hari Saputro Universitas Sahid Surakarta
  • Astri Charolina Universitas Sahid Surakarta
  • Dwi Retnoningsih Universitas Sahid Surakarta
  • Erna Indriastiningsih Universitas Sahid Surakarta
DOI: https://doi.org/10.36728/iceete.v3i1.263

Abstrak

The Village Fund Direct Cash Assistance (BLT DD) is a government program aimed at supporting rural communities by improving their economic conditions and quality of life. According to Indonesian regulations, there are five categories of eligible beneficiaries, including those who have lost their livelihood, have a chronically ill or disabled family member, are not receiving assistance from the Family Hope Program, live in households with a single elderly member, or are female-headed households from extremely poor families. However, the regulation lacks clear criteria regarding the income threshold for extreme poverty, creating uncertainty during the beneficiary selection process. This study proposes the use of the Fuzzy Tsukamoto method as a decision support tool to assist verification officers in determining the eligibility of potential BLT DD recipients. The Fuzzy Tsukamoto method, based on fuzzy logic principles, allows for degrees of truth and membership, enabling more nuanced decision-making in conditions of uncertainty. By applying this method, the selection process can become more objective, transparent, and aligned with the actual socioeconomic conditions of rural residents. The research is expected to contribute to the accurate targeting of government aid and to help reduce poverty in rural areas. Additionally, this study enhances understanding of fuzzy logic applications in social assistance programs and highlights its potential for broader use in complex decision-making environments.

Referensi

Alamsyah, D. P., Ramdhani, Y., & Nurbeni, R. D. (2022). Implementation of the Fuzzy Inference System Tsukamoto Method in the Decision Support System. IEEE.
Astri Charolina, F. F. (2024). Fuzzy Mamdani Model for Assessing the Level of Service Satisfaction for Requirements of Social Welfare Services at the "Prof. Dr. Soeharso" . IJCIS.
Chaouki Ghenai, O. A.-M.-I. (2022). Chaouki Ghenai, Omar Ahmed Abduljabbar Al-Mufti, Omar Adil Mashkoor Al-Isawi, Lutfi Hatem Lutfi Amirah, Adel Merabet,. Journal of Building Engineering.
Danang Rifai, F. F. (2023). Penerapan Logika Fuzzy Sugeno dalam Keputusan Jumlah Produksi
Berbasis Website. Hello World Jurnal Ilmu Komputer, 102-109.
Darko Bozanic, D. T. (2023). Ranking challenges, risks and threats using Fuzzy Inference System. Decision Making: Applications in Management and Engineering, 933-947.
Deden Farhan, F. S. (2023). IMPLEMENTATION OF FUZZY TSUKAMOTO LOGIC TO DETERMINE THE NUMBER OF SEEDS KOI FISH IN THE SUKAMANAH CIANJUR FARMER`S GROUP. JUTIF.
Ikbal, G. A. (2023). Legal Assistance for Underprivileged Communities to Access Justice within the Human Rights Perspective. Lampung Journal Of International Law (LaJIL), 93 - 102.
Applying the Fuzzy Tsukamoto Method to Determine Eligibility for Village Fund BLT (Direct Cash Assistance)
Ipung Dwi Antoni, Y. F. (2024). Implementation of Fuzzy Logic to Determine the Amount of Bread Production Using Tsukamoto Method. Smatika Jurnal.
Isnaini Muhandhis, A. S. (2021). Implementasi Metode Inferensi Fuzzy Tsukamoto Untuk Memprediksi Curah Hujan Dasarian Di Sumenep. Jurnal Ilmiah Edutic .
Lukman Medriavin Silalahi, D. J. (2022). Internet of things implementation and analysis of fuzzy Tsukamoto in prototype irrigation of rice. International Journal of Electrical and Computer Engineering (IJECE) .
MEHRAN MAZANDARANI, X. L. (2020). Fractional Fuzzy Inference System: The New Generation of Fuzzy Inference Systems. ICORIS (hal. 126066 - 126082). IEEE.
Miriam Mutevere, T. R. (2024). Empowering underprivileged students beyond financial aid: Insights from a scholarship program's monitoring and evaluation,. Evaluation and Program Planning.
Raul Boadh, D. D. (2022). Study and prediction of prostate cancer using fuzzy inference system. Materialstoday: Proceedings, (hal. 157-164).
Shahid Hussain, Y.-S. K. (2022). Optimization of Waiting Time for Electric Vehicles Using a Fuzzy Inference System. IEEE Transactions on Intelligent Transportation System, 15396-15407.
Sunardi, Yudhana, A., & Furiza. (2023). Tsukamoto Fuzzy Inference System on Internet of Things-Based for Room Temperature and Humidity Control. IEEE.
Diterbitkan
2025-07-30
##submission.howToCite##
Fitriyadi, F., Saputro, F. H., Charolina, A., Retnoningsih, D., & Indriastiningsih, E. (2025). Applying the Fuzzy Tsukamoto Method to Determine Eligibility for Village Fund BLT (Direct Cash Assistance). ICEETE Conference Series, 3(1), 247-355. https://doi.org/10.36728/iceete.v3i1.263
Terbitan
Vol 3 No 1 (2025): 2025 - 3rd ICEETE
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