IMPLEMENTASI METODE HYBRID FUZZY MAMDANI MULTI-STAGE DAN IMPROVED ANT COLONY OPTIMIZATION PADA PENGATURAN LAMPU LALU LINTAS : Studi Kasus di Simpang Jalan Bypass Kota Cirebon

    Dwi andriyani, - and Khusnul Novianingsih, - and Encum Sumiaty, - (2025) IMPLEMENTASI METODE HYBRID FUZZY MAMDANI MULTI-STAGE DAN IMPROVED ANT COLONY OPTIMIZATION PADA PENGATURAN LAMPU LALU LINTAS : Studi Kasus di Simpang Jalan Bypass Kota Cirebon. S1 thesis, Universitas Pendidikan Indonesia.

    Abstract

    Penelitian ini membahas masalah pengaturan lampu lalu lintas pada simpang empat, yang bertujuan untuk mengurangi kemacetan melalui pengaturan durasi lampu hijau yang lebih adaptif terhadap kondisi lalu lintas. Permasalahan ini diselesaikan menggunakan pendekatan hybrid, yaitu dengan menggabungkan metode Fuzzy Mamdani Multi-Stage dan algoritma Improved Ant Colony Optimization (IACO). Sistem fuzzy digunakan untuk menentukan prioritas fase dan tambahan durasi hijau berdasarkan data seperti panjang antrian, lama antrian, dan jumlah kendaraan tersisa. Sementara itu, algoritma IACO diimplementasikan untuk mengoptimalkan durasi hijau secara numerik, dengan meminimalkan total waktu tunggu kendaraan. Setiap semut dalam populasi merepresentasikan solusi kandidat berupa kombinasi durasi hijau, yang kemudian diperbaiki menggunakan proses mutasi dan local search sebelum iterasi dihentikan. Hasil implementasi menunjukkan bahwa kombinasi metode fuzzy dan IACO mampu menghasilkan pengaturan lampu lalu lintas yang lebih efisien dibandingkan metode statis. Penelitian ini juga menunjukkan bahwa penggunaan nilai parameter jejak feromon yang lebih besar dibandikan dengan visibilitas jalur dalam algoritma IACO memberikan hasil probabilitas solusi terbaik yang lebih tinggi, sehingga memperkuat efektivitas pendekatan hybrid dalam sistem pengendalian lalu lintas. This research addresses the issue of traffic light control at a four-way intersection, aiming to reduce congestion by adjusting the green light duration to be more adaptive to traffic conditions. The problem is addressed using a hybrid approach, which combines the Multi-Stage Fuzzy Mamdani method with the Improved Ant Colony Optimization (IACO) algorithm. The fuzzy system is used to determine phase priorities and additional green time based on input data such as queue length, queue duration, and the number of remaining vehicles. Meanwhile, the IACO algorithm is applied to numerically optimize the green light duration by minimizing the total vehicle waiting time. Each ant in the population represents a candidate solution in the form of a green duration combination, which is refined through mutation and local search processes before the iteration ends. The implementation results show that the combination of the fuzzy method and IACO produces more efficient traffic light control compared to static methods. The study also indicates that assigning a greater weight to the pheromone trail parameter than to the path visibility in the IACO algorithm results in a higher probability of finding the optimal solution. This reinforces the effectiveness of the hybrid approach in traffic control systems.

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    Official URL: https://repository.upi.edu/
    Item Type: Thesis (S1)
    Additional Information: https://scholar.google.com/citations?view_op=new_profile&hl=en ID SINTA DOSEN PEMBIMBING Khusnul Novianingsih : 0428117701 Encum Sumiaty : 0020046302
    Uncontrolled Keywords: Fuzzy Mamdani, Multi-stage, Improved Ant Colony Optimization, Lampu Lalu Lintas, Optimasi Fuzzy Mamdani, Multi-stage, Improved Ant Colony Optimization, Traffic Light, Optimization.
    Subjects: H Social Sciences > HE Transportation and Communications
    Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Matematika - S1
    Depositing User: Devi Dwi Andriyani
    Date Deposited: 20 Aug 2025 09:52
    Last Modified: 20 Aug 2025 09:52
    URI: http://repository.upi.edu/id/eprint/135454

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