Treffer: Optimasilisasi Rute Transportasi Dan Biaya Pengangkutan Sampah Di TPS 3R USU Menggunakan Metode Saving Matrix.

This research aims to optimize the transportation route and cost of transporting waste at TPS 3R USU using the Saving Matrix method with the help of Machine Learning Python. The background of the research is based on the increasing volume of waste along with population growth, especially in Medan City, which produces around 2,000 tons of waste per day. The main problem faced is the inefficiency of waste transportation routes, which causes waste of time and money. The Saving Matrix method was chosen due to its ability to minimize mileage, time, and cost by considering vehicle capacity and waste volume. The data used includes coordinates of TPS locations, waste generation, and vehicle capacity, which are then processed using the Python programming language to generate optimal routes. The Nearest Neighbor algorithm was applied to determine the order of the closest visits from the depot (TPS3R USU). The results showed that the route optimization successfully reduced the total mileage and operational costs. The developed Python program produced 12 new routes with an optimal fuel cost of Rp 139,732,713 per year. In addition, this method proved to be flexible and can be applied on a larger scale. The conclusion of this research is that the Saving Matrix method is effective in minimizing the cost and distance of waste transportation. Suggestions for future research include consideration of road dynamics, development of Python programs for additional variables, and evaluation of waste segregation to improve efficiency. [ABSTRACT FROM AUTHOR]

Penelitian ini bertujuan untuk mengoptimalkan rute transportasi dan biaya pengangkutan sampah di TPS 3R USU menggunakan metode Saving Matrix dengan bantuan Machine Learning Python. Latar belakang penelitian didasarkan pada meningkatnya volume sampah seiring pertumbuhan penduduk, khususnya di Kota Medan, yang menghasilkan sekitar 2.000 ton sampah per hari. Permasalahan utama yang dihadapi adalah ketidakefisienan rute pengangkutan sampah, yang menyebabkan pemborosan waktu dan biaya. Metode Saving Matrix dipilih karena kemampuannya dalam meminimalkan jarak tempuh, waktu, dan biaya dengan mempertimbangkan kapasitas kendaraan dan volume sampah. Data yang digunakan meliputi koordinat lokasi TPS, timbulan sampah, dan kapasitas kendaraan, yang kemudian diolah menggunakan bahasa pemrograman Python untuk menghasilkan rute optimal. Algoritma Nearest Neighbor diterapkan untuk menentukan urutan kunjungan terdekat dari depot (TPS3R USU). Hasil penelitian menunjukkan bahwa optimasi rute berhasil mengurangi total jarak tempuh dan biaya operasional. Program Python yang dikembangkan menghasilkan 12 rute baru dengan biaya bahan bakar optimal sebesar Rp 139.732.713 per tahun. Selain itu, metode ini terbukti fleksibel dan dapat diterapkan pada skala yang lebih besar. Kesimpulan dari penelitian ini adalah metode Saving Matrix efektif dalam meminimalkan biaya dan jarak pengangkutan sampah. Saran untuk penelitian selanjutnya mencakup pertimbangan dinamika jalan, pengembangan program Python untuk variabel tambahan, serta evaluasi pemilahan sampah untuk meningkatkan efisiensi. [ABSTRACT FROM AUTHOR]

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