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All Journal Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Perspectives in Mathematics and Applications (PERMATA)
Priska Sari Dewi
Universitas Nahdlatul Ulama Purwokerto
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Physics

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APLIKASI TRAVELLING SALESMAN PROBLEM PADA PENGEDROPAN BARANG DI ANJUNGAN MENGGUNAKAN METODE INSERTION Priska Sari Dewi; Triyani Triyani; Siti Rahmah Nurshiami
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 12 No 2 (2020): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2020.12.2.3617

Abstract

Travelling Salesman Problem (TSP) is a problem to find the shortest path a salesman visitS all the cities exactly once, and return to the starting city. In this reseacrh, the methods for TSP used are the nearest insertion method, the cheapest insertion method, and the farthest insertion method. With help the function of Software R to creat a minimum TSP Program from three insertion methods.The TSP results for same number of point using three insertion methods do not always have the same weight and route but depending on the data used.
Analisis deret waktu dan peramalan pengangguran di Kabupaten Purbalingga menggunakan metode penghalusan eksponensial ganda Brown: Evaluasi berbasis akurasi. Dian Pratama; Chandra Sari Widyaningrum; Priska Sari Dewi
Perspectives in Mathematics and Applications Vol 2 No 01 (2026): Juni
Publisher : Kreasi Pustaka Mandiri (Krestama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66256/permata.v2i1.43

Abstract

Unemployment remains a persistent socioeconomic challenge in Indonesia, including Purbalingga Regency, Central Java. This study analyzes the unemployment trend and forecasts the number of unemployed individuals in Purbalingga Regency using a time-series approach. Annual unemployment data for 2010–2024 from the Central Bureau of Statistics (BPS) were modeled using Brown’s Double Exponential Smoothing (DES), which is suitable for non-seasonal series with a linear trend. The smoothing parameter (α) was examined from 0.1 to 0.9, and model performance was evaluated using MAD, MSE, and MAPE based on in-sample fitted errors over the 2010–2024 period. The results indicate a fluctuating but upward trend, particularly after the COVID-19 period. The best-performing parameter was α = 0.2, producing the lowest MAD and MAPE; under this evaluation setting, MAPE was below 1%, indicating low in-sample error. Using the selected model, unemployment in 2025 is forecast at approximately 31,795 people. These findings suggest that Brown’s DES can provide a practical baseline forecast to support evidence-based labor market policy and regional economic planning, while the results should be interpreted with caution, given the linear-trend and univariate assumptions.
Co-Authors Chandra Sari Widyaningrum Dian Pratama Siti Rahmah Nurshiami, Siti Rahmah Triyani Triyani