Optimalisasi Peramalan Permintaan dan Perencanaan Agregat Toko Roti Eco Kabupaten Tangerang.

Abstract

Toko Roti Eco sebagai salah satu toko roti di Kabupaten Tangerang menghadapi kendala dalam merencanakan dan mengendalikan produksinya. Keadaan yang sering terjadi ialah produksi yang melebihi permintaan sehingga banyak roti yang tidak terjual dan menyebabkan inefisiensi pendapatan. Oleh karena itu, tujuan dari penelitian ini adalah meramalkan permintaan dari empat jenis roti di Toko Roti Eco, yaitu roti tawar original, roti tawar pandan, roti manis, dan roti unyil dan menentukan strategi perencanaan agregatnya. Penelitian dilakukan di Toko Roti Eco yang berlokasi di Kabupaten Tangerang sejak bulan Januari sampai April 2024. Metode peramalan permintaan yang digunakan meliputi weighted moving average, exponential smoothing with trend adjustment, dan trend analysis. Sedangkan opsi strategi perencanaan agregat menggunakan level strategy, chase strategy, dan mixed strategy. Hasil peramalan menunjukkan bahwa metode trend analysis merupakan metode terbaik karena memberikan tingkat kesalahan peramalan yang terkecil. Hasil perencanaan agregat menunjukkan bahwa mixed strategy merupakan strategi yang terbaik karena menghasilkan biaya yang terkecil.

Eco Bakery as one of the bakeries in Tangerang Regency faces obstacles in planning and controlling its production. A situation that often occurs is that production exceeds demand, resulting in a lot of bread not being sold and causing income inefficiencies. Therefore, the goals of this research was to predict the demand for four types of bread at the Eco Bakery, namely original white bread, pandan white bread, sweet bread, and small bread, and to determine the aggregate planning strategy. The research was conducted at the Eco Bakery Shop located in Tangerang Regency from January to April 2024. The demand forecasting methods used included the weighted moving average, exponential smoothing with trend adjustment, and trend analysis. Meanwhile, the aggregate planning strategy options used were the level strategy, pursuit strategy, and mixed strategy. The forecasting results showed that the trend analysis method was the best method because it provided the smallest level of forecasting error. The aggregate planning results showed that the mixed strategy was the best strategy because it produced the smallest costs.