TUNGKUP, ENDANG LUMBAN (2025) ANALISIS PRODUK FARMASI MENGGUNAKAN METODE FORECASTING STATISTICAL STRAIGHT LINE (Studi Kasus OTC PT. Bernofarm). S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Predictions of best-selling products in future product sales are intended to control existing product stocks. So that product shortages or excess stock can be minimized. When product sales can be predicted accurately, it can be done to meet consumer demand on time and company cooperation and relationships are maintained well so that the company can avoid losing sales and consumers. In order to predict the best-selling products, the straight line statistical forecasting method is applied at PT Bernform, especially in the over the counter (OTC) product segment for the next year. With intense business competition in the pharmaceutical industry, predicting anticipated product sales is very important to support production planning and marketing strategies. Historical product sales data is used as a basis for designing a linear trend model which is expected to provide an accurate picture of demand projections. This method is analyzed using the level of accuracy through Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). Keywords: Forecasting, Straight Line, OTC Products, Best Sellers Prediction. Prediksi produk terlaris dalam penjualan produk di masa depat dimaksudkan untuk mengendalikan stok produk yang ada. Supaya kekurangan atau kelebihan stok produk dapat diminimalkan. Ketika produk terlaris dapat diprediksi dengan akurat maka pemenuhan permintaan konsumen dapat diusahakan tepat waktu dan kerjasama perusahaan dengan relasi tetap terjaga dengan baik sehingga perusahaan dapat terhindar dari kehilangan penjualan maupun konsumen. Agar dapat memprediksi produk terlaris penerapan metode forecasting statistical straight line di PT Bernform khususnya segmen produk over the counter (OTC) untuk satu tahun kedepan. Dengan adanya persaingan bisnis yang ketat dalam industri farmasi, prediksi produk yang diantisipasi menjadi terlaris sangat penting untuk mendukung perencanaan produksi dan strategi pemasaran. Data penjualan historis produk digunakan sebagai dasar untuk merancang model tren linier yang diharapkan dapat memberikan gambaran proyeksi permintaan ayng akurat. Metode ini dianalisis menggunakan tingkat akurasi melalui Mean Absolute Percentage Error (MAPE) dan Root Mean Squared Error (RMSE). Kata kunci: Forecasting, Straight Line, Produk OTC, Prediksi Penjualan Terlaris.
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