FORECASTING KEBUTUHAN OBAT RUMAH SAKIT AKADEMIK UNIVERSITAS GADJAH MADA KATEGORI FAST, SLOW, DAN MEDIUM MOVING MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE

Irvan Jullian, Prof. Dr. apt. Akhmad Kharis Nugroho, M.Si; apt.Taufiqurrohman M.Clin.Pharm

2023 | Skripsi | FARMASI

Perencanaan dan pengendalian obat yang baik merupakan hal penting dalam mencapai efisiensi pengelolaan obat. Pengelolaan obat di rumah sakit yang kurang baik dan tidak efisien dapat menimbulkan beberapa kerugian. Berdasarkan penelitian sebelumnya yang dilakukan di Instalasi Farmasi Rumah Sakit Akademik Universitas Gadjah Mada (RSA UGM), didapatkan nilai persentase obat rusak dan kadaluarsa sebesar 4,71 persen serta stok mati 7,89 persen. Oleh karena itu, diperlukan adanya metode forecasting yang akurat untuk mendukung perencanaan. Penelitian ini bertujuan untuk mengetahui kelayakan metode forecasting Autoregressive Integrated Moving Average (ARIMA) sebagai pertimbangan dalam proses perencanan obat di RSA UGM. Penelitian ini menggunakan metode kuantitatif non-eksperimental berbentuk observasional dengan analisis deskriptif yang bersifat retrospektif. Sampel diambil dengan cara purposive sampling. Sampel tersebut adalah 20 obat urutan tertinggi dari masing- masing kategori fast, medium, dan slow moving pada tahun 2021-2022 dengan kriteria tertentu. Peramalan dilakukan dengan metode ARIMA menggunakan software Eviews 12, selanjutnya dihitung ukuran kesalahannya, yaitu Mean Absolute Percentage Error (MAPE) dengan menggunakan Microsoft Excel. Hasil penelitian menunjukkan bahwa peramalan metode ARIMA layak digunakan sebagai pertimbangan dalam proses perencanaan kebutuhan obat di RSA UGM pada obat kategori fast dan medium moving karena memiliki lebih banyak sampel dengan nilai MAPE <50>fast moving. Namun, pada kategori medium dan slow moving metode konvensional (RSA UGM) lebih akurat.

Good planning and control of medications are essential for achieving efficient medication management. Poor and inefficient medication management in hospitals can lead to various losses. Based on previous research conducted at the Pharmacy Department of the Academic Hospital of Gadjah Mada University (RSA UGM), the percentage of damaged and expired medications was found to be 4.71 percent, with a dead stock of 7.89 percent. Therefore, the implementation of an accurate forecasting method is necessary to support planning. This study aims to determine the feasibility of the Autoregressive Integrated Moving Average (ARIMA) forecasting method as a consideration in the medication planning process at RSA UGM. This research adopts a non-experimental quantitative method in the form of observational study with retrospective descriptive analysis. The samples were obtained through purposive sampling. The samples consisted of the top 20 medications from each category (fast, medium, and slow-moving) in the years 2021-2022, based on specific criteria. The forecasting was conducted using the ARIMA method with Eviews 12 software, and the Mean Absolute Percentage Error (MAPE) was calculated using Microsoft Excel. The results of the study indicate that the ARIMA forecasting method is suitable for consideration in the medication planning process at RSA UGM for the fast and medium-moving categories. This is because there are more samples with MAPE values below 50 percent. The ARIMA method is more accurate compared to the conventional method (RSA UGM) for the fast-moving category. However, for the medium and slow-moving categories, the conventional method (RSA UGM) is more accurate.

Kata Kunci : Forecasting, Autoregressive Integrated Moving Average, MAPE, RSA UGM