PREDIKSI PENDAPATAN SALON MENGGUNAKAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) SEBAGAI PENDUKUNG PERENCANAAN PENJUALAN

Silvi yani; Denni Pratama

Authors

Silvi yani STMIK IKMI CIREBON, Indonesia
Denni Pratama STMIK IKMI Cirebon, Indonesia

Keywords:

pendapatan salon, Peramalan, Time Series, ARIMA, Komputerisasi Akuntansi

Abstract

Pendapatan merupakan salah satu indikator utama dalam keberlangsungan usaha salon kecantikan karena berperan penting dalam perencanaan keuangan dan pengambilan keputusan manajerial. Permasalahan yang sering dihadapi oleh usaha salon adalah fluktuasi pendapatan yang menyulitkan pemilik usaha dalam memperkirakan pendapatan pada periode mendatang. Ketidakakuratan prediksi pendapatan dapat berdampak pada perencanaan penjualan, pengelolaan arus kas, serta penyusunan strategi operasional. Penelitian ini bertujuan untuk menerapkan metode Autoregressive Integrated Moving Average (ARIMA) dalam memprediksi pendapatan salon berdasarkan data historis. Data yang digunakan berupa data pendapatan harian salon pada periode Januari 2023 hingga November 2025. Tahapan penelitian meliputi pembacaan data, pra-pemrosesan data, penerapan model ARIMA, serta proses peramalan pendapatan. Pengolahan dan pemodelan data dilakukan menggunakan perangkat lunak RapidMiner/AI Studio. Hasil penelitian menunjukkan bahwa model ARIMA mampu menghasilkan pola prediksi pendapatan yang mengikuti tren data historis. Model prediksi yang dihasilkan dapat digunakan sebagai alat bantu dalam memperkirakan pendapatan di masa mendatang sehingga mendukung perencanaan penjualan dan pengambilan keputusan berbasis data.

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