Arianto, Joko (2025) PENERAPAN ALGORITMA ARIMA DAN SARIMA UNTUK PREDIKSI PROFIT PEMASUKAN PENJUALAN INTERNET RETAIL BROADBAND DI PT PRESTASI PIRANTI INFORMASI. S1 thesis, Universitas Mercu Buana Jakarta - Menteng.
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Abstract
Penelitian ini menerapkan algoritma AutoRegressive Integrated Moving Average (ARIMA) dan Seasonal ARIMA (SARIMA) untuk memprediksi profit pemasukan penjualan internet retail broadband di PT Prestasi Piranti Informasi. Data historis penjualan dari Januari 2015 hingga Desember 2024 diolah melalui proses pembersihan dan analisis awal untuk memastikan kualitas. Hasil evaluasi menunjukkan bahwa model ARIMA dan SARIMA memiliki akurasi tinggi dalam prediksi, dengan Mean Absolute Error (MAE) sebesar 58,43% pada data pelatihan dan 68,34% pada data pengujian. Selain itu, tren peningkatan profit yang signifikan terlihat pada Januari hingga Juni 2024, yang menjadi peluang strategis bagi perusahaan. Penelitian ini tidak hanya mengonfirmasi keandalan algoritma ARIMA dan SARIMA untuk data time series dengan pola musiman, tetapi juga memberikan kontribusi nyata dalam pengembangan analisis data di industri telekomunikasi. Temuan ini diharapkan dapat digunakan untuk mendukung pengambilan keputusan strategis dalam merancang strategi bisnis yang lebih efektif. This research applies AutoRegressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) algorithms to predict broadband retail internet sales revenue at PT Prestasi Piranti Informasi. Historical sales data from January 2015 to December 2024 is processed through a cleaning process and preliminary analysis to ensure quality. The evaluation results show that the ARIMA and SARIMA models have high accuracy in prediction, with a Mean Absolute Error (MAE) of 58.43% on training data and 68.34% on testing data. In addition, a significant upward trend in profits was seen from January to June 2024, which is a strategic opportunity for the company. This research not only confirms the reliability of ARIMA and SARIMA algorithms for time series data with seasonal patterns, but also makes a real contribution to the development of data analysis in the telecommunications industry. The findings are expected to be used to support strategic decision-making in designing more effective business strategies
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41520110033 |
| Uncontrolled Keywords: | Internet broadband, Prediksi profit, ARIMA, SARIMA, Analisis data, Strategi penjualan. Broadband internet, Profit prediction, ARIMA, SARIMA, Data analysis, Sales strategy. |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | OKTAFIYANI AZ ZAHRO |
| Date Deposited: | 08 Feb 2025 03:15 |
| Last Modified: | 08 Feb 2025 03:15 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/94006 |
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