ADINDA AYU LESTARI NASUTION, NPM 2209100001 (2026) ANALISIS PREDIKSI JUMLAH KUNJUNGAN PASIEN DI PUSKESMAS AEK KOTA BATU MENGGUNAKAN METODE REGRESI LINEAR. Skripsi thesis, Universitas Labuhanbatu.
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Abstract
Jumlah kunjungan pasien di Puskesmas Aek Kota Batu mengalami perubahan pada setiap periode sehingga diperlukan suatu metode untuk memprediksi jumlah kunjungan pada periode berikutnya sebagai dasar perencanaan pelayanan kesehatan. Penelitian ini bertujuan untuk menganalisis pola data historis kunjungan pasien dan membangun model prediksi menggunakan metode regresi linear. Data yang digunakan berupa data kunjungan pasien bulanan periode tahun 2025–2026 yang diolah melalui tahapan Knowledge Discovery in Database (KDD), meliputi data selection, preprocessing, transformation, data mining, dan evaluation. Proses analisis dilakukan menggunakan aplikasi POM-QM for Windows dengan lima variabel independen berbasis time series lag (lag-5 hingga lag-1). Hasil penelitian menunjukkan bahwa metode regresi linear mampu membentuk model prediksi berdasarkan hubungan antara data historis dan jumlah kunjungan pasien pada periode berikutnya. Kinerja model dievaluasi menggunakan nilai R², MAE, MSE, RMSE, RMAE dan MAPE untuk mengetahui tingkat akurasi prediksi. Model yang dihasilkan dapat dimanfaatkan sebagai pendukung pengambilan keputusan dalam merencanakan kebutuhan tenaga kesehatan, sarana, dan pelayanan di Puskesmas Aek Kota Batu sehingga proses pelayanan dapat berlangsung lebih efektif dan efisien. Kata Kunci: Prediksi, Kunjungan Pasien, Regresi Linear, KDD, POM-QM for Windows ========================================== Patient visit numbers at the Aek Kota Batu Community Health Center (Puskesmas) fluctuate over time; therefore, a method is required to predict visit volumes for future periods to inform healthcare service planning. This study aims to analyze historical patient visit patterns and develop a prediction model using linear regression. Monthly patient visit data from 2025 to 2026 were processed using the Knowledge Discovery in Databases (KDD) framework, comprising data selection, preprocessing, transformation, data mining, and evaluation. Analysis was conducted using POM-QM for Windows software, incorporating five independent variables based on time-series lags (lag-5 through lag-1). The results demonstrate that linear regression can generate a prediction model based on the relationship between historical data and future patient visit volumes. Model performance was evaluated using R², MAE, RMAE, MSE, RMSE, and MAPE metrics to assess prediction accuracy. The resulting model can serve as a decision-support tool for planning healthcare personnel, facilities, and services at the Aek Kota Batu Community Health Center, thereby enhancing the effectiveness and efficiency of service delivery. Keywords: Prediction, Patient Visits, Linear Regression, KDD, POM-QM for Windows
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Prediksi, Kunjungan Pasien, Regresi Linear, KDD, POM-QM for Windows===============Prediction, Patient Visits, Linear Regression, KDD, POM-QM for Windows |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 04 Sep 2026 08:02 |
| Last Modified: | 04 Sep 2026 08:02 |
| URI: | http://repository.ulb.ac.id/id/eprint/2755 |
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