ABDI PAHMAN SIREGAR, NPM 2109100001 (2025) PENERAPAN ALGORITMA NAÏVE BAYES DALAM MENILAI TINGKAT KEPUASAN PENGGUNA BPJS KESEHATAN (STUDI KASUS DI RSUD KOTAPINANG). Skripsi thesis, Universitas Labuhanbatu.
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Abstract
Penelitian ini membahas penerapan algoritma Naïve Bayes dalam menilai tingkat kepuasan pengguna layanan BPJS Kesehatan di RSUD Kotapinang. Permasalahan utama yang dihadapi adalah masih adanya keluhan pasien terkait waktu tunggu, keterbatasan fasilitas, dan prosedur administrasi yang berbelit. Untuk mengevaluasi hal tersebut, dilakukan analisis data kepuasan pengguna menggunakan pendekatan data mining dengan metode Naïve Bayes. Dataset penelitian terdiri dari 55 data training dan 110 data testing yang diperoleh melalui survei kepuasan pasien. Proses penelitian meliputi pengumpulan data, preprocessing, pelatihan model, serta evaluasi menggunakan confusion matrix. Hasil implementasi dengan perangkat lunak RapidMiner menunjukkan bahwa algoritma Naïve Bayes memiliki tingkat akurasi sebesar 98% pada data training dan 90% pada data testing, dengan nilai precision 91%, recall 72%, dan AUC 1.0. Kesimpulan penelitian ini adalah algoritma Naïve Bayes efektif digunakan untuk mengklasifikasikan kepuasan pengguna BPJS Kesehatan, serta dapat membantu pihak rumah sakit dalam mengidentifikasi faktor-faktor yang memengaruhi kepuasan pasien. Rekomendasi penelitian selanjutnya adalah penggunaan dataset yang lebih besar dan pembandingan dengan algoritma lain untuk memperoleh hasil yang lebih komprehensif. Kata Kunci: Naïve Bayes, BPJS Kesehatan, Kepuasan Pasien, Data Mining, RapidMiner ======================================================== This study discusses the application of the Naïve Bayes algorithm in assessing the satisfaction level of BPJS Health service users at Kotapinang Regional General Hospital (RSUD Kotapinang). The main issues encountered include patient complaints regarding long waiting times, limited facilities, and complicated administrative procedures. To evaluate these issues, a user satisfaction data analysis was conducted using a data mining approach with the Naïve Bayes method. The research dataset consists of 55 training data and 110 testing data obtained through a patient satisfaction survey. The research process includes data collection, preprocessing, model training, and evaluation using a confusion matrix. The implementation results using RapidMiner software show that the Naïve Bayes algorithm achieved an accuracy rate of 98% on training data and 90% on testing data, with a precision of 91%, recall of 72%, and an AUC of 1.0. The conclusion of this study is that the Naïve Bayes algorithm is effective for classifying the satisfaction level of BPJS Health service users and can assist hospitals in identifying factors that influence patient satisfaction. Future research is recommended to use a larger and more diverse dataset and to compare the performance of Naïve Bayes with other algorithms to obtain more comprehensive results. Keywords: Naïve Bayes, BPJS Health, Patient Satisfaction, Data Mining, RapidMiner
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Naïve Bayes, BPJS Kesehatan, Kepuasan Pasien, Data Mining, RapidMiner================Naïve Bayes, BPJS Health, Patient Satisfaction, Data Mining, RapidMiner |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 23 Oct 2025 02:43 |
| Last Modified: | 23 Oct 2025 02:43 |
| URI: | http://repository.ulb.ac.id/id/eprint/1850 |
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