FAAZA, NAIMA (2025) PERANCANGAN SISTEM PAKAR MENGGUNAKAN METODE CERTAINTY FACTOR DAN FORWARD CHAINING UNTUK REKOMENDASI PRODUK SERUM SOMETHINC. S1 thesis, Universitas Mercu Buana - Menteng.
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Abstract
Sistem pakar telah lama digunakan untuk sistem keputusan diberbagai bidang. Produk serum Somethinc memiliki banyak pilihan produk. Akibat keberagaman pilihan produk yang tersedia maka dilakukan hasil survei terhadap 18 responden pengguna Serum Somethinc dengan usia di atas 22 tahun. Hasil survei menunjukkan sebanyak 88,9% responden mengungkapkan kesulitan dalam memilih. Data penelitian menggunakan 27 produk serum Somethinc, 30 gejala atau kondisi kulit, dan 6 jenis skin concern pada serum Somethinc. Sistem pakar berbasis web dengan python framework diusulkan untuk membantu pengguna. Sistem pakar ini menggabungan metode certainty factor dan teknik inferensi forward chaining untuk membantu pengguna dalam memilih serum yang sesuai dengan kebutuhan. Hasil uji sistem dilakukan dengan 101 sampel kasus yang menghitung kesesuaian antara kesimpulan sistem dengan pakar menggunakan recall untuk multi-label model. Evaluasi kinerja menunjukkan bahwa sistem memiliki nilai Recall Multi-Label sebesar 87,1% dari label relevan yang ada dalam ground truth. Expert systems have long been utilized in decision-making across various fields. Somethinc serum products offer a wide range of options. Due to the diversity of available products, a survey was conducted involving 18 respondents aged over 22 who use Somethinc serums, with 88.9% of them expressing difficulty in making a choice. The research data includes 27 Somethinc serum products, 30 skin conditions or symptoms, and 6 types of skin concerns addressed by Somethinc serums. A web-based expert system using a Python framework is proposed to assist users. This expert system combines the certainty factor method and forward chaining inference techniques to help users select the serum that meets their needs. System testing was conducted using 101 case samples to evaluate the alignment between system conclusions and expert opinions, using recall as a metric for the multi-label model. Performance evaluation showed that the system achieved a Multi-Label Recall score of 87.1% based on relevant labels in the ground truth.
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41520120010 |
| Uncontrolled Keywords: | Sistem Pakar, Certainty Factor, Forward Chaining, Confusion Matrix Expert System, Certainty Factor, Forward Chaining, Confusion Matrix |
| 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: | SUTRA DEWANGGA |
| Date Deposited: | 31 Jan 2025 07:55 |
| Last Modified: | 31 Jan 2025 07:55 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/93800 |
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