Perbandingan Model
Filter Batch Dataset
🥧 Distribusi Data — Data Mentah MBG
5616
Total
1026
Positif
3167
Negatif
1423
Netral
📊 Grafik Perbandingan Metrik Evaluasi
🌲 Random Forest (Training Terakhir)
| Akurasi | 71.14% |
| Precision | 72% |
| Recall | 71.14% |
| F1-Score | 71.49% |
| Data Train / Test | 7968 / 1171 |
| Waktu Training | 1755.97 detik |
📍 KNN (Training Terakhir)
| Akurasi | 56.79% |
| Precision | 66.55% |
| Recall | 56.79% |
| F1-Score | 58.46% |
| Data Train / Test | 7968 / 1171 |
| Waktu Training | 84.849 detik |
Confusion Matrix — Random Forest
| Aktual \ Prediksi | negatif | netral | positif |
|---|---|---|---|
| negatif | 518 | 96 | 50 |
| netral | 73 | 178 | 44 |
| positif | 33 | 42 | 137 |
Confusion Matrix — KNN
| Aktual \ Prediksi | negatif | netral | positif |
|---|---|---|---|
| negatif | 348 | 200 | 116 |
| netral | 36 | 184 | 75 |
| positif | 22 | 57 | 133 |
Classification Report — Random Forest
| Label | Precision | Recall | F1-Score | Support |
|---|---|---|---|---|
| negatif | 83.01% | 78.01% | 80.43% | 664 |
| netral | 56.33% | 60.34% | 58.27% | 295 |
| positif | 59.31% | 64.62% | 61.85% | 212 |
* Support = jumlah data uji per kelas · F1-Score = harmonic mean precision & recall
Classification Report — KNN
| Label | Precision | Recall | F1-Score | Support |
|---|---|---|---|---|
| negatif | 85.71% | 52.41% | 65.05% | 664 |
| netral | 41.72% | 62.37% | 50% | 295 |
| positif | 41.05% | 62.74% | 49.63% | 212 |
* Support = jumlah data uji per kelas · F1-Score = harmonic mean precision & recall
Kesimpulan Perbandingan
Berdasarkan hasil training terakhir pada dataset batch "Data Mentah MBG", algoritma Random Forest menghasilkan akurasi lebih tinggi yaitu 71.14%, unggul 14.35 poin persen dibandingkan algoritma pembanding.
Seluruh Riwayat Training
| Waktu | Batch | Algoritma | Akurasi | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 15/08/2026 21:39 | Data Mentah MBG | 📍 KNN | 56.79% | 66.55% | 56.79% | 58.46% |
| 15/08/2026 21:34 | Data Mentah MBG | 🌲 RF | 71.14% | 72% | 71.14% | 71.49% |
| 15/08/2026 21:02 | Data Mentah MBG | 🌲 RF | 70.62% | 72.21% | 70.62% | 71.14% |
| 15/08/2026 20:55 | Data Mentah MBG | 🌲 RF | 56.62% | 71.59% | 56.62% | 57.7% |
| 15/08/2026 20:42 | Data Mentah MBG | 🌲 RF | 54.48% | 71.17% | 54.48% | 55.77% |
| 15/08/2026 20:20 | Data Mentah MBG | 📍 KNN | 55.59% | 64.16% | 55.59% | 57.36% |
| 15/08/2026 20:17 | Data Mentah MBG | 🌲 RF | 59.95% | 72.94% | 59.95% | 61.46% |