memperbaiki dependencies

.gitignore

@@ -1,11 +1,25 @@
-# Python
+# Python & Bytecode
 __pycache__/
 *.py[cod]
+*$py.class
+*.so
+.Python
+build/
+dist/
+*.egg-info/
+
+# Environments & Virtual Environments
 .venv/
 venv/
-
-# Environments & IDEs
+ENV/
+env/
 .env
+
+# uv & Version Pinning
+uv.lock
+.python-version
+
+# IDEs & Notebooks
 .vscode/
 .idea/
 .ipynb_checkpoints/
@@ -13,3 +27,4 @@ venv/
 # OS
 .DS_Store
 Thumbs.db
+

experiments/08_sentimen_gap.py

@@ -1,6 +1,4 @@
 import os
-os.environ["TF_USE_LEGACY_KERAS"] = "1"  # Bypass Keras 3 & optree
-
 import re
 import numpy as np
 import pandas as pd
@@ -16,11 +14,11 @@ from sklearn.metrics import (
 )
 
 import tensorflow as tf
-import tf_keras as keras
-from tf_keras import layers
-from tf_keras.callbacks import EarlyStopping
-from tf_keras.preprocessing.text import Tokenizer  # type: ignore
-from tf_keras.preprocessing.sequence import pad_sequences
+from tensorflow import keras
+from tensorflow.keras import layers
+from tensorflow.keras.callbacks import EarlyStopping
+from tensorflow.keras.preprocessing.text import Tokenizer  # type: ignore
+from tensorflow.keras.preprocessing.sequence import pad_sequences
 
 # ============================================================
 # KONFIGURASI DIREKTORI PENYIMPANAN
@@ -159,7 +157,7 @@ print("SEL 9 — MODEL GAP")
 print("=" * 60)
 
 sent_model = keras.Sequential([
-    layers.Embedding(input_dim=VOCAB_SIZE, output_dim=EMBED_DIM, input_length=MAX_LEN),
+    layers.Embedding(input_dim=VOCAB_SIZE, output_dim=EMBED_DIM),
     layers.GlobalAveragePooling1D(),
     layers.Dense(64, activation="relu"),
     layers.Dropout(0.4),

results/reports/classification_report_gap_sentimen.txt

@@ -1,8 +1,8 @@
               precision    recall  f1-score   support
 
- Negatif (0)       0.58      0.34      0.42       185
- Positif (1)       0.98      0.99      0.99      7572
+ Negatif (0)       0.59      0.22      0.32       185
+ Positif (1)       0.98      1.00      0.99      7572
 
     accuracy                           0.98      7757
-   macro avg       0.78      0.66      0.71      7757
-weighted avg       0.97      0.98      0.98      7757
+   macro avg       0.78      0.61      0.65      7757
+weighted avg       0.97      0.98      0.97      7757