Update app.py

app.py

@@ -108,7 +108,7 @@ def select_sentiment_model(selected_model):
 
 # Fungsi untuk prediksi sentimen
 @st.cache_data
-def predict_sentiment(text, model, tfidf_vectorizer, slang_dict):
+def predict_sentiment(text, _model, tfidf_vectorizer, slang_dict):
     # Tahap-1: Membersihkan dan normalisasi teks
     cleaned_text = clean_text(text)
     norm_slang_text = normalize_slang(cleaned_text, slang_dict)
@@ -173,7 +173,7 @@ else:
 # Analisis sentimen
 results = []
 analisis = False
-if input_option == "Teks Manual" and user_input:
+if st.button("Analysis") and input_option == "Teks Manual" and user_input:
     # Pisahkan teks yang dimasukkan pengguna menjadi baris-baris terpisah
     user_texts = user_input.split('\n')
     for text in user_texts:
@@ -184,7 +184,7 @@ if input_option == "Teks Manual" and user_input:
         results.append((text, cleaned_text, norm_slang_text, sentiment_label, emoticon))
         analisis = True
 
-elif input_option == "Unggah Berkas XLSX" and uploaded_file is not None:
+elif st.button("Analysis") and input_option == "Unggah Berkas XLSX" and uploaded_file is not None:
     if 'Text' in df.columns:
         for text in texts:
             sentiment_label = predict_sentiment(text, sentiment_model, tfidf_vectorizer, lookp_dict)
@@ -196,8 +196,10 @@ elif input_option == "Unggah Berkas XLSX" and uploaded_file is not None:
             
     else:
         st.warning("Berkas XLSX harus memiliki kolom bernama 'Text' untuk analisis sentimen.")
+
+        
 st.info('Tekan "Analysis" kemabli jika tampilan menghilang', icon = 'ℹ️')
-if results and analisis == True and st.button("Analysis"):
+if results and analisis == True:
     # Membagi tampilan menjadi dua kolom
     columns = st.columns(2)