skripsi-bertopic

This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.

Usage

To use this model, please install BERTopic:

pip install -U bertopic

You can use the model as follows:

from bertopic import BERTopic
topic_model = BERTopic.load("Athallie/skripsi-bertopic")

topic_model.get_topic_info()

Topic overview

• Number of topics: 2
• Number of training documents: 7490

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
0	tidak bisa buka - tidak jelas - bisa login - tidak bisa login - tidak masuk	4693	0_tidak bisa buka_tidak jelas_bisa login_tidak bisa login
1	tidak rumit - banyak fitur - transaksi transaksi - digunakan transaksi - banyak promo	2797	1_tidak rumit_banyak fitur_transaksi transaksi_digunakan transaksi

Training hyperparameters

• calculate_probabilities: True
• language: None
• low_memory: False
• min_topic_size: 60
• n_gram_range: (1, 1)
• nr_topics: 3
• seed_topic_list: None
• top_n_words: 10
• verbose: True
• zeroshot_min_similarity: 0.7
• zeroshot_topic_list: None

Framework versions

• Numpy: 2.0.2
• HDBSCAN: 0.8.42
• UMAP: 0.5.12
• Pandas: 2.2.2
• Scikit-Learn: 1.6.1
• Sentence-transformers: 5.4.0
• Transformers: 5.0.0
• Numba: 0.60.0
• Plotly: 5.24.1
• Python: 3.12.13