Syamsu Wais Al Qorni, Nur (2024) PENERAPAN ALGORITMA K-MEANS CLUSTERING ULASAN PENGGUNA MERDEKA MENGAJAR DI PLAY STORE. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.
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Abstract
Nur Syamsu Wais Al Qorni, 2024, Penerapan Algoritma K-Means Clustering Pada Ulasan Pengguna Merdeka Mengajar di Play Store. Skripsi Jurusan Teknik Informatika, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma, Pembimbing (I) Wahyuni, S.Kom., M.Kom., Pembimbing (II) Pitrasacha Adytia, S.T., M.T. Kata Kunci : Algoritma K-Means Clustering, Analisis Klaster, Aplikasi Merdeka Mengajar, CRISP-DM, Google Play Store. Dinas Pendidikan dan Kebudayaan atau Kemendikbudristek memberikan kemudahan bagi para tenaga pengajarnya melalui aplikasi Merdeka Mengajar. Aplikasi ini membantu para guru dalam mengajar secara efektif serta meningkatkan kompetensi mereka. Namun, banyaknya ulasan pengguna di Google Play Store mengenai aplikasi ini menunjukkan adanya kebutuhan untuk memahami fitur-fitur yang disukai dan dikeluhkan. Penelitian ini bertujuan untuk menerapkan Algoritma K-Means Clustering dalam menganalisis ulasan pengguna aplikasi Merdeka Mengajar. Metode CRISP-DM digunakan dalam proses ini, yang mencakup tujuh tahapan: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation, Deployment, dan Evaluation System. Data ulasan dikumpulkan menggunakan teknik scrapping dan diproses menggunakan berbagai library seperti NLP-ID, Sastrawi, dan NLTK. Analisis klasterisasi menunjukkan bahwa model Bag of Words (BoW) dan TF-IDF optimal pada 3 klaster, sedangkan model Word2Vec menunjukkan hasil terbaik pada 7 klaster. Namun, penelitian ini menggunakan 3 klaster dengan Word2Vec untuk konsistensi kinerja. Hasil klasterisasi mengidentifikasi tiga tema utama: "Aplikasi sangat membantu untuk Guru," "Memudahkan membuat Administrasi bagi Guru," dan "Pelatihan secara online maupun offline." Penelitian ini memberikan rekomendasi untuk pengembangan lebih lanjut, termasuk pengambilan data dari berbagai media sosial, pembangunan sistem berbasis Android, dan analisis sentimen yang lebih mendalam. ============================================================ Nur Syamsu Wais Al Qorni, 2024, Application of the K-Means Clustering Algorithm in Merdeka Mengajar User Reviews on the Play Store. Thesis Department of Informatics Engineering, Widya Cipta Dharma College of Information and Computer Management, Supervisor (I) Wahyuni, S.Kom., M.Kom., Supervisor (II) Pitrasacha Adytia, S.T., M.T. Keywords: K-Means Clustering Algorithm, Cluster Analysis, Merdeka Mengajar Application, CRISP-DM, Google Play Store. The Department of Education and Culture or Kemendikbudristek provides convenience for its teaching staff through the Merdeka Mengajar application. This application helps teachers teach effectively and improve their competence. However, the many user reviews on the Google Play Store regarding this application indicate a need to understand the features that are liked and complained about. This study aims to apply the K-Means Clustering Algorithm in analyzing user reviews of the Merdeka Mengajar application. The CRISP-DM method is used in this process, which includes seven stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment, and Evaluation System. Review data is collected using scraping techniques and processed using various libraries such as NLP-ID, Sastrawi, and NLTK. Clustering analysis shows that the Bag of Words (BoW) and TF-IDF models are optimal at 3 clusters, while the Word2Vec model shows the best results at 7 clusters. However, this study uses 3 clusters with Word2Vec for performance consistency. The clustering results identified three main themes: "The application is very helpful for teachers," "Makes it easier to create administration for teachers," and "Training both online and offline." This study provides recommendations for further development, including data collection from various social media, building an Android-based system, and deeper sentiment analysis.
| Item Type: | Thesis (S1 Teknik Informatika) |
|---|---|
| Additional Information: | Pembimbing 1 : Wahyuni, S.Kom., M.Kom Pembimbing 2 : Pitrasacha Aditya, S.T., M.T., |
| Uncontrolled Keywords: | Algoritma K-Means Clustering, Analisis Klaster, Aplikasi Merdeka Mengajar, CRISP-DM, Google Play Store. |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Teknik Informatika |
| Depositing User: | Nur Syamsu Wais Al Qorni |
| Date Deposited: | 07 Aug 2024 07:10 |
| Last Modified: | 07 Aug 2024 07:10 |
| URI: | http://repository.wicida.ac.id/id/eprint/5600 |
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