Khamal Fauzan Somantri, - (2022) PENGEMBANGAN APLIKASI ARSG : ASSOCIATION RULES AND SURVEY GENERATOR MENGGUNAKAN ALGORITMA FP-GROWTH DENGAN METODE LAPI UNTUK PENANGANAN INCREMENTAL DATA (STUDI KASUS : FAKTOR KEMATIAN AKIBAT COVID-19). S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
ABSTRAK Seiring berkembangnya penggunaan data dengan skala besar serta kebutuhan data mining yang terus meningkat, maka komputasi tinggi dibutuhkan oleh berbagai macam sistem. Sistem perlu mengumpulkan dan menganalisis data yang benar-benar dibutuhkan sebelum mengambil suatu keputusan. Selain itu, kurangnya integrasi data menyebabkan tantangan interoperabilitas dalam bidang kesehatan, sehingga menjadi tantangan kritis dalam situasi pandemi Covid-19. Data yang dibutuhkan merupakan incremental data, maka jumlah pembacaan data set dan pemeliharaan hubungan antar item secara efisien perlu dilakukan. Penelitian ini menggunakan algoritma FP-Growth dengan metode LAPI untuk penanganan incremental data tersebut. Hasil dari penelitian ini adalah aplikasi Association Rules and Survey Generator (ARSG) yang dibangun berhasil menjadi pengumpul dan pengolah data secara terpusat dan terintegrasi, sehingga siapapun mudah untuk mengaksesnya dan berkontribusi. Hal tersebut didasarkan pada hasil testing aplikasi yaitu 100% fungsi pada aplikasi berjalan dengan baik. Juga untuk mengetahui faktor apa saja yang paling berpengaruh terhadap kematian pada penyintas Covid-19. Selain itu aplikasi ARSG mampu melibatkan banyak orang yang mau berbagi pengalaman terkait orang terdekatnya yang positif Covid-19 dan meninggal dunia. ABSTRACT As the use of large-scale data grows and the need for data mining continues to increase, computing is needed by various systems. The system needs to collect and analyze data that is really needed before making a decision. In addition, the lack of data integration causes interoperability challenges in healthcare, making it a critical challenge in the Covid-19 pandemic situation. The data needed is incremental data, so the number of readings of the data set and maintaining the relationship between data items efficiently needs to be done. This study used the FP-Growth algorithm with the LAPI method to handle the incremental data. The result of this research is that the Association Rules and Survey Generator (ARSG) application that was built has succeeded in becoming an integrated and integrated data collector and processor, so that it is easy for everyone to access it and contribute. This is based on the results of application testing, it was 100% of the functions in the application are running well. Also to find out what factors have the most influence on death in Covid-19 survivors. In addition, the ARSG application involved many people who want to share experiences related to their closest people who were positive for Covid-19 and died.
| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | ID SINTA Dosen Pembimbing: Rani Megasari : 5992674 Yudi Ahmad Hambali : 6745712 |
| Uncontrolled Keywords: | Association Rules, Covid-19, FP-Growth, Look Ahead for Promising Item (LAPI), Survey Generator |
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology L Education > L Education (General) |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Ilmu Komputer |
| Depositing User: | Khamal Fauzan Somantri |
| Date Deposited: | 14 Sep 2022 03:33 |
| Last Modified: | 14 Sep 2022 03:33 |
| URI: | http://repository.upi.edu/id/eprint/80423 |
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