KKHOSASIH, ADAM MAULANA (2021) ANALISIS PERBANDINGAN ALGORITMA CLUSTERING DBSCAN DENGAN SNN UNTUK PEMETAAN DAERAH PENYEBARAN COVID19 DI DKI JAKARTA. S1 thesis, Universitas Mercu Buana Jakarta.
|
Text (HAL COVER)
01 COVER.pdf Download (1MB) | Preview |
|
![[img]](https://repository.mercubuana.ac.id/style/images/fileicons/text.png) |
Text (BAB I)
02 BAB 1.pdf Restricted to Registered users only Download (125kB) |
|
|
Text (BAB II)
03 BAB 2.pdf Restricted to Registered users only Download (116kB) |
|
|
Text (BAB III)
04 BAB 3.pdf Restricted to Registered users only Download (50kB) |
|
|
Text (BAB IV)
05 BAB 4.pdf Restricted to Registered users only Download (167kB) |
|
|
Text (BAB V)
06 BAB 5.pdf Restricted to Registered users only Download (108kB) |
|
|
Text (DAFTAR PUSTAKA)
07 DAFTAR PUSTAKA.pdf Restricted to Registered users only Download (168kB) |
|
|
Text (LAMPIRAN)
08 LAMPIRAN.pdf Restricted to Registered users only Download (276kB) |
Abstract
Covid-19 is a disease that attacks the respiratory tract, causing high fever, cough, flu, shortness of breath and sore throat. With the increasingly widespread spread of Covid-19 in various regions, especially in the DKI Jakarta Province, this has led to the issuance of a Large-Scale Social Restriction (PSBB) policy in each region. To prevent the spread of COVID-19, especially in the DKI Jakarta Province, mapping the causes of COVID-19 is needed. The purpose of this study is to compare the DBSCAN clustering algorithm with Shared Nearest Neighbor in identifying the area of the spread of COVID-19 in DKI Jakarta Province. From the two algorithms, it can be concluded that the DBSCAN Algorithm can be better used to map the area of the spread of COVID-19 in DKI Jakarta Province, with validation results using the Dunn Index of 0.99, while the SNN is 0.95. The results of profiling the spread of COVID-19 in the DKI Jakarta Province area were obtained from the DBSCAN Algorithm with 2 clusters, namely vurnerable and alert clusters. Key words: Covid-19, Clustering, DBSCAN, SNN Covid-19 merupakan penyakit yang menyerang saluran pernafasan sehingga menyebabkan demam tinggi, batuk, flu, sesak nafas serta nyeri tenggorokan. Dengan semakin meluasnya penyebaran Covid-19 di berbagai wilayah, khususnya di wilayah Provinsi DKI Jakarta, menyebabkan keluarnya kebijakan Pembatasan Sosial Berskala Besar (PSBB) di setiap wilayahnya. Untuk mencegah penyebaran COVID-19, khususnya diwilayah Provinsi DKI Jakarta, dibutuhkanya pemetaan penyebarah COVID-19. Tujuan dari penelitian ini adalah untuk membandingkan antara Algoritma clustering DBSCAN dengan Shared Nearest Neighbor dalam mengidentifikasi area penyebaran COVID-19 di Provinsi DKI Jakarta. Dari kedua algoritma tersebut dapat disimpulkan bahwa Algoritma DBSCAN dapat lebih baik digunakan untuk memetakan daerah penyebaran COVID-19 di Provinsi DKI Jakarta, dengan hasil validasi menggunakan Dunn Index sebesar 0,99, sedangkan SNN sebesar 0,95. Hasil profiling penyebaran COVID-19 di wilayah Provinsi DKI Jakarta yang didapat dari Algoritma DBSCAN dengan jumlah cluster sebanyak 2 yaitu, cluster rawan dan waspada. Kata kunci: Covid-19, Clustering, DBSCAN, SNN
| Item Type: | Thesis (S1) |
|---|---|
| NIM/NIDN Creators: | 41517010099 |
| Uncontrolled Keywords: | Covid-19, Clustering, DBSCAN, SNN |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | ASHAIDAH AZLYA PUTRI |
| Date Deposited: | 11 Oct 2023 07:02 |
| Last Modified: | 11 Oct 2023 07:02 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/82337 |
Actions (login required)
 |
View Item |
