{"id":2913,"date":"2023-07-20T03:12:14","date_gmt":"2023-07-20T03:12:14","guid":{"rendered":"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/"},"modified":"2023-07-20T03:12:14","modified_gmt":"2023-07-20T03:12:14","slug":"pencocokan-fuzzy-di-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/","title":{"rendered":"Cara melakukan pencocokan fuzzy di r (dengan contoh)"},"content":{"rendered":"

<\/p>\n

\n

Seringkali Anda mungkin ingin menggabungkan dua kumpulan data di R berdasarkan string yang tidak cocok secara sempurna. Hal ini kadang-kadang disebut pencocokan fuzzy<\/strong> .<\/span><\/p>\n

Cara termudah untuk melakukan pencocokan fuzzy di R adalah dengan menggunakan fungsi stringdist_join()<\/strong> dari paket fuzzyjoin<\/strong> .<\/span><\/p>\n

Contoh berikut menunjukkan cara menggunakan fungsi ini dalam praktiknya.<\/span><\/p>\n

Contoh: pencocokan fuzzy di R<\/strong><\/span><\/h3>\n

Misalkan kita memiliki dua bingkai data berikut di R yang berisi informasi tentang berbagai tim bola basket:<\/span><\/span><\/p>\n

 #create data frames<\/span>\ndf1 <- data. frame<\/span> (team=c('Mavericks', 'Nets', 'Warriors', 'Heat', 'Lakers'),\n                  points=c(99, 90, 104, 117, 100))\ndf2 <- data. frame<\/span> (team=c('Mavricks', 'Warrors', 'Heat', 'Netts', 'Kings', 'Lakes'),\n                  assists=c(22, 29, 17, 40, 32, 30))\n\n#view data frames\n<\/span>print<\/span> (df1)\n\n       team points\n1 Mavericks 99\n2 Nets 90\n3 Warriors 104\n4 Heat 117\n5 Lakers 100\n\nprint<\/span> (df2)\n\n      team assists\n1 Mavricks 22\n2 Warriors 29\n3 Heat 17\n4 Netts 40\n5 Kings 32\n6 Lakes 30\n<\/strong><\/pre>\n
 Sekarang katakanlah kita ingin melakukan penggabungan kiri<\/strong> di mana kita menyimpan semua baris dari bingkai data pertama dan menggabungkannya berdasarkan nama tim yang paling cocok dengan bingkai data kedua.<\/span><\/p>\n
 Kita dapat menggunakan kode berikut untuk melakukan ini:<\/span><\/p>\n
 library<\/span> (fuzzyjoin)\nlibrary<\/span> (dplyr)\n\n#perform fuzzy matching left join\n<\/span>stringdist_join(df1, df2, \n                by=' team<\/span> ', #match based on team<\/span>\n                mode=' left<\/span> ', #use left join<\/span>\n                method = \" jw<\/span> \", #use jw distance metric<\/span>\n                max_dist=99, \n                distance_col=' dist<\/span> ') %>%\n  group_by(team.x) %>%\n  slice_min(order_by=dist, n= 1<\/span> )\n\n# A tibble: 5 x 5\n# Groups: team.x [5]\n  team.x points team.y assists dist\n                 \n1 Heat 117 Heat 17 0     \n2 Lakers 100 Lakes 30 0.0556\n3 Mavericks 99 Mavricks 22 0.0370\n4 Nets 90 Nets 40 0.0667\n5 Warriors 104 Warriors 29 0.0417\n<\/strong><\/span><\/pre>\n
 Hasilnya adalah bingkai data yang berisi masing-masing dari lima nama tim asli dari bingkai data pertama serta tim yang paling cocok dengan bingkai data kedua.<\/span><\/p>\n
 Catatan #1<\/strong> : Kami memilih untuk menggunakan metrik jarak jw<\/strong> untuk pencocokan. Ini adalah kependekan dari jarak Jaro-Winkler<\/a> , yang merupakan metrik yang mengukur perbedaan antara dua string.<\/span><\/p>\n
 Catatan #2:<\/strong> Kami menggunakan fungsi slice_min()<\/strong> dari paket dplyr untuk hanya menampilkan nama tim dari bingkai data kedua yang paling cocok dengan nama tim dari bingkai data pertama.<\/span><\/p>\n
 Sumber daya tambahan<\/strong><\/span><\/h3>\n
 Tutorial berikut menjelaskan cara melakukan tugas umum lainnya di R:<\/span><\/p>\n
 Cara menggabungkan beberapa frame data di R<\/a>
 Cara menggabungkan bingkai data berdasarkan beberapa kolom di R<\/p>\n","protected":false},"excerpt":{"rendered":"
Seringkali Anda mungkin ingin menggabungkan dua kumpulan data di R berdasarkan string yang tidak cocok secara sempurna. Hal ini kadang-kadang disebut pencocokan fuzzy . Cara termudah untuk melakukan pencocokan fuzzy di R adalah dengan menggunakan fungsi stringdist_join() dari paket fuzzyjoin . Contoh berikut menunjukkan cara menggunakan fungsi ini dalam praktiknya. Contoh: pencocokan fuzzy di R […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"\nCara Melakukan Pencocokan Fuzzy di R (dengan Contoh) - Statorial<\/title>\n<meta name=\"description\" content=\"Tutorial ini menjelaskan cara melakukan pencocokan fuzzy antara dua dataset di R, dengan sebuah contoh.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cara Melakukan Pencocokan Fuzzy di R (dengan Contoh) - Statorial\" \/>\n<meta property=\"og:description\" content=\"Tutorial ini menjelaskan cara melakukan pencocokan fuzzy antara dua dataset di R, dengan sebuah contoh.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-20T03:12:14+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Ditulis oleh\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimasi waktu membaca\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 menit\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/\",\"url\":\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/\",\"name\":\"Cara Melakukan Pencocokan Fuzzy di R (dengan Contoh) - Statorial\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-20T03:12:14+00:00\",\"dateModified\":\"2023-07-20T03:12:14+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Tutorial ini menjelaskan cara melakukan pencocokan fuzzy antara dua dataset di R, dengan sebuah contoh.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/pencocokan-fuzzy-di-r\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Cara melakukan pencocokan fuzzy di r (dengan contoh)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/id\/#website\",\"url\":\"https:\/\/statorials.org\/id\/\",\"name\":\"Statorials\",\"description\":\"Panduan anda untuk kompetensi statistik!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/id\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"id\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"id\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/image\/\",\"url\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Halo, saya Benjamin, pensiunan profesor statistika yang menjadi guru Statorial yang berdedikasi. 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