{"id":158,"date":"2021-11-30T00:00:00","date_gmt":"2021-11-30T00:00:00","guid":{"rendered":"https:\/\/majapahit.id\/blog?p=158"},"modified":"2025-09-03T17:37:09","modified_gmt":"2025-09-03T10:37:09","slug":"apa-itu-data-science","status":"publish","type":"post","link":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/","title":{"rendered":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya"},"content":{"rendered":"\r\n<p style=\"line-height: 2;\">Majapahit Teknologi &#8211; Perkembangan&nbsp;teknologi&nbsp;telah merambah luas ke berbagai kegiatan termasuk pada pengolahan data. Sehingga, terbitlah berbagai pekerjaan yang menggambarkan tentang pengolahan data tersebut. Salah satu pekerjaan yang berkecimpung di dunia pengolahan data adalah data science.<\/p><p style=\"line-height: 2;\">Melalui artikel ini akan dijelaskan berbagai penjelasan mengenai apa itu data science yang perlu Anda ketahui.<\/p><div id=\"ez-toc-container\" class=\"ez-toc-v2_0_83 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Daftar Isi<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #383838;color:#383838\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #383838;color:#383838\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Pengertian_Data_Science\" >Pengertian Data Science<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Tujuan_Data_Science\" >Tujuan Data Science<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Manfaat_Data_Science_untuk_Bisnis\" >Manfaat Data Science untuk Bisnis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Jenis_Pembelajaran_Data_Science\" >Jenis Pembelajaran Data Science<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Supervised_Learning_Prediksi\" >Supervised Learning (Prediksi)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Unsupervised_Learning_Deskripsi\" >Unsupervised Learning (Deskripsi)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Reinforced_dan_Deep_Learning_Prediksi\" >Reinforced dan Deep Learning (Prediksi)<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Skill_yang_Dibutuhkan\" >Skill yang Dibutuhkan<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Pemahaman_Bisnis\" >Pemahaman Bisnis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Menganalisis_Data\" >Menganalisis Data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Kemampuan_Pemograman\" >Kemampuan Pemograman<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Kemampuan_Database_Query_dan_Pengolahan_Data\" >Kemampuan Database, Query, dan Pengolahan Data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Kemampuan_Statistik\" >Kemampuan Statistik<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Pilar_Utama_Data_Science\" >Pilar Utama Data Science<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Bisnis\" >Bisnis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Matematika_dan_Statitiska\" >Matematika dan Statitiska<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Teknologi\" >Teknologi<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Langkah_Proses_Data_Science\" >Langkah Proses Data Science<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Obtain\" >Obtain<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Scrub\" >Scrub<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Explore\" >Explore<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Model\" >Model<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Interpret\" >Interpret<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Gaji_Data_Science\" >Gaji Data Science<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#Kesimpulan\" >Kesimpulan<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"pengertian-data-science\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Pengertian_Data_Science\"><\/span>Pengertian Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Data science adalah pekerjaan yang berkecimpung di bidang Analisa data dengan memanfaatkan gabungan ilmu. Adapun ilmu \u2013 ilmu yang terdapat pada data science tersebut adalah ilmu matematika, statitiska, dan ilmu computer.<\/p><p style=\"line-height: 2;\">Pengolahan data oleh data scence tersebut memiliki andil penting suatu perusahaan dalam menentukan sebuah keputusan.<\/p><h2 id=\"tujuan\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Tujuan_Data_Science\"><\/span>Tujuan Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Tujuan yang dimiliki oleh seorang data science adalah menganalisis data dan memberikan informasi dengan tujuan spesifik.<\/p><p style=\"line-height: 2;\">Adapun tujuan spesifik yang dimaksud adalah sebagai berikut:<\/p><ul><li style=\"line-height: 2;\">Deskripsi: Dimana data dideskripsikan untuk menampilkan pola data agar masalah ditemukan secara mudah.<\/li><li style=\"line-height: 2;\">Prediksi: Dimana informasi yang didapatkan akan diprediksikan nilainya yang selanjutnya hasilnya menjadi rekomendasi pengambilan keputusan sebuah perusahaan.<\/li><\/ul><h2 id=\"manfaat\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Manfaat_Data_Science_untuk_Bisnis\"><\/span>Manfaat Data Science untuk Bisnis<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Terdapat sejumlah manfaat dari data science yang bertujuan untuk mempermudah dunia bisnis. Adapun manfaat yang dimaksud tersebut adalah sebagai berikut:<\/p><p style=\"line-height: 2;\">Memudahkan bisnis untuk berkembang, sebab dari data yang ditemukan dapat diputuskan keadaan bisnis sekarang dan kemungkinan bisnis kedepannya.<\/p><p style=\"line-height: 2;\">Dapat mengamati masalah apa yang terdapat pada suatu bisnis, sehingga dapat menyelesaikannya dengan cepat dan tepat.<\/p><h2 id=\"jenis\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Jenis_Pembelajaran_Data_Science\"><\/span>Jenis Pembelajaran Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Terdapat jenis \u2013 jenis pembelajaran data science yang dilakukan untuk meningkatkan kemampuan.<\/p><p style=\"line-height: 2;\">Adapun jenis \u2013 jenis pembelajaran data science tersebut adalah sebagai berikut:<\/p><h3 style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Supervised_Learning_Prediksi\"><\/span>Supervised Learning (Prediksi)<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Supervised learning ini memungkinkan terjadinya training dan data fakta (labelled training).<\/p><p style=\"line-height: 2;\">Dimana, sistem yang akan ditraining tersebut akan membentuk pola data yang kemudian digunakan untuk memprediksi keputusan yang tepat pada sebuah perusahaan.<\/p><h3 id=\"unsupervised\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Unsupervised_Learning_Deskripsi\"><\/span>Unsupervised Learning (Deskripsi)<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Pembelajaran selanjutnya dalam data science dinamakan dengan unsupervised learning. Dimana, pembelajaran ini tidak membutuhkan training sehingga pembentukan pola datanya tidak bersifat prediksi tetapi deskripsi.<\/p><h3 id=\"Reinforced\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Reinforced_dan_Deep_Learning_Prediksi\"><\/span>Reinforced dan Deep Learning (Prediksi)<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Reinforced dan Deep Learning dilakukan secara berulang \u2013 ulang memanfaatkan algoritma neural.<\/p><p style=\"line-height: 2;\">Hasil yang didapatkan dari jenis pembelajaran ini hampir sama dengan supervised learning yaitu berupa prediksi, atau dikenal dengan sebutan sistem coba \u2013 coba (trial and error) hingga mendapatkan hasil yang optimal.<\/p><p style=\"line-height: 2;\"><img decoding=\"async\" src=\"data:image\/jpeg;base64,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\" data-filename=\"Pengertian Data Science.jpg\" style=\"width: 100%;\"><br><\/p><h2 id=\"skill\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Skill_yang_Dibutuhkan\"><\/span>Skill yang Dibutuhkan<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Beberapa skill ini kerap dibutuhkan untuk dapat melahirkan seorang data science yang sukses dan cerdas. Adapun skill \u2013 skill yang dibutuhkan tersebut adalah:<\/p><h3 id=\"pemahaman\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Pemahaman_Bisnis\"><\/span>Pemahaman Bisnis<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Skill pertama yang dibutuhkan oleh seorang data science adalah pemahaman bisnis.<\/p><p style=\"line-height: 2;\">Sebab, dari data \u2013 data yang ditampilkan tentu saja akan berkecimpung pada dunia bisnis yang selanjutnya membutuhkan rekomendasi solusi dari data yang ditampilkan.<\/p><h3 id=\"menganalis\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Menganalisis_Data\"><\/span>Menganalisis Data<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Tentu saja skill selanjutnya yang dibutuhkan oleh seorang data science adalah menganalisis data.<\/p><p style=\"line-height: 2;\">Hal ini disebabkan oleh pekerjaan utama seorang data science adalah menganalisis data dan memproses data tersebut agar dapat digunakan sesuai dengan tujuannya masing \u2013 masing.<\/p><h3 id=\"kemampuan-program\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Kemampuan_Pemograman\"><\/span>Kemampuan Pemograman<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Sebab dari aplikasi \u2013 aplikasi yang digunakan oleh data science cukup kompleks, sehingga seorang data science sangat diwajibkan memiliki kemampuan mendalam mengenai pemograman.<\/p><p style=\"line-height: 2;\">Hal ini tentu saja mempermudah aksi pekerjaan data science tersebut.<\/p><h3 id=\"kemampuan-database\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Kemampuan_Database_Query_dan_Pengolahan_Data\"><\/span>Kemampuan Database, Query, dan Pengolahan Data<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Kemampuan mengelola database, queory, dan melakukan pengolahan data tersebut wajib dimiliki oleh seorang data science. Sebab, posisi tersebut akan sering bertemu dengan berbagai komponen ini.<\/p><h3 id=\"kemapuan-stastik\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Kemampuan_Statistik\"><\/span>Kemampuan Statistik<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Kemampuan statistic adalah kemampuan dasar yang diperlukan oleh data science agar dapat melakukan pengolahan data. Sebab, data science tidak akan jauh dari komponen awalnya yaitu matematika, statistic, dan ilmu computer.<\/p><h2 id=\"pilar\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Pilar_Utama_Data_Science\"><\/span>Pilar Utama Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Data science memiliki beberapa pilar utama yang wajib Anda pahami dengan baik. Adapun pilar \u2013 pilar utama data science yang dimaksud tersebut adalah sebagai berikut:<\/p><h3 id=\"bisnis\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Bisnis\"><\/span>Bisnis<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Bisnis dijadikan sebagai pilar utama data science sebab bisnis tidak akan jauh dari penggunaan data science.<\/p><p style=\"line-height: 2;\">Apa yang terjadi pada suatu bisnis, seperti masalah, keuntungan, perkembangan, penurunan, peningkatan, dan berbagai hal lainnya akan tercermin melalui data science.<\/p><p style=\"line-height: 2;\">Oleh sebab itu, bisnis menjadi pilar utama kehadiran data science agar dapat digunakan dalam mengatasi problematikan tersebut.<\/p><p style=\"line-height: 2;\">Data \u2013 data yang digambarkan melalui data science tersebut tentunya akan membantu perkembangan bisnis menjadi lebih baik. Sehingga, sangat disarankan pengolahan data science tersebut harus dilakukan secara baik.<\/p><h3 id=\"matematika\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Matematika_dan_Statitiska\"><\/span>Matematika dan Statitiska<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Matematika dan statitiskan tentu saja tidak menjadi hal yang dilewatkan dalam data science.<\/p><p style=\"line-height: 2;\">Sebab, pengolahan data menggunakan data science tersebut tidak akan terlepas dari kehadiran matematika dan statitiska.<\/p><p style=\"line-height: 2;\">Oleh sebab itu, pemahaman mengenai matematika dan statitiska harus dimiliki oleh seorang data scientist.<\/p><p style=\"line-height: 2;\">Selain itu, komponen dari matematika dan statitiska kiat menjadi solusi dari pengolahan data tersebut.<\/p><p style=\"line-height: 2;\">Sehingga visualisasi masalah berserta rekomendasi solusinya akan tergambar secara jelas apabila data science dapat mengolah kedua ilmu tersebut dengan baik.<\/p><h3 id=\"teknologi\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Teknologi\"><\/span>Teknologi<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Seperti namanya, tentu saja data science ini tidak akan terlepas dari yang namanya teknologi.<\/p><p style=\"line-height: 2;\">Sehingga, tidak perlu dipungkiri bahwa kehadiran data science harus dibarengi dengan teknologi agar hasilnya baik dan terarah secara tepat. Selain itu, aplikasi \u2013 aplikasi dari data science tentu saja memanfaatkan kehadiran teknologi.<\/p><h2 id=\"langkah\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Langkah_Proses_Data_Science\"><\/span>Langkah Proses Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><div class=\"wp-block-image\" style=\"line-height: 2;\"><figure class=\"aligncenter size-full\"><\/figure><\/div><p style=\"line-height: 2;\"><span style=\"font-weight: 600;\">Baca:&nbsp;<\/span><a href=\"https:\/\/majapahit.id\/blog\/2021\/11\/19\/big-data-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\">Big Data Analytics Tools<\/a>&nbsp;Terbaik | Sesuai Kebutuhan Bisnis Anda !<\/p><p style=\"line-height: 2;\">Terdapat sejumlah langkah proses data science yang wajib Anda ketahui. Adapun langkah \u2013 langkah proses data science tersebut adalah:<\/p><h3 id=\"obtain\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Obtain\"><\/span>Obtain<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Obtain memiliki artian berupa proses pengumpulan data atau informasi yang selanjutnya akan diproses menggunakan MySQL atau software \u2013 software pengolah data lainnya.<\/p><h3 id=\"scrub\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Scrub\"><\/span>Scrub<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Proses scrub ini dilakukan tepat setelah obtain, dimana data \u2013 data yang telah dikumpulkan dari berbagai sumber akan difilter dan diseleksi berdasarkan kegunaannya masing \u2013 masing.<\/p><h3 id=\"explore\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Explore\"><\/span>Explore<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Setelah proses scrub tersebut, maka dilakukan analisis lebih lanjut mengenai data yang telah diperoleh.<\/p><p style=\"line-height: 2;\">Data \u2013 data akan diproses, diperiksa, dan divisualisasikan dalam berbagai bentuk agar intisari dari data tersebut dapat tersampaikan dengan jelas.<\/p><h3 id=\"model\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Model\"><\/span>Model<span class=\"ez-toc-section-end\"><\/span><\/h3><p style=\"line-height: 2;\">Model merupakan kegiatan memprediksikan nilai pada waktu mendatang yang didapat dari proses exploring data dengan metode regresi. Dengan model, tentu saja dapat ditemukan status bisnis apakah berkembang atau tidak.<\/p><h2 id=\"interpret\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Interpret\"><\/span>Interpret<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Langkah terakhir yang dilakukan dalam proses data science adalah interpret. Dimana, pada interpret ini merupakan tahapan interpretasi data untuk menyampaikan intisari yang didapat dari pengolahan data tersebut.<\/p><h2 id=\"gaji\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Gaji_Data_Science\"><\/span>Gaji Data Science<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Dengan ilmu, skil, dan job deskripsi yang cukup rumit tentu saja data scientist ini tidak sembarangan dalam memberikan tarif.<\/p><p style=\"line-height: 2;\">Dimana, posisi data scientist ini memiliki besaran bayaran mulai dari 7,5 \u2013 90 juta perbulannya. Sangat menggiurkan tentunya?<\/p><h2 id=\"kesimpulan\" style=\"line-height: 2;\"><span class=\"ez-toc-section\" id=\"Kesimpulan\"><\/span>Kesimpulan<span class=\"ez-toc-section-end\"><\/span><\/h2><p style=\"line-height: 2;\">Dari berbagai informasi di atas tentu saja Anda semakin paham mengenai apa itu data science, baik dari pengertian, tujuan, hingga gajinya yang sangat menggiurkan.<\/p><p style=\"line-height: 2;\">Tentunya dengan memahami penjelasan di atas Anda bisa menentukan bahkan menggiurkan mengenai keinginan menjadi seorang data scientist tersebut!<\/p>\r\n","protected":false},"excerpt":{"rendered":"<p>Majapahit Teknologi &#8211; Perkembangan&nbsp;teknologi&nbsp;telah merambah luas ke berbagai kegiatan termasuk  [&#8230;]<\/p>\n","protected":false},"author":7,"featured_media":100158,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1325,1326],"tags":[1170],"class_list":["post-158","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-otomatisasi","category-teknologi-bisnis","tag-apa-itu-data-science"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya<\/title>\n<meta name=\"description\" content=\"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya\" \/>\n<meta property=\"og:description\" content=\"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik\" \/>\n<meta property=\"og:url\" content=\"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog &amp; Berita - Majapahit Teknologi\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/facebook.com\/majapahit.id\" \/>\n<meta property=\"article:published_time\" content=\"2021-11-30T00:00:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-09-03T10:37:09+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1\" \/>\n\t<meta property=\"og:image:height\" content=\"1\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Paradita Umbara\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Paradita Umbara\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/\"},\"author\":{\"name\":\"Paradita Umbara\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#\\\/schema\\\/person\\\/23b57e756ad75e89690097bdf1872192\"},\"headline\":\"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya\",\"datePublished\":\"2021-11-30T00:00:00+00:00\",\"dateModified\":\"2025-09-03T10:37:09+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/\"},\"wordCount\":1044,\"publisher\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2021\\\/12\\\/Data-Science.jpg\",\"keywords\":[\"apa itu data science\"],\"articleSection\":[\"AI &amp; Otomatisasi\",\"Teknologi Bisnis\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/\",\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/\",\"name\":\"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2021\\\/12\\\/Data-Science.jpg\",\"datePublished\":\"2021-11-30T00:00:00+00:00\",\"dateModified\":\"2025-09-03T10:37:09+00:00\",\"description\":\"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#primaryimage\",\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2021\\\/12\\\/Data-Science.jpg\",\"contentUrl\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2021\\\/12\\\/Data-Science.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/2021\\\/11\\\/30\\\/apa-itu-data-science\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"AI &amp; Otomatisasi\",\"item\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/category\\\/ai-otomatisasi\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#website\",\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/\",\"name\":\"Berita & Blog Perkembangan Teknologi Terkini\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#organization\"},\"alternateName\":\"Majapahit Teknologi\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#organization\",\"name\":\"Majapahit Teknologi\",\"alternateName\":\"PT Majapahit Teknologi Nusantara\",\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2025\\\/05\\\/only-logo.png\",\"contentUrl\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/wp-content\\\/uploads\\\/2025\\\/05\\\/only-logo.png\",\"width\":1500,\"height\":1500,\"caption\":\"Majapahit Teknologi\"},\"image\":{\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#\\\/schema\\\/logo\\\/image\\\/\"},\"sameAs\":[\"https:\\\/\\\/facebook.com\\\/majapahit.id\",\"https:\\\/\\\/instagram.com\\\/majapahit.id\"]},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/#\\\/schema\\\/person\\\/23b57e756ad75e89690097bdf1872192\",\"name\":\"Paradita Umbara\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g\",\"caption\":\"Paradita Umbara\"},\"url\":\"https:\\\/\\\/majapahit.id\\\/blog\\\/author\\\/umbara\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya","description":"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/","og_locale":"en_US","og_type":"article","og_title":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya","og_description":"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik","og_url":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/","og_site_name":"Blog &amp; Berita - Majapahit Teknologi","article_publisher":"https:\/\/facebook.com\/majapahit.id","article_published_time":"2021-11-30T00:00:00+00:00","article_modified_time":"2025-09-03T10:37:09+00:00","og_image":[{"url":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg","width":1,"height":1,"type":"image\/jpeg"}],"author":"Paradita Umbara","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Paradita Umbara","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#article","isPartOf":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/"},"author":{"name":"Paradita Umbara","@id":"https:\/\/majapahit.id\/blog\/#\/schema\/person\/23b57e756ad75e89690097bdf1872192"},"headline":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya","datePublished":"2021-11-30T00:00:00+00:00","dateModified":"2025-09-03T10:37:09+00:00","mainEntityOfPage":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/"},"wordCount":1044,"publisher":{"@id":"https:\/\/majapahit.id\/blog\/#organization"},"image":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#primaryimage"},"thumbnailUrl":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg","keywords":["apa itu data science"],"articleSection":["AI &amp; Otomatisasi","Teknologi Bisnis"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/","url":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/","name":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya","isPartOf":{"@id":"https:\/\/majapahit.id\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#primaryimage"},"image":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#primaryimage"},"thumbnailUrl":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg","datePublished":"2021-11-30T00:00:00+00:00","dateModified":"2025-09-03T10:37:09+00:00","description":"Pahami segera apa itu data science yang bisa membantu Anda untuk menganalisa data yang bisa digunakan untuk proses bisnis yang baik","breadcrumb":{"@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#primaryimage","url":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg","contentUrl":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2021\/12\/Data-Science.jpg"},{"@type":"BreadcrumbList","@id":"https:\/\/majapahit.id\/blog\/2021\/11\/30\/apa-itu-data-science\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/majapahit.id\/blog\/"},{"@type":"ListItem","position":2,"name":"AI &amp; Otomatisasi","item":"https:\/\/majapahit.id\/blog\/category\/ai-otomatisasi\/"},{"@type":"ListItem","position":3,"name":"Apa Itu Data Science : Pengertian, Tujuan, Langkah Prosesnya"}]},{"@type":"WebSite","@id":"https:\/\/majapahit.id\/blog\/#website","url":"https:\/\/majapahit.id\/blog\/","name":"Berita & Blog Perkembangan Teknologi Terkini","description":"","publisher":{"@id":"https:\/\/majapahit.id\/blog\/#organization"},"alternateName":"Majapahit Teknologi","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/majapahit.id\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/majapahit.id\/blog\/#organization","name":"Majapahit Teknologi","alternateName":"PT Majapahit Teknologi Nusantara","url":"https:\/\/majapahit.id\/blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/majapahit.id\/blog\/#\/schema\/logo\/image\/","url":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2025\/05\/only-logo.png","contentUrl":"https:\/\/majapahit.id\/blog\/wp-content\/uploads\/2025\/05\/only-logo.png","width":1500,"height":1500,"caption":"Majapahit Teknologi"},"image":{"@id":"https:\/\/majapahit.id\/blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/facebook.com\/majapahit.id","https:\/\/instagram.com\/majapahit.id"]},{"@type":"Person","@id":"https:\/\/majapahit.id\/blog\/#\/schema\/person\/23b57e756ad75e89690097bdf1872192","name":"Paradita Umbara","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/b587321a687e2f98a58b867b630f6b76f25f064a08ca60d1fe9e83eb302f2d04?s=96&d=mm&r=g","caption":"Paradita Umbara"},"url":"https:\/\/majapahit.id\/blog\/author\/umbara\/"}]}},"_links":{"self":[{"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/posts\/158","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/comments?post=158"}],"version-history":[{"count":1,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/posts\/158\/revisions"}],"predecessor-version":[{"id":100673,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/posts\/158\/revisions\/100673"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/media\/100158"}],"wp:attachment":[{"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/media?parent=158"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/categories?post=158"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/majapahit.id\/blog\/wp-json\/wp\/v2\/tags?post=158"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}