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Database ```sakila``` merupakan sample dummy database yang menyimpan informasi seputar toko rental DVD.\n\n*__Soal :__* Aktifkan server MySQL Anda, lalu gunakan database ```sakila``` dan tuliskan langkah-langkah/query MySQL untuk menyelesaikan perintah berikut. Anda dilarang membuat database baru, merubah struktur table, membuat view atau segala bentuk tindakan yang mengubah struktur database.\n\n1. Tampilkan daftar __10 film komedi dengan durasi tersingkat__. Urutkan data berdasarkan film dengan durasi terpendek. Kolom yang diwajibkan tampil adalah __title__, __category__ dan __length__. Output yang diharapkan:\n\n    ```bash\n    +------------------+----------+--------+\n    | title            | category | length |\n    +------------------+----------+--------+\n    | DOWNHILL ENOUGH  | Comedy   |     47 |\n    | HEAVEN FREEDOM   | Comedy   |     48 |\n    | PARADISE SABRINA | Comedy   |     48 |\n    | HURRICANE AFFAIR | Comedy   |     49 |\n    | LION UNCUT       | Comedy   |     50 |\n    | ZORRO ARK        | Comedy   |     50 |\n    | CLOSER BANG      | Comedy   |     58 |\n    | AIRPLANE SIERRA  | Comedy   |     62 |\n    | LONELY ELEPHANT  | Comedy   |     67 |\n    | DOOM DANCING     | Comedy   |     68 |\n    +------------------+----------+--------+\n    ```\n\n2. Tampilkan daftar lengkap __kategori film beserta jumlah film tiap kategori \u0026 rata-rata harga sewa DVD film tiap kategori__. Urutkan data dari kategori dengan jumlah film terbanyak. Kolom yang diwajibkan ada minimal adalah __kategori__, __jumlah film__ dan __rata-rata harga sewa__. Output yang diharapkan:\n\n    ```bash\n    +-------------+-------------+---------------+\n    | kategori    | jumlahMovie | rataHargaSewa |\n    +-------------+-------------+---------------+\n    | Foreign     |          73 |      3.099589 |\n    | Sports      |          73 |      3.099589 |\n    | Family      |          69 |      2.758116 |\n    | Documentary |          68 |      2.666471 |\n    | Animation   |          66 |      2.808182 |\n    | Action      |          64 |      2.646250 |\n    | New         |          63 |      3.116984 |\n    | Drama       |          61 |      2.990000 |\n    | Games       |          61 |      3.252295 |\n    | Sci-Fi      |          61 |      3.219508 |\n    | Children    |          60 |      2.890000 |\n    | Comedy      |          58 |      3.162414 |\n    | Classics    |          57 |      2.744386 |\n    | Horror      |          56 |      3.025714 |\n    | Travel      |          56 |      3.275714 |\n    | Music       |          51 |      2.950784 |\n    +-------------+-------------+---------------+\n    ```\n\n3. [Motion Picture Association of America](https://en.wikipedia.org/wiki/Motion_Picture_Association_of_America_film_rating_system) memiliki sistem rating untuk film berdasarkan konten \u0026 target penontonnya dengan klasifikasi sebagai berikut:\n\n    - **G** : General Audiences\n    - **PG** : Parental Guidance Suggested\n    - **PG-13** : Parental Guidances for Children Under 13\n    - **R** : Restricted\n    - **NC-17** : No Children Under 17 Admitted\n\n    Tampilkan daftar lengkap __rating film beserta keterangan arti rating \u0026 jumlah film tiap rating__. Kolom yang diwajibkan ada minimal adalah __rating__, __keterangan rating__ dan __jumlah film__. Output yang diharapkan:\n\n    ```bash\n    +--------+---------------------------------+--------------+\n    | rating | keterangan                      | jumlahMovie  |\n    +--------+---------------------------------+--------------+\n    | G      | General Audiences               |          178 |\n    | PG     | Parental Guidance Suggested     |          194 |\n    | PG-13  | Parental Guidances for Under 13 |          223 |\n    | R      | Restricted                      |          195 |\n    | NC-17  | No Children Under 17 Admitted   |          210 |\n    +--------+---------------------------------+--------------+\n    ```\n\n4. Tampilkan daftar __10 aktor/aktris yang paling banyak membintangi film__. Kolom yang ditampilkan minimal: __id aktor__, __nama depan__, __nama belakang__ dan __jumlah film yang dibintangi__ kemudian urutkan dari aktor/aktris yang membintangi film terbanyak. Output yang diharapkan:\n\n    ```bash\n    +----------+------------+-------------+--------------+\n    | actor_id | first_name | last_name   | jumlah_Movie |\n    +----------+------------+-------------+--------------+\n    |      107 | GINA       | DEGENERES   |           42 |\n    |      102 | WALTER     | TORN        |           41 |\n    |      198 | MARY       | KEITEL      |           40 |\n    |      181 | MATTHEW    | CARREY      |           39 |\n    |       23 | SANDRA     | KILMER      |           37 |\n    |       81 | SCARLETT   | DAMON       |           36 |\n    |      158 | VIVIEN     | BASINGER    |           35 |\n    |      144 | ANGELA     | WITHERSPOON |           35 |\n    |      106 | GROUCHO    | DUNST       |           35 |\n    |       60 | HENRY      | BERRY       |           35 |\n    +----------+------------+-------------+--------------+\n    ```\n\n5. Dari soal sebelumnya diketahui ```Gina Degeneres``` merupakan aktris yang paling banyak membintangi film, dengan total **42** judul film. Kategori film apakah yang paling banyak dibintanginya? Untuk mengetahuinya, tampilkan daftar __kategori film beserta jumlah film yang pernah dibintangi oleh ```Gina Degeneres```__. Kolom yang diwajibkan ada yaitu __kategori film__ dan __jumlah film yang dibintangi__. Output yang diharapkan:\n\n    ```bash\n    +-------------+--------------+\n    | category    | jumlah_Movie |\n    +-------------+--------------+\n    | Documentary |            3 |\n    | Foreign     |            2 |\n    | Music       |            4 |\n    | New         |            1 |\n    | Sci-Fi      |            7 |\n    | Action      |            3 |\n    | Drama       |            2 |\n    | Animation   |            4 |\n    | Horror      |            1 |\n    | Family      |            4 |\n    | Comedy      |            3 |\n    | Children    |            2 |\n    | Classics    |            2 |\n    | Sports      |            2 |\n    | Games       |            1 |\n    | Travel      |            1 |\n    +-------------+--------------+\n    ```\n\n6. Dari soal sebelumnya diketahui ```Gina Degeneres``` paling banyak membintangi film bergenre science-fiction, dengan total **7** judul film. Tampilkan daftar __judul film sci-fi yang pernah dibintangi oleh ```Gina Degeneres```__. Kolom yang diwajibkan ada yaitu __judul film__ dan __kategorinya__. Output yang diharapkan:\n\n    ```bash\n    +---------------------+----------+\n    | title               | category |\n    +---------------------+----------+\n    | CHARIOTS CONSPIRACY | Sci-Fi   |\n    | COLDBLOODED DARLING | Sci-Fi   |\n    | FRISCO FORREST      | Sci-Fi   |\n    | GOODFELLAS SALUTE   | Sci-Fi   |\n    | LICENSE WEEKEND     | Sci-Fi   |\n    | OPEN AFRICAN        | Sci-Fi   |\n    | SPIRITED CASUALTIES | Sci-Fi   |\n    +---------------------+----------+\n    ```\n\n7. Tampilkan daftar __10 aktor/aktris yang paling banyak membintangi film horror__. Kolom yang ditampilkan minimal: __id aktor__, __nama depan__, __nama belakang__ dan __jumlah film horror yang dibintangi__ kemudian urutkan dari aktor/aktris yang membintangi film horror terbanyak. Output yang diharapkan:\n\n    ```bash\n    +----------+------------+-----------+--------------+\n    | actor_id | first_name | last_name | jumlah_Movie |\n    +----------+------------+-----------+--------------+\n    |       27 | JULIA      | MCQUEEN   |            7 |\n    |       42 | TOM        | MIRANDA   |            6 |\n    |       60 | HENRY      | BERRY     |            5 |\n    |       14 | VIVIEN     | BERGEN    |            5 |\n    |       94 | KENNETH    | TORN      |            4 |\n    |       75 | BURT       | POSEY     |            4 |\n    |       54 | PENELOPE   | PINKETT   |            4 |\n    |      102 | WALTER     | TORN      |            4 |\n    |       12 | KARL       | BERRY     |            4 |\n    |       40 | JOHNNY     | CAGE      |            4 |\n    +----------+------------+-----------+--------------+\n    ```\n\n8. Dari soal sebelumnya diketahui ```Julia McQueen``` merupakan aktris yang paling banyak membintangi film horror, dengan total **7** judul film. Tampilkan daftar __judul film horror yang pernah dibintangi oleh ```Julia McQueen```__. Kolom yang diwajibkan ada yaitu __judul film__ dan __kategorinya__. Output yang diharapkan:\n\n    ```bash\n    +--------------------+----------+\n    | title              | category |\n    +--------------------+----------+\n    | ARABIA DOGMA       | Horror   |\n    | FREDDY STORM       | Horror   |\n    | HIGH ENCINO        | Horror   |\n    | MONTEREY LABYRINTH | Horror   |\n    | SPIRIT FLINTSTONES | Horror   |\n    | STRANGERS GRAFFITI | Horror   |\n    | TRAIN BUNCH        | Horror   |\n    +--------------------+----------+\n    ```\n\n    ✅ _Lampirkan jawaban berupa daftar query MySQL dalam bentuk file __.txt__ (atau format text file lainnya) dan kirimkan via email ke _lintang@purwadhika.com_!_\n\n#\n\n### **Soal 2 - 👨‍🎓 Kerja Kerja Kerja**\n\nDisediakan sebuah dataset yang berisi daftar profesi beberapa responder, unduh: [profesi.csv](https://raw.githubusercontent.com/LintangWisesa/Ujian_AnalyticsVisualization_JCDS07/master/profesi.csv). Buatlah sebuah file python (__.py__) atau notebook (__.ipynb__) yang dapat menyelesaikan perintah berikut.\n\n1. __Ada berapa jenis profesi yang ada dalam dataset tersebut? Sebutkan!__\n    \n    Output yang diharapkan:\n    \n    ```bash\n    21\n\n    ['technician', 'other', 'writer', 'executive', 'administrator', 'student', 'lawyer', 'educator', 'scientist', 'entertainment', 'programmer', 'librarian', 'homemaker', 'artist', 'engineer', 'marketing', 'none', 'healthcare', 'retired', 'salesman', 'doctor']\n    ```\n\n2. __Buatlah sebuah dataframe yang menunjukkan data usia maksimal, minimal \u0026 rata-ratanya, kemudian dikelompokkan berdasarkan profesi \u0026 gender!__\n\n    Output yang diharapkan:\n\n    \u003cimg src='./soal2b.png' width='40%' height='40%'\u003e\n\n3. __Buatlah sebuah dataframe yang menunjukkan persentase pria \u0026 wanita tiap profesi!__\n\n    Output yang diharapkan:\n\n    \u003cimg src='./soal2c.png' width='40%' height='40%'\u003e\n\n✅ *Commit \u0026 push source code jawaban soal ini ke __Github__ Anda, buatlah repo dengan nama __Daftar_Profesi__, kemudian lampirkan __url link repo Github__ Anda via email ke _lintang@purwadhika.com!_*\n\n#\n\n### **Soal 3 - 🏋‍♂ SEA Games 2019**\n\n![seagames](./seagames.png)\n\nIndonesia mengakhiri SEA Games 2019 di posisi ke-empat. Total, atlet-atlet Tanah Air sukses mengumpulkan 267 medali, dengan rincian 72 emas, 84 perak, dan 111 perunggu selama perhelatan ajang multi-event olahraga se-Asia Tenggara tersebut, sejak 30 November-11 Desember 2019. Panitia SEA Games Filipina 2019 mempublikasikan daftar peserta \u0026 perolehan medali di situs resmi: [www2.2019seagames.com](https://www2.2019seagames.com/).\n\n- [Data peserta \u0026 perolehan medali SEA Games Malaysia 2017](https://www2.2019seagames.com/countries/)\n- [Data peserta \u0026 perolehan medali SEA Games Filipina 2019](https://www2.2019seagames.com/medals/)\n\nGunakanlah teknik _web scraping_ pada situs di atas untuk mendapatkan data lengkap perolehan medali SEA Games 2017 \u0026 2019. Kemudian buatlah sebuah file python (__.py__) atau notebook (__.ipynb__) yang dapat memvisualisasikan data __total raihan medali emas__ beserta __persentase raihan medali emas__ tiap Negara pada SEA Games 2017 \u0026 2019. Contoh output yang diharapkan:\n\n- Total raihan medali emas SEA Games 2017 \u0026 2019. Berikan marker khusus pada Negara dengan raihan medali emas terbanyak.\n\n    ![](./seagames_line.png)\n\n- Persentase raihan medali emas SEA Games 2017 \u0026 2019. Tampilkan nilai persentase pada diagram lingkaran.\n\n    ![](./seagames_pie.png)\n\n✅ *Commit \u0026 push source code jawaban soal ini ke __Github__ Anda, buatlah repo dengan nama __SEA_Games__, kemudian lampirkan __url link repo Github__ Anda via email ke _lintang@purwadhika.com!_*\n\n#\n\n### *__#HappyCoding__* :relaxed:\n\n#### Lintang Wisesa :love_letter: _lintangwisesa@ymail.com_\n\n[Facebook](https://www.facebook.com/lintangbagus) | \n[Twitter](https://twitter.com/Lintang_Wisesa) |\n[Google+](https://plus.google.com/u/0/+LintangWisesa1) |\n[Youtube](https://www.youtube.com/user/lintangbagus) | \n:octocat: [GitHub](https://github.com/LintangWisesa) |\n[Hackster](https://www.hackster.io/lintangwisesa)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flintangwisesa%2Fujian_analyticsvisualization_jcds07","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flintangwisesa%2Fujian_analyticsvisualization_jcds07","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flintangwisesa%2Fujian_analyticsvisualization_jcds07/lists"}