[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120798-id":3,"doc-seo-120798-113":31,"detail-sidebar-cat-0-id-113":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},120798,962084925502,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",54,"Penelitian & Laporan","Klasifikasi Kualitas Air Minum - Penerapan Algoritma Machine Learning dengan Pendekatan Supervised Learning","Kebutuhan air bersih terus meningkat, namun akses terhadap air minum yang layak sering tidak sejalan dengan kemampuan dan pengetahuan pengawasan kualitas. Mayoritas masyarakat belum mampu menentukan apakah air aman dikonsumsi, padahal kualitas minum dapat dibedakan melalui parameter mineral. Naskah ini mengklasifikasikan kualitas air sampel menggunakan algoritma machine learning dengan model Logistic Regression, Support Vector Machine, Random Forest Classifier, K-Nearest Neighbor, dan XGBoost. Hasil menunjukkan akurasi tertinggi pada Random Forest Classifier sebesar 78%.","VOLUME 02, No 01, Juni 2023 e-ISSN: 2987-906X  \n[https://ejournal.unib.ac.id/diophantine](https://ejournal.unib.ac.id/diophantine),  \nKlasifikasi Kualitas Air Minum menggunakan Penerapan Algoritma Machine Learning dengan Pendekatan Supervised Learning  \nLidya Savitri 1*, Rahmat Nursalim 1  \n1Department of Mathematics, Universitas Bengkulu, Indonesia  \n* Corresponding Author  \n\n| Article Information |  | Abstract |\n| --- | --- | --- |\n| Article History:\u003Cbr>Submitted: 06 15 2023\u003Cbr>Accepted: 06 28 2023\u003Cbr>Published: 06 30 2023 |  | The need for the provision and service of clean water from time to time is increasing which is sometimes not matched by the ability and knowledge of clean water. The majority of people still do not know whether water is suitable for consumption or not. The quality of drinking water can be distinguished based on the mineral parameters contained in the water. This article will explain the classification of water sample data by applying a Machine Learning Algorithm, which includes modeling with Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, K- Nearest Neighbor(KNN), XGBoost Classifier. Classification models produce varying degrees of accuracy. The highest accuracy is obtained in the Random Forest Classifier model with an accuracy rate of 78% . Analysis of drinking water quality with machine learning algorithms is very easy to understand, because the results of this study produce very simple results so that they are easy to understand. |\n| KeyWords:\u003Cbr>KlasifikasiAir minum Machine learning Logistic Regression Support Vector Machine Random Forest Classifier K-Nearest Neighbor XGBoost Classifier |  |  |\n\n1. PENDAHULUAN  \nAir merupakan kebutuhan penting untuk kelangsungan hidup makhluk hidup yang ada di bumi[1] . Di Perkotaan air merupakan kebutuhan yang sangat penting, terutama kebutuhan akan air bersih. Kebutuhanyang semakin tahun semakin meningkat tetapi berbanding terbalik dengan persediaan air bersih yang semakin terbatas yang diakibatkan banyaknya pembangunan yang tidak memperhatikan daerah resapan air yang semakin sempit[2] . Krisis air bersih melanda berbagai negara di dunia, bahkan air bersih yang dapatdikonsumsi oleh manusia hanya sebesar 1% dari total air yang ada. Jumlah air bersih yang kecil menyebabkan susahnya penduduk mengakses air bersih. berdasarkan data dari WHO sebanyak 663 jutapenduduk kesusahan untuk mengakses air bersih [3] .  \nBerdasarkan Peraturan Menteri Kesehatan Nomor 492/MENKES/PER/IV/2010, Pasal (1) ayat (1) Persyaratan Air minum adalah air yang melalui proses pengolahan atau tanpa proses pengolahan yang memenuhi syarat kesehatan dan dapat langsung diminum[4] . Untuk memenuhi standar kualitas air minum upaya pengawasan di daerah sumber air sangatlah penting. Dengan adanya pengawasan sumber air akanterjaga dan mampu menghasilkan kualitas air dengan standar yang layak dikonsumsi oleh manusia[5] .  \nPenelitian tentang klasifikasi air minum sudah banyak dilakukan, khususnya mengenai klasifikasikualitas air minum menggunakan penerapan machine learning. Penelitian yang dilakukan oleh Aldi dkk, menggunakan metode Naive bayes, Decision Tree, dan K-Nearest Neighbours pada penelitian ini untuk mengetahui tingkat keakuratan yang paling tinggi dan didapat keakuratan yang paling tinggi adalah metode Decision Tree[7] . Sedangkan penelitian yang dilakukan Prismahardi dkk, menggunakan metode Support Vector Machine, Decision Tree, Naïve Bayes, dan Artificial Neural Network dari penelitian ini didapat tingkat keakuratan yang paling tinggi metode Random Forest Classifier[8] .  \nLidya Savitri, Rahmat Nursalim.  \nPengukuran kualitas air minum menggunakan parameter dan variabel, dengan pengambilan dataset padakaggle yang berjudul water_potability.csv yang memuat sepuluh parameter. Pada penelitian ini penulis melakukan klasifikasi kualitas air minum dengan menggunakan penerapan Machine Learning, yang mencakup pemodelan dengan Logistic Regression, Support Vector Machine (S","cbCaisvVt3JluT8M","https://ap.wps.com/l/cbCaisvVt3JluT8M","pdf",419208,4,1,8,"Indonesian","id",113,"# Pendahuluan\n## Latar belakang kebutuhan air bersih dan standar kualitas\n## Peraturan kesehatan terkait air minum\n## Studi terdahulu tentang klasifikasi kualitas air minum\n# Metode\n## Deskripsi dataset water_potability.csv\n## Parameter kualitas air yang digunakan\n## Tahapan pengolahan data (pre-processing)","[{\"question\":\"Mengapa klasifikasi kualitas air minum penting dilakukan?\",\"answer\":\"Kebutuhan air bersih meningkat sementara akses terhadap air layak terbatas. Banyak orang belum mengetahui apakah air aman dikonsumsi, sehingga klasifikasi berdasarkan parameter kualitas diperlukan.\"},{\"question\":\"Model machine learning apa saja yang digunakan untuk klasifikasi kualitas air minum?\",\"answer\":\"Penelitian memakai Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, K-Nearest Neighbor (KNN), dan XGBoost Classifier.\"},{\"question\":\"Berapa akurasi tertinggi yang dicapai pada penelitian ini?\",\"answer\":\"Akurasi tertinggi diperoleh oleh Random Forest Classifier dengan tingkat akurasi 78%.\"}]","Klasifikasi Kualitas Air Minum - Penerapan Algoritma Machine Learning dengan Pendekatan Supervised Learning | PDF",1785732087,12,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"classification-of-drinking-water-quality-machine-learning-algorithms-with-supervised-learning-approach","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/id/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/id/document/penelitian-laporan/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/id/document/classification-of-drinking-water-quality-machine-learning-algorithms-with-supervised-learning-approach/120798/",{"url":53,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-18","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Mengapa klasifikasi kualitas air minum penting dilakukan?","Question",{"text":76,"@type":77},"Kebutuhan air bersih meningkat sementara akses terhadap air layak terbatas. Banyak orang belum mengetahui apakah air aman dikonsumsi, sehingga klasifikasi berdasarkan parameter kualitas diperlukan.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Model machine learning apa saja yang digunakan untuk klasifikasi kualitas air minum?",{"text":81,"@type":77},"Penelitian memakai Logistic Regression, Support Vector Machine (SVM), Random Forest Classifier, K-Nearest Neighbor (KNN), dan XGBoost Classifier.",{"name":83,"@type":74,"acceptedAnswer":84},"Berapa akurasi tertinggi yang dicapai pada penelitian ini?",{"text":85,"@type":77},"Akurasi tertinggi diperoleh oleh Random Forest Classifier dengan tingkat akurasi 78%.","https://schema.org",{"og:url":53,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,99,103,107,111,115,117,121,125,129,133],{"id":95,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":100,"doc_module":4,"doc_module_name":47,"category_name":101,"show_sort_weight":97,"slug":102},48,"Cerita & Novel","story-novel",{"id":104,"doc_module":4,"doc_module_name":47,"category_name":105,"show_sort_weight":97,"slug":106},56,"Gaya Hidup","lifestyle",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":97,"slug":110},51,"Komik","comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":97,"slug":114},53,"Layanan Kesehatan","healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":97,"slug":116},"research-report",{"id":118,"doc_module":4,"doc_module_name":47,"category_name":119,"show_sort_weight":97,"slug":120},49,"Sastra","literature",{"id":122,"doc_module":4,"doc_module_name":47,"category_name":123,"show_sort_weight":97,"slug":124},52,"Teknologi","technology",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":127,"show_sort_weight":97,"slug":128},50,"Ujian","exam",{"id":130,"doc_module":4,"doc_module_name":47,"category_name":131,"show_sort_weight":97,"slug":132},57,"Umum","general",{"id":134,"doc_module":4,"doc_module_name":47,"category_name":135,"show_sort_weight":4,"slug":136},181,"Formulir","formulir"]