[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124268-id":3,"doc-seo-124268-113":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},124268,549768702563,"Sage","https://ap-avatar.wpscdn.com/avatar/8000c4aa63b76e948b?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786536092046926083",54,"Penelitian & Laporan","Analisis Data Penjualan Tiket Pesawat ke Jepang Menggunakan Classic Machine Learning pada PT. TTD","Penelitian ini menganalisis data penjualan tiket pesawat ke Jepang menggunakan pendekatan classic machine learning pada PT. TTD. Permintaan tiket penerbangan yang tidak menentu menjadi tantangan karena banyak faktor yang kompleks dan berubah-ubah. Data penjualan tahun 2022–2023 untuk Japan Airlines dan All Nippon Airways dibersihkan dan disusun menjadi dataset untuk klasifikasi. Model dievaluasi dengan K-Nearest Neighbors, Naïve Bayes, dan Decision Tree melalui prediction model, model test & score, serta confusion matrix, dengan akurasi tertinggi pada KNN (99,5% dan 98,9%).","Analis Data Penjualan Tiket Pesawat Ke Jepang Menggunakan Classic Machine Learning Pada PT. TTD  \nSyarifuddin  \nProgram Studi Teknik Informatika S-2, Universitas Pamulang, Tangerang Selatan, Banten  \nEmail: [syarif.unpam@gmail.com](syarif.unpam@gmail.com)  \nABSTRACT  \nAirline ticket sales to Japan is an important topic in the ever-evolving travel industry. The unpredictable demand for airline tickets is a common challenge in the aviation industry due to many complex and variable factors. This research analyzes the data on airline ticket sales to Japan using classic machine learning approaches. The data used for the research are the airline ticket sales to Japan in 2022 and 2023 for Japan Airlines and All Nippon Airways. Classical methods such as classification were applied to identify factors influencing the ticket sales patterns. The collected data was cleaned and organized to obtain a dataset for use in Machine Learning with the K-Nearest Neighbors, Naïve Bayes, and Decision Tree algorithms. After evaluating the models created using these three algorithms, the evaluation results with prediction models, model test & score, and confusion matrix, showed that the K-Nearest Neighbor algorithm achieved the highest values compared to the Naïve Bayes and Decision Tree algorithms with an accuracy of 99.5%(model predictions evaluation) & 98.9%(model test & score evaluation). The majority of ticket sales to Japan were for JAL flights, economy class tickets, and spring season being the most popular choices. The conclusion from this data is that Japan Airlines holds a strong market share in ticket sales to Japan.  \nKeywords: Data Mining, Classification, Airline Ticket Sales, KNN, Naïve Bayes, Decision Tree.  \nABSTRAK  \nPenjualan tiket pesawat ke Jepang adalah topik penting dalam industri perjalanan yang terus berkembang. Permintaan tiket pesawat yang sulit diprediksi adalah tantangan umum dalam industripenerbangan karena dipengaruhi oleh banyak faktor yang kompleks dan berubah-ubah. Dalam penelitian ini dilakukan analisis data terhadap pola penjualan tiket pesawat ke Jepang menggunakan pendekatan classic machine learning. Data yang digunakan untuk penelitian adalah data penjualan tiket pesawat khusus ke Jepang tahun 2022 dan 2023 dengan tipe pesawat Japan Airlines dan All Nippon Airways. Metode klasikseperti klasifikasi diterapkan untuk mengidentifikasi faktor-faktor yang mempengaruhi pola penjualan tiket. Data yang sudah dikumpulkan kemudian dilakukan pembersihan dan perapihan sehinggamendapatkat dataset yang akan digunakan pada Machine Learning dengan menggunakan Algoritma KNearest Neighbors, Naïve Bayes dan Decision Tree. Setelah dilakukan evaluasi model yang dibuat menggunakan ke tiga algortima tersebut, Hasil evaluasi dengan model prediction , model test & score dan confusion matrix, Pada Algoritma K-Nearest Neighbor mendapatkan nilai tertinggi dibandingan denganalgoritma Naïve Bayes dan Decision Tree dengan nilai accuracy sebesar 99,5%( evaluasi model predictions ) & 98,9%( evaluasi model test & score ) dan Penjualan tiket ke Jepang terbanyak mengunakan pesawat JAL, kelas tiket kelas ekonomi dan musim spring merupakan pilihan terbanyak. kesimpulan dari data tersebut adalah bahwa Japan Airlines memegang pangsa pasar yang kuat dalam penjualan tiket ke Jepang.  \nKata Kunci : Data Mining, Klasifikasi, Penjualan tiket pesawat, KNN, Naïve Bayes, Deision Tree.  \n1. PENDAHULUAN  \nPT. TTD ( tours & travel ) yang sudah berdiri sejak tahun 1972 merupakan agentour & travel yang menawarkan paket perjalan dan penjualan tiket pesawat khususnyauntuk perusahaan Jepang yang ada di indonesia dengan tujuan kenegara Jepang. Sebanyak 1120 perusahaan perjalanan wisata berdasarkan informasi dari statistik jasa perjalanan wisata tours & travel service statistics 2011 membuat perusahaan saling bersaing untuk membuat penawaran yang terbaik kepada customer sehingga membuat para pengelola ingin menunjukan strategi pemasaran yang lebih baik. Untuk itu maka para","cbCaigopG98BYfpN","https://ap.wps.com/l/cbCaigopG98BYfpN","pdf",466846,4,1,12,"Indonesian","id",113,"# Pendahuluan\n## Latar Belakang dan Permasalahan\n## Penelitian Terdahulu","[{\"question\":\"Penelitian ini menggunakan data penjualan tiket tahun berapa dan maskapai apa saja?\",\"answer\":\"Data yang digunakan adalah penjualan tiket pesawat ke Jepang tahun 2022 dan 2023 untuk Japan Airlines dan All Nippon Airways.\"},{\"question\":\"Algoritma machine learning klasik apa yang digunakan untuk klasifikasi?\",\"answer\":\"Algoritma yang digunakan adalah K-Nearest Neighbors, Naïve Bayes, dan Decision Tree untuk mengidentifikasi faktor yang memengaruhi pola penjualan tiket.\"},{\"question\":\"Bagaimana hasil evaluasi model dan algoritma mana yang paling baik?\",\"answer\":\"Evaluasi dilakukan dengan prediction model, model test \\u0026 score, dan confusion matrix. K-Nearest Neighbor memperoleh nilai tertinggi dengan akurasi 99,5% (evaluasi prediction) dan 98,9% (evaluasi test \\u0026 score).\"}]","Analisis Data Penjualan Tiket Pesawat ke Jepang Menggunakan Classic Machine Learning pada PT. TTD | PDF",1785821294,18,{"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},"data-analysis-of-airline-ticket-sales-to-japan-using-classic-machine-learning-at-pt-ttd","",{"@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/data-analysis-of-airline-ticket-sales-to-japan-using-classic-machine-learning-at-pt-ttd/124268/",{"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","2026-08-16","2026-08-04",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},"Penelitian ini menggunakan data penjualan tiket tahun berapa dan maskapai apa saja?","Question",{"text":76,"@type":77},"Data yang digunakan adalah penjualan tiket pesawat ke Jepang tahun 2022 dan 2023 untuk Japan Airlines dan All Nippon Airways.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Algoritma machine learning klasik apa yang digunakan untuk klasifikasi?",{"text":81,"@type":77},"Algoritma yang digunakan adalah K-Nearest Neighbors, Naïve Bayes, dan Decision Tree untuk mengidentifikasi faktor yang memengaruhi pola penjualan tiket.",{"name":83,"@type":74,"acceptedAnswer":84},"Bagaimana hasil evaluasi model dan algoritma mana yang paling baik?",{"text":85,"@type":77},"Evaluasi dilakukan dengan prediction model, model test & score, dan confusion matrix. K-Nearest Neighbor memperoleh nilai tertinggi dengan akurasi 99,5% (evaluasi prediction) dan 98,9% (evaluasi test & score).","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"]