Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms
This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. With the rapid growth of digital marketing, selecting the right keywords has become crucial for improving conversion rat...
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| Format: | Article |
| Language: | Indonesian |
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Islamic University of Indragiri
2025-05-01
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| Series: | Sistemasi: Jurnal Sistem Informasi |
| Subjects: | |
| Online Access: | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5174 |
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| _version_ | 1849222079421874176 |
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| author | Muhammad Sya'ban Harahap Alva Hendi Muhammad |
| author_facet | Muhammad Sya'ban Harahap Alva Hendi Muhammad |
| author_sort | Muhammad Sya'ban Harahap |
| collection | DOAJ |
| description | This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. With the rapid growth of digital marketing, selecting the right keywords has become crucial for improving conversion rates. The research utilized a dataset of 673 entries with 12 relevant attributes, collected from historical ads and the Google Ads Keyword Planner. A comparative experimental approach was employed, with the data split into training (80%) and testing (20%) sets. The analysis revealed that the C4.5 algorithm achieved higher accuracy (85.41%) compared to K-NN (74.86%). Evaluation was based on metrics such as accuracy, precision, recall, and F1-score, which indicated that C4.5 was more effective in predicting conversions using the given dataset. These findings offer valuable insights for advertisers aiming to optimize their ad campaigns by selecting more effective keywords. However, the study also acknowledges limitations and recommends further research using larger and more diverse datasets to enhance model accuracy. |
| format | Article |
| id | doaj-art-e8a8ee7b77dd4b4eaf6a6efffc2db852 |
| institution | Kabale University |
| issn | 2302-8149 2540-9719 |
| language | Indonesian |
| publishDate | 2025-05-01 |
| publisher | Islamic University of Indragiri |
| record_format | Article |
| series | Sistemasi: Jurnal Sistem Informasi |
| spelling | doaj-art-e8a8ee7b77dd4b4eaf6a6efffc2db8522025-08-26T08:05:47ZindIslamic University of IndragiriSistemasi: Jurnal Sistem Informasi2302-81492540-97192025-05-011431370137710.32520/stmsi.v14i3.51741076Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 AlgorithmsMuhammad Sya'ban Harahap0Alva Hendi Muhammad1Universitas Amikom YogyakartaUniversitas Amikom YogyakartaThis study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. With the rapid growth of digital marketing, selecting the right keywords has become crucial for improving conversion rates. The research utilized a dataset of 673 entries with 12 relevant attributes, collected from historical ads and the Google Ads Keyword Planner. A comparative experimental approach was employed, with the data split into training (80%) and testing (20%) sets. The analysis revealed that the C4.5 algorithm achieved higher accuracy (85.41%) compared to K-NN (74.86%). Evaluation was based on metrics such as accuracy, precision, recall, and F1-score, which indicated that C4.5 was more effective in predicting conversions using the given dataset. These findings offer valuable insights for advertisers aiming to optimize their ad campaigns by selecting more effective keywords. However, the study also acknowledges limitations and recommends further research using larger and more diverse datasets to enhance model accuracy.https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5174k-nearest neighborc4.5konversigoogle adsdigital marketing |
| spellingShingle | Muhammad Sya'ban Harahap Alva Hendi Muhammad Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms Sistemasi: Jurnal Sistem Informasi k-nearest neighbor c4.5 konversi google ads digital marketing |
| title | Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms |
| title_full | Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms |
| title_fullStr | Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms |
| title_full_unstemmed | Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms |
| title_short | Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms |
| title_sort | conversion prediction in google search ads keyword selection using the k nearest neighbor and c4 5 algorithms |
| topic | k-nearest neighbor c4.5 konversi google ads digital marketing |
| url | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5174 |
| work_keys_str_mv | AT muhammadsyabanharahap conversionpredictioningooglesearchadskeywordselectionusingtheknearestneighborandc45algorithms AT alvahendimuhammad conversionpredictioningooglesearchadskeywordselectionusingtheknearestneighborandc45algorithms |