IMPLEMENTASI ALGORITMA CLUSTERING K-MEANS PADA PENGGUNA WARTEL DI PONDOK PESANTREN SALAFIYAH SYAFI'IYAH SUKOREJO

This research discusses the application of the K-Means Clustering algorithm to analyze the usage patterns of wartel services at the Salafiyah Syafi'iyah Sukorejo Islamic Boarding School. The purpose of this research is to group users into several clusters based on call duration, frequency of use, and total call cost. User data was analyzed using the stages in the SEMMA method (Sample, Explore, Modify, Model, Assess) to ensure systematic and structured data processing. The results showed that the K-Means algorithm was able to form three main clusters, namely users with low, medium, and high intensity. The majority of users belong to the low-intensity cluster with short average call duration and minimal expenditure, while the high-intensity cluster consists of users who make long calls with high costs. Further analysis shows that the highest usage time is at night (19.00-21.00). Based on these results, it is recommended that wartel managers optimize operating hours and provide promotional call packages according to the needs of each user cluster. In addition, diversification of services such as cheap internet access can also increase the attractiveness of wartel in the digital era. This research uses clustering methods to assist data-based strategic decision-making, as outlined by Han and supported by the application of SEMMA from SAS Institute (1998).

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Publication Details

Journal
Jurnal Ilmiah Multidisiplin Ilmu
Published
2024-12-31
DOI
https://doi.org/10.69714/55xet429
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

IMPLEMENTASI ALGORITMA CLUSTERING K-MEANS PADA PENGGUNA WARTEL DI PONDOK PESANTREN SALAFIYAH SYAFI'IYAH SUKOREJO

Khairullah Irfansyah, Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu
Data Mining and Machine Learning Applications
article

IMPLEMENTASI ALGORITMA CLUSTERING K-MEANS PADA PENGGUNA WARTEL DI PONDOK PESANTREN SALAFIYAH SYAFI'IYAH SUKOREJO

Khairullah Irfansyah, Zaehol Fatah
article en

Abstract

This research discusses the application of the K-Means Clustering algorithm to analyze the usage patterns of wartel services at the Salafiyah Syafi'iyah Sukorejo Islamic Boarding School. The purpose of this research is to group users into several clusters based on call duration, frequency of use, and total call cost. User data was analyzed using the stages in the SEMMA method (Sample, Explore, Modify, Model, Assess) to ensure systematic and structured data processing. The results showed that the K-Means algorithm was able to form three main clusters, namely users with low, medium, and high intensity. The majority of users belong to the low-intensity cluster with short average call duration and minimal expenditure, while the high-intensity cluster consists of users who make long calls with high costs. Further analysis shows that the highest usage time is at night (19.00-21.00). Based on these results, it is recommended that wartel managers optimize operating hours and provide promotional call packages according to the needs of each user cluster. In addition, diversification of services such as cheap internet access can also increase the attractiveness of wartel in the digital era. This research uses clustering methods to assist data-based strategic decision-making, as outlined by Han and supported by the application of SEMMA from SAS Institute (1998).

Jurnal Ilmiah Multidisiplin IlmuVol. 1(5)
Universitas Ibrahimy (ID)
Openalex Percentile: Top 52%
Data Mining and Machine Learning Applications
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