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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Journal of Data Mining and Information Systems
Fidela, Anindya
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Penerapan Data Mining Untuk Klasifikasi Kualitas Udara di Daerah Istimewa Yogyakarta Menggunakan Algoritma C4.5 Nur Adiya, Az Zahra Dwi; Desvita, Amanda Fitria; Fidela, Anindya; Amelia, Dwi; Astuti, Tri
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 2 (2024): August 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i2.2800

Abstract

Air pollution is a global environmental problem that is of serious concern in various regions around the world, including in Indonesia. Poor air quality has negative impacts on human health, ecosystems and economic growth. The purpose of this research is to classify the air quality in the Special Region of Yogyakarta. Classification is done using data mining techniques with the C4.5 algorithm or decision tree. The results of the analysis that has been studied using the C4.5 algorithm used 5822 data and 20 replacement samples with 100 repetitions, so the results of this study obtained 7 decisions or leaves with a success rate of 99.9485% and a failure rate of 0.0515%.
Penerapan Algoritma FP-Growth untuk Strategi Penjualan Toko Kelontong Cipta Lestari Tarwoto; AL-Haq, Ahnaf Vanning; Fidela, Anindya; Audiana, Wini; Hani, Zulfa Ummu
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3278

Abstract

This research uses the FP-Growth algorithm to identify sales patterns at the Cipta Lestari convenience store to support inventory management efficiency and marketing strategies. The data used in this research consists of daily sales transaction data that includes product types and the quantities sold. This analysis employs a support parameter of 0.95 and a confidence level of 0.8, with a maximum limit of 100,000 items. The results indicate that products such as Kchoco, sambal sauce, and tea 3350ml are often purchased together with Torabika coffee, soy sauce, and instant fried noodles. This combination pattern enables the store to create more effective product promotions and optimize inventory. The goal of this research is to develop business strategies that are more responsive to customer needs, enhance satisfaction with the right product offerings, and strengthen competitive marketing. This research is expected to contribute to the development of traditional marketing strategies and serve as a reference for analyzing consumer purchasing patterns in future studies.
Penerapan Algoritma FP-Growth untuk Strategi Penjualan Toko Kelontong Cipta Lestari Tarwoto; AL-Haq, Ahnaf Vanning; Fidela, Anindya; Audiana, Wini; Hani, Zulfa Ummu
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3278

Abstract

This research uses the FP-Growth algorithm to identify sales patterns at the Cipta Lestari convenience store to support inventory management efficiency and marketing strategies. The data used in this research consists of daily sales transaction data that includes product types and the quantities sold. This analysis employs a support parameter of 0.95 and a confidence level of 0.8, with a maximum limit of 100,000 items. The results indicate that products such as Kchoco, sambal sauce, and tea 3350ml are often purchased together with Torabika coffee, soy sauce, and instant fried noodles. This combination pattern enables the store to create more effective product promotions and optimize inventory. The goal of this research is to develop business strategies that are more responsive to customer needs, enhance satisfaction with the right product offerings, and strengthen competitive marketing. This research is expected to contribute to the development of traditional marketing strategies and serve as a reference for analyzing consumer purchasing patterns in future studies.
Co-Authors AL-Haq, Ahnaf Vanning Amelia, Dwi Audiana, Wini Desvita, Amanda Fitria Hani, Zulfa Ummu Nur Adiya, Az Zahra Dwi Tarwoto Tri Astuti