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All Journal AGRIVITA, Journal of Agricultural Science Jurnal Informatika dan Teknik Elektro Terapan JurTI (JURNAL TEKNOLOGI INFORMASI) Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal ICT : Information Communication & Technology JATI (Jurnal Mahasiswa Teknik Informatika) JISA (Jurnal Informatika dan Sains) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Renewable Energy, Electrical, and Computer Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) PENA ABDIMAS : Jurnal Pengabdian Masyarakat BULLET : Jurnal Multidisiplin Ilmu Jurnal Sistem Informasi dan Manajemen Jurnal Kecerdasan Buatan dan Teknologi Informasi Spektra : Jurnal Ilmu-ilmu Sosial Educommunity Jurnal Pengabdian Masyarakat As-Sulthan Journal of Education Jurnal Komtika (Komputasi dan Informatika)
Irfan Ali, Irfan
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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FP-Growth for Data-Driven Purchase Pattern Analysis and Product Recommendations at Flanetqueen Store Marwah, Sopa; Rahaningsih, Nining; Ali, Irfan; Marthanu, Indra Wiguna; Kaslani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1850

Abstract

The advancement of information technology has encouraged the use of data analytics to support data-driven business decision-making. This study aims to analyze purchasing patterns of hoodie products and provide product recommendations for customers at Flanetqueen Store using the FP-Growth (Frequent Pattern Growth) algorithm. The research applies the Knowledge Discovery in Database (KDD) framework, consisting of five stages: data selection, preprocessing, transformation, data mining, and interpretation/evaluation. The dataset comprises hoodie sales transactions recorded from January to December 2024. Data analysis was conducted using RapidMiner Studio version 10.3 with a minimum support of 0.2 and minimum confidence of 0.4. The analysis produced 26 itemsets and 11 association rules indicating product correlations. The strongest rule, Bloods → Champion, achieved a confidence of 0.414, revealing that customers who purchased Bloods hoodies were also likely to buy Champion hoodies. These findings were used to design cross-selling strategies and generate relevant product recommendations. The study demonstrates that FP-Growth effectively extracts frequent purchase patterns and contributes to the development of data-driven recommendation systems in the local fashion retail industry.
Segmentation of Coffee Purchasing Behavior Based on Transaction Time Using the K-Means Algorithm Yuslia Devitri; Rahaningsih, Nining; Ali, Irfan; Prihartono, Willy
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1863

Abstract

This studyaims to identify customer behavior patterns based on the time of purchaseof beverages at a coffee shop using the K-Means method.Transaction data includes purchase time, payment type, product name,time category, day, and month. The research stages include data cleaning, time attribute transformation, and numerical feature normalization. The optimal number of clustersis determined through testing k = 2–10 with four evaluation metrics,namely Inertia, Silhouette Score, Davies–Bouldin Index, and Calinski–HarabaszIndex. Based on the validation results, k = 3 was selected because it provided the best balancebetween compactness and cluster separation. The clustering results showedthree main customer groups based on transaction time trends:nighttime buyers with a peak around 10:27 p.m., afternoon to early evening buyerswith a centroid of 7:01 p.m., and morning to noon buyers with a centroid11:13. The frequency distribution indicates that the morning–afternoon buyer groupis the largest, while the early evening–night group is thesmallest. Visualization of scatter plots, boxplots, and time category graphsemphasizes the differences in characteristics between clusters. Overall,this study proves that K-Means is effective in mapping the temporal patternsof customer behavior. These findings can be used to develop time-based marketing strategies, operational arrangements, and product stock management,as well as form the basis for further analysis in the industry.
Co-Authors Abdul Rohim, Adi Nur Abdul Rosid, Rizal Adella, Luthfiyyah Iffah Adi Supriyatna Adinata, Adinata Ahmad Faqih Ahmad Jaelani Akbar, Miftahul Al-Maulid, Hisyam Aldiyansyah, Aldiyansyah Alfin Maulana Alfudola, Mahfudz Alkatiri, Nazwa Alvianatinova, Via Amalia, Rosnita Amer, Abdu Shobarudin Ana Amalia, Ana Andriyanti, Rina Annurfariz, Aditya Apriliana Janatu Marwa Aqlani, Zaheer Ahmed Arofah, Mila Asep Yoyo Wardaya Auliya, Suci Az-Zahra, Asih Azrul, Ahmad Azzam, Ahmad Brohi, Sheeraz Aleem Dahri, Shahzad Hussain Dahri, Zakir Hussain Dahri, Zamin Hussain Dendy Indriya Efendi Destiawati, Deby Dewanty Rafu, Maria Dienwati Nuris, Nisa Dikananda, Arif Rinaldi Dikananda, Fatihanursari Efendi , Dendy Indriya Effendy, Dendy Indria ETI KURNIAWATI Faisal Adam, Faisal Faqih, Habib Fasa, Saefullah Fatmawati, Aisyah FAUZAN, AKMAL Fitria, Lailatul Gifthera Dwilestari Gitacahyani, Adisty Gunia, Euis H Hadiyanto Hayati, Umi Hendiana, Hendiana Hermawan, Ramdan Hidayah, Freni Mega Hidayattullah, Rizky Huda, Irhamul Hurifiani, Alfia Ikbal, Ali Ilham, Mokhamad Indah Indah Indriya Efendi, Dendy Indriyan Dwi Kesuma, Adri Irma Purnama sari, Ade Irma Purnamasari , Ade Irma Purnamasari, Ade Julkarnaen, Agus Juwita, Ita Karbala, Syahid Kaslani Khalda Rifdan, Ghina Lana Sularto Lestari, Gifthera Dwi Listianto, Ahmad Bilal Lisyana, Zita Lukman Rohmat, Cep Mahdalena, Putri Ayu Mangrio, Abdul Ghafoor Mangrio, Munir Ahmed Mariyani, Dinda Martanto . Marthanu, Indra Wiguna Marwah, Sopa Maulana, Ali Mayang Fadilah, Dewi Muharam, Arbi Adi Muharram, Akbar Muhimmatul ulya, Syilwa Nawang Wulan, Hidayah Nining Rahaningsih Nugraha, Rifqi Nugroho, Rizwar Adi Nur Alam, Alfian Nur Aziziah, Aldila Nurdiawan, Rudi Nurhidayat, Muhammad Nursaniah, Rini Nursatika Kusuma, Ines Odi Nurdiawan Pajri, Riki Prahara, Sukma Prihartono, Willy Purnamasari, Ade Irma Putra Pratama, Aeri Putriana, Eka R, Nining Raafi, Muhammad Rahmi Safitri, Rahmi Ramanto, Aditiya Ramdani, Rizki Rayhan, Tubagus Muhammad Rifa'i, Akhmad Rifqi Khairul Anam Rikiyashi, Afkan Rismala, Rismala Rizki Rinaldi, Ade Rizky Wulandhari, Putri Rodhiyana, Mu'allimah Rohman, Dede Rohmat, Cep Lukman Rosyd, Abdul Roziqin, Ahmad Khoirur Rudi Kurniawan Sadiyah, Ainur Rohimatus Salamah, Soviatus Saleem, Salman Saputra, Muhammad Sariah Sariah Setianingsih, Indri Setiawan, Riyan Shaikh, Irfan Ahmed Sholihin Fauzan, Aldi Sofialaela, Annisa Solihudin, Dodi Sri Widyastuti Suarna, Nana Sudrajat, Adi Suryana, Aldi Susana, Heliayanti Susana, Heliyanti Syahrul, Adis Tohidi, Edi Vina, Vina Wahyudin, Edi Windy Mardiyyah, Nita Wirdiyan, Farhan Azfa Wisnu Saputra, Adrian wiwied pratiwi, wiwied Yuslia Devitri Zahrudin Zhahiran Herlambang, Prilanisa