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All Journal MEDIA ELEKTRIKA WARTA Jurnal Pengabdian UntukMu NegeRI Al Ishlah Jurnal Pendidikan CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control DoubleClick : Journal of Computer and Information Technology JURNAL SIMTIKA (Sistem Informasi dan Informatika) Jurnal Riset Informatika Jurnal Sistem Informasi Kaputama (JSIK) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Education Informatic Technology and Science Unri Conference Series: Community Engagement Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Abdimas Bina Bangsa BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Jurnal Ilmu Pendidikan (SOKO GURU) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Pengabdian Masyarakat Sains dan Teknologi Journal of Software Engineering and Information System (SEIS) Jurnal Pengabdian Kepada Masyarakat Ekonomi, Pendidikan, dan Sosial Humaniora Journal of Information Systems Management and Digital Business Sintaksis: Publikasi Para Ahli Bahasa dan Sastra Inggris Katalis Pendidikan: Jurnal Ilmu Pendidikan dan Matematika Soko Guru: Jurnal Ilmu Pendidikan
Finanta Okmayura
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : Journal of Software Engineering and Information System (SEIS)

 1 
PEMODELAN RFM & K-MEANS CLUSTERING UNTUK SEGMENTASI PELANGGAN DALAM PENJUALAN ONLINE Lukas, Ivander; Finanta Okmayura; Aidha Tita Irani; Ernia Juliastuti; Muhammad Amirulhaq; Rizky Ardiansyah; Sherly Fillia
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9556

Abstract

The exponential growth of e-commerce platforms necessitates sophisticated customer analytics to maintain competitive advantage and optimize revenue streams. This study addresses the critical challenge of understanding heterogeneous customer purchasing behaviors in online retail environments through advanced data mining techniques. The research implements RFM (Recency, Frequency, Monetary) modeling integrated with K-Means clustering algorithm to achieve comprehensive customer segmentation for strategic marketing optimization. A quantitative-exploratory methodology was employed, utilizing a comprehensive online sales dataset comprising over 40,000 transactional records. The analytical framework involved systematic data preprocessing using Python libraries (Pandas, NumPy), followed by RFM parameter calculation and standardization through StandardScaler normalization. K-Means clustering was subsequently applied with optimal cluster determination via Elbow Method validation, yielding three distinct customer segments. Visualization and interpretation were conducted using Tableau, Matplotlib, and Seaborn for comprehensive segment characterization. Results demonstrate successful identification of strategically significant customer clusters: high-value loyal customers, moderate-engagement prospects, and potential churn-risk segments, each exhibiting distinctive RFM behavioral patterns. The segmentation framework enables targeted marketing strategy formulation, personalized customer retention programs, and optimized resource allocation. This research contributes valuable insights for e-commerce practitioners seeking data-driven approaches to enhance customer relationship management and sustain long-term business profitability in competitive online marketplaces.
PEMODELAN MACHINE LEARNING DENGAN ALGORITMA RANDOM FOREST DALAM MEMPREDIKSI RISIKO STROKE Arman, Doni; Indayana, Nurul Sakhila; Okmayura, Finanta; Anjani, Suci Putri; Dayani, Fitri Nur; Farhan, Muhammad; Faturrahman, Ariya
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9590

Abstract

Stroke is one of the diseases that significantly affects health and economy, becoming the second most common cause of death in the world after coronary heart disease. Based on data from the World Health Organization (WHO), stroke is ranked second as the leading cause of death in the world after ischemic heart disease. In 2019, stroke was responsible for around 11% of total global deaths. One important way to reduce the death rate from stroke is to make prevention efforts through early prediction. Machine learning methods, especially Random Forest, are used in this study to predict the risk of stroke. The data used comes from a public dataset that includes age, gender, blood pressure, blood sugar, smoking status, and other medical history. The research process includes data pre-processing stages (data cleaning, outlier handling, and category coding), model training using the Random Forest algorithm, and model evaluation using a confusion matrix to evaluate accuracy, precision, recall, and F1 score. The evaluation results show an accuracy value of 97.55%, which indicates very good predictive performance so that this model has very good predictive performance.
Co-Authors Adlian Jefiza Adlian Jefiza Agus, Weni Oktavia Agustin Agustin Ahmad Khaidir Ahmad Khaidir Aidha Tita Irani Al Azhar, Safri Alfala, Resi Fazri Anfilla Tahany Angguni, Melati Anjani, Suci Putri Ansyah, Dandi Arfa Fadilah Arman, Doni Bestari Aulia Ananda Boy Zidan Nadjal Cahyo, Brian Agung Chairunnisa, Azzahra Cily Tria Marisa Dawita, Yanda Rahmadani Dayani, Fitri Nur Deprizon Dewi Fatimahwati Diny Syahputri Dira Yanti dwi winarti winarti Effendi, Noverta Efrizoni, Lusiana Eliya Mei Sisri Elvianti, Suci Ernia Juliastuti Faila, Arfa Fatayat Faturrahman, Ariya Febby Wilyani Fikri, Khusnul Fitri Hasanah Fitri, Tiara Greghard Shawenner Gunawan Ali Gustiara, Delya Haana Udtari Anjani Habibie, Dedi Rahman Harahap, Lelis Nawiyah Hayami, Regiolina Herdani, Inka friska Herlandy, Pratama Benny Husnah, Mirdatul Impian Sefria Nanda Indayana, Nurul Sakhila Jayus Jayus Jefiza, Adlian Junadhi, Junadhi Khairiyah Alifya Azizah Khairul Anshari Khairunnisah Khairunnisah Khalik, Ananda Difni Khusnul Hanafi Lukas, Ivander marisa, cily Melati Angguni Melly Novalia Melly Novalia Melly Novalia Melly Novalia Melly Novalia, Melly Molizarni Molizarni Mufty, Nouval Ditya Muhammad Amirulhaq Muhammad Farhan Muhammad Ryan Pratama Yudha Muhammad Zidhan Muhammad Zidhan Muslim Muslim Nanda Sopira Nelysa, Mise Novchi, Raja Widya Nur Fadilah Achmad Nurul Azani Oktariandi, Ital Pangestu, Rudi Rahayu Setianingsih rahmad Kurniawan Rahmat Hidayat Rahmat Hidayat Raihan Khairunisa Raimando, Dego Akbar Raja , Widya Novchi Raja Arlizon Raja Widya Novchi Ramadhani, Witri Risanto, Joko Risnal Diansyah, Risnal Rizky Aditya RIZKY ARDIANSYAH Robby Satria Robby Satria Robby Roma Tika Adi Putra Salsabila, Adilah Santia, Erma Saputra, Haris Tri Saputra, Tio Meylandi Saputro, Reihan Hersi Sherly Fillia Siti Niah, Siti Solihulibad, Akma Sridevi yuliani Suandevin, Hichmaed Tachta Hinggo Sulis Martiana Suryadila, Lusi Sy, Yandiko Saputra Teguh Sujana Vitriani Vitriani Vitriani Vitriani Vitriani Vitriani Vitriani Vitriani, Vitriani Wiranti Yolanda, Amalia Zaiful Bahri Zidhan, Muhammad