Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Teknik Mesin, Industri, Elektro dan Informatika J-CEKI
Deigo Anugrah Pratama
Unknown Affiliation
Humanities Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Terjadinya Kanker Paru-Paru Pada Pasien Menggunakan Decision Tree: Penerapan Algoritma C4.5 Dan RapidMiner Untuk Menentukan Risiko Kanker Pada Gejala Pasien Deigo Anugrah Pratama; Ibnu Rizal Mutaqin; Kevin Rafael Manuela
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 2 No. 4 (2023): Desember : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jtmei.v2i4.3004

Abstract

The innovative approach to cancer patient data modeling has been employed in this research. We utilized the "Decision Tree" concept as a machine learning algorithm to analyze a dataset containing detailed information about patients, including age, gender, family history, and other medical test results. Through meticulous data study steps, we compiled a relevant dataset and then performed data classification to determine the target variable, whether a patient can be categorized as likely to have lung cancer or not. Input variables were carefully grouped to ensure the accuracy of the analysis. Data analysis using the Decision Tree algorithm provided profound insights into the significant factors in predicting cancer symptoms in patients. The results of this analysis were interpreted carefully, and performance model evaluation metrics, such as accuracy and precision, were provided to offer a comprehensive understanding of the reliability of the generated model. The findings of this research have important implications for the understanding and management of cancer in patients. The application of this method can enhance accuracy in predicting cancer status, assist in clinical decision-making, and ultimately improve the quality of patient care.
Eksplorasi Pola Penjualan Produk di E-Commerce menggunakan Web Scraping Deigo Anugrah Pratama; Kevin Rafael Manuela Feltya; Ibnu Rizal Mutaqin Muyasar; Belsana Butar Butar; Elly Indrayuni
J-CEKI : Jurnal Cendekia Ilmiah Vol. 5 No. 1: Desember 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v5i1.12966

Abstract

Penelitian ini membahas tentang pola penjualan produk dan data ulasan pengunjung pada platform e‑commerce Shopee, dengan memanfaatkan teknik web scraping pada data ulasan pelanggan sebagai proxy tanggal transaksi. Tujuan penelitian meliputi eksplorasi pola penjualan produk, identifikasi lonjakan penjualan menurut waktu, dan penyajian visualisasi interaktif sebagai alat dukung keputusan. Data dikumpulkan melalui web scraping berbasis JavaScript yang dijalankan pada developer console untuk mengekstrak ulasan pelanggan. Setelah itu data diproses pada tahap pra pemrosesan data menggunakan alat google colab dan library python, untuk selanjutnya diunggah ke aplikasi Looker Studio sebagai bentuk pembuatan dashboard interaktif. Visualisasi yang dihasilkan lewat looker studio mendukung optimasi strategi bisnis seperti: digital marketing, dan perencanaan stok Studi ini menegaskan web scraping pada ulasan pelanggan dapat menjadi pendekatan praktis untuk pengambilan keputusan bisnis dan analisa kompetitor.
Co-Authors Belsana Butar Butar Elly Indrayuni Ibnu Rizal Mutaqin Ibnu Rizal Mutaqin Muyasar Kevin Rafael Manuela Kevin Rafael Manuela Feltya