Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan
Julieta Cahya Mestika
Unknown Affiliation
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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

Found 2 Documents
Search

 1 
Menjelajahi Teknik-Teknik Supervised Learning untuk Pemodelan Prediktif Menggunakan Python Julieta Cahya Mestika; Matheos Oktavio Selan; Muhamad Iqbal Qadafi
Buletin Ilmiah Ilmu Komputer dan Multimedia Vol 1 No 1 (2023): Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) INPRESS
Publisher : Shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Predictive modeling has become increasingly important in various fields such as data science, artificial intelligence, finance, healthcare, and many others. In this context, supervised learning has emerged as one of the most commonly used approaches to building predictive models. By employing supervised learning algorithms, models can be used to classify data into appropriate categories or make numerical predictions. In the realm of predictive modeling, the Python programming language has become a primary choice for practitioners and researchers. This research aims to provide a comprehensive understanding of supervised learning techniques that can be applied using Python. Qualitative research methods with a case study approach are employed to gain in-depth insights into the specific context and challenges. The researcher conducts experiments using real-world datasets relevant to predictive modeling to test the effectiveness of implemented supervised learning techniques. The findings of this research are expected to offer practical guidance to researchers and practitioners interested in leveraging supervised learning with Python to build efficient and reliable predictive models.
PENERAPAN METODE TOPSIS DALAM PENENTUAN E- COMMERCE TERBAIK UNTUK PENGAMBILAN KEPUTUSAN YANG EFEKTIF Julieta Cahya Mestika; Siti Maulida Zahra; Wahyu Muhamad Sidik; Perani Rosyani
AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan Vol. 1 No. 2 (2023): Jurnal AI dan SPK : Jurnal Artificial Inteligent dan Sistem Penunjang Keputusan
Publisher : CV. Shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini fokus pada penerapan Metode Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) dalam menentukan platform E-commerce terbaik guna mendukung pengambilan keputusan yang efektif. Metode TOPSIS digunakan untuk mengevaluasi beberapa platform E-commerce berdasarkan kriteria-kriteria yang signifikan. Tujuan utama penelitian ini adalah memberikan wawasan mendalam terhadap faktor-faktor kunci yang mempengaruhi efektivitas sebuah E-commerce. Data dari berbagai sumber dievaluasi menggunakan Metode TOPSIS untuk merangking dan mengidentifikasi platform E- commerce terbaik. Penelitian ini memberikan kontribusi dalam memberikan panduan bagi pengambil keputusan untuk memilih platform E-commerce yang sesuai dengan kebutuhan bisnis dan tujuan mereka. Hasil penelitian diharapkan dapat meningkatkan pemahaman industri terkait penerapan Metode TOPSIS dalam konteks pengambilan keputusan E-commerce, dan memberikan landasan bagi pengembangan strategi yang lebih efektif dalam lingkungan perdagangan digital
Co-Authors Matheos Oktavio Selan Muhamad Iqbal Qadafi Perani Rosyani Siti Maulida Zahra Wahyu Muhamad Sidik