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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Jurnal Eksplora Informatika SPIRIT VCD : Journal of Visual Communication Design Jurnal Pengabdian Masyarakat Asia International Journal of Robotics and Control Systems International Journal of Community Service Joutica : Journal of Informatic Unisla PELS (Procedia of Engineering and Life Science) Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia JUSIFOR : Jurnal Sistem Informasi dan Informatika International Journal of Community Service (IJCS) Mestaka: Jurnal Pengabdian Kepada Masyarakat Jurnal Inovasi Teknologi dan Edukasi Teknik Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Sistem Komputer Asia Jeskovsia (Jurnal Desain Komunikasi Visual Asia) Jurnal ilmiah teknologi informasi Asia
Rina Dewi Indahsari
Institut Teknologi Dan Bisnis Asia Malang
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Komparasi Kinerja Algoritma XGBoost dengan Reduksi Dimensi PCA pada Klasifikasi Diabetes Nusa, Rivale Belano; Indahsari, Rina Dewi
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8563

Abstract

Diabetes is one of the most prevalent chronic diseases worldwide and requires accurate early detection to prevent long-term complications. In the field of medical data analysis, the application of machine learning algorithms such as XGBoost has proven effective in classifying disease risk. This study aims to compare the performance of the XGBoost algorithm before and after applying Principal Component Analysis (PCA) in diabetes risk classification using the Early Stage Diabetes Risk Prediction Dataset. The research stages include data preprocessing involving missing value checking, label encoding, outlier removal, normalization, and followed by the application of PCA with a 90% variance retention threshold. The experimental results show that the XGBoost model without PCA achieved the highest accuracy of 99.04%, while the model with PCA achieved 98.08%. Although the application of PCA slightly reduced accuracy, this technique successfully decreased the number of features and improved computational efficiency without losing important information. Therefore, PCA is proven to be effective in simplifying data complexity while maintaining optimal model performance.
Integrasi Teknologi Artificial Intelligence dalam Pengolahan Gambar dan Produksi Video Irsyada, Abdulloh Eizzi; Setyorini, Setyorini; Arifin, Jaenal; Andini, Titania Dwi; Indahsari, Rina Dewi
Mestaka: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2026): APRIL 2026
Publisher : Pakis Journal Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58184/mestaka.v5i2.914

Abstract

Artificial Intelligence is now an integral part of learning activities, especially for the younger generation. This includes digital image processing and video production. These activities are driven by the importance of mastering digital technology as one of the key competencies in facing the era of Industry 4.0 and Society 5.0, particularly for vocational high school students who are being prepared for careers in the digital creative field. The implementation methods include interactive training, hands-on practice with AI-based software, and guidance in digital content creation projects. Students are introduced to various AI applications and tools for automatic image editing, background removal, resolution enhancement, and the creation of text- and synthetic voice-based videos. The results of these activities demonstrate an improvement in students' understanding and skills in utilizing AI technology to support their creative processes. The digital products created through the training also demonstrate improved visual quality and efficiency in the production process. This activity is expected to serve as a model for integrating AI technology into vocational curricula and to foster the emergence of a creative generation adaptable to technological advancements.
Implementation of a Profit Website and Introduction of IoT Technology to Support Business Decision-Making for MSMEs in Plaosan Village Wahyuni, Ida; Arifin, Samsul; Aqromi, Nur Lailatul; Adipraja, Philip Faster Eka; Afiyah, Siti Nurul; Indahsari, Rina Dewi; Jaafar, Mime Azrina; Mustahidin, Nur Farhana; Ishak, Khairul Anuar; Suparman, Isyati Binti; Mohidin, Mohd. Sahran@Awang Bin
International Journal of Community Service (IJCS) Vol. 5 No. 1 (2026): January-June
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijcs.v5i1.1791

Abstract

Digital transformation in the agricultural Micro, Small, and Medium Enterprises (MSMEs) sector is crucial for enhancing the economic competitiveness of rural communities. Plaosan Village in Malang Regency, a producer of Mount Kawi coffee, faces challenges in financial management and agronomic efficiency. This community service program aims to: (1) implement the “Hitung Profit Kopi” web application (https://indowhiz.com/kopikawi) as a Decision Support System (DSS) for calculating farming profitability; and (2) introduce Internet of Things (IoT) concepts for post-harvest quality control. The program consisted of needs assessment, website design and testing, hands-on training on website use, and lectures plus demonstrations of an IoT prototype. Evaluation used short pre- and post-tests, satisfaction questionnaires, and observation of participants’ engagement during practice sessions. The results show that participants were able to operate the profit website, input their own business data, and interpret the calculated outputs. Furthermore, participants’ understanding of IoT and its potential applications increased, as indicated by improved post-test scores and feedback. This program represents an initial step towards the digital transformation of MSMEs in Plaosan Village through data-driven business management.
Co-Authors ., Setyorini A.A. Ketut Agung Cahyawan W Abdulloh Eizzy Irsyada Adit Sugiarto Aditya Tri Istanto Aqromi , Nur Lailatul Aryo Prakosa Broto Poernomo T.P Danar Kurniawan, Karolus Daniel, Kevin Oktavianus Dina Komar Lia Dyah Lestari Effendi, Mas Iwan Ali Endang Setyati Fadilla Cahyaningtyas Farah Rifdah Arzumni Farokhah, Lia Hari Kurniawan, Hironimus Ida Wahyuni Imam Zuhdi irsyada, abdulloh eizzi Ishak, Khairul Anuar Jaafar, Mime Azrina Jaenal Arifin Jaenal Arifin Justita Dura Kala'lembang, Adriani Kurniawan, Hironimus Hari Kurniawan, Karolus Danar Lailatu Aqromi , Nur Lalu Ryan Ravisafitra Louvareto Costa Câmara Marito De Oliveira Amaral Barreto Mohidin, Mohd. Sahran@Awang Bin Muhammad Saikhul Masykur Mustahidin, Nur Farhana Nasirin, Rahmad Khoirun Nur Lailatul Aqromi, Nur Lailatul Nur Munawaroh Nurul Afiyah, Siti Nusa, Rivale Belano Philip Faster Eka Adipraja Poernomo T.P, Broto Rizqi, Afif Naufal Samsul Arifin Setyorini . Setyorini Setyorini Siti Nurul Afiyah Siti Sendari Suastika Yulia Riska Suparman, Isyati Binti Supriadi, Joko Titania Dwi Andini Tivvany Aijen, Loudry Vivi Aida Fitria Wahyu Sakti Gunawan Irianto Yuliana Melita Pranoto Yuwono Sindunata Yuwono Sindunata, Yuwono Zaeni, Ilham Ari Elbaith