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Menampilkan 11–20 dari 41 artikel
Meningkatkan Ketrampilan Masyarakat Desa Dengan Kreasi Bahan Pangan Lokal Jagung Di Giriwoyo Kabupaten Wonogiri: MENINGKATKAN KETERAMPILAN MASYARAKAT DESA DENGAN KREASI BAHAN PANGAN LOKAL JAGUNG DI GIRIWOYO KABUPATEN WONOGIRI
Sumarmi, Sumarmi
; Triyono, Kharis
; Karyantina, Merkuria
; Handayani, Dewi
; Rosariastuti, MMA Retno
Adi Widya: Jurnal Pengabdian Masyarakat
Vol 9
, No 1
(2025)
This community servis aims to improve the skills of the people of Giriwoyo village, Wonogiri, through training in the creation of local corn food. The methods used include practical training and demonstrations on making various processed corn-based products, such as cakes and snacks. Apart from that, this activity also succeeded in creating awareness of the potential of corn as a food source with economic value. It is hoped that participants can utilize the skills acquired to develop small busin...
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Youth Engagement in Global Affairs: FPCI Goes to SMA Muhammadiyah 3 Jakarta
An International Journal Tourism and Community Review
Vol 2
, No 2
(2025)
This article discusses the implementation of FPCI Goes to School (FGTS) 4.0, an educational outreach initiative conducted by the Foreign Policy Community of Indonesia (FPCI) Chapter UPN Veteran Jakarta, with the objective of increasing students’ awareness and understanding of international political dynamics. The initiative addresses the growing need for public literacy on global issues that often have indirect but significant effects on national and local communities, such as trade disruptions...
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Integrating Hybrid Statistical and Unsupervised LSTM-Guided Feature Extraction for Breast Cancer Detection
Setiadi, De Rosal Ignatius Moses
; Ojugo, Arnold Adimabua
; Pribadi, Octara
; Kartikadarma , Etika
; Setyoko, Bimo Haryo
; Widiono, Suyud
; Robet, Robet
; Aghaunor, Tabitha Chukwudi
; Ugbotu, Eferhire Valentine
Journal of Computing Theories and Applications
Vol 2
, No 4
(2025)
Breast cancer is the most prevalent cancer among women worldwide, requiring early and accurate diagnosis to reduce mortality. This study proposes a hybrid classification pipeline that integrates Hybrid Statistical Feature Selection (HSFS) with unsupervised LSTM-guided feature extraction for breast cancer detection using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Initially, 20 features were selected using HSFS based on Mutual Information, Chi-square, and Pearson Correlation. To addres...
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Aspect-Based Sentiment Analysis on E-commerce Reviews using BiGRU and Bi-Directional Attention Flow
Setiadi, De Rosal Ignatius Moses
; Warto, Warto
; Muslikh, Ahmad Rofiqul
; Nugroho, Kristiawan
; Safriandono, Achmad Nuruddin
Journal of Computing Theories and Applications
Vol 2
, No 4
(2025)
Aspect-based sentiment Analysis (ABSA) is vital in capturing customer opinions on specific e-commerce products and service attributes. This study proposes a hybrid deep learning model integrating Bi-Directional Gated Recurrent Units (BiGRU) and Bi-Directional Attention Flow (BiDAF) to perform aspect-level sentiment classification. BiGRU captures sequential dependencies, while BiDAF enhances attention by focusing on sentiment-relevant segments. The model is trained on an Amazon review dataset wit...
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Feature Fusion with Albumentation for Enhancing Monkeypox Detection Using Deep Learning Models
Pratama, Nizar Rafi
; Setiadi, De Rosal Ignatius Moses
; Harkespan, Imanuel
; Ojugo, Arnold Adimabua
Journal of Computing Theories and Applications
Vol 2
, No 3
(2025)
Monkeypox is a zoonotic disease caused by Orthopoxvirus, presenting clinical challenges due to its visual similarity to other dermatological conditions. Early and accurate detection is crucial to prevent further transmission, yet conventional diagnostic methods are often resource-intensive and time-consuming. This study proposes a deep learning-based classification model by integrating Xception and InceptionV3 using feature fusion to enhance performance in classifying Monkeypox skin lesions. Giv...
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Analisis Kesulitan Belajar Siswa Broken Home melalui AUM PTSDL di SMP PAB 8 Sampali
Wiweka Rajagukguk
; Miswanto Miswanto
; Rosalinda Pardede
; Nazwa Elminda Mendrof
; Tary Azahra
; Desi Sri Rezeki Boangmanalu
Inspirasi Dunia: Jurnal Riset Pendidikan dan Bahasa
Vol 4
, No 1
(2025)
AUM PTSDL is a problem expression tool in a typical student to see the effectiveness of student learning. The purpose of this research is to provide an overview of the implementation of the AUM PTSDL problem directly to students, especially in PAB 8 sampali junior high school students. in the application of AUM PTSDL can accelerate overcoming problems in learning, especially broken home students. This research uses a descriptive method with a case study approach. This research was conducted at P...
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A Quantum Circuit Learning-based Investigation: A Case Study in Iris Benchmark Dataset Binary Classification
Journal of Computing Theories and Applications
Vol 2
, No 3
(2025)
This study presents a Quantum Machine Learning (QML) architecture for perfectly classifying the Iris flower dataset. The research addresses improving classification accuracy using quantum models in machine-learning tasks. The objective is to demonstrate the effectiveness of QML approaches, specifically the Variational Quantum Circuit (VQC), Quantum Neural Network (QNN), and Quantum Support Vector Machine (QSVM), in achieving high performance on the Iris dataset. The proposed methods result in pe...
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Outlier Detection Using Gaussian Mixture Model Clustering to Optimize XGBoost for Credit Approval Prediction
Setiadi, De Rosal Ignatius Moses
; Muslikh, Ahmad Rofiqul
; Iriananda, Syahroni Wahyu
; Warto, Warto
; Gondohanindijo, Jutono
; Ojugo, Arnold Adimabua
Journal of Computing Theories and Applications
Vol 2
, No 2
(2024)
Credit approval prediction is one of the critical challenges in the financial industry, where the accuracy and efficiency of credit decision-making can significantly affect business risk. This study proposes an outlier detection method using the Gaussian Mixture Model (GMM) combined with Extreme Gradient Boosting (XGBoost) to improve prediction accuracy. GMM is used to detect outliers with a probabilistic approach, allowing for finer-grained anomaly identification compared to distance- or densit...
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Pengaruh Kompetensi, Kompleksitas dan Workload terhadap Kualitas Audit dengan Pemahaman Sistem Informasi Sebagai Variabel Moderasi
JURNAL EKONOMI MANAJEMEN AKUNTANSI
Vol 30
, No 2
(2024)
Purpose: The purpose of this study is to analyze the Influence of Competence, Complexity, Workload on Audit Quality. In addition, this study is to determine whether or not there is a role of understanding information systems in moderating the influence of Competence, Complexity, Workload on Audit Quality. Method: The population in this study were auditors working in Public Accounting Firms in Semarang City. The research sample used a purposive sampling technique. The data collection technique wa...
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Effects of Data Resampling on Predicting Customer Churn via a Comparative Tree-based Random Forest and XGBoost
Ako, Rita Erhovwo
; Aghware, Fidelis Obukohwo
; Okpor, Margaret Dumebi
; Akazue, Maureen Ifeanyi
; Yoro, Rume Elizabeth
; Ojugo, Arnold Adimabua
; Setiadi, De Rosal Ignatius Moses
; Odiakaose, Chris Chukwufunaya
; Abere, Reuben Akporube
; Emordi, Frances Uche
; Geteloma, Victor Ochuko
; Ejeh, Patrick Ogholuwarami
Journal of Computing Theories and Applications
Vol 2
, No 1
(2024)
Customer attrition has become the focus of many businesses today – since the online market space has continued to proffer customers, various choices and alternatives to goods, services, and products for their monies. Businesses must seek to improve value, meet customers' teething demands/needs, enhance their strategies toward customer retention, and better monetize. The study compares the effects of data resampling schemes on predicting customer churn for both Random Forest (RF) and XGBoost ense...
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