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Menampilkan 1–10 dari 35 artikel
A Web-Based Ultrasonic Sensor-Based Water Level Measurement System in the Water Reservoir at Diponegoro Vocational School (Case Study at Diponegoro Vocational School)
Muhammad, Rasul Louise
; Setiadi, Teguh
; Suasana, Iman Saufik
; Muhammad, Rasul Louise
; Setiadi, Teguh
; Suasana, Iman Saufik
JUISI : Jurnal Ilmiah Sistem Informasi
Vol 4
, No 3
(2025)
Pengelolaan air yang efisien merupakan aspek penting dalam mendukung kegiatan operasional di SMK Diponegoro. Tandon air yang selama ini dikelola secara manual sering menimbulkan kendala, seperti tandon meluap atau kosong akibat keterlambatan pengisian. Hal ini menyebabkan pemborosan air dan listrik serta meningkatkan beban kerja staf pengelola. Untuk mengatasi permasalahan tersebut, penelitian ini merancang sistem pendeteksi ketinggian air otomatis berbasis sensor ultrasonik dan Programmable Log...
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Integrating Quantum, Deep, and Classic Features with Attention-Guided AdaBoost for Medical Risk Prediction
Kusuma, Muh Galuh Surya Putra
; Setiadi, De Rosal Ignatius Moses
; Herowati, Wise
; Sutojo, T.
; Adi, Prajanto Wahyu
; Dutta, Pushan Kumar
; Nguyen, Minh T.
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
Chronic diseases such as chronic kidney disease (CKD), diabetes, and heart disease remain major causes of mortality worldwide, highlighting the need for accurate and interpretable diagnostic models. However, conventional machine learning methods often face challenges of limited generalization, feature redundancy, and class imbalance in medical datasets. This study proposes an integrated classification framework that unifies three complementary feature paradigms: classical tabular attributes, dee...
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PENGARUH LATIHAN KEKUATAN DAN DIET PROTEIN TERHADAP KADAR GULA DARAH PADA LANSIA PREDIABET
Maulana, Nova
; Fatimah, Andini Nur
; Febsi, Yania
; Nurlita, Lani
; Fiana, Marista
; Yuarsa, Tri Agus
; Budiman, Muhammad Algifari
; Setiadi, Adi
; Hidayat, Arif
Nursing Science Journal
Vol 6
, No 1
(2025)
Pendahuluan : Kadar gula darah perlu dijaga dalam batas normal karena kadar yang terlalu tinggi atau terlalu rendah dapat menyebabkan masalah Kesehatan. Hipoglikemia bisa menyebabkan gejala yang mengancam jiwa. sedangkan hiperglikemia sering terkait dengan diabetes, dan bisa menyebabkan berbagai komplikasi serius jika tidak terkontrol. Tujuan : penelitian ini yaitu untuk menganalisa pengaruh technologi angkat beban dan diet protein terhadap kadar gula darah pada lansia prediabet. Metode : P...
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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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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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Evaluasi Keamanan Website dengan Menggunakan Metode NIST SP 800-115
Populer: Jurnal Penelitian Mahasiswa
Vol 3
, No 4
(2024)
Perkembangan teknologi yang semakin meningkat seiring dengan berjalanya waktu dimana semua pengguna harus mempelajari teknologi yang semakin berkembang. Dengan perkembangan yang semakin meningkat maka ancaman dalam pengguna internet akan semakin meningkat akan serangan siber dengan mencuri data atau informasi peribadi melalui website. Maka perlu dilakukan pengujian kerentanan keamanan pada website untuk mengurangi ancaman dari serangan siber dengan memberikan solusi yang dapat digunakan sebagai...
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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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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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