Article Per Year (5 Year)
p-Index From 2021 - 2026
3.171
P-Index
This Author published in this journals
All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Jurnal Sains dan Informatika Prosiding Seminar Nasional Riset Kuantitatif Terapan 2017 JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Teknologi Terapan Infotekmesin Jurnal E-Komtek Bulletin of Computer Science Research Jurnal Informatika: Jurnal Pengembangan IT
Riyadi Purwanto
Unknown Affiliation
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Neuroscience Social Sciences Transportation Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
Evaluasi Kinerja Model Machine Learning dalam Klasifikasi Penyakit THT: Studi Komparatif Naïve Bayes, SVM, dan Random Forest Prasetya, Nur Wachid Adi; Wanti, Linda Perdana; Purwanto, Riyadi; Bahroni, Isa; Listyaningrum, Rostika
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2798

Abstract

Classification of Ear, Nose, and Throat (ENT) diseases is essential to support faster and more accurate diagnosis. However, no prior studies have specifically compared the performance of Naïve Bayes, Support Vector Machine (SVM), and Random Forest algorithms in ENT cases. This study aims to evaluate and compare the three classification models in identifying ENT diseases with or without comorbidities. Medical record data were processed through preprocessing, feature selection using ANOVA, and class balancing with SMOTE. The results showed that SVM outperformed the other models with the highest accuracy (59%), followed by Random Forest (57%), and Naïve Bayes (48%). SVM demonstrated superior performance due to its consistent scores across all evaluation metrics. The study concludes that the choice of classification model significantly impacts the accuracy of ENT disease diagnosis.
Pemanfaatan Algoritma Random Forest Regression dalam Memprediksi Kepuasan Mahasiswa Terhadap Dosen Listyaningrum, Rostika; Purwanto, Riyadi; Dwi Novia Prasetyanti; Cahya Vikasari; Artdhita Fajar Pratiwi
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2808

Abstract

Student satisfaction with lecturers is a key indicator in assessing the quality of higher education. However, commonly used evaluation approaches remain largely descriptive and subjective, making them less effective in supporting sustainable quality improvement. Moreover, the comprehensive use of lecturer competency indicators in predictive models is still limited. This study addresses the gap by developing a student satisfaction prediction model using the Random Forest Regression algorithm, optimized through grid search and feature selection using the Recursive Feature Elimination (RFE) method combined with 5-fold cross-validation. Data were collected from the EDOM system of Politeknik Negeri Cilacap, involving 24 indicators based on national lecturer competency standards, and analyzed using R software. The best model was achieved with parameters mtry = 1 and ntree = 300, yielding RMSE = 0.0222, MAE = 0.0118, and R² = 0.9959. The three most influential indicators identified were structured assignments, diversity of teaching methods, and punctuality. These findings are expected to inform policies for improving the quality of higher education.
The Certainty Factor Method in An Expert System for Tuberculosis Disease Diagnosis Kumara, Dimas Maulana Dwi; Linda Perdana Wanti; Purwanto, Riyadi
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.549

Abstract

Tuberculosis is an infection caused by acid-fast bacilli (AFB) and is an infectious disease that can attack anyone through the air. This disease is hazardous and chronic, with a high prevalence among individuals aged 15-35 years. The diagnosis of tuberculosis traditionally takes a long time because it involves an interview process by medical experts and testing sputum samples in the laboratory to determine whether the patient is positive or negative for this disease. This process is not only time-consuming but also requires significant resources. To overcome this problem and speed up the diagnosis process, a technology-based approach is needed, namely the Expert System with the certainty factor method. This method can handle uncertainty in medical diagnosis by providing a certainty value for each observed symptom. This article discusses in depth the application of the certainty factor method in an expert system to diagnose Tuberculosis. By using this method, the system can provide faster and more accurate diagnosis results in diagnosing tuberculosis with a confidence level of 94.6% and reduce the workload of medical personnel. The application of the certainty factor method allows the integration of various symptoms and relevant medical data to produce more precise and reliable diagnostic conclusions.
Performance Evaluation and Optimization of an IoT-Based Fish Smoking Monitoring System for Ensuring Product Quality Syafirullah, Lutfi; Mahardika, Fajar; Purwanto, Riyadi; Prasetyanti, Dwi Novia
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15736

Abstract

Fish smoking is a widely used preservation method; however, the quality of smoked fish is highly dependent on the stability of temperature, humidity, and smoking duration. Manual control of these parameters has limitations and may reduce product quality. Existing studies on fish smoking monitoring systems primarily focus on temperature control without providing quantitative evaluation of how multi-parameter process stability affects product quality and shelf life. This study aims to design and implement an Internet of Things (IoT)-based monitoring system for fish smoking equipment to ensure the quality of smoked fish. The research method used is Research and Development (R&D), which includes needs analysis, system design, development, testing, and evaluation stages. The system integrates temperature and humidity sensors, a microcontroller, and an IoT platform for real-time monitoring. The test results show that the system is capable of monitoring the smoking chamber temperature within a range of 60–80 °C with an average error of ±1.5 °C compared to a standard measuring instrument, and maintaining an optimal temperature of 70 °C during the smoking process. Quality testing of the smoked fish indicates uniform doneness, a golden-brown color, firm texture, and an average moisture content reduction of 35%. Shelf-life testing shows that the smoked fish can last up to 7–10 days at room temperature and up to 21 days under cold storage without significant changes in aroma and texture. Unlike previous works, this study provides quantitative evidence that improved stability of multiple smoking parameters through IoT-based monitoring significantly enhances product quality consistency and extends the shelf life of smoked fish.
Optimalisasi Platform Digital: Studi Kasus Perancangan Website Profil Berfitur Virtual Tour 360° untuk Meningkatkan Digital Exposure Desa Widarapayung Wetan Prihantara, Andesita; Purwanto, Riyadi; Prasetyanti, Dwi Novia; Listyaningrum, Rostika; Vikasari, Cahya; Rahadi, Nur Wahyu; Abda'u, Prih Diantono
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 6 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i6.10044

Abstract

Abstrak - Permasalahan utama yang dihadapi Desa Wisata Widarapayung adalah rendahnya digital exposure (paparan digital) yang berimbas pada terbatasnya daya tarik bagi wisatawan domestik. Meskipun memiliki potensi wisata pantai yang indah dan pengelolaan yang baik, strategi promosi yang ada belum mengoptimalkan platform digital yang imersif dan mudah diakses. Penelitian ini bertujuan mengatasi kesenjangan tersebut melalui pengembangan sebuah website profil desa yang mengintegrasikan fitur Virtual Tour 360°. Metode pengembangan sistem menggunakan pendekatan Multimedia Development Life Cycle (MDLC) yang terdiri atas tahap konseptual, perancangan, pengumpulan materi, pembuatan, pengujian, dan distribusi. Hasil dari penelitian ini adalah sebuah website fungsional yang berhasil memetakan seluruh area wisata utama ke dalam pengalaman visual Virtual Tour 360°. Implementasi sistem ini memberikan manfaat signifikan dalam meningkatkan digital exposure dan daya tarik visual destinasi, yang ditunjukkan dengan respons positif dari pengelola wisata dan pengunjung website selama uji coba. Sistem ini tidak hanya berfungsi sebagai media promosi yang inovatif, tetapi juga menjadi model yang dapat diadopsi oleh desa wisata lainnya untuk memperkuat kehadiran mereka di dunia digital.Kata kunci: Digital Exposure; Virtual Tour 360°; Website Profil Desa; Desa Wisata; MDLC; Abstract - The main problem faced by Widarapayung Tourism Village is low digital exposure, which limits its appeal to domestic tourists. Despite its beautiful beach tourism potential and good management, existing promotional strategies have not optimized immersive and easily accessible digital platforms. This study aims to address this gap by developing a village profile website that integrates a 360° Virtual Tour feature. The system development method uses the Multimedia Development Life Cycle (MDLC) approach, which consists of conceptualization, design, material collection, creation, testing, and distribution stages. The result of this research is a functional website that successfully maps all major tourist areas into a 360° Virtual Tour visual experience. The implementation of this system provides significant benefits in increasing the digital exposure and visual appeal of the destination, as demonstrated by the positive responses from tourism managers and website visitors during the trial period. This system not only functions as an innovative promotional medium, but also serves as a model that can be adopted by other tourist villages to strengthen their presence in the digital world.Keywords : Digital Exposure; 360° Virtual Tour; Village Profile Website; Tourism Village; MDLC;
Co-Authors Abda'u, Prih Diantono Afrizal Abdi Musyafiq Alina Mei Cahyaningtyas Annas Setiawan Prabowo Cahya Vikasari Cahya Vikasari, Cahya Dodi Satriawan, Dodi Dwi Novia Prasetyanti Dwi Novia Prasetyanti Hera Susanti, Hera Ida Ayu Putu Sri Widnyani Isa Bahroni, Isa Kumara, Dimas Maulana Dwi Linda Perdana Wanti Listyaningrum, Rostika Lutfi Syafirullah Mahardika, Fajar Maharrani, Ratih Hafsarah Muh. Yamin, Muh. Novia Prasetyanti, Dwi Nur Wachid Adi Prasetya Nurrohman, Devi Taufiq Nur’Aini, Ummu Habibah Prasetyanti, Dwi Novia Prih Diantono Abda’u3 Prihantara, Andesita Rahadi, Nur Wahyu Rahadi, Nur Wahyu Ratih Hafsarah Maharrani Riezkiadi, Wily Rostika Listyaningrum Supriyono, Abdul Rohman Supriyono, Abdul Rohman Wahyu Rahadi, Nur Wanti, Linda Perdana