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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sistemasi: Jurnal Sistem Informasi SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Infomedia Progresif: Jurnal Ilmiah Komputer Buletin Ilmiah Sarjana Teknik Elektro Jurnal Abdi Insani Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Jurnal Algoritma SmartComp The Indonesian Journal of Computer Science Tanggap Masyarakat untuk Aksi dan Sinergi
Ashari, Wahid Miftahul
Universitas AMIKOM Yogyakarta
Agriculture, Biological Sciences & Forestry Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics

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Journal : Jurnal Algoritma

 1 
Optimalisasi Engine Optimalization On-Page untuk Meningkatkan Kinerja Situs Berita Digital Menggunakan Analisis CTR dan UX Martisa Fiorentina, Rinda; Miftahul Ashari, Wahid; Kuswanto, Jeki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2377

Abstract

This study analyzes the application of Search Engine Optimization (SEO) strategies on the Radar Jogja website to increase its visibility on search engines. With internet penetration in Indonesia reaching 78.19% in 2023, digital platforms have become an important necessity for media companies. Radar Jogja faces the challenge of competing for top positions on Google's search engine results pages (SERPs), where most users only access the first two pages. This study uses a descriptive-analytical method to evaluate key SEO elements such as titles, URLs, internal link structure, and page performance. Test results show that CTR increased from 2% to 4.75% and average position improved from 12th to 6th. In addition, dwell time increased to 2.25 minutes and bounce rate decreased, indicating a significant improvement in user experience. The results of this study contribute to content-based SEO strategies for local media to increase digital competitiveness and gain better visibility on search engines.
Kalibrasi Regresi Linier untuk Peningkatan Akurasi Load Cell pada Kursi Roda Cerdas Hakim, Muhamad Nauval; Miftahul Ashari, Wahid; Kuswanto, Jeki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3023

Abstract

Smart wheelchairs are an innovation designed to facilitate user mobility while monitoring their condition in real time. One of the main features developed is an integrated weight reading system. However, the accuracy of the sensor is still affected by sitting posture, body position, and surrounding environmental conditions. This study aims to improve the accuracy of the weighing system on smart wheelchairs by applying linear regression analysis as a sensor calibration method. Data collection was conducted under four conditions of use, namely sitting upright, sitting tilted, walking while sitting upright, and walking while sitting tilted, which represent variations in user load distribution. The calibration model was constructed using the average sensor reading data and evaluated using the R², MAE, and MAPE parameters. The results showed a significant improvement in accuracy with an R² value of 1.0000, MAE of 0.0687 kg, and MAPE of 0.111%, as well as a decrease in the average error from ±1.2 kg to ±0.07 kg after the calibration process. The linear regression method proved to be effective in improving the accuracy of sensor readings with light computational calculations. This study also demonstrates the potential of linear regression as an efficient lightweight calibration method for IoT-based medical systems, particularly on devices such as ESP32 or Arduino that display real-time, high-precision body weight measurements.
Perbandingan Kinerja Algoritma Machine Learning Deteksi Malware dengan Z-Score Normalization Hasil Terbaik pada Random Forest Gilang Ramadhan, Zaka; Miftahul Ashari, Wahid; Koprawi, Muhammad
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3077

Abstract

Malware detection is a major challenge in the world of cybersecurity, especially with the increasing complexity and variety of attacks. Traditional approaches are often unable to identify these new threats, making machine learning (ML) an effective solution. The purpose of this study is to compare the performance of three machine learning algorithms, namely Random Forest, XGBoost, and Support Vector Machine (SVM), in detecting malware in the SOMLAP dataset consisting of Windows executable files. Data processing, the use of the SMOTE technique for class imbalance, and assessment using metrics such as accuracy, precision, recall, and F1 score are all part of the research methodology. This study also applies Z-Score Normalization to reduce the influence of extreme values in the data, which helps the model handle data with different scales. The results show that Random Forest has the best performance with an accuracy of 99.16%, followed by XGBoost and SVM. Random Forest excels in the balance between precision, recall, and accuracy, making it the most effective algorithm for detecting malware. This study suggests further algorithm development using ensemble techniques and other optimizations to improve malware detection accuracy in the future.
Co-Authors Amalina, Inna Nur Andriyan Dwi Putra Arginanta, Dallarizki Asharudin, Firman Astari, Devi Wening Baita, Anna Dony Ariyus Eko Pramono Fajar Nur Aini Dwi Fatimah Fatimah, Fajar Nur Aini Dwi Febrian Putra Pratama Firman Asharudin Firman Asharudin Gilang Ramadhan, Zaka Hakim, Muhamad Nauval Hakim, Walidy Rahman Indrajati, Damar Jeki Kuswanto Jeki Kuswanto Koprawi, Muhammad Lukman Lukman Martisa Fiorentina, Rinda Muhammad Koprawi Muhammad Tofa Nurcholis Muhammad Wildan Nenden Ranuma Ratri Nevy Bella Samantha Norhikmah Norhikmah Nugraha, Anggit Ferdita Nur'aini Nurussa'adah, Erfina Putra, Andriyan Dwi Putra, Wahyu Sukestyastama Rahim, Abd Mizwar A. Ramadhan, Rafiq Fajar Rina Pramitasari Rohmaniah, Diana Saputra Aji, Dian Satrya Bhayangkara, Dimas Senie Destya Setiawan, Rangga Wahyu Sismoro, Heri Sunu Pamungkas, Hanfazano Rahmadimasti Supriatin Supriatin, Supriatin Yansyah, Aiko Nur Hendry Yoki Irawan