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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi dan Manajemen Informatika Jurnal Algoritma Eksergi: Chemical Engineering Journal JAIS (Journal of Applied Intelligent System) JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING International Journal of New Media Technology Sebatik Jurnal ULTIMATICS KOMPUTIKA - Jurnal Sistem Komputer Jurnal Pendidikan Fisika dan Teknologi METIK JURNAL Building of Informatics, Technology and Science Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) International Journal of Advances in Data and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) JoMMiT : Jurnal Multi Media dan IT Jurnal Algoritma Literasi: Jurnal Pendidikan Guru Indonesia NERO (Networking Engineering Research Operation) Journal of Multiscale Materials Informatics Jurnal Inovasi Pendidikan dan Pembelajaran Journal of Teaching and Elementary Education
Akrom, Muhamad
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

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Journal : Jurnal Algoritma

 1 
Investigasi Model Machine Learning Regresi Pada Senyawa Obat Sebagai Inhibitor Korosi Rosyid, Muhammad Reesa; Mawaddah, Lubna; Akrom, Muhamad
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1598

Abstract

Korosi merupakan tantangan signifikan bagi daya tahan material, yang seringkali menyebabkan kerugian ekonomi yang besar. Penelitian ini memanfaatkan teknik Machine Learning (ML) untuk memprediksi efektivitas senyawa obat sebagai inhibitor korosi. Kami menggunakan lima algoritma ML yang menonjol: Regresi Linear, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Random Forest, dan XGBoost. Model-model ini dilatih dan dievaluasi menggunakan dataset yang terdiri dari 14 fitur molekuler dengan efisiensi inhibisi korosi (IE%) sebagai variabel target. Hasil pelatihan model awal mengidentifikasi Random Forest dan XGBoost sebagai yang berkinerja terbaik berdasarkan metrik seperti Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), dan R-squared (R²). Penyetelan hiperparameter lebih lanjut menggunakan GridSearchCV menunjukkan bahwa XGBoost, setelah penyetelan, secara signifikan mengungguli model lainnya, mencapai kesalahan terendah dan nilai R² tertinggi, menunjukkan akurasi prediktif yang superior untuk aplikasi ini. Temuan ini menegaskan potensi ML, khususnya XGBoost, dalam meningkatkan pemodelan prediktif inhibitor korosi, sehingga memberikan wawasan berharga bagi bidang ilmu korosi.
Klasifikasi Otomatis Korosi Menggunakan Convolutional Neural Network dan Transfer Learning dengan Model MobileNetV2 Rizky Pratama, Muhammad Hafiz; Akrom, Muhamad; Santosa, Akbar Priyo; Rosyid, Muhammad Reesa; Mawaddah, Lubna
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2182

Abstract

Corrosion is a major problem that causes significant economic losses in various industries, including transportation, energy, and manufacturing. Early detection of corrosion is essential to reduce its negative impact. This research aims to develop an automatic corrosion classification system based on Convolutional Neural Networks (CNN) with a transfer learning approach. Two models were evaluated, namely a simple CNN architecture and the pre-trained MobileNetV2. The dataset consists of corrosion and non-corrosion images divided into training, validation, and testing data. Data augmentation techniques are applied to increase the variety and number of samples in the training process. The experimental results show that MobileNetV2 achieves a testing accuracy of 95%, which is higher than that of a simple CNN that only reaches 82%. In addition, MobileNetV2 showed better performance in identifying both classes (corrosion and non-corrosion). Despite indications of overfitting due to dataset limitations, the transfer learning approach significantly improved the classification performance. This system has the potential to be applied in real-time industrial applications to reduce economic losses due to corrosion. Further research is recommended to improve the generalization of the model by using a larger dataset and applying more robust regularization techniques.
Co-Authors Achmad Wahid Kurniawan Adiprasetya, Vicenzo Frendyatha Aldiansah, Ilham Pratama Alfa Trisnapradika, Gustina Amri, Sahrul Ardyansyah, Nibras Bahy Ariyanto, Noval Ayu Pertiwi Budi, Setyo De Rosal Ignatius Moses Setiadi Desrina Desrina Diah Rahayu Ningtias, Diah Rahayu Dian Arif Rachman Ditha Sabrani, Amalia Gumelar, Rizky Syah habiburrahman, Lalu Hadi, Mashal Hariati, Endang Harun Al Azies Herawati, Wise Herowati, Wise Hidayat, Ari Hidayat, Novianto Hidayat, Novianto Nur Hilmy, Nur Amalina Rahmaputri HOTIMAH, NURUL Huryati, Huryati Husnawati Amini, Titik Ignasius, Darnell Ikhsanudin, Nur Islahudin Jalaluddin Jalaluddin Jannah, Rauhun Junaidi Junaidi Kurniawan, Azril Lingga Dewi, Adhe Maharani, Desvita Mawaddah, Lubna Miyati, Hijiul Moch Anjas Aprihartha Muhamad Fadil Muhammad Naufal Muhammad Sanusi Mulyana, Yudha Musafir, Musafir Noor Ageng Setiyanto, Noor Ageng Nur Safitri, Aprilyani Oktaviansyah, Brenendra Putra Prabowo, Wahyu Aji Eko Pratama, Fikri Luqman Putra, Dzaki Asari Surya Putranto, Nicholaus Verdhy Rachmat Imam Muslim Raesah Ayu, Siti Rahman, Irfan Fauzia Ramadhani, Johana Oktavia Rana, Bastion Jader Ristina Wahyu Astuti Rizky Pratama, Muhammad Hafiz Rizqi, Aliyah Zahratu Rosyid, Muhammad Reesa Sabahiyah, Sabahiyah Safitri, Aprilyani Nur Sahrul Kadri, Agus Santosa, Akbar Priyo setiawan, nabila putri Sheilla Rully Anggita Sudibyo, Usman Sumarjono, Cornellius Adryan Putra Supriadi Rustad T. Sutojo Trinapradika, Gustina Alfa Trisnapradika, Gustina Alfa Umam, Saripul Widia Wati, Via Yani, Rindi Zihab, Zihab Zulfiani, Nila