Article Per Year (5 Year)
p-Index From 2019 - 2024
5.871
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Faktor Exacta Conference on Innovation and Application of Science and Technology (CIASTECH) Petir Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Telematika Progresif: Jurnal Ilmiah Komputer Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Computer Science and Information Technologies Scientific Student Journal for Information, Technology and Science Jurnal Buana Pengabdian Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Scientific Journal of Informatics
Siregar, Amril Mutoi
Teknik Informatika, Universitas Buana Perjuangan Karawang
Religion Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

Published : 48 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

 1 
Comparison of Dairy Cow on Morphological Image Segmentation Model with Support Vector Machine Classification Amril Mutoi Siregar; Y Aris Purwanto; Sony Hartono Wijaya; Nahrowi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (328.719 KB) | DOI: 10.29207/resti.v6i4.4156

Abstract

Pattern recognition is viral in object recognition and classification, as it can cope with the complexity of problems related to the object of the image. For example, the category of dairy cows is essential for farmers to distinguish the quality of dairy cows for motherhood. The current problem with breeders is still using the selection process manually. If the selection process using the morphology of dairy cows requires the presence of computer vision. The purpose of this study is to make it easier for dairy farmers to choose the mothers to be farmed. This work uses several processes ranging from preprocessing, segmentation, and classification of images. This study used the classification of three segmentation algorithms, namely Canny, Mask Region-Based Convolutional Neural Networks (R-CNN), and K-Means. This method aims to compare the results of the segmentation algorithm model with SVM); the model is measured with accuracy, precision, recall, and F1 Score. The expected results get the most optimal model by using multiple resistant segmentation. The most optimal model testing achieved 90.29% accuracy, 92.49% precision, 89.39% recall, and 89.95% F1 Score with a training and testing ratio of 90:10. So the most optimal segmentation method uses the K-Means algorithm with a test ratio of 90:10.
Comparison of the Accuracy of Drug User Classification Models Using Machine Learning Methods Nursela Basuni; Amril Mutoi Siregar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5401

Abstract

Drug abuse are on the rise, with many users enter the addiction phase, often resulting in overdose and death. Drugs are chemical compounds that are capable of affecting biological functions, and they can induce feelings of happiness and reduce pain. To address this growing problem, a proactive measure is needed. Therefore, this study aims to classify drug users and non-users, so that health workers and therapists can educate about the dangers of drugs to non-users and rehabilitate drug users. This study uses drug consumption data taken from the UCI Irvine Machine Learning Repository. The data consist of 1885 rows with 32 attributes and 2 classes, where there are 18 types of legal and illegal drugs. This research utilizes machine learning methods, specifically Artificial Neural Networks (ANN), Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF), in addition to evaluation methods such as Confusion Matrix and Area Under Curve (AUC). The results showed that RF outperformed the other methods, with accuracy, precision, and recall of 93%, and an f1 score of 89%, while the AUC value was still suboptimal at 0.66. DT had the worst results, with 82% precision, 87% precision, 82% recall, 84% f1 score, and an AUC value of 0.56. With these results, this research can be continued into an application that can classify drug users and nonusers.
Co-Authors Abdul Mufti Ahmad Fauzi Ahmad Fauzi Alma Hidayanti Andri Juliyanto Anton Romadoni Junior Baihaqi, Kiki Ahmad Deden Wahiddin Dwi Sulistya Kusumaningrum Dwi Sulistya Kusumaningrum Dwi Sulistya Kusumaningrum Kusumaningrum Dwi Vina Wijaya Farkhina Dwi Utari Fitri Nur Masruriyah, Anis Hanny Hikmayanti Hanny Hikmayanti H Hanny Hikmayanti Handayani Indi Nurul Hassanah Indra, Jamaludin Jaman, Jajam Haerul Juwita, Ayu Ratna Lestari, Santi Arum Puspita Lutfiah Adeliana Maulana Abdur Rofik Mudzakir, Tohirin Al Mulya Cahya Ramadanty Murniasih Nahrowi Nahrowi Nahrowi Nofita Sari Nursela Basuni Permana, Tedi Priyatna, Bayu Rahmad Nahar Siregar Rizqi Fahrozi Salsa Desmalia Santi Arum Puspita Lestari Sekar Wuni Sinta Candra Dewi Sinung Suakanto SITI NURJANAH Siti Silvia Arifin Slamet Hermawan Sony Hartono Wijaya Sony Hartono Wijaya Sutan Faisal Sutan Faisal Sutan Faisal Tatang Rohana Tatang Rohana Tia Astiyah Hasan Tjong Wan Sen Tjong Wan Sen Tohirin Al Mudzakir Tohirin Al Mudzakir Tria Pratiwi Sutriyani Tukino Tukino Vira Bunga Tiara Wilda Amalia Y Aris Purwanto Yana Cahyana Yana Cahyana Cahyana Yholanda Maldini Yogi Firman Alfiansyah Yusuf Khoiruddin