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All Journal International Conference on Engineering and Technology Development (ICETD) Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Ilmiah Sinus bit-Tech Jurnal Informatika Ekonomi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer System and Informatics (JoSYC) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal Automation Computer Information System (JACIS) Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Journal of Practical Computer Science (JPCS) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Mandiri Universal Raharja Community (URNITY Journal) Jurnal Lentera Pengabdian Jurnal Informatika Ekonomi Bisnis Riwayat: Educational Journal of History and Humanities International Journal of Applied Research and Sustainable Sciences (IJARSS) International Journal of Sustainable Applied Sciences (IJSAS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian SAINTEK International Journal of Integrated Science and Technology EduBase: Journal of Basic Education
Muhamad Fatchan
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Transforming Supply Chain Forecasting Using Transformer Models and K-NN Analysis Moch. Nauval Faris Muzaki; Muhamad Fatchan; Irfan Afriantoro
International Journal of Applied Research and Sustainable Sciences Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijarss.v2i6.2026

Abstract

The study optimizes supply chain logistics in Asia using the K-Nearest Neighbors (K-NN) algorithm to enhance delivery efficiency and profitability. It suggests that future research should explore ensemble methods and deep learning models for better accuracy and robustness. Comparative analyses with traditional models provide valuable insights. Investigating the impact of real-time data analytics and IoT can improve visibility and control. Big data analytics for predictive models in risk management and resilience against disruptions like natural disasters and geopolitical instability is crucial. Exploring collaborative networks where stakeholders share data and resources can significantly advance logistics efficiency. These directions will help develop efficient, resilient, and sustainable supply chain systems, offering practical solutions for businesses in Asia's complex market.
Detect the Activity of Benign and Malignant Breast Cancer Ayu Fitriyani; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1870

Abstract

Breast cancer detection is an important stage for early cancer diagnosis. In this study, a Convolutional Neural Network (CNN) algorithm is used to detect breast cancer. The dataset used consists of MRI scan images of benign and malignant breast cancer, which are processed through breast image cropping and data augmentation. The model was trained using CNN architecture with transfer learning method of VGG-16 model. The results of the model training showed good performance with an accuracy of 62%. These findings show the potential of using CNN and transfer learning in improving early detection of breast cancer.
Valuation of Svm Kernel Performance in Organic and Non-Organic Waste Classification Dahyoung Yenuargo; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1873

Abstract

In an era of increasing concern for environmental sustainability, waste management remains an important global issue. Efficient waste classification, in particular distinguishing between organic and recyclable materials, is essential for reducing environmental impact. Traditional manual classification methods are often error-prone and inefficient. This research evaluates the performance of SVM models with RBF and Polynomial kernels for waste classification, using SqueezeNet for feature extraction. Datasets from Kaggle were preprocessed and augmented to improve model training. The experimental results show that the SVM model with RBF kernel outperforms the Polynomial kernel in classifying organic and recyclable waste, with an accuracy of 97.9% compared to 97.3% for the Polynomial kernel. This finding underscores the importance of kernel selection and parameter tuning in optimising SVM models for non-linear classification tasks. This research contributes to the development of more efficient and accurate waste classification technologies, promoting better waste management practices. Further research is recommended to explore advanced feature extraction methods and expand the scope of classification to cover a wider range of waste categories.
Industrial Safety Helmet Detection: Innovative CNN-Based Classification Approach Febro Herdyanto; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1925

Abstract

This study presents the development and evaluation of a CNN-based model for detecting safety helmets in industrial settings. Utilizing a dataset from GitHub, which includes images of individuals wearing safety helmets in various industrial environments, the model was trained using the YOLOv8 architecture over 100 epochs. The comprehensive training process involved data augmentation techniques to enhance generalization capabilities. The evaluation results demonstrated high precision (0.92) and recall (0.856) for helmet detection, with an overall mAP50 of 0.766. Visual analysis through precision-confidence curves confirmed the model's high reliability in detecting helmets at higher confidence thresholds. These findings suggest that the implementation of this model in real-time monitoring systems could significantly enhance industrial safety by reducing manual inspection efforts and ensuring compliance with safety regulations
PENGGUNAAN AHP DALAM SISTEM PENGAMBILAN KEPUTUSAN PEMILIHAN MARKETPLACE: STUDI KASUS : MARKETPLACE E-COMMERCE DI ERA DIGITAL Reza Maulana, Muhammad; Ariza, Rini; Hidayat, Chaerul; Halim Anshor, Abdul; Fatchan, Muhamad
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12447

Abstract

Marketplace merupakan salah satu platform e-commerce terpopuler di Indonesia karena kemudahan transaksi dan aksesibilitas yang ditawarkannya. Namun, banyaknya pilihan di marketplace dapat membuat konsumen bingung saat menentukan platform mana yang memenuhi kebutuhan mereka. Penelitian ini bertujuan untuk menerapkan metode Analytical Hierarchy Process (AHP) dalam sistem pengambilan keputusan untuk membantu konsumen memilih marketplace terbaik berdasarkan banyak kriteria seperti harga, minat dan diskon. Data dikumpulkan melalui kuesioner kepada 10 responden yang aktif berbelanja online. Hasil analisis menunjukkan bahwa Shopee menempati posisi terdepan sebagai marketplace yang dipilih konsumen, disusul oleh Lazada dan Tokopedia. Kriteria diskon memiliki pengaruh paling besar terhadap keputusan konsumen. Kami berharap penelitian ini dapat menjadi referensi bagi konsumen untuk memilih marketplace yang tepat serta membantu pengusaha meningkatkan strategi pemasarannya
Implementasi Algoritma K-Nearest Neighbor dalam Klasifikasi Penyakit Kanker Paru Paru Hadiansyah, Zikri; Rozikin, Zaenur; Fatchan, Muhamad
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6195

Abstract

Lung cancer is one type of cancer with the highest death rate in the world. Smoking is the main risk factor that causes 20% of cancer deaths and 70% of lung cancer deaths in the world. However, people who do not smoke can also suffer from lung cancer, especially if they are frequently exposed to air pollution, live in an environment contaminated with dangerous substances, or have a family member who suffers from lung cancer. Early detection in the classification of lung cancer is an important factor in increasing the patient's chances of survival. Therefore, this study aims to classify lung cancer using the K-Nearest Neighbor algorithm. The K-Nearest Neighbor algorithm was chosen because in various studies it has a better level of accuracy compared to other supervised learning algorithms. To overcome data imbalance, the Random oversampling technique is used. Based on tests carried out using the Confusion Matrix, the results of measuring the performance values ​​of Accuracy, Precision, Recall and f1-score using the K-Nearest Neighbor algorithm with Random oversampling technique, it can be concluded that the K-Nearest Neighbor algorithm received an Accuracy value of 0.99, Precision 0.99, Recall 0.99 and f1-score 0.99.
Perbandingan Efektivitas Metode SAW dan AHP dalam Seleksi Penerima Beasiswa di LIPIA Jakarta Clarita, Anggita Risqi Nur; Fadhillah, Faizah Via; Nurhaliza, Zahra; Fatchan, Muhamad; Anshor, Abdul Halim
Jurnal Ilmiah SINUS Vol 23, No 1 (2025): Vol. 23 No. 1, Januari 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v23i1.877

Abstract

This research discusses the application of SAW and AHP methods in the selection process of scholarship recipients at LIPIA Jakarta. Given the complexity of assessing potential recipients, both methods are evaluated to determine which one provides the most accurate and efficient results. SAW and AHP methods are used to process the assessment of several criteria, such as Arabic Written Test, Arabic Oral Test, Diploma Score, Memorization and Good Behavior which have been given weights and scales according to their importance. The main objective of this research is to compare the effectiveness of the two methods in determining scholarship recipients who meet the criteria at LIPIA. The results of this comparison are expected to provide recommendations regarding the most suitable method to improve objectivity, accuracy, and efficiency in scholarship selection.
SISTEM INFORMASI RAWAT JALAN BERBASIS WEB MENGGUNAKAN METODE WATERFALL ( STUDI KASUS PANTI PENGOBATAN GURU SINGA ) Yupita Fitria Riyanti; Muhamad Fatchan; Edora
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 5 No 3 (2023): Desember
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v5i3.263

Abstract

Perkembangan teknologi mengalami kemajuan yang begitu pesat, salah satunya pada bidang kesehatan, dengan menjadikan komputer sebagai salah satu alat penunjang yang sangat di butuhkan dalam pengelolahan data dan dalam penyajian data informasi. Panti pengobatan guru singa ini mulai di rasakan perlunya pengembangan untuk meningkatkan kebutuhan pelayanan kesehatan bagi Masyarakat. Proses pendaftaran pasien rawat jalan masih menggunakan cara yang manual, yang meliputi kegiatan pendaftaran pasien, pencarian data rekam medis pasien, dengan adanya perkembangan teknologi sistem informasi yang semakin pesat. Maka penulis merancang sistem informasi rawat jalan berbasis web yang menggunakan metode waterfall dengan bahasa pemograman PHP dan database MySql. penerapan metode waterfall terhadap system informasi rawat jalan berbasis web pada panti pengobatan guru singa menjadi efektif dan efisien dengan memberikan penyelesaian dalam permasalah data rekam medis, pendaftaran pasien rawat jalan, tidak terjadinya penumpukan dokumen. Melalui penerapan sistem yang telah dirancang diharapkan dapat mempermudah dan mempercepat pengelolaan data pasien rekam medis di panti pengobatan gurur singa. Perancangan sistem rawat jalan ini dapat dijadikan sebagai referensi penelitian selanjutnya dan disarankan untuk dapat disempurnakan dengan menambahkan fitur-fitur yang dibutuhkan di masa depan.
Comparison of ReLu Activation and Logistics Functions in Classification of Casting Product Defects with Perceptron Multilayer Approach Apriyandi M; Muhamad Fatchan; Suratman
International Journal of Integrated Science and Technology Vol. 2 No. 10 (2024): October 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i10.2596

Abstract

In the industrial sector, production quality is very important for company operations and must be managed effectively. ISO 9001 emphasizes quality management to direct processes and improve organizational efficiency. Quality control is important to prevent defects in materials, because foundry production must produce high quality materials so that they can be used in the long term. ISO 14001 environmental management environment, with high output impacts on the environment due to lack of transparency. This research uses ReLu and Logistics Activities to improve casting quality using multilayer perceptron technology, finding that ReLu activities have a higher dominance (99%) compared to other actives.
MENGOPTIMALKAN KLASIFIKASI SINYAL ELECTROENCEPHALOGRAM UNTUK MENDETEKSI KEJANG EPILEPSI DENGAN BACKPROPAGATION NEURAL NETWORK Najwa Sabilla, Nurul; Fatchan, Muhamad; Aguswin, Ahmad
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13428

Abstract

Epilepsi adalah gangguan neurologis yang memengaruhi lebih dari 50 juta orang di seluruh dunia, dengan sekitar 6 juta penderita di Eropa. Penyakit ini memiliki tingkat kesalahan diagnosis yang tinggi dan dapat menyebabkan gangguan psikologis akibat stigma sosial. Klasifikasi epilepsi berdasarkan Electroencephalogram (EEG) sangat penting dalam diagnosis, namun interpretasi hasil EEG seringkali sulit dan memerlukan keahlian khusus. Kesulitan dalam mendiagnosis epilepsi secara akurat akibat interpretasi EEG yang membutuhkan pengalaman dan waktu, hal ini memengaruhi efektivitas pengobatan. Penelitian ini bertujuan untuk mengoptimalkan klasifikasi kejang epilepsi secara akurat dengan menghasilkan performa tinggi. Backpropagation Neural Network adalah salah satu metode dari pempelajaran mendalam digunakan pada kasus memprediksi klasifikasi untuk menurunkan tingkat kesalahan dalam diagnosis dan pemantauan kejang epilepsi dan non-epilepsi. Hasil dari penelitian ini menghasilkan tingkat akurasi 98,63%. Pelatihan pada split data 80:20, learning rate 0.1, jumlah neuron pada hidden layer terdapat 9 neuron, dengan 100 epoch pelatihan. Saat dilatih menggunakan data target berhasil digunakan dalam 418 diprediksi sebagai epilepsi dan 1791 sebagai non-epilepsi.
Co-Authors . Ermanto . Suratman Abdul Halim Anshor Abdul Hasyim Abizar Ar Rifa’i Rifa’i Agus Suwarno, Agus Aguswin, Ahmad Ahmad Turmudi Zy al fiyan Andri Firmansyah Andrian Andrian Anisa Rahmawati Annisa Maulana Majid Aprila Hardi, Resty Apriyandi M Ariza, Rini Asep Hidayat Asep Suprianto Ayu Fitriyani Aziz, Faruq B.M.A.S. Anaconda Bangkara Bagoes Ramadhan Bagus Dwi Saputro Butsianto, Sufajar Clarita, Anggita Risqi Nur Dahyoung Yenuargo Dendy K. Pramudito Doni, Muhamad Edora Edora Edora Edy Widodo Edy Widodo Edy Widodo Elkin Rilvani Endah Yaodah Kodratilah Fadhillah, Faizah Via Febro Herdyanto Fitriani Galang Rintang Widya Pratama Hadiansyah, Zikri Halim Anshor, Abdul Hari Sugeng Hendra Lesmana Hidayat, Chaerul Indra Permana, Indra Irfan Afriantoro Irsyad Syhruddin Jamroni, A. Reza Baehaqa Jamroni Linda Marlinda Listanto, Firgiawan Marayasa, I Gde Bayu Priyambada Moch. Nauval Faris Muzaki Muhamad Ekhsan Muhamad Sudharsono Muhammad Farhan Alfarizi Muhtajuddin Danny Najwa Sabilla, Nurul Nanang Tedi Kurniadi Nasution, Annio Indah Lestari Naufal Muyassar Naya, Candra Ngudi Wiyatno, Tri Nuraeniah, Iin Nurhadi Surojudin Nurhaliza, Zahra Nur’aeni Nur’aeni Oktavianto, Rainal Zulian Pengestu, Rayendra Pipin Angela Purwanto Purwanto Putri Nabila Amir Qori yumansyah Qori Retno Purwani Setyaningrum Reza Maulana, Muhammad Rika Anugrahaini, Savariana Rindiani Tri Lestari Rozikin, Zaenur Sifa Fauziah Sri Indriyani Sugiarto, Jumat Azzam SUPRAPTO suratman Surya Bintarti Surya Bintarti Suryadi Tedi, Nanang Tiani Ayu Lestari TITIN SUNARYATI Tri Ngudi Wiyatno Turmudi Zy, Ahmad Valentin*, M Ryan Bagus Wahyu Hadi Kristanto Wahyu Hadikristanto Wahyu Indrarti Widi Winjani Widiyawati , Widiyawati Yumansyah, Qori Yupita Fitria Riyanti