Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

4.557

P-Index

This Author published in this journals

All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Syntax Jurnal Informatika Indonesian Journal of Artificial Intelligence and Data Mining JMM (Jurnal Masyarakat Mandiri) SINTECH (Science and Information Technology) Journal Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama Journal of Information Systems and Informatics Jurnal Sistem Informasi dan Informatika (SIMIKA) JISA (Jurnal Informatika dan Sains) International Journal of Advances in Data and Information Systems Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Pengabdian Masyarakat Nusantara Journal of Artificial Intelligence and Engineering Applications (JAIEA) IT For Society : Journal of Information Technology Journal of Comprehensive Science Jurnal Hasil Penelitian dan Pengembangan (JHPP) Journal of Data Science, Technology, and Artificial Intelligence

Fahmi, Hasanul

Unknown Affiliation

Author-ID : 1150697

Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

Published : 39 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4

Penerapan Sistem Pakar Mendiagnosa Kerusakan Sepeda Motor Automatic Dan Injeksi Berbasis Android Dengan Metode Forward Chaining Sihombing, Darvin Markus; Fahmi, Hasanul
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 4 No. 2 (2021): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9767/jikomsi.v4i2.144

Motorbikes are a means of transportation that is widely used by Indonesians, therefore knowledge about motorbikes, especially if there is damage, needs to be controlled by the user. The system that was developed to diagnose motorcycle damage is called an automatic motorcycle failure diagnosis system and injection. The purpose of this research is to develop a diagnosis system for automatic motorcycle damage and injection, which uses the Forward Chaining method where the steps are carried out using basic data and certain rules or codes to build a knowledge base in the form of rules used in diagnosing automatic motorcycle damage and injection. . Method stages starting from assessment, knowledge acquisition, design, testing, documentation and maintenance. Based on the steps that have been carried out, a prototype system for automatic motorcycle damage diagnosis and injection is obtained using the Android Studio programming language. This expert system provides facilities in the form of a page containing the automatic motorcycle damage diagnosis system and injection, then a damage list page, then the user can consult about automatic motorcycle damage and injection according to the symptoms, so the system will display the results of diagnosing automatic motorcycle damage. and injection in the form of the name of the vehicle damage and its solution.

Analisis Sistem Pakar Dengan Metode Forward Chaining untuk Pengenalan Jenis Kulit Wajah pada Manusia Sulindawaty, Sulindawaty; Fahmi, Hasanul
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 5 No. 2 (2022): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jikomsi.v5i2.336

Wajah merupakan hal utama yang menjadi perhatian maupun daya tarik bagi sesorang dalam berpenampilan. Kulit wajah yang sehat dan bersih menjadi hal yang sangat didambakan oleh manusia. Keberagaman produk kosmetik serta praktik kecantikan menjadi salah satu yang sangat diminati untuk memberikan solusi kesehatan dan kecantikan kulit wajah. Untuk mempermudah setiap orang dalam mengenali jenis kulit wajah, dapat diterapkan sistem pakar dengan menggunakan metode forward chaining. Sistem Pakar dapat memberikan solusi dalam menganalisis jenis kulit wajah karena pada sistem ini data yang diperoleh dari para pakar secara langsusng. Forward chaining digunakan untuk menelusuri jenis kulit wajah berdasarkan penalaran atau pelacakan suatu data dari fakta-fakta yang diperoleh untuk mendapatkan kesimpulan. Dari pengujian yang dilakukan dalam penelitian ini menunjukkan nilai akurasi sebesar 83,3% yang menunjukkan hasil sesuai dengan diagnosa pakar. Hasil penelitian ini menunjukan bahwa sistem pakar dengan menerapkan metode backward chaining efektif dalam menghasilkan informasi untuk mengetahui jenis kulit wajah pada manusia sehingga dapat melakukan perawatan maupun memilih jenis kosmetik yang sesuai.

Deblurring Photos With Lucy-Richardson And Wiener Filter Algorithm In Rgba Color Rustam, Michiavelly; Fahmi, Hasanul; Herry Utomo, Wiranto
Journal of Comprehensive Science Vol. 3 No. 3 (2024): Journal of Comprehensive Science (JCS)
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v3i3.655

Photographers and social media influencers create engaging posts every day to captivate their audience with engaging content.Central to success is the need for high-quality images that allow the viewer to clearly perceive and engage with the information being conveyed. However, a persistent challenge in the field of photography is that hand tremors during image capture can result in accidentally blurred photos. In response, I propose a comprehensive solution that leverages the advanced Lucy-Richardson (L-R) and Wiener filter algorithms.This innovative approach is tailored to reduce the effects of blur caused by unstable handling, allowing for sharper, noise-free images. By incorporating these cutting-edge algorithms into their workflows, creators can not only reduce the frustration of blurry footage, but also increase the overall visual impact of their posts, foster deeper connections with their viewers, and create dynamic setting a new standard of excellence in a global world.

Developing an Inclusive Information System Interface: The Design of an Accessible Bus Information Board Using Ergonomic and Visual Communication Principles Aulia, Afina Nisa; Fahmi, Hasanul; Wahyuni, Elda; Ayu, Desita Puspita; Cexarian, Hafizh
IT for Society Vol 9, No 1 (2024): Vol 9, No 1
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v9i1.6351

Hybrid Feature Combination of TF-IDF and BERT for Enhanced Information Retrieval Accuracy Aprilio, Pajri; Felix, Michael; Nugraha, Putu Surya; Fahmi, Hasanul
JISA(Jurnal Informatika dan Sains) Vol 8, No 1 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i1.2179

Text representation is a critical component in Natural Language Processing tasks such as information retrieval and text classification. Traditional approaches like Term Frequency-Inverse Document Frequency (TF-IDF) provide a simple and efficient way to represent term importance but lack the ability to capture semantic meaning. On the other hand, deep learning models such as Bidirectional Encoder Representations from Transformers (BERT) produce context-aware embeddings that enhance semantic understanding but may overlook exact term relevance. This study proposes a hybrid approach that combines TF-IDF and BERT through a weighted feature-level fusion strategy. The TF-IDF vectors are reduced in dimension using Truncated Singular Value Decomposition and aligned with BERT vectors. The combined representation is used to train a fully connected neural network for binary classification of document relevance. The model was evaluated using the CISI benchmark dataset and compared with standalone TF-IDF and BERT models. Experimental results show that the hybrid model achieved a training accuracy of 97.43 percent and the highest test accuracy of 80.02 percent, outperforming individual methods. These findings confirm that combining lexical and contextual features can enhance classification accuracy and generalization. This approach provides a more robust solution for improving real-world information retrieval systems where both term specificity and contextual relevance are important.

PREDICTING REVENUE OF SHARIA BANKING TRANSACTIONS USING RNN, LSTM, GRU, DECISION TREE, AND QSPM (CASE STUDY: PT BANK TBV SYARIAH) Septian Fakhrudin Arianto; Hasanul Fahmi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3467

The banking business will continue to grow significantly along with the increase in the number of transactions carried out by customers through the channels provided by the bank. The variety of products and features offered by PT Bank TBV Syariah to customers means that resources are not optimal. Hence, the bank's revenue growth target still needs to be achieved. This research aims to predict transactions that can affect bank revenues by using transaction data sources for the period January 2022 to February 2024 and which products and features need to be optimized so that it is hoped that banks can run their business appropriately and according to targets. The methods in this research are the RNN, LSTM, GRU, and Decision Tree methods. To enrich information, this research adds QSPM-based strategy analysis using SWOT that the company previously defined. The expected results are to prove the effectiveness of the model used in predicting PT Bank TBV Syariah transaction data to produce MAE, MSE, and RMSE with the lowest values, as well as recommendations that PT Bank TBV Syariah must carry out to increase revenue. This research is expected to provide accurate and effective predictions for projecting PT Bank TBV Syariah transaction data, support strategic decision-making, and produce recommendations for significantly increasing bank income.

The Application of ANN Predicts Students' Understanding of Subjects During Online Learning Using the Backpropagation Algorithm at SMAN 1 Perbaungan rendiarno rendiarno; Hasanul Fahmi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 3 (2022): June 2022
Publisher : Yayasan Kita Menulis

This study is a study to predict the level of students' understanding of the subjects given by educators at SMAN 1 Perbaungan. This study aims to determine how far the level of understanding of students in understanding lessons, especially during the current covid-19 pandemic, which is a process of teaching and learning activities carried out from their respective homes or using online learning media. The method used is an artificial neural network with Backpropagation algorithm with variables used are knowledge values, skill scores, mid-semester exam results, end-semester exam results, and attitude scores. The five variables are used to support predicting the level of student understanding of the subject using the single layer Backpropagation Algorithm. The architectural model used is 5-2-1 with a success accuracy of 85%. The smaller the error value that is close to 0, the smaller the deviation of the results of the Artificial Neural Network with the desired target.

EXPERT SYSTEM FOR HYPOTHYROIDISM DIAGNOSIS USING CASE BASED REASONING METHOD (CASE STUDY OF MELATI II Public Health Center) dewinda rimanti; Hasanul Fahmi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 3 (2022): June 2022
Publisher : Yayasan Kita Menulis

In this study, we will discuss the development of an expert system application for diagnosing Hypothyroidism. In diagnosing Hypothyroidism, this expert system will use the Case-Based Reasoning (CBR) method. CBR uses artificial intelligence in solving problems based on knowledge from previously stored cases. Case data was obtained from medical records from the results of handling Hypothyroidism patients diagnosed by internal medicine specialists. There are 5 types of hypothyroidism disease with one symptom of the disease in the old case. And there are new cases that will be used to calculate the similarity value to the old cases that exist in the knowledge base owned by the system.

DECISION SUPPORT SYSTEM FOR DETERMINING THE BEST TEACHER USING TOPSIS METHOD (CASE STUDY : SMP NEGERI 1 GALANG) iinvera niar; Hasanul Fahmi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 3 (2022): June 2022
Publisher : Yayasan Kita Menulis

SMP Negeri 1 Galang has activity in determining the best teacher, however, at SMP Negeri 1 Galang the determination of the best teacher still uses the manual method, namely by calculating on paper with a predetermined format. In this case, of course, it takes a long time, considering that there are many junior high school teachers, and also requires many criteria. This is what makes researchers want to conduct research in order to design a decision support system for determining the best teacher using the TOPSIS method at the 1st Galang Junior High School. The Technique for Order Preference by Similarity to Ideal Solution (Topsis) method is one method that is often used in determining a decision, therefore researchers use this method in making a system. With the existence of a decision support system, it can help the school in determining the best teacher, so that the determination of the best teacher can be done accurately and quickly

Co-Authors Ahmad Zaki Fadilla Rangkuti Alifah, Nurli Aprilio, Pajri Arifiandy, Rony Aulia, Afina Nisa Ayu, Desita Puspita BROTOKUNCORO, AGUNG Cexarian, Hafizh ChungKiat, Ong Daniel Happy Putra Dewinda Rimanti Felix, Michael FUYU, FUYU Girsang, Rame R GUFANG, GUFANG harianja, turiami Hariyanto, Dian Tri Hastuti, Rani Puji Herry Utomo, Wiranto iinvera niar Lianzhai, Duan Linli, Peng murdani, toynbe Naswir, Ahmad Fadhil natanael, anju mastaurat Nugraha, Putu Surya Nurul Putri Utami Prabu Wardono Pratama, Jaka Yudhi Rahman, Fajri Fathur rendiarno rendiarno Ricky Setiawan Rila Mandala Rosalina Rosalina Rusdianto Roestam Rustam, Michiavelly Sahuri, Genta Sahuri Saptona, Albert Septian Fakhrudin Arianto Siahaan, R. Fanry Sihombing, Darvin Markus Simangunsong, Agustina Simanjorang, R. Mahdalena Sinaga, Anita Sindar RM Sitohang, Rirido Apriyanto sofyan, mhd heri Sulindawaty Tengfei, Li Tjong Wan Sen turnip, hendra nicodemus Wahyuni, Elda Wika Wahyuni Williem Williem, Williem Wiranto Herry Utomo Yunita, Yustina Zhang Jie

Title

Found 39 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 39 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 39 Documents
Search