Article Per Year (5 Year)
p-Index From 2021 - 2026
1.325
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) CommIT (Communication & Information Technology) JOIV : International Journal on Informatics Visualization ComTech: Computer, Mathematics and Engineering Applications Engineering, Mathematics and Computer Science Journal (EMACS)
Derwin Suhartono
Computer Science Department, Bina Nusantara University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search
Journal : ComTech: Computer, Mathematics and Engineering Applications

 1 
Pengembangan Algoritma Fast Inversion dalam Membentuk Inverted File untuk Text Retrieval dengan Data Skala Besar Suhartono, Derwin
ComTech: Computer, Mathematics and Engineering Applications Vol 3, No 1 (2012): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v3i1.2461

Abstract

The rapid development of information systems generates new needs for indexing and retrieval of various kinds of media. The need for documents in the form of multimedia is increasing currently. Thus, the need to store or retrieve now becomes a primary problem. The multimedia type commonly used is text types, as widely seen as the main option in the search engines like Yahoo, Google or others. Essentially, search does not just want to get results, but also a more efficient process. For the purposes of indexing and retrieval, inverted file is used to provide faster results. However, there will be a problem if the making of an inverted file is related to a large amount of data. This study describes an algorithm called Fast Inversion as the development of base inverted file making method to address the needs related to the amount of data.
Single Document Automatic Text Summarization using Term Frequency-Inverse Document Frequency (TF-IDF) Christian, Hans; Agus, Mikhael Pramodana; Suhartono, Derwin
ComTech: Computer, Mathematics and Engineering Applications Vol 7, No 4 (2016): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v7i4.3746

Abstract

The increasing availability of online information has triggered an intensive research in the area of automatic text summarization within the Natural Language Processing (NLP). Text summarization reduces the text by removing the less useful information which helps the reader to find the required information quickly. There are many kinds of algorithms that can be used to summarize the text. One of them is TF-IDF (TermFrequency-Inverse Document Frequency). This research aimed to produce an automatic text summarizer implemented with TF-IDF algorithm and to compare it with other various online source of automatic text summarizer. To evaluate the summary produced from each summarizer, The F-Measure as the standard comparison value had been used. The result of this research produces 67% of accuracy with three data samples which are higher compared to the other online summarizers.
Using K-Nearest Neighbor in Optical Character Recognition Ong, Veronica; Suhartono, Derwin
ComTech: Computer, Mathematics and Engineering Applications Vol 7, No 1 (2016): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v7i1.2223

Abstract

The growth in computer vision technology has aided society with various kinds of tasks. One of these tasks is the ability of recognizing text contained in an image, or usually referred to as Optical Character Recognition (OCR). There are many kinds of algorithms that can be implemented into an OCR. The K-Nearest Neighbor is one such algorithm. This research aims to find out the process behind the OCR mechanism by using K-Nearest Neighbor algorithm; one of the most influential machine learning algorithms. It also aims to find out how precise the algorithm is in an OCR program. To do that, a simple OCR program to classify alphabets of capital letters is made to produce and compare real results. The result of this research yielded a maximum of 76.9% accuracy with 200 training samples per alphabet. A set of reasons are also given as to why the program is able to reach said level of accuracy.
Aplikasi E-Tour Guide dengan Fitur Pengenalan Image Menggunakan Metode Haar Classifier Suhartono, Derwin; Permana, William Surya; Wiguna, Antoni; Putra, Ferlan Gisman
ComTech: Computer, Mathematics and Engineering Applications Vol 4, No 2 (2013): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v4i2.2593

Abstract

Smartphone has became an important instrument in modern society as it is used for entertainment and information searching except for communication. Concerning to this condition, it is needed to develop an application in order to improve smart phone functionality. The objective of this research is to create an application named E-Tour Guide as a tool for helping to plan and manage tourism activity equipped with image recognition feature. Image recognition method used is the Haar Classifier method. The feature is used to recognize historical objects. From the testing result done to 20 images sample, 85% accuracy is achieved for the image recognition feature.
Eve: An Automated Question Answering System for Events Information Christanno, Ivan; Priscilla, Priscilla; Maulana, Jody Johansyah; Suhartono, Derwin; Wongso, Rini
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 1 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i1.3781

Abstract

The objective of this research was to create a closed-domain of automated question answering system specifically for events called Eve. Automated Question Answering System (QAS) is a system that accepts question input in the form of natural language. The question will be processed through modules to finally return the most appropriate answer to the corresponding question instead of returning a full document as an output. Thescope of the events was those which were organized by Students Association of Computer Science (HIMTI) in Bina Nusantara University. It consisted of 3 main modules namely query processing, information retrieval, and information extraction. Meanwhile, the approaches used in this system included question classification, document indexing, named entity recognition and others. For the results, the system can answer 63 questions for word matching technique, and 32 questions for word similarity technique out of 94 questions correctly.
Question Categorization using Lexical Feature in Opini.id Saputra, Christian Eka; Suhartono, Derwin; Wongso, Rini
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 4 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i4.4026

Abstract

This research aimed to categorize questions posted in Opini.id. N-gram and Bag of Concept (BOC) were used as the lexical features. Those were combined with Naïve Bayes, Support Vector Machine (SVM), and J48 Tree as the classification method. The experiments were done by using data from online media portal to categorize questions posted by user. Based on the experiments, the best accuracy is 96,5%. It is obtained by using the combination of Bigram Trigram Keyword (BTK) features with J48 Tree as classifier. Meanwhile, the combination of Unigram Bigram (UB) and Unigram Bigram Keyword (UBK) with attribute selection in WEKA achieves the accuracy of 95,94% by using SVM as the classifier.
Design of Distribution Optimization Application using Firefly Algorithm Manik, Ngarap Imanuel; Nursalim, Yunggih; Suhartono, Derwin
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 3 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i3.2567

Abstract

The goal of this research was to optimize the distribution of goods and computerize. The method consisted of problem identification, analysis, implementation, and evaluation. Firefly algorithm was used as a method for optimizing the distribution of goods. The results achieved are the shortest distribution route of goods in accordance with the existing constraints and low cost of distribution. It can be concluded that the research can beused too ptimizethe distribution of goods and tominimize distributioncost.
Co-Authors Agus, Mikhael Pramodana Alison, Richard Chandra Halim Christanno, Ivan Christian, Hans Ciputri, Marcella Marella Eka Putra, Nathanael Geordie Fieri, Brillian Jonathan, Welly Karentia, Angel La'la, Joshua Manik, Ngarap Imanuel Maulana, Jody Johansyah Nugroho, Nico Ardian Nursalim, Yunggih Ong, Veronica Permana, William Surya Priscilla, Priscilla Putra, Ferlan Gisman Putri Masaling, Nikita Ananda Rini Wongso Rudy Salim, Calvin Erico Saffachrissa, Maria Astrid Coenradina Saputra, Christian Eka Setiawan, Dennis Susilo, Stefanny Tamara, Shintia Wiguna, Antoni