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Journal : ComEngApp : Computer Engineering and Applications Journal

Robotics Current Issues and Trends Siti Nurmaini
Computer Engineering and Applications Journal Vol 2 No 1 (2013)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (930.261 KB) | DOI: 10.18495/comengapp.v2i1.13

Abstract

The ongoing research and development work in the field of robotics have resulted in so many new technological trends. There are revolution which are being achieved with the use of latest technology in robotics, giving birth to new possibilities for automating tasks and enriching human lives for better. One can easily witness the presence of robotics in every sphere of life from industrial robots, service robots to personal robots. It other words, robots have become a part of our world to meet new demands of a new society.DOI: 10.18495/comengapp.21.117120
Swarm Robot Implementation in Gas Searching Using Particle Swarm Optimization Algorithm Nyayu Latifah Husni; Ade Silvia; Siti Nurmaini; Falah Yuridho; Irsyadi Yani
Computer Engineering and Applications Journal Vol 6 No 3 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.811 KB) | DOI: 10.18495/comengapp.v6i3.221

Abstract

In this reseach, a PSO method is impelemented in searching a gas leakage. A swarm robot consisted of 3 agents, yelow, blue, and green, was used. The research was done in 2 type of experiments, i.e. in simulation and real expeiment. A Matlab is used as a simulation validation while for the real experiment, a 2 x 2 m arena is used. From the experiment, it can be concluded that a good performance of a swam can be achieved using PSO method.
Improving Data Integrity of Individual-based Bibliographic Repository Using Clustering Techniques Firdaus Firdaus; Oky Budiyarti; Muhammad Anshori; Mira Afrina; Siti Nurmaini
Computer Engineering and Applications Journal Vol 7 No 1 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.066 KB) | DOI: 10.18495/comengapp.v7i1.223

Abstract

This paper presents a method to improve data integrity of individual-based bibliographic repository. Integrity improvement is done by comparing individual-based publication raw data with individual-based clustered publication data. Hierarchical Agglomerative Clustering is used to cluster the publication data with similar author names. Clustering is done by two steps of clustering. The first clustering is based on the co-author relationship and the second is by title similarity and year difference. The two-step hierarchical clustering technique for name disambiguation has been applied to Universitas Sriwijaya Publication Data Center with good accuracy.
Fuzzy Logic-Ant Colony Optimization for Explorer-Follower Robot with Global Optimal Path Planning Bambang Tutuko; Siti Nurmaini; Ganesha Ogi
Computer Engineering and Applications Journal Vol 7 No 1 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1097.948 KB) | DOI: 10.18495/comengapp.v7i1.241

Abstract

Path planning is an essential task for the mobile robot navigation. However, such a task is difficult to solve, due to the optimal path needs to be rerouted in real-time when a new obstacle appears. It produces a sub-optimal path and the robot can be trapped in local minima. To overcome the problem the Ant Colony Optimization (ACO) is combined with Fuzzy Logic Approach to make a globally optimal path. The Fuzzy-ACO algorithm is selected because the fuzzy logic has good performance in imprecision and uncertain environment and the ACO produce simple optimization with an ability to find the globally optimal path. Moreover, many optimization algorithms addressed only at the simulation level. In this research, the real experiment is conducted with the low-cost Explorer-Follower robot. The results show that the proposed algorithm, enables them to successfully identify the shortest path without collision and stack in “local minima”.
Localization of Leader-Follower Robot Using Extended Kalman Filter Siti Nurmaini; Sahat Pangidoan
Computer Engineering and Applications Journal Vol 7 No 2 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1094.548 KB) | DOI: 10.18495/comengapp.v7i2.253

Abstract

Non-holonomic leader-follower robot must be capable to find its own position in order to be able to navigating autonomously in the environment this problem is known as localization. A common way to estimate the robot pose by using odometer. However, odometry measurement may cause inaccurate result due to the wheel slippage or other small noise sources. In this research, the Extended Kalman Filter (EKF) is proposed to minimize the error or the inaccuracy caused by the odometry measurement. The EKF algorithm works by fusing odometry and landmark information to produce a better estimation. A better estimation acknowledged whenever the estimated position lies close to the actual path, which represents a system without noise. Another experiment is conducted to observe the influence of numbers of landmark to the estimated position. The results show that the EKF technique is effective to estimate the leader pose and orientation pose with small error and the follower has the ability traverse close to leader based-on the actual path.
Swarm Intelligent in Bio-Inspired Perspective: A Summary Nyayu Husni Latifah; Ade Silvia; Ekawati Prihatini; Siti Nurmaini; Irsyadi Yani
Computer Engineering and Applications Journal Vol 7 No 2 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (612.245 KB) | DOI: 10.18495/comengapp.v7i2.255

Abstract

This paper summarizes the research performed in the field of swarm intelligent in recent years. The classification of swarm intelligence based on behavior is introduced. The principles of each behaviors, i.e. foraging, aggregating, gathering, preying, echolocation, growth, mating, clustering, climbing, brooding, herding, and jumping are described. 3 algorithms commonly used in swarm intelligent are discussed. At the end of summary, the applications of the SI algorithms are presented.
Real-Time Lighting Control System with Fuzzy-Mamdani for Smart Home Application Dimas Budianto; Siti Nurmaini; Bambang Tutuko; Sarifah Putri Raflesia
Computer Engineering and Applications Journal Vol 7 No 3 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1014.261 KB) | DOI: 10.18495/comengapp.v7i3.267

Abstract

The use of pervasive computing in the context of home automation equipment will greatly facilitate life. Several building still use manual switch to turn on or turn off the lighting system. It becomes ineffective if the house has a lot of lights, due to it sometimes forget to turn off. Hence, the real-time control system for automatic lighting processing is desirable. An automatic control system will allow to control the illumination and it will decrease the energy costs. In this paper, the Fuzzy logic system-based Mamdani style is used to adjust the intensity of the lights. Based on simple algorithm the controller board is working in a real-time condition. As a result found, the implementation is successfully to control the lighting system with good performance. Thus, the fuzzy system can be built smart home concept that facilitate the human life.
Skin Lesion Classification Based on Convolutional Neural Networks Renny Amalia Pratiwi; Siti Nurmaini; Dian Palupi Rini
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (490.711 KB) | DOI: 10.18495/comengapp.v8i3.290

Abstract

Melanoma causes the majority of skin cancer deaths. The population level of melanoma has increased over the past 30 years. It kills around 9.320 people in the US every year. Melanoma can often be found early, when it is most likely to be cured. Medical diagnoses using digital imaging with machine learning methods have become popular because of their ability to recognize patterns in digital images. Image diagnosis accuracy allows disease cured at an early stage. This paper proposes a simulation that can be used for early detection of skin cancer that can help dermatologists to distinguish melanomas from other pigmented lesions on the skin. Some researchers have developed a system using machine learning algorithms used to classify skin lesions from dermoscopy images of human skin. In this study, we proposed Convolutional Neural Network (CNN) to our model. CNN is very efficient for image processing because feature extractors can be optimized, applied to each feature image position. The results of skin lesion classification of benign nevi and melanoma based on CNN models produces high accuracy (area under the receiver operator characteristics (ROC) curve (AUC) is 92.59 %, sensitivity is 89.47%, specificity is 100.0%, precision is 100 % and F1 score is 94.44 %).
A Deep Learning Approach to Integrate Medical Big Data for Improving Health Services in Indonesia Bambang Tutuko; Siti Nurmaini; Muhammad Naufal Rachmatullah; Annisa Darmawahyuni; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (426.189 KB) | DOI: 10.18495/comengapp.v9i1.328

Abstract

Medical Informatics to support health services in Indonesia is proposed in this paper. The focuses of paper to the analysis of Big Data for health care purposes with the aim of improving and developing clinical decision support systems (CDSS) or assessing medical data both for quality assurance and accessibility of health services. Electronic health records (EHR) are very rich in medical data sourced from patient. All the data can be aggregated to produce information, which includes medical history details such as, diagnostic tests, medicines and treatment plans, immunization records, allergies, radiological images, multivariate sensors device, laboratories, and test results. All the information will provide a valuable understanding of disease management system. In Indonesia country, with many rural areas with limited doctor it is an important case to investigate. Data mining about large-scale individuals and populations through EHRs can be combined with mobile networks and social media to inform about health and public policy. To support this research, many researchers have been applied the Deep Learning (DL) approach in data-mining problems related to health informatics. However, in practice, the use of DL is still questionable due to achieve optimal performance, relatively large data and resources are needed, given there are other learning algorithms that are relatively fast but produce close performance with fewer resources and parameterization, and have a better interpretability. In this paper, the advantage of Deep Learning to design medical informatics is described, due to such an approach is needed to make a good CDSS of health services.
Author Matching Classification with Anomaly Detection Approach for Bibliomethric Repository Data Zaqqi Yamani; Siti Nurmaini; Dian Palupi Rini
Computer Engineering and Applications Journal Vol 9 No 2 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.294 KB) | DOI: 10.18495/comengapp.v9i2.335

Abstract

Authors name disambiguation (AND) is a complex problem in the process of identifying an author in a digital library (DL). The AND data classification process is very much determined by the grouping process and data processing techniques before entering the classifier algorithm. In general, the data pre-processing technique used is pairwise and similarity to do author matching. In a large enough data set scale, the pairwise technique used in this study is to do a combination of each attribute in the AND dataset and by defining a binary class for each author matching combination, where the unequal author is given a value of 0 and the same author is given a value of 1. The technique produces very high imbalance data where class 0 becomes 98.9% of the amount of data compared to 1.1% of class 1. The results bring up an analysis in which class 1 can be considered and processed as data anomaly of the whole data. Therefore, anomaly detection is the method chosen in this study using the Isolation Forest algorithm as its classifier. The results obtained are very satisfying in terms of accuracy which can reach 99.5%.
Co-Authors A. Darmawahyuni A. I. Sapitri Ade Iriani Sapitri Ade Iriani Sapitri Ade Iriani Sapitri Ade Silvia Ade Silvia Ade Silvia Handayani Aditya Aditya Aditya, Aditya Agung Juli Anda Agus Triadi Agus Triadi Agus Triadi Ahmad Zarkasi Ahmad Zarkasi Ahmad Zarkasi Ahmad Zarkasih Akhiar Wista Arum Andre Herviant Juliano Anggun Islami Anggun Islami Annisa Darmawahyuni Ardy Hidayat Arief Cahyo Utomo Armansyah, Risky Arnaldo, Muhammad Arum, Akhiar Wista Aulia Rahman Thoharsin B. Tutuko Bambang Tutuko Bambang Tutuko Bayu Wijaya Putra Benedictus Wicaksono Widodo Bhakti Yudho Suprapto Bhakti Yudho Suprapto Bhakti Yudho Suprapto Cindy Kesty Darmawahyuni, Annisa Darmawahyuni, Annisa Deris Stiawan Dewi, Kemala Dewi, Tresna Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dimas Budianto Dinda Lestarini Dodo Zaenal Abidin Dwi Mei Rita Sari Ekawati Prihatini Erliza Yuniarti Fachrudin Abdau Fahreza, Irvan Falah Yuridho Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus, Firdaus Firsandaya Malik, Reza Ganesha Ogi GITA FADILA FITRIANA Hadipurnawan Satria Hanif Habibie Supriansyah Huda Ubaya Huda Ubaya Huda Ubaya Husnawati Husnawati Husnawati Husnawati Husnawati Husni, Nyayu Latifah Husni, Nyayu Latifah Irfannuddin Irfannuddin Irsyadi Yani Irvan Fahreza Iryadi Yani Iryadi Yani, Iryadi Isdwanta, Rendy Islami, Anggun Jasmir Jasmir Jasmir Jasmir Jordan Marcelino Kemala Dewi Khairunnisa, Cholidah Zuhroh Krisna Murti Kurniawan, Anggy Tias Kurniawan, Anggy Tyas Legiran Legiran M. Hashim, Siti Zaiton M. N. Rachmatullah M. Naufal Rachmatullah Maharani, Masayu Nadila Marcelino, Jordan Masayu Nadila Maharani Mira Afrina Muhamad Akbar Muhammad Afif Muhammad Anshori Muhammad Arnaldo Muhammad Fachrurrozi Muhammad Fachrurrozi Muhammad Irham Rizki Fauzi Muhammad Naufal Rachmatullah Muhammad Naufal, Muhammad Muhammad Roriz Muhammad Taufik Roseno, Muhammad Taufik Muzakkie, Mufida Nabilah, Aini Nadia Ayu Oktabella, nadia ayu oktabella Novi Yusliani Nurqolbiah, Fatihani Nuswil Bernolian Nuswil Bernolian Nyayu Latifah Husni Nyayu Latifah Husni, Nyayu Latifah Oky Budiyarti Osvari Arsalan Passa, Rahma Satila Patiyus Agustiansyah PATIYUS AGUSTIANSYAH, PATIYUS Pola Risma PP Aditya, PP, Aditya, PP Pratama, Jimiria Putri Mirani Rachmamtullah, Muhammad Naufal Radiyati Umi Partan Radiyati Umi Partan Radiyati Umi Partan Radiyati Umi Partan, Radiyati Umi Rahma Satila Passa Rendy Isdwanta Renny Amalia Pratiwi Reza Firsandaya Malik Reza Firsandaya Malik Ria Nova Ricy Firnando Ricy Firnando Ricy Firnando Rizal Sanif Rizki Kurniati Rossi Passarella Sahat Pangidoan Samsuryadi Samsuryadi Saparudin Saparudin Saparudin, Saparudin Sapitri, Ade Iriani Saputra, Tommy Sari, Dwi Mei Rita Sarifah Putri Raflesia Sarifah Putri Raflesia, Sarifah Putri Sastradinata, Irawan Sigit Prasetyo Noprianto Siti Zaiton Siti Zaiton M. Hashim Soedjana, Hardi Siswo Sri Desy Siswanti Suci Dwi Lestari Suci Dwi Lestari Suhandono, Nugroho Sukemi Sukemi Sukemi Sukemi Sukemi Sukman Tulus Putra Sutarno Sutarno Syamsul Arifin Syaputra, Hadi Tio Artha Nugraha Tresna Dewi Tresna Dewi Tri Undari Triadi, Agus Triadi, Agus Varindo Ockta Keneddi Putra Velia Yuliza Winda Kurnia Sari Wisnu Adi Putra Yani, Iryadi Yesi Novaria Kunang Yurni Oktarina Zaqqi Yamani