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INDONESIA
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Published by Universitas Gadjah Mada
ISSN : 19781520     EISSN : 24607258     DOI : https://doi.org/10.22146/ijccs
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 476 Documents
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Lampung Script Recognition Using Convolutional Neural Network Panji Bintoro; Agus Harjoko
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.70041

Abstract

The Lampung script is often used in writing words in Lampung language. The Lampung language itself is used by native Lampung people and people who learn Lampung language. The Lampung script is difficult to learn because there are many combinations of parent characters and subletters. CNN is a method in the field of object recognition that has a specific layer, namely a convolution layer and a pooling layer that allows the feature learning process well. Handwriting recognition as in character recognition in MNIST, CNN produces better performance compared to other methods. From the advantages of CNN, the CNN method with DenseNet architecture was chosen as the best architecture to recognize each Lampung script. In this study, there are 2 main processes, namely preprocessing, and recognition. This study succeeded in applying the CNN method which can recognize Lampung script. The dataset is divided into 4 groups of characters that have different sounds. First, the parent character data get 98% accuracy. Second, the parent letter data with the above letters get 98% accuracy. Third, the parent character data with the sub-letters on the side get 98% accuracy. Fourth, the parent letter data with the lower letters get 97% accuracy.
Tegal Tourism Object Selection Decision Support System Using Fuzzy Logic Dika Permana Putra; Sigit Priyanta
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.70226

Abstract

There are many agencies that have databases but are left without proper management. For example, in tourist attractions in Kota & Kab. Tegal, along with the rapid development of tourism technology, the tourism industry requires the tourism industry to apply information technology to provide convenience for tourists to find out tourist areas according to the cost, and the distance of the tourist attractions entered. The provision of tourism information helps tourists to consider and make decisions to travel. Tahani Fuzzy Logic was chosen because the concept of Fuzzy logic is easy to understand, flexible, and because the Tahani logic method is a form of decision support where the main tool is functional with the main input criteria determined by the user/tourist. This system was implemented using web programming and MySQL database, where the variables to be considered are Type of Tour, Number of Facilities, Price of Tour Tickets, Number of Tourist Visitors, Travel Distance from City Center. The results of this study are a decision support system for tourism selection in Tegal using Fuzzy Tahani which can recommend tourist attractions in Tegal which are determined by tourists depending on tourist criteria based on the firestrength of the selected variables
Fast Non-dominated Sorting in Multi Objective Genetic Algorithm for Bin Packing Problem Muhammad Bintang Bahy; Aina Musdholifah
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.70677

Abstract

The bin packing problem is a problem where goods with different volumes and dimensions are put into a container so that the volume of goods inserted is maximized. The problem of multi-objective bin packing is a problem that is more commonly found in everyday life, because what is considered in packing is usually not only volume.In this research, a multi-objective genetic algorithm is proposed to solve the multi-objective bin packing problem. The proposed genetic algorithm uses non-dominated sorting and crowding distance methods to get the best solution for each objective and to avoid bias. The algorithm is then tested with several test classes that represent different combinations of item and container sizes.From the results of the tests carried out, it was found that the proposed algorithm can find several solutions which are the best candidate solutions for each objective. Also found how the correlation of each objective in the population.
Decision Support System to Prioritize Ventilators for COVID-19 Patients using AHP, Interpolation, and SAW Nikolas Adhi Prasetyo; Retantyo Wardoyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.70985

Abstract

Ventilator shortages is a common problem faced by hospitals during the COVID-19 pandemic era. Healthcare workers are forced to make choices because of how big the difference between resources and lives needing it. This issue rarely comes, because normally every patient has the same rights to receive treatment and resources, but it becomes a clear problem when there are barely enough resources. Therefore, a prioritization mechanism that can objectively decide the allocation must be made to achieve the best outcome.A decision support system is a system that can support humans using data as decision makers to help them decide semi-structured/unstructured problems. The goal of this research is to create a DSS to prioritize patients who need a ventilator by incorporating two different methods, which are AHP, Interpolation, and SAW. It is hoped that the result of the research can be used to rank patients based on predetermined criterias and policy.
Behind the Mask: Detection and Recognition Based-on Deep Learning Ade Nurhopipah; Irfan Rifai Azziz; Jali Suhaman
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.72075

Abstract

COVID-19 prevention procedures are executed to support public services and business continuity in a pandemic situation. Manual mask use monitoring is not efficient as it requires resources to monitor people at all times. Therefore, this task can be supported by automated surveillance systems based on Deep Learning. We performed mask detection and face recognition for a real-environment dataset. YOLOV3 as a one-stage detector was implemented to simultaneously generate a bounding box of the face area and class prediction. In face recognition, we compared the performance of three pre-trained models, namely ResNet152V2, InceptionV3, and Xception. The mask detection showed promising results with MAP=0.8960 on training and MAP=0.8957 on validation. We chose the Xception model for face recognition because it has equal quality as ResNet152V2 but has fewer parameters. Xception achieved a minimal loss value in the validation of 0.09157 with perfect accuracy on facial images larger than 100 pixels. Overall the system delivers promising results and can identify faces, even those behind the mask.
Modification Weight Criteria With Webbed Model For Selection Artist Music Festival Using Analytical Hierarchy Process (AHP) I Gede Iwan Sudipa; Putu Sugiartawan; I Komang Arya Ganda Wiguna
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 1 (2022): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.72434

Abstract

The process of selecting from many alternatives to the criteria is a decision that is often determined in decision making. The criteria for which criteria can consist of many attributes are used by decision-makers in making the selection or are called multi-criteria decision making (MADM ). Determining the Artist Music Festival at an event has quite a complicated difficulty, because the assessment of the criteria is heterogeneous. The spider web's approach to integrating criteria results in the selection of the artist form that attracts the most attention, and public interest. Model AHP use of multi-attributes is used in selecting artists to perform at music festivals, selecting artists using criteria, namely Number of Followers (C1), stamp C2, Average Popular Tracks (C3), Average Youtube Viewers (C4), and the price of the artist (C5). Data on the number of followers, popularity, average popular tracks, and average YouTube viewers were obtained using the Spotify and Youtube APIs. The settlement method applied is the Analytical Hierarchy Process (AHP) and the Rating Scale algorithm, with an alternative using five samples of Indonesian artists. The research results are expected to provide recommendations for artists as performers in the music festival.
Mobile-based Primate Image Recognition using CNN Nuruddin Wiranda; Agfianto Eko Putra
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 2 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.65640

Abstract

Six out of 25 species of primates most endangered are in Indonesia. Six of these primates are namely Orangutan, Lutung, Bekantan, Tarsius tumpara, Kukang, and Simakobu. Three of the six primates live mostly on the island of Borneo. One form of preservation of primate treasures found in Kalimantan is by conducting studies on primate identification. In this study, an android app was developed using the CNN method to identify primate species in Kalimantan wetlands. CNN is used to extract spatial features from primate images to be very efficient for image identification problems. The data set used in this study is ImageNets, while the model used is MobileNets. The application was tested using two scenarios, namely using photos and video recordings. Photos were taken directly, then reduced to a resolution of 256 x 256. Then, videos were taken in approximately 10 to 30 seconds with two megapixel camera resolution. The results obtained was an average accuracy of 93.6% when using photos and 79% when using video recordings. After calculating the accuracy, the usability test using SUS was performed. Based on the SUS results, it is known that the application developed is feasible to use.
On the Design of a Blockchain-based Fraud-prevention Performance Appraisal System Bryan Andi Gerrardo; Agus Harjoko; Nai Wei Lo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 2 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.67669

Abstract

 The job recruitment process takes a lot of process and number of documents. It is very well known for applicants to exaggerated and falsify their work history data. It may put a company at legal risk and significant commercial losses. Generally, company use third-party to verify applicant’s work history data which is time-consuming and costly. It also makes companies relies on third-party which may not trustworthy and cause several other risks. Generally, experience letters is used as a proof of work history documents of employee. However, the process of publishing an experience letter may contain conflict of interest between company and employee. Yet, publishing an experience letter is not mandatory in several places. In this research, we propose a system to verify applicant’s work history data by using performance appraisal as proof of work history and utilizing Blockchain to provide secure system, tampered-proof and real-time verification. The proposed approach also minimizes trust issues and privacy of data sharing by adding encryption and digital signature schema using Elliptic Curve Cryptography (ECC) algorithm. Furthermore, we have implemented a prototype to demonstrate how the proposed system work using a Quorum-based consortium blockchain.
Aspect-Based Sentiment Analysis of KAI Access Reviews Using NBC and SVM Huda Mustakim; Sigit Priyanta
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 2 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.68903

Abstract

The existence of KAI Access from PT. KAI prove their sincerity in serving consumers in this modern era. However, many negative reviews found in Google Play Store. There has been research on the review, but the analysis stage still at document level so the aspect related to the application is not known clearly and structured. So it is necessary to do an aspect-based sentiment analysis to extract the aspects and the sentiment. This study aims to do an aspect-based sentiment analysis on user reviews of KAI Access using Naive Bayes Classifier (NBC) and Support Vector Machine (SVM), with 3 scenarios. Scenario 1 uses NBC with Multinomial Naive Bayes, scenario 2 uses SVM with default Sklearn library parameter, and scenario 3, uses SVM with hyperparameter tunning, while the data scrapped from Google Play Store. The results show the majority of user sentiment is negative for each aspect, with most discussed errors aspect shows the high system errors. The test results gives the best model from scenario 3 with an average accuracy 91.63%, f1-score 75.55%, precision 77.60%, and recall 74.47%.
Mangrove-based Ecotourism Sustainability Analysis using NDVI and AHP Approach Yerik Afrianto Singgalen; Danny Manongga
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 16, No 2 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.68986

Abstract

 This article aims to analyze the sustainability of mangrove ecotourism using the Normalized Difference Vegetation Index (NDVI) and Analytical Hierarchy Process (AHP) approaches. Based on Landsat 8 OLI satellite imagery calculation using the NDVI technique, there has been a decrease in vegetation value on Dodola Island in 2017. This condition needs to be analyzed scientifically, considering the Dodola Island mangrove area to be preserved. In addition to the interests of tourism infrastructure development. The research method used is a mixed research method through a case study approach in Dodola Island, Morotai Island Regency, North Maluku Province, Indonesia. This study adopts remote sensing techniques and decision support systems to describe the results of sustainable mangrove ecotourism analysis. This study indicates that the calculation results of Landsat 8 OLI spatial data from 2013-to 2021 show a significant decrease in vegetation value in 2017, where the maximum NDVI value is 0.30, and the minimum NDVI value is 0.11. Specifically, the mangrove area also experienced a decrease in vegetation value with a maximum NDVI value is 0.23 and a minimum NDVI value is 0.02. To anticipate environmental damage in mangrove areas, this study recommends mangrove conservation programs, namely rehabilitation, restoration, reclamation, and conservation of mangrove areas. In addition, the results of the priority analysis using the AHP approach show that the rehabilitation program is a program that needs to be prioritized because it follows the existing conditions and capabilities of the Dodola Island managers.

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