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International Journal of Informatics and Computation
Published by Universitas Respati Yogyakarta
ISSN : 26858711     EISSN : 27145263     DOI : 10.35842/ijicom
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Computation (IJICOM) is an international, peer-reviewed, open-access journal, that publishes original theoretical and empirical work on the science of informatics and its application in multiple fields. Our concept of Informatics includes technologies of information and communication as well as the social, linguistic, and cultural changes that initiate, accompany, and complicate their development. IJICOM aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices. The scope of this journal includes IoT, 5G, Artificial Intelligence, sensor networks, and high-resolution imaging techniques. This new discipline in science combines computational thinking, modern computational methods, devices, and collateral technologies to address problems far beyond the scope of traditional numerical methods
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 61 Documents
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COMPARISON OF HOP COUNT ON WIRELESS MESH NETWORK Eliza Staviana; Hizbul Wathan
International Journal of Informatics and Computation Vol 2 No 2 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i2.29

Abstract

Wireless Mesh Network (MWN) is a self-configured and self-organized network that can typically be implemented on 802.11 hardware. It consists of several nodes that make up the network backbone in a multi-story and sealed room, in contrast to building a hall or a place without bulkheads. This experiment uses an odd and even number scheme with a maximum number of routers of 8 pieces. In a sealed room, the performance of the method of installation of the number of strange Hops is better than the number of even Hops, with throughput calculation of 2665.19 KB, delay 0.25 s, data lost 0.60 %, and jitter 0.01 s and the best scheme that is with the number of Hops as much as five pieces, with the calculation of the number of throughput 7001.88 KB, delay 0.51s, data lost 0.47%, and jitter 0.002 s. In the free spaces, it can produce the better performance of the even hop count calculation scheme than the odd hop count by building throughput 16709.8 KB, delay 0.2 s, data lost 0.08 %, and jitter 0.03 s. and the best scheme that is with the number of throughput 68975,2 KB, wait for 0.0148 s, data lost 0 %, and jitter 0.0014 s. WMN performance in unshared space is more maximized than the version in a sealed area, with throughput values of 11786.82 kbps, delay of 2.08 ms, and data lost by 0.08 %, and jitter 0.03 s.it can produce the better performance of the even hop count calculation scheme than the odd hop count by producing throughput 16709.8 KB, delay 0.2 s, data lost 0.08 %, and jitter 0.03 s. and the best scheme that is with the number of throughput 68975,2 KB, wait for 0.0148 s, data lost 0 %, and jitter 0.0014 s. WMN performance in unshared space is more maximized than the version in sealed space, with throughput values of 11786.82 kbps, delay of 2.08 ms, and data lost by 0.08 %, and jitter 0.03 s. and data lost by 0.08%, and jitter 0.03s.
IMPLEMENTATION OF THE COMSTOCK METHOD FOR ANDROID BASED PATIENT LEFTOVERS FOOD MANAGEMENT lu'luil maknun sundarina
International Journal of Informatics and Computation Vol 2 No 1 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i1.24

Abstract

Nowadays, nutritionists should count manually to know how much nutrition that patients get as the development of technology, human work easier likewise in counting the patient's food waste so it will be more efficient and not waste a lot of time. This research aims to build an application that can facilitate nutritionists in the calculating amount of food waste by using the Comstock method. The system is designed to use Unified Modeling Language (UML) and programming language Hypertext Preprocessor (PHP) and Hyper Markup Language (HTML). The result of this research is in the form of application which could be used by nutritionists at hospital calculate the amount of food waste of patients using the android-based Comstock method at the hospital using the Comstock method.
Design and Build a Seminar Management Information System to Manage 2019 Indonesian Qualitative Seminar & Workshop (SLKI) Simon Prananta Barus
International Journal of Informatics and Computation Vol 2 No 1 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i1.25

Abstract

Matana University collaborated with Indonesia Qualitative Researcher Association (IQRA) held a 2019 Indonesian Qualitative Seminar & Workshop (SLKI) 2019. The organizer required a seminar management information system (SIM) to run this event smoothly. However, seminar SIM was not available at that time, and needed to be built according to the needs of 2019 SLKI. The methodology to build seminar SIM is study literature system development with prototyping model which has the stages of user requirement, system / sub system prototyping, prototype evaluation, prototype improvement, system testing, system implementation, system maintenance. SIM 2019 SLKI consists of 2 (two) main applications, namely a web-based data management application and mobile based attendance application. QR Code was used for the attendance of participants. This seminar SIM successfully has been built and implemented in this event. This seminar SIM helped the participants and the committee to share data and information that can be done anytime and anywhere as long they are connected to the internet. In the future, it is necessary to develop several features such as article management, QR code generator, automatic certificate generation, digital payment, and more complete reporting & webinar implementation.
Modern Web Semantic Application For Selling Fish Marselina Endah
International Journal of Informatics and Computation Vol 2 No 1 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i1.26

Abstract

Betta fish is famous as a fighter fish with a difference between betta fish with other types of fishes. Many people are interested in buying the Betta fish with a beautiful tail and attractive color with a giant belly. Thus, the paper aims to build a Semantic Web with API of delivery services. We design a system to enable and increase the betta fish sales of the Yogyakarta Community, Indonesia. We construct an application with REST of a web semantics to retrieve various data, including places and shipping cost of items to enable buyers to estimate fish prices and shipping costs.
Implementation of CNN for Plant Leaf Classification Mohammad Diqi; Sri Hasta Mulyani
International Journal of Informatics and Computation Vol 2 No 2 (2020): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v2i2.28

Abstract

Many deep learning-based approaches for plant leaf stress identification have been proposed in the literature, but there are only a few partial efforts to summarize various contributions. This study aims to build a classification model to enable people or traditional medicine experts to detect medicinal plants by using a scanning camera. This Android-based application implements the Java programming language and labels using the Python programming language to build deep learning applications. The study aims to construct a deep learning model for image classification for plant leaves that can help people determine the types of medicinal plants based on android. This research can help the public recognize five types of medicinal plants, including spinach Duri, Javanese ginseng, Dadap Serep, and Moringa. In this study, the accuracy is 0.86, precision 0.22, f-1 score 0.23, while recall is 0.2375.
Sentiment Analysis of Hotel User Review using RNN Algorithm Theresia Arwila Utami
International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i1.34

Abstract

Sentiment analysis in user review is a growing research area at the current time. Usually, the website becomes a source of data in knowing the quality of the hotel services, and the provider can utilize the review for monitoring and evaluation. However, determining the positive or negative sentiment of a user review in unstructured textual data takes a long time. As a result, we present a model to classify positive or negative sentiment in user reviews in this article. This study suggests the RNN method in building an effective model to classify user sentiment. Based on the experiment, our model can produce accurate results in organizing hotel reviews. Furthermore, the proposed method achieved a higher evaluation metrics score with an f1-score of 91.0%.
Efficient Fruits Classification Using Convolutional Neural Network ADNAN ADNAN ABIDIN; Hamzah Hamzah; Marselina Endah
International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i1.31

Abstract

Classification of fruits is a growing research topic in image processing. Various papers propose various techniques to deal with the classification of apples. However, some traditional classification methods remain drawbacks to producing an effective result with the big dataset. Inspired by deep learning in computer vision, we propose a novel learning method to construct a classification model, which can classify types of apples quickly and accurately. To conduct our experiment, we collect datasets, do preprocessing, train our model, tune parameter settings to get the highest accuracy results, then test the model using new data. Based on the experimental results, the classification model of green apples and red apples can obtain good accuracy with little loss. Therefore, the proposed model can be a promising solution to deal with apple classification.
The Design Of Augmented Reality Media Koi Fish Literacy Using Fast Corner Algorithm Mohammad Rofi Rahman
International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i1.32

Abstract

Ornamental fish that are quite famous and in demand in the market is the koi fish. This fish has a relatively high economic value, and its demand is increasing. There are still many difficulties in maintaining this fish so that it can cause the growth of disease and even death in the fish. It is due to the lack of public attention in terms of literacy about koi fish. Researchers used augmented reality technology to design koi fish literacy media based on these problems using the FAST Corner algorithm. So it is hoped that it could help improve public literacy about koi fish by introducing real-time information. The Fast Corner detection algorithm is helpful to accelerate the computational time when detecting corners in real-time with the markerless Augmented Reality technique. In this technique, the marker used for object tracking has been replaced with pattern recognition or pattern recognition of an object. The study results showed that experiments using this algorithm could track targets with good and faster performance and a maximum level of accuracy.
Effective Soil Type Classification Using Convolutional Neural Network Antomy David Ronaldo
International Journal of Informatics and Computation Vol 3 No 1 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i1.33

Abstract

Soil classification is a growing research area in the current era. Various studies have proposed different techniques to deal with the issues, including rule-based, statistical, and traditional learning methods. However, the plans remain drawbacks to producing an accurate classification result. Therefore, we propose a novel technique to address soil classification by implementing a deep learning algorithm to construct an effective model. Based on the experiment result, the proposed model can obtain classification results with an accuracy rate of 97% and a loss of 0.1606. Furthermore, we also received an F1-score of 98%.
Weather Forecasting Analysis using Bayesian Regularization Algorithms Indo Intan
International Journal of Informatics and Computation Vol 3 No 2 (2021): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v3i2.35

Abstract

Weather forecasting has become very urgent in various fields of human life, including in big cities. The need for weather forecasting accuracy will be effective and efficient in managing the quality of civilization flexibly. Bayesian regularization is one of the techniques used to obtain accurate results and development of artificial neural networks. The training process achieves the smallest epoch using a general processing unit to solve big data and high resolution. Scenarios performed via dataset partitioning and MSE enhancement. The addition of training data will improve system performance which indicates a significant increasing accuracy. Likewise, the decrease in MSE can increase the system accuracy to achieve a convergence stability point. Weather forecasting can recommend work units within the city and its surroundings, even between provinces or countries.

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