JOIV : International Journal on Informatics Visualization
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
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"Vol 3, No 2-2 (2019): Internet of Things and Smart Environments"
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<![CDATA[Secure Information Flow for IoT Applications ]]>
<![CDATA[Tri Minh Ngo]]>;
<![CDATA[Nhat Vien Duy Nguyen]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2.231
<![CDATA[This paper discusses how to ensure security, i.e., confidentiality and integrity properties, for data in IoT applications. While confidentiality could be assessed via information flow analysis, integrity is ensured by error-correcting codes. In addition to errors, many communication channels also cause erasures, i.e., the demodulator cannot decide which symbol the received waveform represents. The paper proposes a method that might correct both errors and erasures together. Our method is efficient in reducing memory storage as well as decoding complexity.]]>
<![CDATA[Smart Hospital for Heart Disease Prediction using IoT ]]>
<![CDATA[Avinash Golande]]>;
<![CDATA[Pranav Sorte]]>;
<![CDATA[Vikas Suryawanshi]]>;
<![CDATA[Utkarsha Yermalkar]]>;
<![CDATA[Sandip Satpute]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.251
<![CDATA[The Internet of Things (IoT) is inter communication of embedded devices using various network technologies. The IoT technology is all set to become the upcoming trend in the future. We are proposing a healthcare monitoring system consisting of ECG Sensors. The parameters which are having a significant amount of importance are sensed by the ECG sensors which are vital for remote monitoring of patient. A mobile app observation is used to continuously monitor the ECG of the patient and various data extraction techniques are performed on the ECG wave to extract attributes to correctly predict heart diseases. .Data mining with its various algorithms reduce the extra efforts and time required to conduct various tests to detect diseases.. Data is collected from ECG sensors. The data is stored onto s storage medium where data mining algorithms are performed on the data collected. These algorithms predict whether the patient has any heart disease. The results can be referred by the doctors for diagnosis purpose. By using IOT technology and data mining algorithms the predication of heart disease is going to do in system.]]>
<![CDATA[Spatial Disaster Risk Assesment of Kelud Eruption, Indonesia, using Fuzzy ]]>
<![CDATA[Titis Octary Satrio]]>;
<![CDATA[Arna Fariza]]>;
<![CDATA[Mu'arifin Mu'arifin]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.262
<![CDATA[Indonesia is one of the countries included in the area of the Ring of Fire or the Ring of the Pacific. This fact can be seen that in Indonesia there are 129 active volcanoes and 10 of them are the most active volcanoes. Mount Kelud is the most active volcano in the province of East Java, Indonesia. This mountain is recorded as actively erupting with a relatively short span of time (9-25 years), making it a volcano that is dangerous for humans. Readiness of citizens is very necessary as an effort to prevent and anticipate the eruption of Mount Kelud in the future. Disaster risk level assessments are needed to provide information for citizen and government preparedness in the face of volcanic eruptions. In this paper a new approach is proposed to assess the level of disaster risk of Kelud eruption using Fuzzy methods in each village in the disaster-prone area (KRB). Fuzzy methods classify disaster risk levels based on criteria of hazards, vulnerabilities and index of capacities. The level of disaster risk is divided into low, medium, and high which are spatially mapped. The result of calculations and spatial visualization show that the approach used produces a level of disaster risk that is fairer than only based on hazard.]]>
<![CDATA[Predicting Diabetes by adopting Classification Approach in Data Mining ]]>
<![CDATA[Rapinder Kaur]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.229
<![CDATA[As the world is growing fast, the metamorphosing of things, lifestyle, perceptions of people and resources is taking place. But the elevation in technology has become a challenge now as the ideas, innovations are amplifying. One of the biggest things the advancement and elevations in technology has given birth is “Big Data”. In this data massive amount of information is hidden. In order to refine or process this data and to find out and unmask the insights, many techniques and algorithms have been evolved, one of which is the data mining. The data mining is the approach or procedure which helps in detaching or extracting profitable and fruitful knowledge, reports and facts from the rough or impure data. The prediction analysis is approach comprehended from data mining to forecast and figure out the future making using classification technique. This research work is based on the diabetes prediction by making use of classification approach. In the existing approach SVM classifier is applied for the prediction analysis. To increase accuracy approach of KNN classifier is applied for the prediction analysis. Both the proposed and existing methods are implemented in Python. The simulation results show that accuracy of KNN is increased and execution time is reduced.]]>
<![CDATA[Thermostats: an Open Source Shiny App for Your Open Data Repository ]]>
<![CDATA[Dasapta Erwin Irawan]]>;
<![CDATA[Muhammad Aswan Syahputra]]>;
<![CDATA[Prana Ugi]]>;
<![CDATA[Deny Juanda Puradimaja]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.282
<![CDATA[Hydrochemical analysis has emerged as a powerful methodology in geothermal system profiling. Indonesia is the capital of geothermal energy with its more than 100 active volcanoes. Therefore we need to have an analytical, data-driven, and user-focused online application of geothermal water quality. Proudly we introduce Thermostats (https://aswansyahputra.shinyapps.io/thermostats/). We collected water quality from 416 geothermal sites across Indonesia. Three main objectives are to provide an online open-free to use data repository, to visualize the dataset to suit user’s needs, and to help users understand the geothermal system of each particular site. At the end, we hope they like this system and donate their own dataset to make it better for future users. We designed this online app using Shiny, because it’s open source, lightweight and portable. It’s very intuitive to load our descriptive, bivariate and multivariate statistics. We selected Principal Component Analysis and Cluster Analysis as two strong statistics for water sample classification. Users could add their own dataset by making a pull request on Github (https://github.com/dasaptaerwin/thermostats) or sending it to us by email to make it visible in the application and included in the visualization. We make this application portable, so it can be installed on a local computer or a server, to enable an easy and fluid way of data sharing between collaborators.]]>
<![CDATA[Application of Graphene Silicone Grease in heat dissipation for the Intel Core i5 Processor ]]>
<![CDATA[Phuong Thi Mai]]>;
<![CDATA[Tuan Anh Bui]]>;
<![CDATA[Hau Van Tran]]>;
<![CDATA[Trinh Van Pham]]>;
<![CDATA[Dinh Nang Nguyen]]>;
<![CDATA[Minh Ngoc Phan]]>;
<![CDATA[Thang Hung Bui]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.260
<![CDATA[Graphene was known as the material that owning many superiority properties and high thermal conductivity. Thermal conductivity of single-layer graphene was up to 5200 W/mK (compared to the thermal conductivity of Carbon nanotubes 2000 W/mK and Silver 410 W/mK). This had suggested that graphene is the most potential material for heat dissipation applications for electronic devices, such as a computer microprocessor, high power LED... To enhance the dispersion of the GNPs silicone matrix, we were functionalized graphene nanoplatelets (GNPs) with carboxyl (-COOH) groups. The silicone thermal greases containing GNPs were prepared by High- Energy Ball Milling method (8000D Mixer /Mill). The results of SEM, FTIR, Raman showed the presence of the carboxyl groups in GNPs and GNPs uniform dispersion dispersed in grease. The results of thermal conductivity from Transient Hot Bridge THB-100 showed that thermal conductivity enhancement was up to 234 % with Gr-COOH 1.0 vol.%. Thermal grease is used as a thermal interface material to coolants for Intel Core i5 processor. The results of thermal dissipation efficiency shown the saturation temperature of the processor using thermal grease containing 1.0 vol.% Gr-COOH decreased 4℃, compared to the silicone grease.]]>
<![CDATA[Application of Remote Sensing Data in Lithological Discrimination of Kerdous Inlier in the Anti Atlas Belt of Morocco ]]>
<![CDATA[Amine Jellouli]]>;
<![CDATA[Abderrazak El Harti]]>;
<![CDATA[Zakaria Adiri]]>;
<![CDATA[El Mostafa Bachaoui]]>;
<![CDATA[Abderrahmane El Ghmari]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.265
<![CDATA[Remote sensing data reveals a great importance for lithological mapping due to their spatial, spectral and radiometric characteristics. Lithological mapping using spatial data is a preliminary and important step to mineral mapping. In this work, several spectral and radiometric transformations methods were applied on Landsat 8 OLI data to enhance lithological units in the study area situated in the Anti Atlas belt. The methods of Optimum Index Factor (OIF), Decorrelation Stretching (DS), Principal Components Analysis (PCA) and Band Ratioing (BR) showed good results for lithological mapping in comparison with the existing geological and field investigation. An RGB color composite of OLI bands 651 was developed for mapping lithological units of the study area by fusing optimum index factor (OIF) and decorrelation stretching methods. furthermore, Band ratios derived from image spectra were applied in two RGB color composites (7+4/2, PC1, PC2) and (PC1, 7/6, 3/7) providing good discrimination of the lithological units. The Landsat-8 OLI data significantly provided satisfied results for lithological mapping.]]>
<![CDATA[Visual Analysis of Correlation Between Diseases Evolution and Human Dynamics ]]>
<![CDATA[Lanyun Zhang]]>;
<![CDATA[Hongyu Jiang]]>;
<![CDATA[Weixin Zhao]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments ]]>
Publisher : <![CDATA[Politeknik Negeri Padang ]]>
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DOI: 10.30630/joiv.3.2-2.279
<![CDATA[With the urbanization and the increasing pervasiveness of medical system, the systems utilizing digital technologies for their operation generates enormous amounts of digital traces capable of reflecting in real-time human behaviors and health situation in the city. It is not only transforming how we study the urbanization effect on disease’s emergence and spread in cities but opens up new possibilities for tools that give people access to up-to-date information about urban dynamics the situation of diseases. Moreover, it was allowing us to make decisions that are more in sync with their environment. This paper introduces a prototype for exploring the dynamic of diseases-urbanization and supports urban planner meaningful access to large amounts of data capable of informing their decisions. We describe the technology context in this project, illustrate the requirements and the architecture of the platform to serve as a base for monitoring the health situation of the city. Finally, we shows the validity and practicability of the system by using real data in M city, China, which including electronic medical record, cellular network data, public transport, Census data.]]>
