Fachrul Kurniawan

Bio: Fachrul Kurniawan is an academic researcher from Islamic University. The author has contributed to research in topics: The Internet & Smart city. The author has an hindex of 4, co-authored 25 publications receiving 47 citations. Previous affiliations of Fachrul Kurniawan include Sepuluh Nopember Institute of Technology & Maulana Malik Ibrahim State Islamic University (Universitas Islam Negeri Maulana Malik Ibrahim Malang).

Market Basket Analysis to Identify Customer Behaviours by Way of Transaction Data

Abstract: Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of following the existing steps on data mining technique. The trial result showed that the development and the implementation of market basket analysis application through association rule method using apriori algorithm could work well. With the means of confidence value of 46.69% and support value of 1.78%, and the amount of the generated rule was 30 rules.

Blockchain-Based Data Sharing for Decentralized Tourism Destinations Recommendation System

Abstract: One thing that tourists need to plan their tourism activities is a recommendation system. The tourism destinations recommendation system in this study has three primary nodes, namely user, server, and sensor. Each node requires the ability to share data to produce recommendations that the user expects through their mobile devices. In this paper, we propose the data-sharing system scheme uses a blockchain-based decentralized network that each node can be connected directly to each other, to support the exchange of data between them. The block architecture used in the blockchain network has three main parts, namely block information, hashes, and data. Each type of node has a different structure and direction of data communication. Where the user node sends destination assessment data to the server node, then the server node sends data from the machine learning process to the user node. The sensor sends dynamic data about popularity, traffic, and weather to the user node as consideration for finalizing the generating recommendations process. In the process of sending data, each node in the blockchain network goes through several functions, including hashing, block validation, chaining block, and broadcast. We conduct web-based experiments and analysis of the data-sharing system to illustrate the system works. The experimental results show that the system handles data circulation with an average time of mine is 84.5 ms in sending multi-criteria assessment data from the user and 119.1 ms in sending data of machine learning result from the server.

Smart Monitoring Agriculture Based on Internet of Things

Abstract: Agriculture is one of the issues that never runs out to be discussed. Since agriculture is one of the main sources of livelihood of the rural population. Therefore, the construction of agricultural data-based internet of things is very important to do. In this paper, we present the steps of making agricultural monitoring tool-based internet of things in a comprehensive manner, using prototyping methods drawn from the experience of the agricultural process. A combination of hardware and software that uses data communication-based wireless fidelity (Wi-Fi) allow monitoring parameters of agricultural data visually and accurately, making it easier for farmers to act when something events that require rapid handling.

Makassar smart city operation center priority optimization using fuzzy multi-criteria decision-making

Abstract: The development of smart city operation room of Makassar possesses several equally important stages which are equally important. There are four stages of development that are 1) data center construction, 2) camera distribution around the city, 3) wall room monitoring construction, and 4) smart operation room architecture construction. Since the time and cost are limited, it forces the project manager to be able to manage and control the priority in conducting the project. There are several usable criteria to determine the priority in conducting the project development through criteria consideration of the entire project stages. Project priority optimization system aims at making every single project activity effective including its evaluation process. It also exposes a ranking illustration of foremost project priority by providing cost preference of the entire development stages. Fuzzy Multi-Criteria Decision-Making is used to illustrate the project priority rank and further to determine the alternative optimal option in conducting the project. This enforces particular project to allocate its cost to the project with a higher level of cost necessity. The company, therefore, enables to make effective funding for the entire project based on the level of importance and time achievement and subsequently it promotes accessible technology integration. The conducted experiment suggests that the first construction of the project is data center construction followed by wall room construction and CCTV distribution. This is relevant with optimization value result of data center 0,405 higher than A2 0,42 for wall room construction and A3 CCTV distribution 0,24.

A Comparison of Naive Bayes Methods, Logistic Regression and KNN for Predicting Healing of Covid-19 Patients in Indonesia

Abstract: Since it was declared a global pandemic by the World Health Organization (WHO), the number of cases of Covid-19 patients who died has continued to increase. One of the countries with the highest death rate in the world is Indonesia. On Saturday, April 4, 2020, Indonesia reached the highest death rate for Covid-19 patients, around 9.11%. This number must be suppressed so that there are no more victims. For this reason, it is necessary to know actually the factors that can reduce the risk of death and predict the chance of curing Covid-19 patients. In data mining, there are several methods that can be used to predict a patient's recovery rate by considering several variables. The variables used in this study were age and gender. Naive Bayes Method, logistic regression, and K-Nearest Neighbor (KNN) are the methods to be chosen in this study to analyze their most accurate performance. The result shows that KNN has the highest accuracy, which is 0.750 compared to logistic regression which has a value of 0.703 as well as Naive Bayes which has the same value. Meanwhile, the level of precision of the three models shows that KNN also has the highest value, namely 0.750 than logistic regression and Naive Bayes which have the same value, namely 0.700. The recall value of the three also shows that the kNN remains the highest with 0.750 compared to the two comparison models which have the same value, namely 0.708.

E Learning Strategies For Delivering Knowledge In The Digital Age

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Application of Decision-Making Methods in Smart City Projects: A Systematic Literature Review

Abstract: In the current era, Smart City projects have to deal with big social, ecological, and technological challenges such as digitalization, pollution, democratic aspirations, more security, etc. The higher involvement of multi-stakeholders in the different phases of the projects is one strategy, enabling a variety of perspectives to be considered and thus to develop a shared vision of the city. Paradoxically, the dynamic and multiple natures of stakeholders appear to be a source of complication and uncertainty in the decision-making process. This study aims to provide a better understanding of this paradox and uses a systematic literature review methodology, as an original big data analysis, in order to investigate decision-making methods, enabling communication between multi-stakeholders, especially the involvement of citizens, into various phases of Smart City projects. Beginning with 606 papers, a bibliometric process led to the selection of 76 of these articles. Detailed analysis of these documents generated a general map for applying different decision-making methods at various levels of decision and implementation phases.

Surveillance of SigFox technology integrated with environmental monitoring

Abstract: Internet of Things (IoT) became an accessible solution to the users for controlling and managing different processes and systems. Those systems can include features such as easily monitoring plants growing process, a thing that is widely needed now because of the population number exponential growth, expecting to reach 9.7 billion until the year 2050. This thing is going to increase the need for food exponentially and at the same thing, it is going to reduce the area of usable soil for agriculture while the available natural resources are going to decrease. The traditional methods of environment data collecting are still in use, such as using human labor periodically to determine the different conditions such as weather, water levels, and possible pests present in the fields. In this article, we are proposing a monitoring system capable of collecting information about the environment (such as, humidity, temperature, and luminosity) that could allow the optimal growth of plants by integrating a network of sensors capable of transmitting the collected data by using the SigFox technology. This system intends to increase productivity and profits, reduce human labor, and eventually, integrate other technologies to make the agricultural process simpler and more efficient.

Domestic Use of Unmanned Aircraft Systems

Abstract: Unmanned aircraft systems (UASs) are aircraft controlled by ground operators, and have begun to expand beyond their military role. Operator controllability ranges from changing only high-level aspects of the mission to taking full control of the UAS. UASs have 3 advantages over manned aircraft in certain niche applications: 1) they are orders of magnitude less expensive; 2) they are not affected by the fatigue of human pilots; and 3) they do not put human pilots at risk. Yet, UASs are not nearly being developed and put to use in the numbers expected, largely due to the Experimental Category Special Airworthiness certification process currently required for commercial UAS flight by the Federal Aviation Administration. These certificates must be obtained for every UAS, no matter its size, material composition, level of autonomy, or flight path. This process is time consuming, constitutes a major deterrent for UAS enterprises, and is burdensome for the FAA. This article discusses this lengthy, often cumbersome certification process that has, to date, granted only about a dozen experimental certificates since 2005 out of many more requests.