Internet of Things and Artificial Intelligence Journal
Internet of Things and Artificial Intelligence Journal (IOTA) is a journal that is officially under the auspices of the Association for Scientific Computing, Electronics, and Engineering (ASCEE), Internet of Things and Artificial Intelligence Journal is a journal that focuses on the Internet of Things (IoT), ISSN 2774-4353, publishing the latest papers in the IoT field and Artificial Intelligence (AI) i.e., Machine Learning (ML), and Deep Learning (DL)., etc., Topics can be included in this journal : IoT for various applications ( medical, sport, agriculture, smart city, smart home, smart environment, etc.) IoT communication and networking protocols ( LoRa, WiFi, Bluetooth Low Energy, etc.) IoT enabling technologies IoT system architecture IoT with a Recently Sensors Technology IoT with Wireless Sensor Network (WSNs) Technology Cloud-based IoT IoT data analytics IoT Security IoT Management Services IoT with Low Power and Energy Harvesting Future technologies for IoT Future Internet design for IoT Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) Drone or UAV, and IoT Analyzes IoT with a Financial Technology (FINTECH) Managemen approach IoT for Education Technology IoT for Industry Computers & Security :: computer security, audit, control and data integrity in all sectors - industry, commerce and academia Computer application for Economy, Finance, Business, Micro, Small & Medium Enterprises (MSMEs), Accounting, Management, and other sectors Review articles on international & national legal rules in the use of computer software, internet of things, frequency usage, etc. Internet of Things and Artificial Intelligence Journal has a frequency of being published 4 times a year or 4 issues every year (February, May, August, and November) with the Peer review process.
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<![CDATA[Modern Farming Biofloc ponds for tilapia aquaculture based on the internet of things use a fuzzy logic algorithm ]]>
<![CDATA[Mabe Parenreng, Jumadi]]>;
<![CDATA[Syahrul, Syahrul]]>;
<![CDATA[Wahid, Abdul]]>;
<![CDATA[Sary, Desta Winda]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v2i4.548
<![CDATA[This study aims to create a smart system in controlling tilapia biofloc ponds. The type of research is laboratory experiments and the category of system testing, namely Functionality testing, is used to measure the performance of the system hardware. Testing the functionality of the prototype is tested in 2 stages, the first test begins with knowing the accuracy of sensor data and testing manually. The second test is to test the prototype as a whole, namely by giving treatment so that the performance of the prototype can be known as desired. The results obtained when the temperature is cold, the water heater heater will turn on and treatment to the pH sensor is obtained, namely an acidic pH condition, then the water pump will turn on and drain the water until the ultrasonic sensor detects the maximum water level that can be drained. Testing on feeding is by monitoring the servo successfully rotating, opening and closing the feed storage container based on the time that has been set. The results of monitoring feeding in the morning, afternoon and evening are successful and can send notifications. Based on the test results, the resulting " Modern Farming Biofloc ponds for tilapia aquaculture based on the internet of things use a fuzzy logic algorithm" can run as expected.]]>
<![CDATA[Analysis of Tourism Businesses Number in the Entertainment and Recreation Sector using Predictive Apriori Algorithm ]]>
<![CDATA[Manurung, Romarta Yemima]]>;
<![CDATA[Sari, Dewi Purwita]]>;
<![CDATA[Agustinah, Nabila]]>;
<![CDATA[Syanahieskara, Razel]]>;
<![CDATA[Tahyudin , Imam]]>;
<![CDATA[Nurfaizah, Nurfaizah]]>;
<![CDATA[Alvi Sholikhatin, Siti]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v2i4.550
<![CDATA[Data Analysis of the Number of Tourism Businesses in the Entertainment and Recreation Sector is used as data sources for extracting information. In this study, data on the number of tourism businesses in the entertainment and recreation sector will be mined to support decision-making information. This research purpose is to analyze the tourism business number in the entertainment and recreation sectors. The method is using predictive Apriori algorithm. The data has been tested using Knime software to process data on the number of tourism businesses in the entertainment and recreation sector at the domestic level by using business data whose numbers are increasing or decreasing. Starting from entering nodes 1, 2 and 3 to getting node 4, which is the final result. The results obtained show the data set that produces the final result for every 1 tourism business data. The result obtained that the tourism number in entertainment and recreation sectors are increasing. Furthermore, the prediction result of entertainment and recreation which have best accuracy are balls, discotheques, massage parlors, karaoke, live music, massage parlors, sports and physical fitness centers, family recreation facilities and spa]]>
<![CDATA[Secure Wireless Sensor Network using Cryptography for Smart Farming Systems ]]>
<![CDATA[Wahid, Abdul]]>;
<![CDATA[Juliady, Ilham]]>;
<![CDATA[Zain, Satria Gunawan]]>;
<![CDATA[Parenreng, Jumadi Mabe]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v2i4.554
<![CDATA[Internet of Things (IoT) technology has become part of human life. Agriculture in many parts is one of IoT implementation segment including the Cultivation of mold oysters. Internet of Things (IoT) is applied to collect data from combined sensors in the Wireless Sensor Network (WSN) will make it easy for farmers to monitor and control garden they remotely. Regardless of the application system control distance far based WSN that will make it easy for a farmer, the system has gap security, and one of them that is hacking and tapping of communication data The IoT . is really dangerous on effort if condition room mold oyster the known by someone hacker who can just is rival effort. It is a needed something method for secure communication when the data transfer process is over-guaranteed. The method used is application Base64 -based data encryption/decryption on WSN node devices and controlling and monitoring mobile devices. Based on results trials carried out after the implementation of Secure WSN with scenario tapping using the Wireshark tool show no data can be read. Analysis results show that this model could be applied as Secure WSN for Smart Farming System.]]>
<![CDATA[A Decision Support System For Selecting The Best Practical Work Students Using MOORA Method ]]>
<![CDATA[Siregar, Victor Marudut Mulia]]>;
<![CDATA[Hanafiah, M. Ali]]>;
<![CDATA[Siagian, Nancy Florida]]>;
<![CDATA[Sinaga, Kalvin]]>;
<![CDATA[Yunus, Muhammad]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v2i4.562
<![CDATA[This research aims to solve the problem of selecting the best practical work students at the Politeknik Bisnis Indonesia. The current selection of the best practical work students at PBI does not yet use a decision support system approach. This problem is solved by building a Decision Support System using Multi-Objective Optimization based on Ratio Analysis (MOORA) method. The criteria used in this DSS consist of discipline, teamwork, skills, quality of work, and attendance. As for the results of data processing from this study, the three best alternative data were obtained, namely alternative Vivi (A6) as the 1st best Practical Work Students with a score of Yi = 36.5954, Hafiz (A1) as the 2nd best Practical Work Students with a score of Yi = 34.5339, Cahaya (A3) as the 3rd best PKL student with a score of Yi = 33.4767. Through this decision support system that has been built, the selection of the best practical work students can be made quickly and effectively.]]>
<![CDATA[Decision Support System for Selecting KIP-K Recipients at Amikom University, Purwokerto Using the TOPSIS Method ]]>
<![CDATA[Khotimah, Khusnul]]>;
<![CDATA[Anggraini, Lintang Wahyu]]>;
<![CDATA[Alfirnanda, Weersa Talta]]>;
<![CDATA[Tahyudin, Imam]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v2i4.566
<![CDATA[The Indonesia Smart College Card Program (KIP-K) is a tuition assistance program (scholarship) from the Government through the Ministry of Education, Culture, Research and Technology (Kemdikbudristek). In the KIP-K scholarship selection process, criteria are needed to determine who is right to receive the KIP-K scholarship. This study aims to carry out the process of determining the ranking of KIP-K scholarship recipients based on the TOPSIS method. To determine scholarship recipients with outstanding achievements, Amikom Purwokerto University selects prospective scholarship recipients based on several criteria. The criteria used are Student DTKS Status, Parents' Income, Parents' Dependents, Average School Exams, Student Transportation Costs. The results obtained from this study are in the form of ranking obtained from the highest value to the lowest value. There were 112 prospective students who were entitled to get KIP-K scholarships out of a total of 314 applicants.]]>
