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.
Articles
174 Documents
<![CDATA[NMC Lithium Ion Battery Management with Distributed Monitoring Topology ]]>
<![CDATA[Andriana, Andriana]]>;
<![CDATA[Rahman, Sutisna Abdul]]>;
<![CDATA[Arrazaq, Fajar]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i2.739
<![CDATA[Lithium-ion battery management often called BMS (Battery Management System) is a system that controls all operations between the battery and the required load. The advantages of lithium-ion batteries, such as high energy density and long service life, make them highly desirable. Along with the increase in demand, the use of lithium-ion batteries is also increasingly complex, such as in the use of electric vehicles and smart grids. The battery must have the same voltage as the battery when connected directly. Safety and battery life are at stake if this condition is not met. BMS is a solution to this problem. The purpose of this research is to create a BMS that has three main features: monitoring, balancing, and protection. The Nano Microcontroller can be used to build the BMS. For nickel-based battery types, namely NMC (Nickel Manganese Cobalt) batteries, the design of a battery management system with a distributed monitoring and protection architecture can help battery packs be used for various applications and reduce battery pack production costs.]]>
<![CDATA[Design of K-Nearest Neighbor Algorithm For Classification of Credit Loan Eligibility At Senarak Dana Purwakarta Cooperative ]]>
<![CDATA[Kurniawan, Imay]]>;
<![CDATA[Santoso, Purwadi Budi]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i2.742
<![CDATA[Semarak Dana Cooperative is a savings and loan cooperative located in Purwakarta that has experience lending money to its members as many as 162 money lending transactions. However, there are 26 instances of bad debts. To avoid bad debts, the cooperative needs to classify loans to its members. Classification is done by using the K-Nearest Neighbor (KNN) method based on the attributes of employment, income, age, credit amount, term, and collateral value. Data taken from as many as 162 members are sorted into 2 parts, namely 149 transactions used as training data and 13 transactions used as testing data. In addition, the data is also sorted into two classes, namely 136 current classes and 26 bad classes. The KNN process consists of four stages. First, determine the parameter K nearest neighbor distance. The second stage is to calculate the distance between testing data and training data using Euclidean distance. The third stage sorts the distance data that has been calculated using selection sort in order from the smallest to the largest value of K. The fourth stage calculates the largest number of classes for the largest number of classes set as the classification result class. Implementation using Borland Delphi and Mysql database. The research method was used by applying the Waterfall method. The Waterfall method used is composed of analysis, design, coding, and testing. System design using Unified Modeling Language (UML) by describing use case diagram, activity diagram, and class diagram. Based on the confusion matrix of the KNN classification process, the percentage of accuracy is 77%, precision is 88%, and recall is 78%. These results can be said that the results obtained are quite good, which exceeds 70%.]]>
<![CDATA[Internet-based Design of Hydroponic Plants Monitoring and Automation Control Systems ]]>
<![CDATA[Parenreng, Jumadi Mabe]]>;
<![CDATA[Andani, Andi Ferry Adlian Tri]]>;
<![CDATA[Yahya, Muhammad]]>;
<![CDATA[Adiba, Fhatiah]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i2.744
<![CDATA[Melons are one of the fruit types widely favored in the market due to their high content of vitamins, minerals, and water. Melon plants are challenging to cultivate when environmental conditions such as soil and air do not align with their characteristics. One way to address this is through hydroponic cultivation, which reduces the interaction of melon fruits with the air and environment. However, this method has a drawback in that the nutrient solution and water circulation of the plants must be continuously monitored. Therefore, a system is needed to automatically monitor and control the conditions of hydroponic plant growth with the assistance of IoT technology. This research proposes the Design and Implementation of a Monitoring and Automation System for Hydroponic Plant Control Based on the Internet of Things. The hydroponic system, specially designed for melon plants, is equipped with various sensors that can monitor soil nutrients in real time through mobile devices. Based on the test results, the TDS sensor yielded a result of 1313 PPM, the pH Water sensor showed 50.1, and the system also measured air temperature and humidity using DHT22, with air temperature at 29.5°C and humidity at 71.2%.]]>
<![CDATA[Performance Evaluation Of Hybrid System Monitoring Solar Panels Based On WSN Case In Smart Regional Drinking Water Company (PDAM) ]]>
<![CDATA[Parenreng, Jumadi Mabe]]>;
<![CDATA[Zain, Satria Gunawan]]>;
<![CDATA[Muhammad Fajri, syamsir]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.747
<![CDATA[This research is to design and build a wireless sensor network system to monitor the performance of the Regional Drinking Water Company (PDAM) smart solar module on the network server using the DS18B20 temperature sensor and the INA219 sensor. Of course, the use of solar panels also greatly reduces costs for consumers, so the design of this tool is a combination of switching methods between solar panels, batteries, and the State Electricity Company (PLN). There are still many obstacles to using solar panels such as: how effectively they absorb solar energy, and this can contribute to or reduce damage to digital meters not working. The working principle of this tool uses the Wireless Sensor Network (WSN) method so that the designed tool is placed on several solar panel modules on the Smart PDAM so that the sensor sends data to the network and technicians can control it in real-time. Data collection techniques use observation techniques and documentation to obtain test data. This research uses quantitative descriptive analysis techniques that are inductive, objective, and scientific, with data obtained in the form of numbers or statements that are evaluated and analyzed. The results of this study with the PDAM PCB board testing scenario with an average of 320.2 measurements with a multimeter showed an average result of 322.8 with a relative error of 2.6%. The test results with Smart PDAM components showed an average power consumption of 1789.2 mW. The observations of the two panels gave an average result of 887.1 on panel 1 and an average result of 908.7 on panel 2. The results of the DS18B20 temperature sensor comparison test showed an average error of 0.5%. The result of a switching scenario with 20 experiments, resulted in 9 switching operations to the battery and 11 switching operations to the solar panel. Monitoring the solar module with the INA219 sensor, 277 voltage, current, and power data were determined with an average of 17.1 V, 513.9 mA, and 481.5 mW. The calculation results use the exponential moving average formula to predict the 278th data with an exponential moving average of 20 based on sensor data showing a value of 294.7 mA while using a simple moving average is 590.1 mA.]]>
<![CDATA[Prediction Analysis of Package C Student Graduation at the Bollo DMansel Community Learning Activity Center (PKBM) with the Naïve Bayes Algorithm Method ]]>
<![CDATA[Yassir, Muhammad]]>;
<![CDATA[Cahyani, Wanda]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.751
<![CDATA[Education plays a crucial role in improving the quality of human resources and is the key to a nation's progress. Bollo DMansel Community Learning Activity Center (PKBM) in West Papua provides a Paket C Equivalency Education program to help those who are underserved by formal education. The main challenge in this program is to increase student graduation rates. This research aims to analyze and predict the graduation of Paket C students at PKBM Bollo DMansel using the Naive Bayes algorithm method. The data used includes historical student data from 2021 to 2023, with a total of 128 students. The research steps include data collection, data pre-processing, Naive Bayes algorithm application, and prediction model evaluation. The results show that the Naive Bayes algorithm can provide graduation prediction with fairly high accuracy. The factors that most influence student graduation were identified, including attendance, test scores, and participation in activities. This research makes a real contribution to improving the quality of education at PKBM Bollo DMansel by providing a prediction tool to identify students at risk of not graduating so that timely intervention can be provided.]]>
<![CDATA[Design and Performance Analysis of a Fuzzy Logic-Based IoT System for Greenhouse Irrigation Control ]]>
<![CDATA[Ambarwari, Agus]]>;
<![CDATA[Widyawati, Dewi Kania]]>;
<![CDATA[Putra, Septafiansyah Dwi]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.764
<![CDATA[Automatic irrigation has long been used to efficiently irrigate large agricultural areas through drip irrigation systems to minimize water wastage. In greenhouse irrigation, computerized control is essential to improve productivity, as conventional control methods that rely on on-off or proportional control are often inefficient. This research introduces a novel approach to monitor greenhouse environmental conditions and control irrigation duration. The monitoring system architecture consists of sensor nodes and a gateway. The irrigation duration control uses a Fuzzy Logic Controller (FLC) based on the Mamdani method. The FLC is implemented on a NodeMCU ESP8266 board integrated with a DHT22 sensor and a soil moisture sensor. Temperature and soil moisture parameters are used as inputs for the fuzzy logic system in determining the appropriate irrigation duration. The linguistic variables used in the fuzzy membership function include soil moisture (categorized as water, wet, and dry), temperature (categorized as cold, normal, and hot), and watering time (categorized as zero, short, medium, and long). A rule base consisting of nine fuzzy rules was developed based on these membership functions. Experimental results show that the FLC implemented on the NodeMCU ESP8266 has an average accuracy of 99.41% compared to the MATLAB simulation. This shows the fuzzy logic-based system's high accuracy and effectiveness in controlling the duration of greenhouse irrigation. This developed system offers a promising solution to optimize water usage and improve irrigation management in a greenhouse environment.]]>
<![CDATA[Design of Equipment for Detecting and Ensuring Reliability of The Substation ]]>
<![CDATA[Ihsan, Hafid]]>;
<![CDATA[Muwardi, Rachmat]]>;
<![CDATA[Yunita, Mirna]]>;
<![CDATA[Yuliza, Yuliza]]>;
<![CDATA[Dani, Akhmad Wahyu]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.774
<![CDATA[Substations are vital elements of electrical infrastructure that necessitate continuous monitoring and maintenance to ensure optimal performance. This research advocates for the deployment and design of devices based on the Raspberry Pi 3 Model B to enhance substation reliability. The project involves developing hardware and software capable of real-time monitoring of substation conditions, utilizing sensors to measure critical parameters such as temperature, current, voltage, and humidity. The monitoring software is designed to collect, analyze, and report data, employing detection algorithms, including the Fuzzy Mamdani method, to ensure accurate sensor and frequency measurements and to identify potential disturbances or anomalies. Additionally, the system integrates automatic mechanisms for maintaining substation conditions, encompassing preventive measures and rapid responses to emergency situations. Testing under various fault scenarios and operational conditions demonstrated the device's effectiveness in detecting issues and providing swift responses, thereby enhancing substation performance. The results show an average error of 0.14% for voltage measurements, 0.31% for current measurements, and 0.02% for data transmission frequency. This implementation is expected to positively impact substation management and maintenance, reduce the risk of system failures, and improve overall operational efficiency. Leveraging Raspberry Pi technology ensures a cost-effective solution that can be seamlessly integrated with existing substation monitoring systems.]]>
<![CDATA[Implementation of Speed Measurement and Speed Limit System on Motorcycles Based on Global Positioning System ]]>
<![CDATA[Nisa, Fidyatun]]>;
<![CDATA[Aulia, Muhammad Haiqal]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.782
<![CDATA[The Indonesian National Police Traffic Corps (Korlantas Polri) recorded many traffic accidents in 2022, with hundreds of lives lost. High riding speed was identified as a contributing risk factor to these accidents. Uncontrolled motorcycle conditions and the lack of rider focus while riding were also identified as potential causes of accidents. Therefore, researchers designed a solution by creating a device to address these issues. The device to be discussed here is a GPS-based speed-measuring and limiting device. This device aims to reduce the risk of accidents by controlling riding speed. The speed sensor utilizes GPS, with the function to temporarily stop the motorcycle when it reaches a speed of 48 km/h, preventing riders from riding at high speeds. The speed limitation at 48 km/h is expected to reduce the risk of traffic accidents. Based on the analysis and calculations of this GPS-based motorcycle speed-limiting device, it is ensured that the motorcycle will not be damaged when the ignition coil is disrupted for 1 second to temporarily turn off the motorcycle upon reaching the specified speed.]]>
<![CDATA[Hotel Administration Application Design Using Delphi and UI/UX Designer ]]>
<![CDATA[Rahmawati, Noni]]>;
<![CDATA[Suroto, Suroto]]>;
<![CDATA[Syah, Tamrin]]>;
<![CDATA[Kurniawan, Tomi]]>;
<![CDATA[Ramadani, Rio]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.786
<![CDATA[The need for attractive and interactive Web Design is the dream of all service providers to get more customers. However, building the UI / UX Design requires software that can collaborate with the database, as well as having an interactive and attractive design, one of the software desired by Web Developers is Open-Source and can be developed for free and can be developed freely by the Web developer community. As developed here is using the Penpot App. In the Penpot App, we can build a Web design that is used as an easy display for web developers such as Layers and Assets. These layers talk about the appearance that will be used or the layout of some of the required components, while these Assets contain all Web components that can be dragged and dropped on the web layer that is being and will be built. Another component is Design and Prototype, these two components are to choose the right design as used to build the Hotel Website. In this Design we can use a Canvas background to determine the right color, hopefully with the UI/UX Designer use of Penpot can be perfect and follow the expectations of making the Hotel website, so that the percentage of visitors can increase by seeing the performance of the website built, other than UI/UX Designer. And administration system can use the Graphical User Interface Delphi by using the latest version.]]>
<![CDATA[Implementation of a Forward Chaining Expert System in Diagnosing Laptop Damage ]]>
<![CDATA[Sakinah, Putri]]>;
<![CDATA[Hendra, Yomei]]>;
<![CDATA[Satria, Budy]]>;
<![CDATA[Rahman, Zumardi]]>;
<![CDATA[Maulana, Fajar]]>;
<![CDATA[Syaputra, Aldo Eko]]>
<![CDATA[ Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] ]]>
Publisher : <![CDATA[Association for Scientific Computing, Electronics, and Engineering (ASCEE) ]]>
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DOI: 10.31763/iota.v4i3.791
<![CDATA[Laptops have become a primary need for almost everyone, but the damage rate is also high. Manual diagnosis of laptop damage requires special expertise and is prone to errors that can exacerbate damage. The purpose of this study was to develop an expert system based on the forward chaining method to diagnose laptop damage. Data obtained through expert interviews, literature study, and the internet comprised 13 symptoms and five main types of laptop damage. Relate data in tables to form IF-THEN rules of the forward chaining method. The test results on six symptoms indicate that the system can diagnose IC Power damage with 100% accuracy, which is the highest diagnosis. In conclusion, the forward chaining method can diagnose laptop damage based on emerging symptoms.]]>
