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Mochammad Apriyadi Hadi Sirad
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ijeeic.unkhair@gmail.com
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ijeeic.unkhair@gmail.com
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Departement of Electrical Engineering, Faculty of Engineering, Universitas Khairun, Address: Yusuf Abdulrahman No. 53 (Gambesi) Ternate City - Indonesia
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Kota ternate,
Maluku utara
INDONESIA
International Journal of Electrical Engineering and Intelligent Computing
Published by Universitas Khairun
ISSN : -     EISSN : 30315255     DOI : 10.33387/ijeeic
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Energy
International Journal of Electrical Engineering and Intelligent Computing, E-ISSN : 3031-5255 is an official publication of the Universitas Khairun. The IJEEIC is an international journal is a peer-reviewed open-access. The IJEEIC that has been published online since 2023.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 28 Documents
 1   2   3 
Prediction of the Number of Motorized Vehicles in Ternate City Using the Average Based Fuzzy Time Series Model Method Friyanti Friyanti; Iis Hamsir Ayub Wahab; Arbain Tata
International Journal Of Electrical Engineering and Inteligent Computing Vol 1 No 2 June (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v1i2.9110

Abstract

Prediction or forecasting is one of the most important elements in decision-making. The impact caused is the number of motorized vehicles, residents, roads, and area area. By predicting the number of motor vehicles, the prediction data can be used from a program to reduce the impact of a high number of motor vehicles. This study aims to determine the Prediction of the Number of Motorized Vehicles in Ternate City using the Average Based Fuzzy Time Series Model Method in Ternate City from 2019 to 2024. Settlement using Average Based Method data and fuzzy time series interval numbers have been determined at the beginning of the calculation process, this process is very influential in the formation of fuzzyrelationship on each number to compare each other which will certainly have an impact on the difference in the results of the reduction calculation. The test results are known that the Fuzzy time series is one of the methods for prediction. One type of method is the average-based fuzzy time series with the average total value calculated using the Mean Absolute Percentage Error (MAPE) method obtained from the number of each indicator of 2.98% which shows that this study is included in the category of good used in the prediction of motor vehicles in Ternate City because it has an accuracy value of less than 20%. From the predictions carried out, the MAPE value of the test was 1.01%, the MSE value of forecasting was 1400.5, and the MAD value of forecasting was 27.93.
Coordinated WECS–BESS Control for Frequency Resilience Enhancement in Low-Inertia Power Systems Andi Syarifuddin; Muhammad Naim; Amelya Indah Pratiwi
International Journal Of Electrical Engineering and Inteligent Computing Vol 3 No 1 December (2025): International Journal Of Electrical Engineering And Intelligent Computin
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v3i1.11314

Abstract

The growing dominance of power-electronics–interfaced renewable resources, particularly wind energy conversion systems (WECS), has led to a substantial reduction in system inertia, posing significant challenges to frequency resilience in modern power grids. Previous national-scale studies on a 23-bus equivalent transmission system have highlighted degraded dynamic performance under high wind penetration; however, active mitigation strategies were not incorporated. This paper extends that work by developing and validating a coordinated control framework combining virtual inertia and adaptive droop mechanisms implemented on Battery Energy Storage Systems (BESS) and DFIG-based WECS. A modified IEEE 23-bus model, scaled from the scaled to represent a national transmission grid, is simulated in MATLAB/Simulink to evaluate performance under various wind penetration and fault conditions. Simulation results demonstrate that the proposed coordinated control improves transient frequency resilience reducing the rate of change of frequency (RoCoF) by up to 38%, increasing frequency nadir by 0.43 Hz, and accelerating voltage recovery within grid-code limits. The MATLAB/Simulink workflow provides a reproducible validation platform for coordinated grid-forming strategies. The proposed approach effectively addresses the low-inertia limitation identified in the previous study and establishes a scalable framework for future techno-economic optimization and hybrid renewable integration in national power systems.  
Overload Protection and Electricity Volume Monitoring on Internet of Things (IOT)-Based Three-Phase Induction Motors Ramly Rasyid; Miftah Muhammad; Mochammad Apriyadi Hadi Sirad
International Journal Of Electrical Engineering and Inteligent Computing Vol 2 No 1 December (2024): International Journal Of Electrical Engineering And Intelligent Computin
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v2i1.9711

Abstract

The protection and monitoring of the amount of electricity in three-phase induction motors that are widely used in the industry needs to be carried out continuously so that the performance of the motor continues to run well and if there is a disturbance, it can be known early. The purpose of the research to be carried out is to make a device to protect and monitor the amount of electricity of a three-phase induction motor based on the Internet of Things (IoT) and see the performance of the device. From the results of the overload protection test with the three-phase induction motor load current indicator, it can be seen that when the motor is loaded until the current rises at the R phase of 1.23 A, the S phase 1.31 A, and the T phase 1.24 A, which means that the maximum current of the induction motor is exceeded by 0.401 A as the relay works to protect the induction motor. As for the calculation of the measurement error presentation, it can be seen that for the error presentation, the voltage measurement ranges from 0.001% to 0.088%, current 0.001% to 3.509%, power factor 0.433% to 4.438%, apparent power 0.020% to 3.774%, active power 0.149% to 4.904%, and reactive power 0.008% to 4.455%.  The tool that is made works well because the protection runs well and the error presentation is below 5%. 
Performance Visualization of Southbound Interface in Software Defined Networking Fahrizal Djohar; Eueung Mulyana; Suciana Suciana; Andi Muhammad Ilyas; Muhammad Natsir Rahman; Achmad Prajudin Sardju
International Journal Of Electrical Engineering and Inteligent Computing Vol 1 No 1 December (2023): International Journal of Electrical Engineering and Intelligent Computin
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v1i1.6926

Abstract

Software Defined Networking (SDN) makes Internet network configuration easier by separating the control plane and data plane. The control plane on the controller has information on network devices in the data plane and centrally control these devices. One of the controllers in SDN being developed is the Open Network Operating System (ONOS). ONOS provides interfaces such as Representational State Transfer (REST) Application Programming Interface (API). The ONOS core REST API provides some information from the network connected to it, such as devices, statistics, and the information in JSON file. The primary objective of this study is to develop an interface that simplifies performance monitoring through graphical representation. This involves testing the visualization with various topologies and conducting a comparative analysis of the visualization results across these topologies. The creation of the interface entails presenting statistical data, available in the form of a JSON file from the ONOS controller via the REST API, on the web interface in graphical format. The resulting visualization generates a graph that aligns with the performance characteristics of each topology, reflecting device details, ports, and additional parameters such as the count of sent and received packets, as well as sent and received bytes. The performance visualization outcomes specific to each topology are consistent with the number of connections and are prominently displayed on the web interface. Additionally, this research evaluates network throughput and bandwidth by sending ICMP packet and iperf tests across each topology. Among all the openflow tests performed on various network topologies, it was observed that the tree topology exhibited the lowest network capacity utilization, followed by the leaf-spine topology, and finally the ring topology.
Analysis of the Magnitude of Load Shedding on Frequency Reduction at the UP3 Cotton Plantation Diesel Power Plant (PLTD) Naomi Lembang
International Journal Of Electrical Engineering and Inteligent Computing Vol 1 No 2 June (2024): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v1i2.9031

Abstract

Load shedding due to frequency reduction in the Fakfak Regency electric power system occurred due to the overload of the KORMAN-01 engine with an installed power of 400 kW, operating power 200 kW, DOSSAN-02 engine, with installed power 500 Kw, operating power 500 kW, and KOMATSU-04 engine with installed power 800 Kw, operating power 600 at PLTD Kebun Kapas, PT. PLN (Persero) ULP FAKFAK, there was an overload on generating machines that were still operating due to a lack of power being generated where the power generated was less than the load on the system which decreased resulting in a black out. The aim is to determine the amount of load shedding when the frequency decreases by calculating. The results obtained by overloading the KORMAN-01, DOSSAN-02, KOMATSU-04 engines resulted in a decrease in frequency to 49,765 Hz, 48,883 Hz, 48,170 Hz approaching the normal frequency of 50 Hz and the calculated load shedding results were 198,108 kW, 23,092 kW, and 153,565 kW.
A digital image recommendation system using Semantic Segmentation Omar Muayad Abdullah
International Journal Of Electrical Engineering and Inteligent Computing Vol 3 No 2 June (2026): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v3i2.11397

Abstract

The research aims to determine the nature and features of a digital image in order to suggest or recommend relative images (candidate) to the image (query) that is determined by the user which may contain high scientific or valuable contents. The proposed method processes the semantic segmentation firstly, then computing the feature similarity, by segmenting the image into meaningful object regions then extracting isolating features for the determined objects, then the system will enhance the matching range between the recommendation query and the output of the semantic level. The sample was consisting of 1380 images based on 70/30 split with selected 3 labels (cars, persons and trees). The preprocessing step has been applied where the features were extracted from the determined image in order to determine its contents then we can recommend (candidate) the images with the relative features, this process is applied using the concept of semantic segmentation, where the procedure is partitioned into several steps: The first step includes grouping (cars, persons and trees) images from multiple online and real-world datasets, the grouped raw data that can be processed by the system normalization have been processed using Min-Max normalization that is used for standardizing the input data. The second step is the feature extraction process which is achieved using a modified VGG-16 net and the fully connected layers have been removed and the output will be a 2-D features map, then we convert this map to a 1-D vector called feature vector using a Global Average Pooling. The next step is obtaining feature labels by applying a Support Vector Machine SVM classifier, then we recommended the images with relative features to the determined (query) image, this step is achieved using a Pearson correlation coefficient. The final step is constructing a Confusion Matrix and applying the (F1-score, Recall, Precision and Accuracy) metrices in order to estimate the performance.
Big Data Driven Approach for Stock Price Forecasting Using Machine Learning Wael Hadeed; Nagham Sultan; Dhuha Abdullah
International Journal Of Electrical Engineering and Inteligent Computing Vol 3 No 2 June (2026): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v3i2.11518

Abstract

Big data is becoming a major factor that changes or influences various things in real world. One of such is the financial market where the use of advanced analytical techniques, which leads to the changes in investment decisions, can be really of huge effect. Simply put, the main point of implementing the most modern tools and methods to analyze the data inflow basing on the idea of data exploitation is clear and obvious. Thus, the impact of big data on the financial markets is massive enough since it can lead to the improvement of the stock price predictions as well as making the decision process of investors more transparent, easier and quicker. This report is a comprehensive review of the Apple Inc. stock trading data from 2020 to 2025. Big data tools will be necessary to load and process a vast amount of financial data, thus, laying a solid foundation for the analysis in order to uncover phenomena and market trends caused by various events. In addition, machine learning algorithms will be deployed to construct accurate forecasting models that can recognize complex data patterns. The objective of this study is to apply big data and machine learning techniques to forecast Apple Inc. stock price which would be an example of how such technological innovations can lead to a significant increase in the accuracy of financial forecasting. In addition, this paper will also compare the predicted data with the real ones so as to figure out the models' performance.
Performance Analysis of 100 KVA Generator Set as AC Backup Supply at Panakukang Electrical Substation Muh. Imran Bachtiar; Andi Wawan Indrawan; Muammar Abidin; Syarifuddin Nojeng; Mochammad Apriyadi Hadi Sirad
International Journal Of Electrical Engineering and Inteligent Computing Vol 3 No 2 June (2026): International Journal Of Electrical Engineering And Intelligent Computing
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/ijeeic.v3i2.12162

Abstract

Substation AC backup supply reliability is critical for sustaining auxiliary equipment operation during grid blackouts. Prior studies on genset sizing and motor starting have not specifically addressed substation AC backup systems integrating continuous loads, non-continuous motor loads, and comparative starting methods. This study evaluates the adequacy of the existing 100 kVA prime / 110 kVA standby genset at Panakkukang Substation using field data collection and ETAP 19.0.1 simulation. The total continuous load is 9.342 kW, requiring a minimum genset capacity of 11.675 kW after applying a 46.7% demand factor and 125% safety factor (per NFPA 110 and ISO 8528-1). The existing genset adequately covers continuous loads at only 10.62% of standby capacity. However, simultaneous starting of the hydrant and oil pump motors exceeds genset capability under all methods tested: Direct-On-Line (DOL) causes a 24.00% voltage dip requiring 463.74 kVA; Wye-Delta reduces voltage dip to 17.48% requiring 231.87 kVA; and VFD limits voltage dip to below 3% requiring only 159.17 kVA, compliant with IEEE Std 1159-2019. This study recommends upgrading genset capacity to at least 160 kVA and adopting VFD motor starting to ensure reliable substation AC backup supply.

Page 3 of 3 | Total Record : 28

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