Ph.D in Computer Science (Artificial Intelligence)
RESEARCH INTERESTS
Kecerdasan Buatan, Internet of Things, Augmented Reality, Virtual Reality.
28
Scopus Publications
Scopus Publications
Proposed model to predict preeclampsia using machine learning approach Raden Topan Aditya Rahman, Muhammad Modi Lakulu, Ismail Yusuf Panessai, Esti Yuandari, Ika Mardiatul Ulfa, et al. Indonesian Journal of Electrical Engineering and Computer Science, 2024 Pregnancy complications, which are the biggest cause of death in productive women, are more common in developing countries with low incomes. One of the contributors to death in pregnant women is preeclampsia which contributes 2-8% every day. Based on research results, more than 70% of the use of technology can be a solution for early prevention in detecting cases of pregnancy. The aim of this research is to build a model for early detection of preeclampsia using a machine learning approach. Sample using retrospective data with sample size 1.473. Based on the result, decision tree (DT) is the best model with accuracy 92.2% (area under curve (AUC): 0.91; Spec: 92.3; and Sens: 83.6), according to weigh correlation we can show 3 (three) highest features causes preeclampsia is history of hypertension, history of diabetes mellitus, and history of preeclampsia. The health of pregnant women is essential in the development of the fetus, so it needs optimal monitoring. Monitoring during pregnancy can now be done through technology-based examinations for assist health workers in making decisions during pregnancy.
Predicting Premature Birth During Pregnancy Using Machine Learning: A Systematic Review International Journal of Intelligent Systems and Applications in Engineering, 2024
Machine Learning-Based Stroke Prediction: A Critical Analysis Agus Byna, Muhammad Modi Lakulu, Ismail Yusuf Panessai, Nurhaeni International Journal on Advanced Science Engineering and Information Technology, 2024 Stroke is a critical public health issue that frequently has long-term impairment and negative effects. Devising innovative methods that enable timely and accurate identification and intervention is crucial. In this regard, machine learning (ML) and deep learning (DL) approaches of artificial intelligence (AI) play a crucial role in reducing the incidence of strokes. This study systematically analyzed articles from 2012 to 2022 using the PRISMA Method. PRISMA is a tool that facilitates researchers' access to an online platform for self-directed learning. The cumulative quantity of articles gathered for ten years reached 1405 from five databases. However, only 79 relevant articles were used for identification. The main objective was to provide a thorough taxonomy that classifies using and implementing machine learning approaches for stroke prediction. The results of this experiment confirm that machine-learning techniques have a great deal of potential for accurate stroke prediction. Nevertheless, challenges such as biased data and algorithms and the need for models that can be adjusted to accommodate various demographics and healthcare systems continue to exist. It is essential to recognize the need for additional research projects that thoroughly explore potential data biases, algorithmic biases, and the generalizability of models across various demographics and healthcare systems. More research is necessary to further the literature on the complete assessment of machine learning models in precisely forecasting stroke occurrences.
Advancing Preeclampsia Prediction with Machine Learning: A Comprehensive Systematic Literature Review International Journal of Intelligent Systems and Applications in Engineering, 2023
Active High Transmitter-receiver energy model for heterogeneous energy optimisation in a pipeline network S K Subramaniam, F S Feroz, A F T Ibrahim, I Y Panessai, R Sujatha Journal of Physics Conference Series, 2022 A network energy management and optimisation are frequently associated to the network lifetime (maximum operation of nodes in a network) that is contributed by heterogeneous energy consumption pattern among nodes arranged in a pipeline layout. This scenario becomes even more critical in a remote monitoring application of an oil and gas pipeline network where a series of sensing points (commonly battery powered wireless nodes) are needed to communicate the measurements to a centralised monitoring station. This paper introduces the Active High Transmitter-receiver energy model (AHiT) which was designed as an adaptive sleep/wake for sensor nodes to optimise energy consumption in the long run. Implementing AHiT energy model on sensor nodes improves the energy consumption based on data transfer activity in a multi-hop pipeline layout wireless sensor network (WSN). In this research, the proposed AHiT energy model optimises node energy by the demand that is unlike to the conventional sleep and wake energy model that is operated on a predefined scheduling scheme that accommodates the data traffic pattern in a network. Generally, in a pipeline network where sensor nodes connectivity is considered critical among neighbouring nodes to support data transfer from one end to the other end of a network. Simulations results in NS2 has indicated node energy consumption is approximately 60% with extended network lifetime around 30% subjected to the data traffic pattern as compared to the conventional energy model.
Learning internet of things by using augmented reality Ismail Yusuf Panessai, Nur Iksan, Siti Aishah Zahari, Azmi Shawkat Abdulbaqi, Muhammad Modi Bin Modi Lakulu, et al. ACM International Conference Proceeding Series, 2021 This research is to find an Augmented Reality (AR) apps that suitable use for education purpose. Today, in school, students and teachers have been introduce to Internet of Thing (IoT) in technology design subject. It has considered using technology application can motivate and increase performance and student achievement in their learning units. The expected of this research is to find a good tools that can be use both of teachers or students in learning and teaching process especially for subject of Technology and Design. The early component in this apps should be a pop out image with details of electronics components until practical exercise. At the end of the used of this application, users are expected to have clear steps in mind about basic Arduino component and installations. For evaluation phases, the apps tested and used by vocational school student in subject of Technology and Design.
A Secure EEG Simulator for Remote Healthcare Evaluation Azhar Kassem Flayeh, Azmi Shawkat Abdulbaqi, Ismail Yusuf Panessai International Conference on Intelligent Technology System and Service for Internet of Everything Itss Ioe 2021, 2021 Electroencephalogram (EEG) Simulator or often called EEG Specter in principle is a signal generator in the form of an "EEG-like" signal or EEG signal that has been recorded. The purpose of this manuscript is to design an EEG Simulator tool. The design through the stages as follows: circuit design and circuit testing. This design is based on Arduino UNO and uses 12-bit Digital to Analog Converter to convert Digital data which is the output of Arduino UNO into Analog data in the form of EEG signals. Based on the measurement results obtained an error rate (ER) of 0.420% sensitivity of 0.5mV, 0.22% sensitivity of 1.0mV, and 0.22% sensitivity of 2.0mV in the BPM setting 30, obtained an ER value of 0.342% sensitivity of 0.5mV, 0.460% sensitivity of 1.0mV, and 0.432 % sensitivity of 2.0mV at BPM setting 60, obtained an error rate value of 0.121% sensitivity of 0.5mV, 0.1% sensitivity of 1.0mV, and 0.1% sensitivity of 2.0mV at setting BPM 120, obtained an error rate value of 0.423% sensitivity of 0.5mV, 0.310% 1.0mV sensitivity, and 0.520% 2.0mV sensitivity at 180 BPM settings and 0.246% 0.5mV sensitivity, 0.230% 1.0mV sensitivity and 0.246% 2.0mV sensitivity at 240 BPM settings.
An efficient method of EEG signal compression and transmission based telemedicine Journal of Theoretical and Applied Information Technology, 2019
Increasing the performance of genetic algorithm by using different selection: Vehicle routing problem cases Lecture Notes in Engineering and Computer Science, 2018
Dual axis sun tracker system based on IoT Journal of Advanced Research in Dynamical and Control Systems, 2018
Approaches method to solve ships routing problem with an application to the indonesian national shipping company Recent Advances in Computers Communications Applied Social Science and Mathematics Proceedings of Icancm 11 Icdcc 11 IC Assse Dc 11, 2011
