Papers by Lailil Muflikhah
Indonesian Journal of Electrical Engineering and Computer Science, 2024
Recent healthcare research has focused a great deal of interest on using genetic data analysis to... more Recent healthcare research has focused a great deal of interest on using genetic data analysis to predict the risk of hypertension. This paper presents a unique method for accurately predicting the vulnerability to hypertension by utilizing single nucleotide polymorphism (SNP) data. We present a novel neural network design utilizing the adaptive moment (Adam) optimizer to describe the intricate temporal correlations in SNPs. The study used a dataset with carefully preprocessed SNP data from a broad cohort for model input. The long short-term memory (LSTM) network was methodically built and trained with hyper-parameter and fine-tuning using the Adam optimizer to converge on ideal weights. Our findings indicate encouraging predictive performance, highlighting the suggested methodology’s usefulness in determining hypertension risk factors. The result showed that the proposed method achieved stability in the performance of 89% accuracy, 96% precision, 88% recall, and 92% F1-score. Due to its higher accuracy and greater predictive power, our SNP-based LSTM methodology is superior to the conventional machine learning method. By providing a novel framework that uses genetic data to predict the risk of hypertension, this research makes substantial contribution to the field of predictive healthcare. This framework helps with early intervention and customized preventative efforts.
Comparative Analysis of Summarization Methods for Skin Care Product Reviews: A Study on BERT, BART, and T5 Models
Deep Learning Approach for High Recall Pneumonia Classification with Swin Transformer and L2 Regularization
Up Sampling Data in Bagging Tree Classification and Regression Decision Tree Method for Dengue Shock Syndrome Detection
Communications in computer and information science, Oct 12, 2023
Unveiling the antibreast cancer mechanism of <i>Euphorbia hirta</i> ethanol extract: computational and experimental study
Journal of biologically active products from nature, Jun 10, 2024
Computational examination to reveal Kaempferol as the most potent active compound from Euphorbia hirta against breast cancer by targeting AKT1 and ERα
Egyptian Journal of Basic and Applied Sciences
International journal of online and biomedical engineering, May 21, 2024
Diabetes may lead to several problems, one of the most prevalent and deadly of which is diabetic ... more Diabetes may lead to several problems, one of the most prevalent and deadly of which is diabetic nephropathy. Therefore, the condition represents a significant threat to one's health since it has the potential to cause irreversible harm to the kidneys' ability to operate. A significant portion of the research that is being conducted now is focused on determining how accurately diabetic people may be predicted to develop kidney illness. Considering this, the research suggests a regression stacking approach for predicting albumin levels. These albumin values will serve as a reference for the incidence of diabetic nephropathy disease. They will be derived from the medical records of patients. The utilization of stacking regression from three different ensemble approaches, using Random Forest and CatBoost regressors, while the Huber algorithm is used as a meta-learner. The accuracy with which the combination of parameters that are employed is determined is a significant factor. It contributes to the high degree of performance that the ensemble approach achieves. Therefore, in this investigation, a grid search was carried out to tune the hyperparameters of both regressor models. We evaluated the performance of the proposed model using accuracy, MAPE, RMSE, and MSE values. The experimental findings demonstrate great performance. Three selected variables including quantitative UACR, semi-quantitative UACR, and urinary creatinine, achieved high performance. Overall, the performance obtained an accuracy rate of more than 98% with an error rate (MAPE, RMSE, and MSE values) of less than 1%. In conclusion, the stack regressor model can be implemented to predict diabetic nephropathy using clinical datasets.
Advances in engineering research, 2023
There is a difficulty in building the implementation of a computational model to build a complex ... more There is a difficulty in building the implementation of a computational model to build a complex Covid-19 drug design involving a smart ecosystem. Covid-19 and the drug design of its new variants are formed by combining the appropriate compound and dose as an antiviral. Drug designs as the candidates for Covid-19 drugs can be in the form of herbal medicines and other materials. In computing the design of this drug, the encountered problem is the way to separate the features between the mixed compounds. The feature extraction received will be optimized into compounds that are useful as Covid-19 drug candidates. On the other hand, drug design using manual computational methods is very complicated and requires a fairly long-time estimation in forming the proper compound with many variants of each compound. From the problems that occur, it requires a system that can perform drug design computations quickly and precisely. Therefore, a new method of combining extreme learning machines and genetic algorithms is made called Geometric Time Variants (GTV) Extreme Genetic Algorithm (XtremeGA or eXGA or ExGA). As a result, drug design optimization using historical data by hybrid Islamic and evolutionary medicine for Covid-19 and its new variants can work quickly, optimally, and achieved convergence conditions.
Classification Comparison of Activity Distraction Detection in Car Driving
7th International Conference on Sustainable Information Engineering and Technology 2022
In view of the frequent multimedia data transfer authentication and protection of images has gain... more In view of the frequent multimedia data transfer authentication and protection of images has gained importance in today's world. In this paper we propose a new watermarking technique, based on bit plane, which enhances robustness and capacity of the watermark, as well as maintains transparency of the watermark and fidelity of the image. In the proposed technique, higher strength bit plane of digital signature watermark is embedded in to a significant bit plane of the original image. The combination of bit planes (image and watermark) selection is an important issue. Therefore, a mechanism is developed for appropriate bit plane selection. Ten different attacks are selected to test different alternatives. These attacks are given different weightings as appropriate to user requirement. A weighted correlation coefficient for retrieved watermark is estimated for each of the alternatives. Based on these estimated values optimal bit plane combination is identified for a given user requirement. The proposed method is found to be useful for authentication and to prove legal ownership. We observed better results by our proposed method in comparison with the previously reported work on pseudorandom watermark embedded in least significant bit (LSB) plane.
International Journal of Advanced Computer Science and Applications
Malaria disease mostly affects children and causes death every year. Multiple factors of the dise... more Malaria disease mostly affects children and causes death every year. Multiple factors of the disease due to failure in treatment, including anti-malaria drug resistance. The resistance is caused by a decrease in the efficacy of the drug against Plasmodium parasites. Therefore, we proposed a computational approach using deep learning methods to predict anti-malarial drug resistance based on genetic variants of the Plasmodium falciparum through DNA barcoding. The DNA Barcode, organism identification from Plasmodium, is employed as data set for predicting the anti-malaria drug resistance. As a univariate amino acid sequence, it is transformed to numerical value data for building classifier model. It is constructed into a classifier model for prediction using Bidirectional Long Term-Short Memory (Bi-LSTM). This algorithm is extended from LSTM by two directions. In the first stage, the sequence is encoded into numerical data as input data for the method using sigmoid activation loss function. Then binary cross entropy is addressed to define the class, resistance or sensitivity. The final stage is applied by tuning hyper-parameter using Adaptive Moment Estimation optimizer to get the best performance. The experimental results show that Bi-LSTM as the proposed method achieves high performance for resistance prediction including precision, recall, and f1-score.
International Journal of Phytopathology
Coffee Leaf Rust (CLR) disease caused by fungal pathogen Hemileia vastatrix is one of devastated ... more Coffee Leaf Rust (CLR) disease caused by fungal pathogen Hemileia vastatrix is one of devastated diseases in coffee plants. Disease RGA (resistance gene analog) primer pair CARF 005 has been reported for leaf rust-resistant screening in Arabica coffee and has never been reported in Liberica coffee. Previously, Liberoid Meranti 1 and 2 (Lim 1 and Lim 2) from Meranti Islands Indonesia were officially published by the government as CLR resistant cultivars and adaptive to peat soil. Our study aimed to analyze the resistance of Liberica coffee plants based on functional primer CARF 005. We sampled healthy plants of three Liberica genotypes (Lim 1, Lim 2, Bengkalis) in commercial farmer fields. DNA was extracted from young leaves, amplified and sequenced using CARF 005 primers. All samples generated DNA band about 400 bp. In addition, nucleotide sequences are similar to Arabica putative disease resistance gene. All the three sequences contain NB-ARC conserved domain which contribute to ...
JAST : Jurnal Aplikasi Sains dan Teknologi
Poverty alleviation efforts in Indonesia are still challenging due to the lack of job opportuniti... more Poverty alleviation efforts in Indonesia are still challenging due to the lack of job opportunities. Therefore, creative efforts are needed that are easy to do at home, especially during this Covid-19 pandemic. In this service activity, the creative business was introduced, which was packaged in multi-culture farming cultivation training. The community service activities were preceded by conducting a field survey on three partners, i.e., the farmer groups in Sunge Geneng Village, Sekaran District, Lamongan Regency, RT 3 / RW III Kauman Village Malang City, and Poncokusumo District Malang Regency. Since the survey plan was carried out during the Covid-19 Pandemic and the frequent Public Activity Restrictions (PPKM), the team could only survey the initial two partners. However, during the implementation process, the second partner was the only one to reach the implementation stage of Multi-Culture Farming with non-AI technology and introduce the use of AI Technology. Therefore, the se...
Indonesian Stock Prices Prediction using Bidirectional Long Short-Term Memory
7th International Conference on Sustainable Information Engineering and Technology 2022
DNA Sequence of Hepatitis B Virus Clustering Using Hierarchical k-Means Algorithm
2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS)
Hepatitis B virus infection is one of the causes of hepatocellular carcinoma. It is a kind of DNA... more Hepatitis B virus infection is one of the causes of hepatocellular carcinoma. It is a kind of DNA virus and has highly various genetic. In bioinformatics research, molecular evolution analysis is implemented to extract information from DNA sequence to nucleotide composition. The large volume of DNA sequence and costly complicates calculating of non-numerical nature of data, it is essential in the clustering task for describing data. Therefore, we propose the clustering method for the sequence using the Hierarchical k-Means clustering algorithm. The method is addressed to improve k-Means by defining an initial cluster center through the mean result of the hierarchical clustering method. The experiment result showed that the proposed method obtained higher performance measures than the conventional k-Means cluster algorithm.
International Journal of Mathematics and Mathematical Sciences, Mar 22, 2022
e purpose of this study is to implement Discourse Network Analysis (DNA) and analyze the results ... more e purpose of this study is to implement Discourse Network Analysis (DNA) and analyze the results in the formation of networks related to issues and actors in a news regarding consumer needs, satisfaction, and attachment to PT Pertamina. is study is the qualitative method that applies a qualitative Discourse Network Analysis (DNA) approach. Sources of DNA data come from various information in cyberspace (mass media, journals, articles, etc.) that are by the research context. Based on the search results in cyberspace, we obtained about 68 relevant news sources discussing consumer service on BBM products PT. Results of DNA taken from 68 news stories in cyberspace show that there are 45 actors from 14 different organizations who have opinions about PT Pertamina's consumers. Two actors only have a negative opinion, two actors have positive and negative opinions, and 41 actors have a positive opinion about the main issue of consumer needs. And we obtained 74 issues from the news obtained grouped into 3 main issues, namely, consumer needs, consumer satisfaction, and consumer engagement. And from 45 actors obtained from online news sources, they are grouped into 11 actor themes. Based on DNA results, it can be seen that there are several variables that have a possible influence on customer service. Variables that are likely to affect customer service include consumer needs, consumer satisfaction, and consumer engagement. e originality of this research lies in the application of DNA regarding consumer needs, satisfaction, and attachment to PT Pertamina.
Documents with various contents are easily obtained from URLs which are associated with their tit... more Documents with various contents are easily obtained from URLs which are associated with their titles. However, the titles of documents may not describe their contents and they just attract the readers to buy and read them. Therefore, the document clustering based on the same category is important to help users to retrieve information they need. Document clustering is an implementation of data mining task. By using similarity measurement of documents‟ characteristic, they can be clustered based on the same category or topic. High dimensionality of the document representation is due to representing of all substantial words in the vector space model. It is one of problems in document clustering that decreases the cluster quality performance including f-measure, entropy and accuracy. In categorical domain, many research have been conducted to reduce the dimension size of term-document matrix representation until by using keyword base. However, the result is obtained low accuracy in vari...
Bulletin of Electrical Engineering and Informatics
Corona virus disease-19 (COVID-19) is growing rapidly because it is an infectious disease. This d... more Corona virus disease-19 (COVID-19) is growing rapidly because it is an infectious disease. This disease is caused by a virus belonging to the type of DNA virus with very diverse genetics. This study proposes a feature extraction method using k-mer to obtain nucleotide frequencies in protein coding. In profiling viral DNA sequences, this study proposes to obtain similarity by country using hierarchical k-means, where the results are averaged by the hierarchical clustering method and then find the initial cluster center. The experimental results show that the silhouette, purity, and entropy are 0.867, 0.208, and 0.892, respectively. Then, we apply the Gini index feature selection to find the important components as characteristics in each country. The selected components are implemented using the ensemble method, Random Forest, to evaluate their performance. The experimental results showed high performance, including sensitivity, accuracy, specificity, and area under the curve (AUC).
Asian Journal of Probability and Statistics, 2021
Purpose: This study aims to map the level of family welfare in the Wajak District. Methods: This ... more Purpose: This study aims to map the level of family welfare in the Wajak District. Methods: This study uses a survey method with a mixed-method approach. The data used in this study is secondary data regarding HDI (Human Development Index), ISSI (Infrastructure Service Satisfaction Index), and EQI (Environmental Quality Index). The population in this study was all villages in Wajak District, which amounted to 13 villages. Then with the sampling technique using simple random sampling, the village selected as the sample for analysis is Bringin Village. The data analysis used in this study includes biplot, cluster, and IPA analysis. Findings: The result of this study is that the level of welfare of the community in Bringin Village is said to be quite prosperous, this can be seen from the results of mapping the variables of religiosity, entrepreneurship, and service quality showing that cluster 1 is quite prosperous with 39 members, while in cluster 2, which is less prosperous, there ar...
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Papers by Lailil Muflikhah