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All Journal International Journal of Advances in Intelligent Informatics MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Computer Science and Information Technology (CoSciTech) J-Intech (Journal of Information and Technology) Jurnal Minfo Polgan (JMP) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Knowbase : International Journal of Knowledge in Database Journal of Artificial Intelligence and Digital Business Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Masyarakat Madani Indonesia Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Jurnal Pengabdian kepada Masyarakat IPTEKS Jurnal Pengabdian Pada Masyarakat IPTEKS Prosiding Seminar Nasional CORISINDO
Galih Hendro Martono
Universitas Bumigora, Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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An extended approach of weight collective influence graph for detection influence actor Galih Hendro Martono; Azhari Azhari; Khabib Mustofa
International Journal of Advances in Intelligent Informatics Vol 8, No 1 (2022): March 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v8i1.800

Abstract

Over the last decade, numerous methods have been developed to detect the influential actors of hate speech in social networks, one of which is the Collective Influence (CI) method. However, this method is associated with unweighted datasets, which makes it inappropriate for social media, significantly using weight datasets. This study proposes a new CI method called the Weighted Collective Influence Graph (WCIG), which uses the weights and neighbor values to detect the influence of hate speech. A total of 49, 992 Indonesian tweets were and extracted from Indonesian Twitter accounts, from January 01 to January 22, 2021. The data collected are also used to compare the results of the proposed WCIG method to determine the influential actors in the dissemination of information. The experiment was carried out two times using parameters ∂=2 and ∂=4. The results showed that the usernames bernacleboy and zack_rockstar are influential actors in the dataset. Furthermore, the time needed to process WCIG calculations on HPC is 34-75 hours because the larger the parameter used, the greater the processing time.
Review implementation of linguistic approach in schema matching Galih Hendro Martono; Azhari SN
International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i1.75

Abstract

Research related schema matching has been conducted since last decade. Few approach related schema matching has been conducted with various methods such as neuron network, feature selection, constrain based, instance based, linguistic, and so on. Some field used schema matching as basic model such as e-commerce, e-business and data warehousing. Implementation of linguistic approach itself has been used a long time with various problem such as to calculated entity similarity values in two or more schemas. The purpose of this paper was to provide an overview of previous studies related to the implementation of the linguistic approach in the schema matching and finding gap for the development of existing methods. Futhermore, this paper focused on measurement of similarity in linguistic approach in schema matching.
Visualisasi data twitter menjadi graph untuk social network analysis Galih Hendro Martono; Sulistianingsih, Neny
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.5722

Abstract

Twitter is one of the most widely used social media in Indonesia. As a form of social media, Twitter is widely used to express opinions/opinions, discuss specific issues, convey complaints or sentiments about a product, and political communication. Twitter user communication data can be processed into useful information for various purposes, so we need a way to process Twitter data. The development of information technology makes it possible to multiply this information so that it becomes valuable information. For example, Twitter data can be helpful for companies to profile consumers so that they can improve marketing efforts. In the political field, Twitter data can be used to find people who influence Twitter who can be used to assist the campaign process. In the legal area, this Twitter data can help analyze networks and the distribution of information related to hate speech and hoaxes. To analyze Twitter data, we need to convert it into a data graph to be explored further. Twitter data visualization into data graphs is done because there are differences in data formats. Twitter data is in the form of string data consisting of tweets reflecting user communication. The data graph is a collection of vertices and edges, denoted as Vertex represents Twitter users, and Edge represents user relationships or communication. This study aims to form a data graph based on Twitter data to facilitate the analysis of Twitter data for various interests.
Identification of top influence users in disseminating information on the 2024 Indonesian National Election Neny Sulistianingsih; Galih Hendro Martono
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 1 (2024): Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Social media has a vital role in general elections in Indonesia because social media is one of the platforms used by presidential candidates for campaigns to gain public support. General elections in Indonesia occur every five years. Many tweets talk about presidential candidates approaching the national election period. Not least, some buzzers deliberately use Twitter to carry out propaganda against a candidate or to bring down other presidential candidates with their opinions because information can spread widely and quickly on Twitter. Based on this, it is necessary to identify influential users in disseminating information related to the 2024 National Election, especially on Twitter. Various centrality methods were used in this study to identify influence users in sharing information about the 2024 National Election such us Degree Centrality, Closeness Centrality, Harmonic Centrality, Eigenvector Centrality, and Load Centrality. For the evaluation in this study, the results of each method were compared to one another to measure the similarity and correlation between the ranking lists of users who were influential in disseminating information about the 2024 National Election.
Enhancing Predictive Models: An In-depth Analysis of Feature Selection Techniques Coupled with Boosting Algorithms Neny Sulistianingsih; Galih Hendro Martono
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 2 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3788

Abstract

This research addresses the critical need to enhance predictive models for fetal health classification using Cardiotocography (CTG) data. The literature review underscores challenges in imbalanced labels, feature selection, and efficient data handling. This paper aims to enhance predictive models for fetal health classification using Cardiotocography (CTG) data by addressing challenges related to imbalanced labels, feature selection, and efficient data handling. The study uses Recursive Feature Elimination (RFE) and boosting algorithms (XGBoost, AdaBoost, LightGBM, CATBoost, and Histogram-Based Boosting) to refine model performance. The results reveal notable variations in precision, Recall, F1-Score, accuracy, and AUC across different algorithms and RFE applications. Notably, Random Forest with XGBoost exhibits superior performance in precision (0.940), Recall (0.890), F1-Score (0.920), accuracy (0.950), and AUC (0.960). Conversely, Logistic Regression with AdaBoost demonstrates lower performance. The absence of RFE also impacts model effectiveness. In conclusion, the study successfully employs RFE and boosting algorithms to enhance fetal health classification models, contributing valuable insights for improved prenatal diagnosis.
Analisis Dampak Pelatihan Canva dalam Komunikasi Visual Neny Sulistianingsih; Hasbullah; Galih Hendro Martono
Jurnal Pengabdian kepada Masyarakat IPTEKS Vol. 1 No. 2 (2024)
Publisher : Rajawali Media Utama

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Abstract

The use of Canva in educational communication has garnered attention, yet research exploring its use in announcements and communication with students remains limited. This study aims to optimize visual communication by providing Canva usage training to academic and program staff, with a focus on announcements and student communication. The engagement method follows a participatory approach and Service learning. Questionnaire results show a significant increase in confidence levels and graphic design abilities post-training. Positive social and behavioral changes are also observed. From a theoretical perspective, these findings are supported by visual design theories and service learning. Conclusions indicate that Canva training is effective in enhancing the quality of visual communication between educational institutions and students. Recommendations include continuing and expanding training and monitoring implementation outcomes.
Pengembangan Skill Masyarakat dalam Peningkatan Ekonomi secara Digital Sulistianingsih, Neny; Martono, Galih Hendro
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol 3 No 2 (2023): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v3i2.408

Abstract

Salah satu bentuk usaha dalam masyarakat yang banyak ditemui adalah perdagangan atau jual beli. Fenomena usaha jual beli mengalami perubahan yang sangat besar seiring dengan perkembangan teknologi informasi terutama perkembangan internet. Awalnya penerapan teknologi informasi dalam jual beli online dilakukan melalui promosi dengan webiste. Namun sejak munculnya media sosial Facebook di tahun 2006, promosi tidak hanya melalui internet saja namun juga media sosial. Perkembangan selanjutnya, promosi tidak hanya melalui media sosial namun juga melalui platform-platform yang secara khusus digunakan untuk jual beli secara online. Melihat hal ini perlu suatu upaya untuk peningkatan kemampuan masyarakat dalam penerapan teknologi informasi yang dapat membantu dalam jual beli secara online. Kegiatan pengabdian kepada masyarakat ini dilakukan untuk membantu masyarakat dalam memperkenalkan proses jual beli secara online atau promosi secara digital. Lebih lanjut, pelatihan dengan praktek secara langsung juga dilakukan. Hasil dari kegiatan pengabdian ini adalah menciptakan masyarakat yang melek terhadap teknologi informasi dan mampu berusaha secara mandiri untuk melakukan promosi serta jual beli secara online.
Enhancing Stroke Diagnosis with Machine Learning and SHAP-Based Explainable AI Models Galih Hendro Martono; Neny Sulistianingsih
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 2 (2024): December 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i2.8720

Abstract

Stroke is a serious illness that needs to be treated quickly to enhance patient outcome. Machine Learning (ML) offers promising potential for automated stroke detection through precise neuroimaging analysis. Although existing research has explored ML applications in stroke medicine, challenges remain, such as validation concerns and limitations within available datasets. The study aims to compare ML models and SHapley Additive exPlanations (SHAP) algorithm insights for stroke detection optimization. The research evaluates classifiers' performance, including Deep Neural Networks (DNN), AdaBoost, Support Vector Machines (SVM), and XGBoost, using data from www.kaggle.com. Results demonstrate XGBoost's superior performance across various data splits, emphasizing its effectiveness for stroke prediction. Utilizing SHAP provides deeper insights into stroke risk factors, facilitating comprehensive risk assessment. Overall, the study contributes to advancing stroke detection methodologies and highlights ML's role in enhancing clinical practice in stroke medicine. Further research could explore additional datasets and advanced ML algorithms to enhance prediction accuracy and preventive measures.
Identification of top influence users in disseminating information on the 2024 Indonesian National Election Sulistianingsih, Neny; Martono, Galih Hendro
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 14 No. 1 (2024): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v14i1.25-32

Abstract

Social media has a vital role in general elections in Indonesia because social media is one of the platforms used by presidential candidates for campaigns to gain public support. General elections in Indonesia occur every five years. Many tweets talk about presidential candidates approaching the national election period. Not least, some buzzers deliberately use Twitter to carry out propaganda against a candidate or to bring down other presidential candidates with their opinions because information can spread widely and quickly on Twitter. Based on this, it is necessary to identify influential users in disseminating information related to the 2024 National Election, especially on Twitter. Various centrality methods were used in this study to identify influence users in sharing information about the 2024 National Election such us Degree Centrality, Closeness Centrality, Harmonic Centrality, Eigenvector Centrality, and Load Centrality. For the evaluation in this study, the results of each method were compared to one another to measure the similarity and correlation between the ranking lists of users who were influential in disseminating information about the 2024 National Election.
Smart Parking Space Detection Using Advanced Deep Learning Techniques Aguswandi, Lalu Heri; Triwijoyo, Bambang Krismono; Martono, Galih Hendro
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6473

Abstract

This study aims to develop an accurate and efficient empty parking slot detection model to assist users in finding parking spaces. The developed model utilizes YOLOv11 as a pretrained model and demonstrates excellent performance with a precision of 99%, recall of 99%, and a Mean Average Precision (mAP) of 99%. These results validate the model's ability to accurately detect empty parking slots with 100 training epochs. Additionally, the model operates in real-time with a frame rate of 25 frames per second (FPS)
Co-Authors Aguswandi, Lalu Heri Astawa, Andhika rama putra Azhari Azhari Azhari SN Hasbullah Hasbullah Hasbullah Hasbullah Helna Wardhana Husain Husain Karor, Iptijanul Khabib Mustofa Lukmana, Aldi Mayadi Muhammad Fathoni, Muhammad Mundika, Eko Neny Sulistianingsih Ni Putu Sinta Dewi Ramadhan, Rahmat Adi Mulya Ria Rismayati Rismayati, Ria Rizki, M Syahrir, Moch. Tenia Wahyuningrum Triwijoyo, Bambang Krismono