2 10 31 https://repository.horizon.ac.id/files/original/2ecb0d765349df148c490836972d36bc.pdf 42ba2d25abda678dd01ab0ab8e968f65 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using Histogram Extracted from Satelite Imagery and Convolutional Network to Predict GRDP in Java Region Subject The topic of the resource convolutional; GRDP; NTL; huber Description An account of the resource Inequality is one of the problems faced by all countries in the world, including Indonesia. The data used to measure development inequality between regions mostly uses GRDP data. However, the GRDP data issued by BPS has a deficiency, it was released after the current year, and this figure is provisional. So, a new data source is needed that can be used to estimate the value of economic activity so that it can be used to measure the level of development inequality in a region. Night-time Light (NTL) satellite imagery data can be an alternative to see socio-economic activity in an area and has been shown to have a strong correlation with socio-economic activity. In this study, we used VIIRS NTL satellite imagery data and Dynamic World land cover data to estimate GRDP. Rather than using statistical features for each area of interest, we use features in the form of histograms extracted from NTL images and land cover images for each area of interest. By using a histogram, we don’t lose spatial information from satellite imagery. Then we proposed a deep learning method in the form of a one-dimensional convolutional neural network using the Huber loss function. This model obtained good accuracy with an R square value of 0.8549, beating the baseline method with two-dimensional convolutional networks. The use of Huber loss function can improve the performance of the model, which has a smaller total loss and have smoother gradient. Creator An entity primarily responsible for making the resource Oemar Syarief Wibisono, Aniati Murni Arymurthy Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text convolutional GRDP huber NTI https://repository.horizon.ac.id/files/original/565227e0fc06d8b5d21c180e1627c65e.pdf 172d890d39b4f2e87dd2fc8c4ed6b72f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Combination of K-NN and PCA Algorithms on Image Classification of Fish Species Subject The topic of the resource fish species; image classification; k-nearest neighbor; principal component analysis Description An account of the resource To do fish farming, you need to know the types of fish to be cultivated. This is because the type of fish will affect how it is handled and managed. So, this study aims to develop an image processing system for classifying fish species, especially fish that are cultivated, with a combination of the K-Nearest Neighbor (K-NN) algorithm and Principal Component Analysis (PCA). The feature extraction used is feature extraction based on its color and shape. The K-NN algorithm can group certain objects by considering the shortest distance from the object. According to the best criteria, the PCA method is employed in the meanwhile to decrease and keep the majority of the relevant data from the original characteristics. Based on the test results, the accuracy value obtained is 85%. The use of a combination of the K-NN and PCA algorithms in the image classification of fish species in the research that has been done has been shown to be able to increase accuracy by 7.5% compared to only using the K-NN algorithm Creator An entity primarily responsible for making the resource Rini Nuraini, Adi Wibowo, Budi Warsito, Wahyul Amien Syafei, Indra Jaya Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text fish species Image classification K-Nearest Neighbor Principal component analysis https://repository.horizon.ac.id/files/original/f23e260c43de73fd63cea5ad82b93598.pdf 5dc55e7dfcb9fa18b9361f333cebf2ae Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Precision Marketing Model using Decision Tree on SME e-commerce Case Study Orebae.com Subject The topic of the resource precision marketing; SME; machine learning; customer preference; supervised learning; decision tree Description An account of the resource The development of the industrial world towards industry 4.0 has resulted in changes in the lifestyle of the wider community in carrying out their activities through digital media, one of which is shopping. This has an impact on the emergence of many business actors in the e-commerce field which brings its own challenges to stay alive and face the competition. The demands for innovation in competitive competition are also increasingly diverse with various approaches ranging from technology, social science, management science and even artificial intelligence. One form of innovation that is widely carried out by e�commerce today is looking for an ideal and effective form of marketing, where the form of marketing itself is considered less able to accommodate e-commerce needs. One form of real innovation in finding the ideal and effective marketing is with precision marketing. Precision marketing itself is marketing that is carried out by utilizing data where consumers are the center of preference for data collection. In fact, many e-commerce companies that were launched were unable to keep up with the competition because they were unable to develop marketing strategies and eventually went bankrupt. Therefore, we need a special way to bridge these problems so that e-commerce can stay alive, especially for e-commerce classified as Small and Medium Enterprises (SMEs). This research will focus on developing a precision marketing model in SME e-commerce, namely orebae.com which can be used as a tool in developing marketing strategies. This research was conducted using a machine learning approach by adopting a decision tree algorithm. From the results of this study, showed that precision marketing model for orebae.com according to customer preferences, can be used to increase the number of orebae.com sales and to reduce marketing cost Creator An entity primarily responsible for making the resource Fadil Indra Sanjaya, Anna Dina Kalifia Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text customer preference Decision Tree machine learning precision marketing SME supervised learning https://repository.horizon.ac.id/files/original/de97a6b40131fc2c3ffce65ed3b1ac8b.pdf cd126f6fc35177558f318a4960df5cb6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Application of Deep Convolutional Generative Adversarial Networks to Generate Pose Invariant Facial Image Synthesis Data Subject The topic of the resource face recognition; pose invariant; generative adversarial networks; deep convolutional generative adversarial networks; hyperparameter tuning Description An account of the resource Even though Artificial Intelligence is advancing, artificial intelligence can still find it difficult to solve problems that are easy for humans to do but difficult for computers to describe, such as facial recognition. There are problems related to the existing facial recognition model, namely the facial recognition model. The model is still unable to recognize facial shapes that are not in a perfect state due to several factors. Among several factors, the most influencing factor is the position of the face. Therefore, in this study, Deep Convolutional Generative Adversarial Networks (DCGAN) will be applied to generate fake image data with varying face positions. This research will be carried out starting from collecting data, processing data, designing, and training models, hyperparameter tuning, and lastly analyzing test results. Based on the results of hyperparameter tuning that carried out sequentially, the best hyperparameter combination produced is 200 epoch, 0.002 Generator learning rate, 0.5 Generator momentum/beta1, Adam as Generator optimizer, 0.0002 Discriminator learning rate, 0.5 Discriminator momentum/beta1, and Adam as Discriminator optimizer. The hyperparameter combination gives a result with FID score of 74.05. Based on testing with human observer, generated fake images has relatively good results, but there are still few bad fake image results Creator An entity primarily responsible for making the resource Jagad Nabil Tuah Imanda, Fitra Abdurrachman Bachtiar, Achmad Ridok Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text deep convolutional generative adversarial networks Face Recognition generative adversarial networks hyperparameter tuning pose invariant https://repository.horizon.ac.id/files/original/e64193891ff70e983a1805bc71cc7e8c.pdf c427414d4a004e53a57fd485b3afc4d3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Credit Risk Detection in Peer-to-Peer Lending Using CatBoost Subject The topic of the resource P2P lending; credit risk detection; catboost; AUC; ROC Description An account of the resource P2P (Peer-to-peer) lending has gained popularity among private borrowers, small businesses, and MSMEs due to its ability to provide direct access to loans without the strict requirements imposed by traditional banks and financial institutions. However, P2P lending faces a significant challenge in terms of credit risk, resulting in a high rate of loan repayment failures. To address this issue, the study aimed to develop a credit risk detection system using a loan dataset obtained from the Bondora company by implementing one of the gradient boosting algorithms which are called the CatBoost (Categorical Boosting) method. The performance of the CatBoost algorithm was evaluated using ROC (Receiver Operating Characteristics) curves and AUC (Area Under Curve). Three scenarios were considered, and the results revealed that scenario 2, with a data splitting ratio of 90:10, achieved the best outcome with an AUC value of 0.80329. This outperformed scenario 1, with a data splitting ratio of 80:20 and an AUC value of approximately 0.789583, as well as scenario 3, with a data splitting ratio of 70:30 and an AUC value of around 0.781066 Creator An entity primarily responsible for making the resource Fadhlurrahman Akbar Nasution, Siti Saadah, Prasti Eko Yunanto Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text AUC CatBoost credit risk detection P2P lending ROC https://repository.horizon.ac.id/files/original/8b43faf412d3b81398d26b4031606a6d.pdf fba7e582a142c016fb7520bab3c9ce5e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource K-Means Algorithm Implementation for Project Health Clustering Subject The topic of the resource project; project health; clustering; K-Means Description An account of the resource Indonesia has several companies that are engaged in the telecommunications sector. Various projects run in parallel to support the success of telecommunications companies. A project’s potential can boost the company’s revenue and productivity. On the other hand, there are some risks that need to be considered for every project when it is about to start. Project data is recorded from start to finish so that the project's progress and improvements can be monitored and analyzed. As the project runs, the project team at one of Indonesia's telecommunication companies, which is responsible for the processes leading to project success, requires a project health category. Therefore, this study is conducted to develop a process for clustering project health, which is included in a type of unsupervised learning that runs on unlabeled data. One of the clustering algorithms is K-Means, which groups data based on similar criteria. Researchers also use dimensionality reduction with the Principal Component Analysis (PCA) method to determine its impact on the clustering process with the K-Means algorithm. From this study, the researcher obtained three clusters or project health categories, consisting of clusters 0, 1, and 2. Evaluation results with the Calinski-Harabasz Index showed that the K-Means model on the dimensionality reduction data with PCA performed better than the standard K-Means model with a Calinski-Harabasz Index value of 55633,12776405707, which is higher than 25914,578262576793. Creator An entity primarily responsible for making the resource Ajeng Arifa Chantika Rindu, Ria Astriratma, Ati Zaidiah Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Clustering K-means project project health https://repository.horizon.ac.id/files/original/c22c5c7d5e2af1dabb6992d0da484617.pdf b3b55c67831ab6f7800eac86ea6f5b2c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Implementation of a Production Monitoring System Using IIoT Based on Mobile Application Subject The topic of the resource production monitoring system, IIoT, OEE, mobile application, notification Description An account of the resource Productivity is a key factor in the success of a company, and real-time monitoring systems are necessary to achieve this goal. Manual data collection is time-consuming and exhausting. Industrial Internet of Things (IIoT) technology has been rapidly advancing in monitoring and optimizing industrial processes. Production processes can be disrupted due to machine problems, hence the need for analyzing machine efficiency using the Overall Equipment Effectiveness (OEE) method. This study implements a system using Industrial Internet of Things technology based on mobile application to monitor production processes, report production results, assess machine performance using the OEE method, and provide maintenance notifications based on time-based maintenance. The research findings indicate that the implemented production monitoring system on a prototype press machine based on an interactive mobile application interface, is capable of monitoring production processes and reporting production results. The system is also able to assess machine performance using the OEE method, with a calculation accuracy of 99.95% and maintenance notifications with a delay time of 1.04 seconds. Creator An entity primarily responsible for making the resource Gun Gun Maulana, Siti Aminah, Berlliyanto Aji Nugraha Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text IoT mobile application Notification OEE production monitoring system https://repository.horizon.ac.id/files/original/5f3f5440528b3fac63562c5e5b5e2593.pdf 1421de15ca6e4983c42288eeab8070dd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Modeling Metadata and Data from Censuses and Surveys with GraphDatabases Subject The topic of the resource graph database; database relational; database modelling Description An account of the resource Relational database users are switching to non-relational databases because non-relational databases are better able to handle dynamic data storage. One of the institutions that require dynamic data storage is Statistics Indonesia (BPS). Currently, data storage for census and survey activities at BPS is done using a relational database, even though there are metadata changes in each activity. Accommodating metadata changes in each activity requires one database, which creates problems when retrieving some raw data. There is an opportunity for convenience if the data collected is stored in a non-relational database, one of which is a graph database. This research discusses the modeling of metadata and data from censuses and surveys at BPS using a graph database. Followed by implementation on Neo4j DBMS and comparing the proposed model with the relational model on Microsoft SQL Server DBMS. Then a comparison of the features and characteristics of each DBMS is done, and finally, performance testing is done with Apache JMeter. Modeling has been able to handle dynamic data structure changes, but Neo4j's performance is still lagging behind Microsoft SQL Server Creator An entity primarily responsible for making the resource Alya Faradila, Lutfi Rahmatuti Maghfiroh Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text database modelling database relational graph database https://repository.horizon.ac.id/files/original/3886b48e785789a45ad5d53fb36d3888.pdf c71b7620b5250d8f47da421c9f05945a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparative Study of Cloud Forensic Investigation Using ADAM And NIST 800-86 Methods in Private Cloud Computing Subject The topic of the resource framework; ADAM; NIST; cloud; comparison Description An account of the resource As information technology advances, the associated risks also increase, particularly in the field of private cloud computing services. These services are subject to potential risks of internal abuse, either due to system vulnerabilities or other factors. However, the investigation of these incidents in private cloud computing varies greatly due to the different frameworks and unique characteristics of each cloud service. The lack of a standardized approach to analyzing and assessing investigative processes in cloud computing services has been a persistent problem. This lack of consensus impacts the accuracy, efficiency, and process of data acquisition when dealing with digital evidence in each method, causing concern among researchers. To overcome this, a comparative study was carried out with a focus on the ADAM (The Advanced Data Acquisition Model) method and the NIST (National Institute of Standards and Technology) method. The goal is to identify the most effective investigative process for dealing with cyber attack incidents on both the server and client side of cloud computing services. By testing these methods in a network that is built on private cloud computing services, then for the results from this research include the weaknesses and strengths of the ADAM and NIST methods are found when applied to cloud computing case studies and these have not been identified in previous research, then produce recommendations for investigators when conducting investigations on case studies on cloud computing, and in this study managed to find a bug in the ownCloud application version 10.9.1. Then this study also aims to provide researchers with valuable references to carry out analysis and assessment in the investigative process, where standardization is still an unresolved issue. Creator An entity primarily responsible for making the resource Reza Febriana, Ahmad Luthfi Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text ADAM cloud Comparison Framework NIST https://repository.horizon.ac.id/files/original/bc0538d1050c8f38d12146963d81f081.pdf e116ccb3f40af4c2d3fc9bf105fffa6e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 5 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparison of Image Enhancement Methods for Diabetic Retinopathy Screening Subject The topic of the resource image enhancement; diaebetic retinopathy; image processing; fundus image Description An account of the resource The most common factor contributing to visual abnormalities that result in blindness is known as diabetic retinopathy (DR). Retinal fundus scanning, a non-invasive method that is integral to the picture pre-processing phase, can be used to identify and monitor DR. Low intensity, irregular lighting, and inhomogeneous color are some of the main issues with DR fundus photographs. Analysis of aberrant characteristics on retinal fundus pictures to identify diabetic retinopathy is one of the key responsibilities of image enhancement. However, a variety of approaches have been created, and it is unknown whether one is best suited for use with retinal fundus images. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. Contrast Limited Adaptive Histogram Equalization (CLAHE) method, Gray Level Slicing method, Median Filtering method, and Low Light method are image improvement methods used to enhance retinal fundus images. The parameters Natural Image Quality Evaluator (NIQE), Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and entropy will be used to assess each image enhancement technique's performance. An ophthalmologist from Hospital University Sains Malaysia (HUSM) provided the image data. The findings indicate that while each technique has its own benefits, the CLAHE technique, with a standard deviation MSE of 0.0004, is the best. Creator An entity primarily responsible for making the resource Dafwen Toresa, Fana Wiza, Keumala Anggraini, Taslim ,Edriyansyah, Lisnawita Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource October 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text diaebetic retinopathy fundus image image enhancement image processing