1 10 6 https://repository.horizon.ac.id/files/original/de26adbd0d4af48455873be38423d94e.pdf 566affb0b893147e4cb42d63e92dd245 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 2 (2023) 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 Industry 4.0 Maturity Models to Support Smart Manufacturing Transformation: A Systematic Literature Review Subject The topic of the resource maturity model; intelligent systems; smart manufacturing; industry 4.0 Description An account of the resource With increasing pressure to revitalize manufacturing industries with Smart Manufacturing capability within the Industry 4.0 (I4.0) context, companies have uneven readiness reflecting their gaps and barriers for transforming to the I4.0 state. Understanding factors and measuring a company’s maturity in addressing the I4.0 transformation is crucial to diagnose the company’s current condition and provide corresponding prescriptive action plan effectively. Despite the positive trend of maturity models for the industries, companies still face challenges with low I4.0 adoption rate. Designing a corresponding diagnostic framework into an intelligent maturity model will ultimately lead the company’s pathways toward the desired capabilities. In response, we systematically review and select the state-of-the-art research through a Systematic Literature Review (SLR) conduct to scrutinize the main characteristics of 14.0 Maturity Models. Subsequently, 35 exceptional articles published between 1980-2020 were selected for in-depth analysis of their structure, dimensions, and analytical features. Our analysis revealed the descriptive method have been widely used in many maturity models while few more-advanced prescriptive models design adopt fuzzy rule-base analytical hierarchy, knowledge based, Monte-Carlo methods, and even expert-system approaches. Furthermore, people, culture, organization, resources, information system, business processes, and smart technology, products and services have been treated as the popular evaluation dimensions which will define the state of an industry’s maturity level Creator An entity primarily responsible for making the resource Akhmad Hadi Susanto1 , Togar M. Simatupang2 , Meditya Wasesa3 Publisher An entity responsible for making the resource available Institut Teknologi Bandung Date A point or period of time associated with an event in the lifecycle of the resource 26-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/fd4bdf2e4d8c03c54228760cdf8e8e6d.pdf 5fde8a76082c5a701f8f6faf7365eebb 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 2 (2023) 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 ResNet101 Model Performance Enhancement in Classifying Rice Diseases with Leaf Images Subject The topic of the resource enhancement; performance; classification; disease; rice; resnet101 Description An account of the resource Indonesia is the fourth biggest rice producer in Asia with its production accounting for 35.4 million metric tons yearly. This figure can increase unless rice crop failure is resolved. Identifying rice diseases, however, may serve as an approach to minimizing the risk of crop failure. The classification to detect rice diseases was previously researched using ResNet101 method with 100% accuracy. Despite this perfect accuracy, this approach does not come without an issue, where the prediction is not yet optimal for each label and loss results which are regarded as too high due to overfitting. Departing from this issue, this research aims to improve the model by reducing the layer complexity of the model and comparing two layers structures of the model, two different data, and the ResNet101 model. The performance resulting from the model could be enhanced with the structuring of simple architectural layers. Despite the small quantity of dataset, the model performance can yield 100% accuracy in the classification of rice diseases with a loss value of 2.91%. The model performance in this research experienced a 2.7% increase at the loss value and it could accurately classify the type of rice diseases according to leaf images on each label. The problem solved by this research is that ResNet101 is able to classify rice disease accurately even with a small amount of data by utilizing the appropriate layer arrangement with data requirements. In addition, the overfitting that occurred in previous research can also be resolved properly. This matter proves that the correlation between the layers of the model with the amount of data is very influential Creator An entity primarily responsible for making the resource Galih Wasis Wicaksono1 , Andreawan2 Publisher An entity responsible for making the resource available Universitas Muhammadiyah Malang Date A point or period of time associated with an event in the lifecycle of the resource 26-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/3118c63b333cf27223f8e48db0ed9792.pdf 0e0e378a79759ec49a0ad9a53f7d21d7 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 2 (2023) 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 Analysis of Forensic Software on Android-based MiChat using ACPO and DFRWS Framework Subject The topic of the resource digital forensic; mobile forensic; michat; smartphone Description An account of the resource Instant Messaging (IM) is a popular and widely used communication application. MiChat is a multi-platform instant chat service with several features that can attract various segments of the population to use it as a tool for committing cybercrimes. A forensic framework and several forensic tools are needed to carry out physical evidence investigation procedures. This study focuses on analyzing and comparing the forensic tools used during the research, based on defined digital evidence parameters and applying a specific mobile forensic framework. The results show that Final Mobile Forensic has the highest ability to obtain digital evidence and can recover deleted data, while Oxygen Forensic Detective has advantages in terms of audio, images, and video but cannot recover data. The best framework is DFRWS, which has the most complete stages so that it can support the investigation process. The best digital evidence is text chat and contacts, which can be used to support valid legal claims. Creator An entity primarily responsible for making the resource Imam Riadi1 , Anton Yudhana2 , Galih Pramuja Inngam Fanani3 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 26-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/9b7f12893df0eb8753be1cd00dafdf37.pdf 9716add21a95f62df60134c9a1065401 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 2 (2023) 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 Integration of Microscopic Image Capturing System for Automatic Detection of Mycobacterium Tuberculosis Bacteria Subject The topic of the resource tuberculosis; sputum; image processing; microscope Description An account of the resource he Ministry of Health of the Republic of Indonesia is running a program to eliminate Tuberculosis (TB) by 2030. At the Primary Health Care level, AFB (acid-fast bacteria) examination confirms the TB diagnosis. In this process, the patient's sputum is prepared in the form of preparation and observed by the laboratory analyst through the lens of a microscope. The reporting process to establish this diagnosis requires calculating the number of TB bacteria in 100 fields of view per preparation. This manual microscopic observation process is tedious, and the reading results are subjective. This study offers an integrated design for automatic microscopic imaging with a computer-integrated TB bacteria detection system. The process of taking pictures is automatically obtained with the help of a driving motor added to the microscope. With the addition of this motor, the process of taking microscopic images for 100 fields of view takes ±450 seconds. The proposed system integration process can reduce laboratory analysts' work fatigue in conducting microscopic observations manually. The TB bacteria detection system utilizes the working principle of image processing techniques by combining color-deconvolution, segmentation, and contour-detection methods. The comparative value of the TB object detection system with experts resulted in a sensitivity value of 77% and a specificity value of 68%. However, the low detection rate is because the image obtained is still blurry. Thus, further investigation is needed to determine the driving motor's movement rate and the right timing for taking microscopic images so that the resulting image is not blurry. The final result that is the focus of this paper is the successful integration of the system carried out between the motor drive system on the preparation stand and the TB bacteria detection system to become a unified system. Creator An entity primarily responsible for making the resource Agus Darmawan1 , Izzati Muhimmah2*, Rahadian Kurniawan3 Publisher An entity responsible for making the resource available Universitas Islam Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 26-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/951cacbbcffe3cec66de47800d6e954d.pdf 4142843f739f39546313a49ff4fff31b 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 2 (2023) 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 Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City Subject The topic of the resource Malnutrition in a child; information technology; predictor; naïve bayes; health problems Description An account of the resource Nutritional status is an important factor in assessing the growth and development rate of babies and toddlers. Cases of malnutrition are increasing, especially in magelang city. Because nutritional problems (Malnutrition) can affect the health of toddlers. Therefore, this study aims to predict the level of prevalence of malnutrition with the Naïve Bayes method. This research uses an observational design, a single center study at the Magelang City Office, using the Naïve bayes method which is used as an application of time series data, and is most widely used for prediction, especially in data sets that have many categorical or nominal type attributes. The Naïve bayes method is used to predict such cases of malnutrition. The results of this study show that the Naïve Bayes method succeeded in predicting the magnitude of cases of malnourished toddlers in Magelang City with an accuracy percentage of 75% due to the very minimal amount of training data, and the areas that have the most malnutrition are in three areas, namely Magersari, North Tidar and Panjang. Creator An entity primarily responsible for making the resource Endah Ratna Arumi1 , Sumarno Adi Subrata2 , Anisa Rahmawati3 Publisher An entity responsible for making the resource available Universitas Muhammadiyah Magelang Date A point or period of time associated with an event in the lifecycle of the resource 03-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/85bb2e21baed2e00d3975443d6b55216.pdf 39a08a18c2f503b560059510b5b28fc1 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 2 (2023) 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 Image Transformation With Lung Image Thresholding and Segmentation Method Subject The topic of the resource transformation; image; threshold; segmentation; lung Description An account of the resource Image transformation is important to obtain and find certain information about an image that was not previously known, such as pixels, geometry, size, and color. Following this, this research aims to analyze image transformation in producing better values using threshold and segmentation methods. The segmentation process is carried out based on two color models, namely hue saturation value (HSV) and red green blue (RGB). The image data used in this study was the x-ray image of the lungs from www.fk.unair.ac.id. which is processed using the Matlab 2021a application to help the analysis process. on the results of the image segmentation analysis carried out in this case, the greater the HSV and RGB threshold values used in the image data, the better and clearer the segmentation of the detected image results. In other words, the size of the thresholding value generated greatly affects the quality, brightness, size, and color of the resulting image. The best lung X-ray image segmentation results were obtained when using the threshold values HSV = 0.9 and RGB = 9 Creator An entity primarily responsible for making the resource Sahat Sonang S1 , Y.Yuhandri2 , Adil Setiawan3 Publisher An entity responsible for making the resource available Politeknik Bisnis Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 26-03-2023 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text