2 10 25 https://repository.horizon.ac.id/files/original/57d33c92e1ab63fad88cab1edd2b4484.pdf eb7c7dd52a29bebfbd7d2e916a120b90 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 1 (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 Web-based CNN Application for Arabica Coffee Leaf Disease Prediction in Smart Agriculture Subject The topic of the resource arabica coffee, convolutional neural networks, image processing, leaf disease, machine learning Description An account of the resource n the agriculture industry, plant diseases provide difficulty, particularly for Arabica coffee production. A first step in eliminating and treating infections to avoid crop damage is recognizing ailments on Arabica coffee leaves. Convolutional neural networks (CNN) are rapidly advancing, making it possible to diagnose Arabica coffee leaf damage without a specialist's help. CNN is aimed to find features adaptively through backpropagation by adding layers including convolutional layers and pooling layers. This study aims to optimize and increase the accuracy of Arabica coffee leaf disease classification utilizing the neural network architectures: ResNet50, InceptionResNetV4, MobileNetV2, and DensNet169. Additionally, this research presents an interactive web platform integrated with the Arabica coffee leaf disease prediction system. Inside this research, 5000 image data points will be divided into five classes—Phoma, Rust, Cescospora, healthy, and Miner—to assess the efficacy of CNN architecture in classifying images of Arabica coffee leaf disease. 80:10:10 is the ratio between training data, validation, and testing. In the testing findings, the InceptionResnetV2 and DensNet169 designs had the highest accuracy, at 100%, followed by the MobileNetV2 architecture at 99% and the ResNet50 architecture at 59%. Even though MobileNetV2 is not more accurate than InceptionResnetV2 and DensNet169, MobileNetV2 is the smallest of the three models. The MobileNetV2 paradigm was chosen for web application development. The system accurately identified and advised treatment for Arabica coffee leaf diseases, as shown by the system's implementation outcomes Creator An entity primarily responsible for making the resource Yazid Aufar1 , Muhammad Helmy Abdillah2 , Jiki Romadoni3 Publisher An entity responsible for making the resource available Politeknik Hasnur Date A point or period of time associated with an event in the lifecycle of the resource 03-02-2023 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/ac4a66119c1dfbe2f4f8a8e9d7139d85.pdf e8b343fb7430096f402ff01c1f8f1922 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 1 (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 Identification of Color and Texture of Ripe Passion Fruit with Perceptron Neural Network Method Subject The topic of the resource color identification, ripeness texture, passion fruit, perceptron Description An account of the resource Research using artificial neural network methods has been developed as a tool that can help human tasks, one of which is for passion fruit UMKM entrepreneurs. The problem so far that has been faced by UMKM entrepreneurs of passion fruit is that it is difficult to identify ripe passion fruit with sweet and sour taste, because there are 6 colors of passion fruit and the color of passion fruit skin is visually slightly different, as well as the texture of maturity. The main purpose of this study was to identify the color structure and texture of the ripeness of passion fruit, in order to recognize the color and texture of the ripeness of passion fruit which is good for processing into syrup, jam, jelly, juice, passion fruit juice powder by entrepreneurs of UMKM of passion fruit. This study empirically tested the color and texture of the ripeness of 10 passion fruit using the perceptron artificial neural network learning method. The data is obtained from an image that will be entered into the program. The results of the identification process using the perceptron artificial neural network from the tests that have been carried out previously, the highest calculation results obtained with the best results using a learning rate of 0.8 and 500 epoch iterations and producing an accuracy of 80%. Creator An entity primarily responsible for making the resource Siswanto1 , Riefky N. Sungkar2 , M. Anif3 , Basuki Hari Prasetyo4 , Subandi5 , Ari Saputro6 , Buana Suhurdin Putra7 Publisher An entity responsible for making the resource available Universitas Budi Luhur, Jakarta Date A point or period of time associated with an event in the lifecycle of the resource 06-02-2023 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/68288889fd766fd1e6edef235bdd8693.pdf 181b1bd1e2b77735af544f4b6d91dd25 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 1 (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 Improved Classification of Handwritten Jawi Script Based on Main Part of Script Body Subject The topic of the resource jawi script; FCC; SVM; the shape of the main part of the character; decision-making rules Description An account of the resource Since the entry of Islam, many ancient relics in the archipelago were written using Jawi script. Due to human or natural factors, these ancient relics will be damaged or destroyed. To avoid the loss of this ancient heritage data, the data must be stored in digital documents. In order to convert digital documents into machine-readable text format, the use of Optical Character Recognition (OCR) technology is inevitable. In this research, OCR technology is implemented on isolated Jawi scripts. Freeman Chain Code (FCC) is used to extract the isolated Jawi script features. Subsequently, the FCC feature is fed into Support Vector Machine (SVM) in order to classify the character. The decision rule classification is applied to the class of SVM classification in the Jawi script form. The results of the SVM classification into 19 classes reached 81.58%, while the results for merging into 15 classes produced better results with the accuracy 84.21%. Feature extraction of dot location is divided into the top, middle, and bottom. Feature extraction of the number of dotss is done by counting the number of dots, while feature extraction of the presence of holes is carried out by detecting the presence of holes in the characters. These features are applied to the class of results from SVM classification with decision-making rules. The percentage of success in applying the decision rules to the results of the classification of incorporation into 15 classes by SVM reached 92.86%. Further research will be conducted to determine the effect of the feature of the location of the dot and the number of dots on the shape of the main part of the character Creator An entity primarily responsible for making the resource Safrizal Razali1 , Fitri Arnia2 , Rusdha Muharrar3 , Kahlil Muchtar4 , Akhyar Bintang5 Publisher An entity responsible for making the resource available Syiah Kuala University Date A point or period of time associated with an event in the lifecycle of the resource 03-02-2023 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/6afdb97ace74ba892886d84b737727d9.pdf f917a5eb8d7ed5f5b7fd11dd86fb7fa6 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 1 (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 Credit Scoring Model for Farmers using Random Forest Subject The topic of the resource agriculture; credit scoring; farmer; land productivity; random forest Description An account of the resource One of the problems faced by farmers in Indonesia is capital. Based on Indonesian Central Statistics Agency survey results, the number of farmers who borrow capital from formal institutions such as banks is still small. This is because the process of applying for loans at banks is lengthy, farmers are considered high-risk and unbankable, and the rating of the agricultural sector is unattractive to banks. This study aims to determine the attributes and design a model of agricultural credit assessment. This study uses secondary data related to bank credit ratings and land productivity from banks in the Telagasari sub-district in 2018–2020 and Cipayung sub-district in 2020. Data were analyzed using random forests. The research process includes four stages: data collection, data pre-processing, model building, and model analysis and evaluation. This study produced five important variables that are relevant to farmers: planting costs, sales, land productivity, total production, and land area. The model built produces the most optimal accuracy of 83% with an AUC score of 81%. Based on the AUC performance classification, it can be concluded that the model that has been made is good at predicting the credit status of farmers because the AUC value is included in the good classification predicate. Creator An entity primarily responsible for making the resource Kharida Aulia Bahri1 , Yeni Herdiyeni2 , Suprehatin Suprehatin3 Publisher An entity responsible for making the resource available , IPB University Date A point or period of time associated with an event in the lifecycle of the resource 03-02-2023 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/62f196c1330d824c408c2df7af222b67.pdf fd6d2c7405456dd3e729e26936104640 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 1 (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 IoT Microcontroller Application Prototype as Data Transceiver from Network to USB Device Subject The topic of the resource interface, microcontroller, USB Host, USB device, network Description An account of the resource Telecommunications technology in the early 2000s until now has experienced a rapid increase. Starting with complex devices to microcomputer devices that are able to connect to the network. With the development of networking technology, it will leave behind non-network-support devices that can still be used. The existence of previous research on "The interface between the IoT microcontroller (ESP32) and the Max3421e USB Host" can be taken advantage of developing a device that can facilitate a non-support-network device into a support-network electronic device. So that non-support-network electronic devices do not become electronic waste and can also become a device that can be used in the present. In this study, a prototype of a data receiver from WiFi was designed, then the data that has been received is reorganized into rows of data that are ready to be sent to non-support-network electronic devices. This developed tool uses an ESP32 IoT microcontroller connected to the USB Host max3421e which has been packaged in the form of a USB host shield module using SPI protocol communication. The result obtained is that data from the network can be sent correctly to the USB Host max3421e via the ESP32 microcontroller. Creator An entity primarily responsible for making the resource Rieke Adriati Wijayanti1 , M. Syirajuddin S 2 , Abdul Rasyid3 , Ahmad Wilda Y4 Publisher An entity responsible for making the resource available Polytechnic State of Malang Date A point or period of time associated with an event in the lifecycle of the resource 03-02-2023 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/54e038839da12a180509695cfd98148f.pdf 5b7c8b561bead717288f0402beb94dd0 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 1 (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 Mobile Application Development to Solve Vehicle Routing Problems in Marketing or Tour Trip Planning Subject The topic of the resource mobile application, optimization, software development, vehicle routing problem Description An account of the resource The vehicle routing problem (VRP) is a combinatorial optimization problem faced by transportation services related to pick up or delivery, such as industrial raw materials distribution, tour and travel, or travel routing problems in general. VRP is an NP-hard problem where the higher the dimensions of the problem will have a higher computational complexity. Without realizing it, VRP problem are often encountered every day. Therefore, it will be very useful if VRP solver is implemented in mobile application media. Previously, the Google Map application also provided a feature for determining route problems, but this did not solve the constraint problems that appeared in VRP. Therefore, the development of existing applications needs to be done. So, the aim of this work is developing a mobile application to get the shortest path and minimal cost in VRP problem. It is integrated by both Mapbox API and Google Maps API to get a real distance for modeling problem. The result show that the developed application can run well in all possibility condition. Creator An entity primarily responsible for making the resource Benni Agung Nugroho1 , Abidatul Izzah2* , Kunti Eliyen3 Publisher An entity responsible for making the resource available PSDKU Polinema di Kota Kediri Date A point or period of time associated with an event in the lifecycle of the resource : 01-02-2023 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/4485524154a90c727a646a4328e05eb8.pdf 12f12c5a134ef7440e0c7cebf9180271 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 1 (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 Herbal Leaves Classification Based on Leaf Image Using CNN Architecture Model VGG16 Subject The topic of the resource classification, herbal leaf, transfer learning, VGG16. Description An account of the resource Herbal leaves are a type that is often used by people in the health sector. The problem faced is the lack of knowledge about the types of herbal leaves and the difficulty of distinguishing the types of herbal leaves for ordinary people who do not understand plants. If any type of plant is used, it will have a negative impact on health. Automatic classification with the help of technology will reduce the risk of misidentification of herbal leaf types. To make identification, a precise and accurate herbal leaf detection process is needed. This research aims to facilitate the classification model of herbal leaf images with a higher accuracy value than previous research. Therefore, the proposed method in this classification process is one of the Transfer Learning methods, namely Convolutional Neural Network (CNN) with a pretrained VGG16 model. This research uses a dataset of herbal leaves with a total of 10 classes: Belimbing Wuluh, Jambu Biji, Jeruk Nipis, Kemangi, Lidah Buaya, Nangka, Pandan, Pepaya, Seledri and Sirih. The performance of the results of the proposed classification method on the test dataset using Classification Report shows an increase in the results of the previous research accuracy value from 82% to 97%. This research also applies Image Data Generator in the augmentation process which aims to improve the image of herbal leaves, reduce overfitting, and improve accuracy. Creator An entity primarily responsible for making the resource Bella Dwi Mardiana1 , Wahyu Budi Utomo2 , Ulfah Nur Oktaviana3 Publisher An entity responsible for making the resource available Agus Eko Minarno5 Date A point or period of time associated with an event in the lifecycle of the resource 01-02-2023 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/ac2bed564b35fe08167d21a2a03670a1.pdf 8a87e7865ad9bf458032b05d2f09c43f 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 1 (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 Development of Quantum Circuit Architecture on Quantum Perceptron Algorithm for Classification of Marketing Bank Data Subject The topic of the resource classification, quantum computing, quantum perceptron, architecture, quantum circuit Description An account of the resource The creation of quantum circuit architecture based on the quantum perceptron algorithm to classify marketing bank data is proposed in this work. A quantum circuit is a quantum gate made up of two quantum gates. Quantum bits are used in this study's computation. The primary proposed learning method was not ideal, which is the context of this study. The percentage of qubits measurement value is still 90.7 percent. It is essential to raise the value of the qubit rate. Using the IBM Quantum Experience quantum computer, researchers measured, trained, and tested the quantum circuit architecture. Bank marketing data from the UCI Machine Learning Repository was used. A quantum circuit architecture model results from this research the quantum circuit measurement results. Creator An entity primarily responsible for making the resource Mochamad Wahyudi1 , Solikhun2 Publisher An entity responsible for making the resource available Universitas Bina Sarana Informatika Date A point or period of time associated with an event in the lifecycle of the resource 01-02-2023 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/f526d0ccf320b3ff829795c379f87b03.pdf d6147f0591066bebc8e01d33519a7be5 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 1 (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 Word Recommendation System Using Hybrid Method for Speed Typing Website Subject The topic of the resource recommendation system, collaborative filtering, content based filtering, speed typing, website Description An account of the resource Typing is one of the most frequently done activities in society therefore a medium is necessary to help train typing words that are often mistyped. Methods used in this research are the Content-Based Filtering Algorithm to gather the words that have a similar pattern to the words that are often mistyped based on the user's previous typing records and the Collaborative Filtering Algorithm that uses other users typing pattern to recommend the words. The result of this study shows the Collaborative Filtering Algorithm was able to gather words that are hard to type by the user with an accuracy of 49.2%, dan the Collaborative Filtering able to predict the score on how difficult for the user to type a word with the result of Root Mean Square Error (RMSE) value of 0.82 and with the Root Mean Square Percentage Error (RMSPE) value of 30% from the actual value, and a website which is the combination of the two algorithms with the result of 28% of the total word that is recommended was indeed difficult to type by the user with the typing speed of 103 WPM, and 72.3% for the user that has a typing speed of 39 WPM. Creator An entity primarily responsible for making the resource Melinda Melinda1 , Maulana Imam Muttaqin2 , Yudha Nurdin3 , Al Bahri4 Publisher An entity responsible for making the resource available University of Syiah Kuala Date A point or period of time associated with an event in the lifecycle of the resource 01-02-2023 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/d701b68bf26d6e25f7bd035224f489e2.pdf 2b37c3faac139fb9cac5f8e4d3aacb99 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 1 (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 Optimization Fuzzy Geographically Weighted Clustering with Gravitational Search Algorithm for Factors Analysis Associated with Stunting Subject The topic of the resource fuzzy geographically weighted clustering (FGWC); gravitational search algorithm (GSA); FGWC-GSA; stunting Description An account of the resource Stunting is a significant threat to the quality of human resources in Indonesia because stunting does not only involve physical growth disorders but can also cause children to be vulnerable to disease and experience disorders of brain development and intelligence. Many factors cause stunting, not only malnutrition in pregnant women and toddlers. Grouping can be done to make it easier to see the characteristics of the factors causing stunting in Indonesia. The grouping is done based on the similarity of the characteristics of the factors causing stunting in each province. This study used Fuzzy Geographically Weighted Clustering (FGWC) with Gravitational Search Algorithm (GSA) to group and assess the best cluster using the Partition Coefficient validity index, Classification Entropy, Separation Index, Xie & Beni's Index, and IFV Index. Furthermore, a difference test was conducted to determine the dominant factor causing stunting in the formed cluster. The results showed that the FGWC-GSA gave the best clustering results on the fuzziness value of 2 with the number of clusters 2. Cluster 1 consisted of 16 provinces, and cluster 2 consisted of 18 provinces. Based on the T-test, the variables of infants who received exclusive breastfeeding had significant differences between clusters. Therefore, cluster 2 is a cluster that has dominant problems related to exclusive breastfeeding. Creator An entity primarily responsible for making the resource Isran K. Hasan1 , Nurwan2 , Nur Falaq3 , Muhammad Rezky Friesta Payu4 Publisher An entity responsible for making the resource available Universitas Negeri Gorontalo Date A point or period of time associated with an event in the lifecycle of the resource 03-02-2023 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