2 10 15 https://repository.horizon.ac.id/files/original/f942ec9b7e619455ff4da59569ccaa4b.pdf acd88fcef56ce1ad7c53ce90291df4ed 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 5 NO 4 (2021) 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 Realtime Object Detection Masa SiapPanenTanaman Sayuran BerbasisMobile Android DenganDeep Learning Subject The topic of the resource real-time, objectdetection, vegetable, harvest,MobileNetV3 Description An account of the resource Determining the harvesting period can be done visually, physically, computationally, and chemically. Since the harvesting process is crucial, late harvesting will affect post-harvest and production quality. Leafy vegetables have a relatively short ready-to-harvest period. Visual recognition of the harvesting period combined with image processing can recognize harvesting vegetables' visual characteristics. This study aims to build a deep learning-based mobile model to detect real-time vegetable plant objectssuch as bok choy, spinach, kale, and curly kale to determine whether these vegetables are ready for harvest. Mobile-based architecture is chosen due to latency, privacy, connectivity, and power consumption reason since there is no round-trip communicationto the server. In this research, we use MobileNetV3 as the base architecture. To find the best model, we experiment using different image input size. We have obtained a maximum MAP score of 0. 705510using a 36,000 image dataset. Furthermore, after implementing the model into the Android mobile application, we analyze the best practice in using the application to capture distance. In real-time detection usage, the detection can be done with an ideal distance of 5 cm and10cm Creator An entity primarily responsible for making the resource Andri Heru Saputra1, Dhomas Hatta Fudholi Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24 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 20 agustus 2021 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 Indoesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/e810b22e1ff6075b72b5cd8e941863b1.pdf dabf33d02a0a11bad56dd6ca8d5da533 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 5 NO 4 (2021) 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 Pengenalan Logo Kendaraan Menggunakan Metode Local Binary Pattern dan Random Forest Subject The topic of the resource recognition system, vehicle logo, local binary pattern, random forest Description An account of the resource The vehicle logo is one of the features that can be used to identify a vehicle. Even so, a lot of Intelligent Transport System which are developed nowadays has yet to use a vehicle logo recognition system as one of its vehicle identificationtools. Hence there are still cases of traffic crimes that haven't been able to be examined by the system, such as cases of counterfeiting vehicle license plates. Vehicle logo recognition itself could be done by using various feature extraction and classification methods.This research project uses the Local Binary Pattern feature extraction method which is often used for many kinds of image recognition systems. Then, the classification method used is Random Forest which is known to be effective and accurate for various classification problems. The data used for this study were asmany as 2000 vehicle logo images consisting of 5 brand classes, namely Honda, Kia, Mazda, Mitsubishi, and Toyota. The results of the tests carried out obtained the best accuracy value of 88.89% for the front view logo image dataset, 77.03% for the side view logo image dataset, and 83% for the dataset with both types of images Creator An entity primarily responsible for making the resource Alda Putri Utami1, Febryanti Sthevanie2, Kurniawan Nur Ramadhani3 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24 Publisher An entity responsible for making the resource available Universitas Telkom Date A point or period of time associated with an event in the lifecycle of the resource 20 agustus 2021 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/dc79073470f65a014645066a99c61538.pdf 60967a43b40f9efcedf055256fc2fa8f 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 5 NO 4 (2021) 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 Aspect Level Sentiment Analysis on Zoom Cloud Meetings App Review Using LDA Subject The topic of the resource LDA, SVM, review, aspect Description An account of the resource During the Covid-19 pandemic,almost all community activities are conducted from home.Therefore, video conference technology is needed for people to carry out their normal activities from home. One of the video conference applications is ZOOM Cloud Meetings. Applications certainly havebeen reviewedgiven by theirusers as a reference for new users andcompanies of the application to know the application’s performance. However, in reviews, some constraints are the number of reviews as well as irregular. Therefore, a solution is needed with sentiment analysis that aims to classify the reviews of the application to be organized by categorizing positive or negative sentiment. In this study, aspect-based sentiment analysis was conducted on ZOOM Cloud Meetings app reviews from Google Play Store. The analysis’s resultof the review data obtained threeaspects,namely aspects of usability, system, and appearance. The modeling topic used istheLatent Dirichlet Allocation(LDA) method and classification using the Support Vector Machine (SVM). This research resulted in the best performance with the best parametersresulting in the performance accuracy of usability aspect is 88.83%, system aspect with 91.2%, appearance aspect with 94.78%, and performance accuracy of all aspects 91.61% Creator An entity primarily responsible for making the resource Janu Akrama Wardhana1, Yuliant Sibaroni Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24 Publisher An entity responsible for making the resource available Telkom University Date A point or period of time associated with an event in the lifecycle of the resource 20 agustus 2021 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/ec8f75cca9ecaf65e1d42c726619669b.pdf 0e68ec9aa8fd12a53391659b6e14b40e 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 5 NO 4 (2021) 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 Implementasi Convolutional Neural NetworkUntuk Deteksi NyeriBayi Melalui Citra Wajah Dengan YOLO Subject The topic of the resource NVDIA Jetson Nano Developer Kit, Pain, Baby, YOLO, PyTorch, CNN, Facial Expresion Description An account of the resource Pain in a baby is difficult to detect is because the method for detecting pain is self-reporting even though babies themselves still cannot describe the pain verbally, then by observing changes in behavior in the form of facial expressions. Statistically, it is also recorded that about 80% of the world's population pays less attention to pain assessment, especially for children, even though this pain gives children a bad experience so that it can interfere with pain responses in the future or psychological trauma. Based on these problems, a prototype system was made using the NVIDIA Jetson Nano Developer kit to help detect pain, especially in infants 0-12 months by using the Convolutional Neural Network (CNN) model with the PyTorch framework and the You Only Look Once (YOLO) algorithm with three detection classification is sad, neutral and sick. From the results ofthe study, it was found that the YOLO algorithm was able to detect the three classifications with mAP@0.5value of sad 97,9%, neutral 99,2%, pain 96,9%, model accuracy 70%. The result of random check and the data from Puskesam Imogiri 1 have accuracy value 90% Creator An entity primarily responsible for making the resource Tomy Abuzairi1, Nurdina Widanti2, Arie Kusumaningrum3, Yeni Rustina Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24 Publisher An entity responsible for making the resource available Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 20 agustus 2021 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/f8f1f359437d4eec315d60b3bff92485.pdf 4e3d11e4011207986b9d442c0dd85f47 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 5 NO 4 (2021) 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 PengembanganMetode Autentikasi pada Sistem PresensiBerbasis Aplikasi Mobile Subject The topic of the resource attendance system, MAC address, IP address, BSSID, Wi-Fi Description An account of the resource Research has been carried out on a mobile-based presence system authentication method using MAC addresses, BSSID and IP addresses for (Wi-Fi) networks.This study aims to develop an authentication method on the attendancesystem that meets two authentication requirements, namely the suitability of employee identity and location suitability, so that the attendance process becomeseasy, effective, fast, and can reduce fraud. The employee's identity can be obtained from the MAC address of the smartphone that has been previously registered, while the employee's location during the attendance process can be confirmed to be in the company environment by checking the BSSID data and IP of the Wi-Finetwork connected to the smartphone. The data is then compared with MAC address data from all Wi-Finetworksinstalled in thecompany area. RAD is used as a development model because it is simple and fast. Overall, employee identification and site checking as authentication of the developed system went well. Other than that, every function on the system works well. Furthermore, the results of the user experience evaluation using the UEQ questionnaire received an average score above 0.8 on 6 scales. This shows that the system has attractiveness, perspicuity, efficiency, dependability, stimulationand novelty Creator An entity primarily responsible for making the resource Komang Sri Utami1, Nyoman Putra Sastra2, Dewa Made Wiharta Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/24 Publisher An entity responsible for making the resource available Universitas Udayana Date A point or period of time associated with an event in the lifecycle of the resource 20 agustus 2021 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