2 10 23 https://repository.horizon.ac.id/files/original/55ddb83adb225e78bb1fa710afa9cb74.pdf 14c55fd16c8e83878003f2a109e9c48c 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 6 NO 1 (2022) 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 Emosi Pembicara Menggunakan Convolutional Neural Networks Subject The topic of the resource Convolutional Neural Networks, Deep Learning, Keras, Speech Emotion Recognition, Tensorflow Description An account of the resource Recognition of the speaker's emotions is an important but challenging component of Human-Computer Interaction (HCI). The need for the recognition of the speaker's emotions is also increasing related to the need for digitizing the company's operational processes related to the implementation of industry 4.0. The use of Deep Learning methods is currently increasing, especially for processing unstructured data such as data from voice signals. This study tries to apply the Deep Learning method to classify the speaker's emotions using an open dataset from SAVEE which contains seven classes of voice emotions in English. The dataset will be trained using the CNN model. The final accuracy of the model is 88% on the training data and 52% on the test data, which means the model is overfitting. This is due to the imbalance of emotion classes in the dataset, which makes the model tend to predict classes with more labels. In addition, the lack of heterogeneity of the dataset makes the character of the emotion class more different from the others so that it can reduce the bias in the model so as not to overfit the model. Further development of this research can be done, such as over-sampling the existing dataset by adding other data sources, then performing data augmentation to get the data character of each emotion class and setting hyperparameter values to get better accuracy values Creator An entity primarily responsible for making the resource Rendi Nurcahyo1 , Mohammad Iqbal2 Publisher An entity responsible for making the resource available Universitas Gunadarma Date A point or period of time associated with an event in the lifecycle of the resource 27-02-2022 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/4febecd61d59867c1f5f0a2243d5a59d.pdf 5b671268ca402c53062dbaee47ec8d91 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 6 NO 1 (2022) 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 Analisis Spasial Untuk Klasifikasi Pengembangan Tempat Penampungan Sementara Menggunakan Metode Jaringan Syaraf Tiruan Subject The topic of the resource : Spatial Analysis, Web-GIS, Garbage Shelters, Artificial Neural Network, Backpropagation Description An account of the resource Garbage is a problem that needs an in-depth study in urban areas because the development of an area has consequences on increasing population density, facilities and infrastructure, public services, and other aspects that impact increasing the volume of waste. The distribution of temporary waste shelters (TPS) in each area is still insufficient to accommodate the volume of waste, and its availability is inadequate. The purpose of this study is to model spatial data through spatial analysis using artificial intelligence methods in classifying the development of integrated temporary shelter locations (TPST) and regional integrated temporary shelters (TPST Regions) by utilizing Web-based technology (Geographical Information System (Web�GIS). The Artificial Neural Network method with the Backpropagation algorithm is used for the spatial analysis process based on the parameters of the population, the amount of organic and inorganic waste, the amount of industrial waste, and the volume of the TPST and Regional TPST capacity. The spatial analysis results using the Artificial Neural Network method obtained an accuracy value of 7171.02%. The results of this study can be the basis for Department of Environment and Cleanliness policies for the development of TPST and TPST areas with information coverage at the village level. Creator An entity primarily responsible for making the resource Luqman Hakim1 , Anik Vega Vitianingsih2 , Gita Indah Marthasari3 , 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 27-02-2022 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/2936ebb7403b249f27a90adc62202f12.pdf 0b07afb99f3c93f5d49f22f4003911a9 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 6 NO 1 (2022) 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 Design of Smart Farm Irrigation Monitoring System Using IoT and LoRA Subject The topic of the resource smart irrigation, monitoring system, internet of things, LoRa Description An account of the resource Agriculture is an essential part of society in Indonesia because most of the population lives off of farming. Water and irrigation are the most critical and central factors in the agricultural system. The uneven distribution of irrigation water can be a problem for farmers. In addition, most of the current irrigation systems are still operated manually, for example, irrigation gates. The gate still works manually and requires human labor to run it. This study aims to design a smart farm irrigation system using internet of things and LoRa communication technology. LoRa can transmit information up to a range of several kilometers without an internet connection. It will be advantageous when the farm's location is deep in the forest, and there is no GSM signal for internet access. The results show that the system can control the farm irrigation automatically without human hands. The water gates in the field are operated based on the water level. The irrigation monitoring process becomes easier because they do not need to come to the farm location. In fact, they can use smartphones to monitor it. Furthermore, the system can be monitored well under distance of 100 meters with LoRa communications Creator An entity primarily responsible for making the resource Kurniawan D. Irianto 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 01-02-2022 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/32e00f7f5fe7adecf8ed7e7fec5f5b06.pdf 5e81f1c27820e8255e4277e2191948ad 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 6 NO 1 (2022) 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 Sistem Pengukuran Suhu Tubuh Menggunakan AMG8833 Dan Kinect Sebagai Pencegahan Penularan Covid-19 Subject The topic of the resource AMG8833, kinect, arduino uno, buzzer, face tracking, internet of thing Description An account of the resource The purpose of this study is to create an effective and safe body temperature measurement system to prevent the transmission of covid-19 using the AMG8833 and Kinect. The method of sending data uses the Internet of Thing (IoT) and face tracking with 3D form as face identification using a kinect type xbox 360 using an arduino uno and a buzzer connected to the AMG8833. AMG8833 has an infrared detector which is arranged in an 8x8 array and reads body temperature non-contact by detecting infrared energy from the body. kinect recognizes facial features based on the distance of the kinect position coordinates on the face. AMG8833 and kinect as input, Arduino uno as AMG8833 data processing and buzzer gives a sound signal if the temperature is above 37.10 0C. Body temperature measurement data was carried out 3 times, namely at a distance of 5,10 and 15cm. Measurement data from this body temperature measuring instrument are compared with a thermogun average error value of 0.11% with a difference between the maximum and minimum average body temperatures of 0.04%. It is hoped that body temperature measurements can be as a precaution against the spread of covid-19. Creator An entity primarily responsible for making the resource Wiwin Lovita1 , Aulia2 , Junaldi3 Publisher An entity responsible for making the resource available Universitas Andalas Date A point or period of time associated with an event in the lifecycle of the resource 27 februari 2022 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/f87335747a384efa76e3c27fb0d58950.pdf a9862538a56f53ba5e6f129b846f08bd 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 6 NO 1 (2022) 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 Gradient Boosting Machine, Random Forest dan Light GBM untuk Klasifikasi Kacang Kering Subject The topic of the resource GBM, RF, LightGBM, Bean Classification, BoxCox Description An account of the resource Bean seed classification is critical in determining the quality of beans. Previously, the same dataset was tested using the MLP, SVM, KNN, and DT algorithms, with SVM producing the best results. The purpose of this study is to determine the most effective model through the use of the BoxCox transformation selection feature and the random forest (RF) algorithm, as well as the gradient boosting machine (GBM), light GBM, and repeated k-folds evaluation model. The bean dataset is available on the UCI Repository website. The BoxCox transformation and repeated k-folds improved the classification prediction's accuracy. The model is used in the optimal training phase for a random forest with decision tree parameters 50 and depth 10, a gradient boosting machine model with a learning rate of 1, and a light gradient boosting machine model with a learning rate of 0.5 and estimator of 500. The best training accuracy results are obtained with light GBM. which is 99 percent accurate, but only 91 percent accurate in terms of validation. According research, the Barbunya, Bombay, Cali, Dermason, Horoz, Seker, and Sira beans classes provided accuracy values of 91 percent, 100 percent, 92 percent, 92 percent, 95 percent, 94 percent, and 84 percent, respectively Creator An entity primarily responsible for making the resource Indrawata Wardhana1 , Musi Ariawijaya2 , Vandri Ahmad Isnaini3 , Rahmi Putri Wirman4 Publisher An entity responsible for making the resource available UIN Sulthan Thaha Saifuddin Jambi Date A point or period of time associated with an event in the lifecycle of the resource 27 februari 2022 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/45e3cddd8d5cada000122ac433346377.pdf 51dd9309b03430107b961ac593ff4d1d 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 6 NO 1 (2022) 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 Monitoring dan Kendali Tegangan Jaringan Listrik Fase-tiga melalui Smartphone Subject The topic of the resource : electric voltage, a three-phase network, Ethernet shield, Arduino microcontroller, Android smartphone Description An account of the resource This paper describes the creation of a minimum system for monitoring and controlling the voltage on a three-phase electrical network. Making a minimum system based on the result of previous research that has been implemented in the forms of device assembly, programming, and performance measurement. The research objectives are (i) assembling the hardware and programming based on Arduino software version 1.8.10 and (ii) measuring the minimum system performance. The research method for achieving the objective of assembling a minimum system is carried out through integrated wiring as an effort to get the hardware achievement, while for programming is an effort to get the software achievement. The implementation of the research method for measuring the performance as an effort to get the achievements of hardware and software is carried out by giving the orders to activate the paths of each phase. The result of the assembly is the integration of the Arduino UNO R3 module, Ethernet Shield type of W5100, MikroTik RouterBoard, relay modules, and Android smartphone, while the results of the programming are compiling and uploading the syntax to the Arduino module and making applications in the .apk format for a smartphone. Performance measurements are carried out by activating conditions for the three phases of phase-R, phase�S, and/or phase-T. The conclusion can be obtained, that the manufacture of a minimum system is appropriate for the fulfillment with respect to the presence of an electronic device for monitoring and controlling the voltage on a three-phase electrical network Creator An entity primarily responsible for making the resource Arief Goeritno1 , Febby Hendryan2 Publisher An entity responsible for making the resource available Universitas Ibn Khaldun Bogor Date A point or period of time associated with an event in the lifecycle of the resource 1 februari 2022 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/77168ca92c493a3caa48d294a83ef9d2.pdf e6094929c5c6652c9fe301fc918165e9 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 6 NO 1 (2022) 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 Prediksi Harga Cryptocurrency Menggunakan Algoritma Long Short Term Memory (LSTM) Subject The topic of the resource Cryptocurrency, RNN, LSTM, Price Forecasting, BTC Description An account of the resource Technological developments continue to encourage the creation of various innovations in almost all aspects of human life. One of the innovations that is becoming a worldwide phenomenon today is the presence of cryptocurrency as a digital currency that is able to replace the role of conventional currency as a means of payment. Currently, the number of cryptocurrency investors in Indonesia has reached 4.45 million people as of March 2021, an increase of 78% compared to the end of the previous year. Very volatile price movements make cryptocurrency investments considered speculative so the risks faced are also very high. The purpose of this study is to build a predictive model that is able to forecast prices on the cryptocurrency market. The algorithm used to build the prediction model is Long Short Term Memory (LSTM). LSTM is the development of the Recurrent Neural Network (RNN) algorithm to overcome problems in the RNN in managing data for a long period. LSTM is considered superior to other algorithms in managing time series data. The data in this study were taken from the Yahoo Finance website using the Pandas Datareader library through Google Collaboratory. The entire prediction model development process is carried out through Google Collaboratory tools. To improve the accuracy of the model, the Nadam optimization algorithm was used and three testing sessions were carried out with the number of Epochs of 1, 10, and 20 in each session. The final test results show that the best prediction performance occurs when testing the DOGE coin type with the number of Epoch 20 which gets an RMSE value of 0.0630. Creator An entity primarily responsible for making the resource Moch Farryz Rizkilloh1 , Sri Widiyanesti2 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 1 februari 2022 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/adf7739f4684e88ef69a3c11292d6267.pdf f03d38eda2577199a746d4a30975bcf8 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 6 NO 1 (2022) 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 of the Fuzzy Logic Method for Autism Spectrum Disorder Diagnosis Subject The topic of the resource : Autism Spectrum Disorder, Expert System, Optimization, Fuzzy Logic Method Description An account of the resource Diagnosis of autism spectrum disorder (ASD) can use a fuzzy inference system. The use of fuzzy logic method to obtain ASD diagnosis results according to experts based on the limits of factors/symptoms of the disease and all the rules obtained from experts. Recommendations for therapy and preventive actions can be given by experts after knowing the results of the diagnosis of ASD using the fuzzy logic method. This study serves to diagnose ASD by optimizing each degree of membership in the fuzzy logic method with the Mamdani method approach which is involved in the autism detection process involving 96 patient data. The Mamdani method itself can process an uncertain value from the user/patient into a definite value whose membership degree can be determined and adjusted to the conditions of the problem. Optimization was carried out on the degree of membership for all variables involved in the process of diagnosing ASD, namely social interaction, social communication and imagination and behavior patterns. The results of this study indicate a relatively small level of fuzzy calculation error with a precision value of 94.4%, a recall precision value of 65.4% and an error rate value of 3.05%. Calculation of accuracy shows a result of 90.59%. Creator An entity primarily responsible for making the resource Linda Perdana Wanti1 , Lina Puspitasari2 Publisher An entity responsible for making the resource available , Politeknik Negeri Cilacap Date A point or period of time associated with an event in the lifecycle of the resource 1 februari 2022 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/d5d7a3012203f039e504917c0de92944.pdf 4fb83a76d9f2fb568b7e3c23a790a5e2 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 6 NO 1 (2022) 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 Detection of Essential Thrombocythemia based on Platelet Count using Channel Area Thresholding Subject The topic of the resource abnormalities, platelet count, essential thrombocythemia, channel area thresholding, k-nearest neighbor. Description An account of the resource Essential Thrombocythemia is one of the Myeloproliferative Neoplasms Syndrome where the mutation of the JAK2V617F gene causes the bone marrow to produce excessive platelets. For early detection of Essential Thrombocythemia disease using a full blood count and peripheral blood smear examination. The main characteristic is that giant platelets are found as large as young lymphocytes with a number of more than 21 cells in one field of view. The purpose of this research is to detect Essential Thrombocythemia by counting the number of platelets in the peripheral blood smear image. This research utilizes computer vision technique where the research stages consist of peripheral blood smear image, color conversion, image enhancement, segmentation, labeling process, feature extraction and K-Nearest Neighbor classification. There are three features used, namely the number of platelet cells, area and perimeter. The K-Nearest Neighbor method is able to classify 215 training data with an accuracy of 98.13% and classify 40 testing data with an accuracy of 100% based on the value of K = 3 Creator An entity primarily responsible for making the resource Prawidya Destarianto1 , Ainun Nurkharima Noviana2 , Zilvanhisna Emka Fitri3 , Arizal Mujibtamala Nanda Imron4 Publisher An entity responsible for making the resource available Politeknik Negeri Jember Date A point or period of time associated with an event in the lifecycle of the resource 1 februari 2022 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/7d47a716ad056a9b160666c4a3076792.pdf cfe3d034112fa553076d0d45917e44e4 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 6 NO 1 (2022) 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 Prediction of Big Five Personality in Twitter Users Subject The topic of the resource Big Five Personality, SVM, TF-IDF, LIWC, Optimization Description An account of the resource Various kinds of information can be acquired from social media platforms; one of them is on Twitter. User biographical information and tweets are the essential assets for research that can describe the Big Five Personality, including openness, conscientiousness, extraversion, agreeableness, and neuroticism. Several previous studies have tried the prediction of Big Five Personality. However, the authors found problems in how to optimize the work of the personality prediction system. So, in this study, Big Five Personality predictions were carried out on users of Twitter and improved the performance of the personality prediction system. We implement optimization techniques such as sampling, feature selection, and hyperparameter tuning to enhance the performance. This study also applies linguistic feature extraction, such as LIWC and TF-IDF. By using 287 Twitter users that have permitted their data to be crawled acquired from an online survey using Big Five Inventory (BFI), and applying all optimization techniques, the average accuracy result is 84.22% which is a 74.44% gain over the specified baseline. Creator An entity primarily responsible for making the resource Gita Safitri1 , Erwin Budi Setiawan2 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 27 februari 2022 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