1 10 37 https://repository.horizon.ac.id/files/original/a3afc181ae20ec52e365145e7d2afac8.pdf 5020cc7957ec92690563121f672b96ab 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 2 (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 Gaussian Distributed Noise Generator Design Using MCU-STM32 Subject The topic of the resource Noise Generator, Gaussian Distribution, Enhanced Box-Muller, MCU-STM32F4 Description An account of the resource The random noise signal is widely used as a test signal to identify a physical or biological system. In particular, the Gaussian distributed white noise signal (Gaussian White Noise) is popularly used to simulate environmental noise in telecommunications system testing, input noise in testing ADC (Analog to Digital Converter) devices as well as testing other digital systems. Random noise signal generation can be done using resistors or diodes. The weakness of the noise generator system using physical components is the statistical distribution. An alternative solution is to use a Pseudo-Random System that can be adjusted for distribution and other statistical parameters. In this study, the implementation of the Gaussian distributed pseudo noise generation algorithm based on the Enhanced Box-Muller method is described. Prototype of noise generation system using a minimum system board based on Cortex Microcontroller or MCU-STM32F4. From the test results, it was found that the Enhanced Box-Muller (E Box-Muller) method can be applied to the MCU-STM32F4 efficiently, producing signal noise with Gaussian distribution. The resulting noise signal has an amplitude of ±1Volt, is Gaussian distributed and has a relatively wide frequency spectrum. The noise signal can be used as a jamming device in a certain frequency band using an Analog modulator Creator An entity primarily responsible for making the resource M. Nanak Zakaria1 , Achmad S.2 , Ahmad Wilda Y3 , Lis Diana Mustafa4 Publisher An entity responsible for making the resource available Malang State Polytechnic Date A point or period of time associated with an event in the lifecycle of the resource 20-04-2022 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/945a445114c3935c2c7cd6f0ddd5cc63.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 2 (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 27-02-2022 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/ba1ddb87c77b3feefa1eab08641b3ded.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 2 (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/97e32c7612d3eaf04647c98c44c6abf6.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 2 (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 , Kresna Arief Nugraha4 , Anastasia Lidya Maukar5 Publisher An entity responsible for making the resource available Informatika, Teknik, 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/a4283d2b00ac015aaeadec33e1b9549b.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 2 (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/0ec9d8e14b77ab4547d97eada35875c7.pdf 048f3e4996a05ca0059e294b8d5ffb1a 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 2 (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 Perbandingan Model Proses Algoritma Alpha dan Alpha++ Pada Aplikasi E-commerce Subject The topic of the resource Alpha, Alpha++, Process Discovery, Process mining, Event log, E-commerce Description An account of the resource Utilization of information technology is currently growing rapidly in helping activities especially in storing an event log. The activity which is behavior of the user can be analyzed using process mining. The process mining purpose to extract information from event logs on business processes that working. Discovery technique is used in this research. The purpose of this study is to compare two algorithms applied by creating an e-commerce application that is aware of the processes. E-commerce applications require event logs to read the behavior of visitor activities against the application. This research method starts from understanding the business processes that working, then designing a website by creating the application used. Furthermore, data collection through applications that are promoted through social media. The application will be recorded user activity and formed an event log. The event log that formed then discovered using alpha and alpha++ algorithms by utilizing the ProM Lite 1.2 tools. The evaluation results show that the alpha algorithm has shortcomings, namely length one loop, length two loop and non-free choice. And the alpha++ algorithm fixed this deficiency Creator An entity primarily responsible for making the resource Bambang Jokonowo1*, Miskah Alfiyyah Kulsum2 , Nita Komala3 , Publisher An entity responsible for making the resource available Universitas Mercu Buana 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/a279554c308ffccc44a9005bee06b60b.pdf d06fe33fe8500ce11fa5a72a73398053 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 2 (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 Pemetaan Pelanggan dengan LRFM dan Two Stage Clustering untuk Memenuhi Strategi Pengelolaan Subject The topic of the resource LRFM, Clustering, Davies Bouldin Index, Customer Mapping, Data Mining Description An account of the resource Maibus is a company of transportation services located in Bali. Transaction data that is owned has not been managed properly. This results in data accumulation and only as a turnover calculation, so LRFM and clustering methods are needed to assist the calculation and processing data in fulfilling customer management strategies. The research was conducted by collecting and understanding data, preprocessing, applying LRFM (Length, Recency, Frequency, Monetary), normalizing LRFM, evaluating the number of clusters with Davies Bouldin Index (DBI), clustering with K-Means, and analyzing cluster results. The data used is transaction data from January 2017 to December 2018 with a total of 14.292 data. The clustering method with the K-means algorithm helps in mapping customers based on transaction data. DBI was used to determine the optimal number of clusters and LRFM used to test the determination of variables in determining customer behavior and loyalty. The results of testing 7.193 invoice using 5 clusters with DBI value is 0.135. The result of customers in cluster 0,2,4 are new customer groups with the proposed strategy is enforced strategy, while the customer in cluster 1 and 3 are lost customers with the proposed strategy is let-go strategy that refers to the customer value and customer loyalty matrix. Creator An entity primarily responsible for making the resource Ni Putu Viona Viandari1 , I Made Agus Dwi Suarjaya2 , I Nyoman Piarsa3 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 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/b038c4f230f17e7917e3915b90d5bfdf.pdf 93ce4dc41a229d48001d51c540646110 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 2 (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 E-commerce Recommender System Using PCA and K-Means Clustering Subject The topic of the resource recommender system, collaborative filtering, principal component analysis, k-means, e-commerce Description An account of the resource Recently, recommender system has an important role in e-commerce to market products for users. One of recommender system approach that used in e-commerce is Collaborative Filtering. This system works by providing product recommendations based on products liked by other users who have similar preferences. However, sparse conditions in user data will cause sparsity problems, namely the system is difficult to provide recommendations because of the lack of important information needed. Therefore, we propose an e-commerce product recommendation system based on Collaborative Filtering using Principal Component Analysis (PCA) and K-Means Clustering. K-Means is used to overcome sparsity problems and to form user clusters to reduce the amount of data that needs to be processed. While PCA is used to reduce data dimensions and improve clustering performance of K-Means. The test results using the sports product dataset on the Olist e-commerce show that the proposed system has a lower RMSE value compared to other methods. For the number of neighbors of 10, 20, 30, and 40, our system obtains values of 0.771806, 0.75747, 0.75304, 0.75304, and 0.75270 Creator An entity primarily responsible for making the resource Dendy Andra A.N1 , Z. K. A. Baizal2 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 Telkom University 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/0cc9e0803ed7e748655c45ac35631671.pdf ee803f3bf84359edbeeb3d15640fadc6 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 2 (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 Implementation of Ensemble Method in Schizophrenia Identification Based on Microarray Data Subject The topic of the resource ensemble method, microarray, schizophrenia, disease detection Description An account of the resource Schizophrenia is a chronic mental illness that leads the patient to hallucinations and delusions with a prevalence of 0.4% worldwide. The importance early detection of Schizophrenia is tracking the pre-syndrome of Schizophrenia during the active phase, and could reduce psychosis symptomatic. However, the method sometimes cannot detect the symptoms accurately. As an alternative, machine learning can be implemented on microarray data for early detection. This study aimed to implement three ensemble methods, i.e., Random Forest (RF), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost) to identify Schizophrenia. Hyperparameter tuning was performed to improve the performance of the models. Based on the results, we found that the model 6, which is developed by the XGBoost method, performs better than other models with the value of accuracy and F1-score are 0.87 and 0.87, respectively. Creator An entity primarily responsible for making the resource Diya Namira Purba1 , Fhira Nhita2 , Isman Kurniawan3 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 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/49a395751dd0e0a77842f1cec9e3bf66.pdf cb110b668c2b33edb3320818447618ea 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 2 (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 Pengembangan Aplikasi Tiga-Tingkat Menggunakan Metode Scrum pada Aplikasi Presensi Karyawan Glints Academy Subject The topic of the resource scrum, software development management, three-tier architecture Description An account of the resource The rapid development of technology requires a software development management system that can be adaptive in rapidly changing circumstances. Scrum is an agile method that has the advantage of being agile and adaptive. Glints Academy holds an Industry Project Exploration as the program to prepare students for the rapid development of technology and reduce the gap between the education field and industrial field by MBKM program from the Ministry of Education and Culture. This study aims to apply the Scrum method in a heterogeneous developer team and divergent ability backgrounds to build an application with three-level architecture. The developer team is college students who come from different regions spread across Indonesia with full online implementation. Scrum is used because it is advantageous to other methods in a relatively fast-changing environment and also provides good quality control. The sprints were carried out in two sprints with two weeks of development in each sprint. The application built is an employee attendance application with a three-tier architecture: client, server, and data. The client-tier application is a front-end server built using the React.js framework while the server-tier and data-tier are built-in back-end servers with the Node.js and Express.js frameworks. JWT (JSON Web Token) authentication determines access role to functions and resources available on the back-end server. The result is a web application that fulfills the entire product backlog determined by the product owner. The results of this research are this method can used to develop features enhancement in the middle of the application development process without affecting the main feature development and this method is effectively used for different team developer backgrounds and during its online development. Creator An entity primarily responsible for making the resource Zidni Iman Sholihati1 , Imam Tahyudin2 Publisher An entity responsible for making the resource available Universitas Amikom Purwokerto 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