1 10 16 https://repository.horizon.ac.id/files/original/0e65a99590ed3878db90252b49e3c44a.pdf 6a184dc60d508c52a736f71ff4d778f4 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 3 (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 PerbandinganOptimasi Feature Selection pada Naïve Bayes untuk KlasifikasiKepuasanAirline Passenger Subject The topic of the resource Data Mining, Classification, Naïve Bayes, Particle Swarm Optimization, Genetic Algorithm Description An account of the resource The quality of an airline's services cannot be measured from the company's point of view, but must be seen from the point of view ofcustomer satisfaction. Data mining techniques make it possible to predict airline customer satisfaction with a classification model. The Naïve Bayes algorithm has demonstrated outstanding classification accuracy, but currently independentassumptions are rarely discussed. Some literature suggests the use of attribute weighting to reduce independentassumptions, which can be done using particle swarm optimization (PSO) and genetic algorithm (GA) through feature selection. This study conducted a comparison of PSO and GA optimization on Naïve Bayes for the classification of Airline Passenger Satisfactiondata taken from www.kaggle.com. After testing, the best performance is obtained from the model formed, namely the classification of Airline Passenger Satisfactiondata using the Naïve Bayes algorithm with PSO optimization, where the accuracy value is 86.13%, the precision value is 87.90%, the recall value is 87.29%, and the value isAUC of 0.923 Creator An entity primarily responsible for making the resource Yoga Religia1, Amal Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Pelita Bangsa Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/d0ae464267944b7bd7d92163e41415a6.pdf 53969816124a655b13a05047cf8b0e6f 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 3 (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 Multi Aspect Sentiment of Beauty Product Reviews using SVM and Semantic Similarity Subject The topic of the resource support vector machine, semantic similarity,TF-IDF Description An account of the resource Beauty products are an important requirement for people, especially women. But, not all beauty products give the expected results. A review in the form of opinion can help the consumers to know the overview of the product. The reviews were analyzed using a multi-aspect-based approach to determine the aspects of the beauty category based on the reviews written on femaledaily.com. First, the review goes through the preprocessing stage to make it easier to be processed, and then it used the Support Vector Machine (SVM) method with the addition of Semantic Similarityand TF-IDF weighting. From the test result using semantic, get an accuracy of 93% on the price aspect, 92% on the packaging aspect, and 86% on the scent aspect. Creator An entity primarily responsible for making the resource rbah Salsabila1, Yuliant Sibaroni2 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 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 juni 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/49e1d6663f067e44a602f3d0ea49f62f.pdf 3a675478c0de1be2aea2babad7bd0c6b 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 3 (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 Evaluasi Topik Tersembunyi Berdasarkan Aspect Extractionmenggunakan PengembanganLatent Dirichlet Allocation Subject The topic of the resource sentiment analysis, aspect, topic, extraction, LDA, evaluation Description An account of the resource Recently, Sentiment Analysis is used forexpression detection of products or services. Sentiment Analysis is one categorytypewith a level of aspect focusedon extracting productaspects. One of the common methods used for aspect extraction is Latent Dirichlet Allocation (LDA) usingrandom topic identification, but this method has not been able to find an acceptable topic with some aspects havingbeen found. Undeterminable topics arereferred to as the hidden topics. This studypurposeis to evaluateand comparethe suitability of identifying hidden topics between human and computer evaluation. The study is also focused on aspect extraction using a variety of LDA innovations.The data used in this study used case studies on e-Commerce. Data were processed using feature selection and grouped using LDA development.Then the dataresultsare processed using Latent Topic Identification basedonsubjective and objective evaluations. The identification of hidden topicresultswasevaluated using several semantic and lexicon tests.The evaluation results indicate the comparisonoftwo hidden topic identification assessmentvaluesis quite relevant with the average difference in value reaching 6%. As a result, computer calculations assist humans in determining topics if each topic has a low coherence value Creator An entity primarily responsible for making the resource Dinda Adimanggala1, Fitra A. Bachtiar2, Eko Setiawan3 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Brawijaya Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/86206ed4629b63e22b5b94d23f04d944.pdf 2a9e6d2b3bd75edb09e8c8e4967e1a21 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 3 (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 AnalisisOptimasi Algoritma Klasifikasi Naive Bayes menggunakanGenetic Algorithm dan Bagging Subject The topic of the resource Classification, Bank Marketing, Naïve Bayes, Bagging, Genetic Algotithm Description An account of the resource he increasing demand for credit applications to banks has motivated the banking world to switch to more sophisticated techniques for analyzing the level of credit risk. One technique for analyzing the level of credit risk is the data mining approach. Datamining provides a technique for finding meaningful information from large amounts of data by way of classification. However, bank marketing data is a type of imbalance data so that if the classification is done the results are less than optimal. The classification algorithm that can be used for imbalance data types can use naïve Bayes. Naïve Bayes performs well in terms of classification. However, optimization is needed in order to obtain more optimal classification results. Optimizationtechniques in handling imbalance data have been developed with several approaches. Bagging and Genetic Algorithms can be used to overcome imbalance data. This study aims to compare the accuracy level of the naïve Bayes algorithm after optimization using the bagging and genetic algorithm. The results showed that the combination of bagging and a genetic algorithm could improve the performance of Naive Bayes by 4.57% Creator An entity primarily responsible for making the resource Agung Nugroho1, Yoga Religia Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Pelita Bangsa Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/e24736103e90b02866055bc2b92e41d2.pdf 6618d3a30cc1703eef53224f58b8a1a3 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 3 (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 Sistem PemantauKondisi Lingkungan Pertanian Tanaman Pangan dengan NodeMCU ESP8266 dan Raspberry Pi Berbasis IoT Subject The topic of the resource precision agriculture, monitoring system, IoT, Node-RED, MQTT Description An account of the resource The increasing need for food is not in line with the clearing of agricultural land for food crops. So that the effort to increase the productivity of agricultural products is by applying precision agriculture. However, in reality, precision agriculture isdifficult to apply to conventional processes, where farmers come to the farm, collect data, then carry out maintenance. This method will make production results not optimal because maintenance is not done accurately. This study introduces a monitoring system for environmental conditions based on the Internet of Things (IoT) for agricultural land, where trials are carried out in a greenhouse. The system that has been developed consists of several sensors designed to collect information related to agricultural environmental conditions, including DHT22 sensor (temperature and humidity), DS18B20 sensor (soil temperature), soil moisture sensor (moisture content in the soil), and BH1750 sensor (light intensity). Based on the Message Queuing Telemetry Transport (MQTT) protocol, the data is sent to a gateway (Raspberry Pi) and a local server via a wireless network to be stored in a database. By using the Node-RED Dashboard, the received sensor data is then displayed on the browser every time the sensor sends data. Inaddition, the local server also publishes sensor data to the public MQTT broker so that sensor data can be accessed through the MQTT Dashboard application on a smartphone. The results of testing for 25days of the system running obtained an average success of thesystem in storing data of 99.64% Creator An entity primarily responsible for making the resource Agus Ambarwari1, Dewi Kania Widyawati2, Anung Wahyudi3 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Politeknik Negeri Lampung Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/edddef7d2732d79d97d97f13156004b1.pdf 619eb9a4ebfbd02246eab7aa9c454434 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 3 (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 Analisis Perbandingan Algoritma Klasifikasi MLPdan CNNpada DatasetAmerican Sign Language Subject The topic of the resource CNN, MLP, ASL, classification Description An account of the resource People who have hearing loss (deafness) or speech impairment (hearing impairment) usuallyuse sign language to communicate. One of the most basic and flexible sign languages is the Alphabet Sign Language to spell out the words you want to pronounce. Sign language uses hand, finger, and face movements to speak the user's thoughts. However, for alphabetical sign language, facial expressions are not used but only gestures or symbols formed using fingers and hands. In fact, there are still many people who don't understand the meaning of sign language. The use of image classification can help people more easily learn and translate sign language. Image classification accuracy is the main problem in this case. This research conducted a comparison of image classification algorithms, namely Convolutional Neural Network (CNN) and Multilayer Perceptron (MLP) to recognize American Sign Language (ASL) except the letters "J" and "Z" because movement is required for both. This is done to see the effect of the convolution and pooling stages on CNN on the resulting accuracy valueand F1 Scorein the ASL dataset. Based on the comparison, the use of CNN which begins with Gaussian Low Pass Filteringpreprocessing gets the best accuracy of 96.93%and F1 Score 96.97% Creator An entity primarily responsible for making the resource Mohammad Farid Naufal1, Sesilia Shania2, Jessica Millenia3, Stefan Axel4, Juan Timothy Soebroto5, Rizka Febrina P.6, Mirella Mercifia7 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Surabaya Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/e4b89b16439034ddb3704332da110c15.pdf a128ef5df11326a02554240178778a81 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 3 (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 Kriptografi Audio MP3 Menggunakan RSA dan Transposisi Kolom Subject The topic of the resource MP3, RSA, transposition, cryptography Description An account of the resource Mp3 is one form of audio file extension that is widely used today. With a variety of uses in a variety of mp3 systems become one of the audio extensions that are commonly found in technology systems of the Internet of Thingsera. However, with the many uses of the .mp3 file extension, there is a new problem, namely the security of the data itself. From these problems, the author aims to examine the security of the mp3 file by designing cryptographic science-based applications. The cryptographic algorithm used in the application is a combination of the asymmetric RSA 2048 algorithm and symmetric columnic transpositions. RSA 2048 algorithm was chosen because it has a keylength in accordance with NIST standards in securing data.By combining the two algorithms, the application system will have the ability to manage mp3 files and encrypt mp3 files with the results of data that cannot be played like mp3 files in general. This application system will be developed by prototype methodwhich is the best method in developing a system with trial and error in algorithm developmen Creator An entity primarily responsible for making the resource Cinantya Paramita1, Usman Sudibyo Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Dian Nuswantoro Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/e9f162cacc2d2e21cb10026766fb1ebe.pdf 24a7b480f3a11fc8317b4cfed105e4e2 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 3 (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 Optimalisasi Penyaluran Bantuan Pemerintah Untuk UMKM Menggunakan Metode Fuzzy C-Means Subject The topic of the resource Clustering, Data Mining, Fuzzy C-Means, MSMEs Description An account of the resource ndonesian MSMEs were very seriously affected by the Covid-19 pandemic, which caused the Indonesian economy hasexperienced deceleration. The Indonesian government has taken several steps to keep economic activity running, such as direct cash assistance for micro-scale businesses but is havingproblems in obtaining real data so that assistance is not on target, the clustering method using Fuzzy C-Means (FCM) is used for grouping MSME data. FCM allows the data to be a member of all clusters in which each cluster has a membership degree value of 0-1. The data used is from the website of the Sleman Regency Cooperatives and SME Service.FCM classifies MSME data based on the attributes of revenue, assets and number of workers. This research resulted in grouping MSME data into 3 priority levels for MSMEs in obtaining assistance, namely high priority, medium priority, and low priority. The results of this study show that the number of MSMEs with high priority is 23,023 MSMEs, medium priority is 9,774 MSMEs and low priority is 3,159 MSMEs. The validation test of the FCM method uses the Partition Coefficient Index (PCI) which has a value of 0.826 which means that value good because it is close to 1. Creator An entity primarily responsible for making the resource Anggara Cahya Putra1, Kristoko Dwi Hartomo Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Kristen Satya Wacana Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 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/d8ed4e6de537211e7318308e9d1afb9f.pdf 80b3e40d2a4765e4cf326ea55a0e076d 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 3 (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 Support Vector Machine to Predict Electricity Consumption in the Energy Management Laboratory Subject The topic of the resource Machine Learning, Prediction of Electricity Consumption, Profile Load, Support Vector Machine Description An account of the resource Predicted electricity consumption is needed to perform energy management. Electricity consumption prediction is also very important in the development of intelligent power grids and advanced electrification network information. we implement a Support Vector Machine (SVM) to predict electrical loads and results compared to measurable electrical loads. Laboratory electrical loads have their own characteristics when compared to residential, commercial, or industrial, we use electrical load data in energy management laboratories to be used to be predicted. C and Gamma as searchable parameters use GridSearchCV to get optimal SVM input parameters. Our prediction data is compared to measurement data and is searched for accuracy based on RMSE (Root Square Mean Error), MAE (Mean Absolute Error) and MSE (Mean Squared Error) values. Based on this we get the optimalparameter values C 1e6and Gamma 2.97e-07, with the result RSME (Root Square Mean Error) ; 0.37, MAE (meaning absolute error); 0.21 and MSE (Mean Squared Error); 0.14 Creator An entity primarily responsible for making the resource zam Zamhuri Fuadi1, Irsyad Nashirul Haq2, Edi Leksono3 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 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 juni 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/639c3a3ddeb221b7ae32b78cb72ee017.pdf 5f40e8b2816ed1088773fe8ee3ac2fe4 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 3 (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 Deteksi Masker Pencegahan Covid19 MenggunakanConvolutional Neural Network Berbasis Android Subject The topic of the resource Convolutional Neural Network, Mask, covid19 Description An account of the resource Masks are an important part of preventing Covid19disease.TheWorld Health Organization (WHO) have also recommended the community use masks when doing activities in public areas. There are many types of masks that are used to cover the nose and mouth. In general, there are about 3 types of masks that are commonly used by the public today, namely medical masks, N95 and cloth masks. This study aims to detect the type of mask used by the community. So that it can make easier for the government to apply discipline in COVID-19 health protocol.The detection method used in this study is a convolutional neural network (CNN). The first step is acquisition of knowledge, which first collects the types of masks on the market, followed by the representation of that knowledge before being modeled into a mathematical calculation formula, which will then be processed using the Convolutional Neural Network method. The system will be carried out by analyzing the recall value, its precision and accuracy.Testing process is carried out on an Android-based device and the mobilenetV2 framework. In this study, the accuracy value is 90%using ADAM Optimization and 80 % using Gradient descent optimization Creator An entity primarily responsible for making the resource Nyoman Purnama1, Putu Kusuma Negara2 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available STMIK PRIMAKARA Date A point or period of time associated with an event in the lifecycle of the resource 26 juni 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