Offline handwriting recognition is a technique used to recognize handwriting in paper document which converting it to digital form. Each handwriting has a unique style and shape that can be used to identify the owner. This research aims to develop a method to recognize the digital data handwriting. The method combines two algorithms; the first is Generalized Hough Transform in feature extraction process to detect arbitrary objects on the image; the second algorithm is Backpropagation to train the neural network based on feature values from feature extraction process. Artificial Neural Network (ANN) is used to improve the accuracy of the recognition system. The experiments are performed by using 100 handwriting images of 10 different people. The number of hidden units is defined through experiment to obtain optimal neural network. The experiment result shows that the recognition accuracy is up to 80%. Index Terms—Artificial Neural Network, Backrpopagation, Generalized Hough Transform, Offline handwiritng recognition
{"title":"Pengenalan Tulisan Tangan Offline Dengan Algoritma Generalized Hough Transform dan Backpropagation","authors":"Farica Perdana Putri, Adhi Kusnadi","doi":"10.31937/sk.v10i1.890","DOIUrl":"https://doi.org/10.31937/sk.v10i1.890","url":null,"abstract":"Offline handwriting recognition is a technique used to recognize handwriting in paper document which converting it to digital form. Each handwriting has a unique style and shape that can be used to identify the owner. This research aims to develop a method to recognize the digital data handwriting. The method combines two algorithms; the first is Generalized Hough Transform in feature extraction process to detect arbitrary objects on the image; the second algorithm is Backpropagation to train the neural network based on feature values from feature extraction process. Artificial Neural Network (ANN) is used to improve the accuracy of the recognition system. The experiments are performed by using 100 handwriting images of 10 different people. The number of hidden units is defined through experiment to obtain optimal neural network. The experiment result shows that the recognition accuracy is up to 80%. \u0000Index Terms—Artificial Neural Network, Backrpopagation, Generalized Hough Transform, Offline handwiritng recognition","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125817712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing violations by smokers in free zone cigarettes, very affecting for human health cigarettes or not smokers. So that designed a supervision system to reduce the number of violations by smokers. The system is based on the aimed to detect and provide a warning to smokers that the room cannot be cigarettes if breaking will be imposed sanctions. This system is made up of hardware, consists of smoke sensor base their MQ2, Camera C270 and Raspberry pi. This system created by the language of Python programming technique. How this appliance if violations by smokers, when smoke is detected then the webcam will take pictures of the offenders and the results of the photo will be sent automatically to the email, if the results of the photo has been sent to email and alert sound alarm will be active and a notification that in the area cannot be cigarettes. The results of the design of this system is not only to detect and provide a notification only, but it also has been able to give a warning and evidence of who is a breach in the zone. Index Terms— Smoke sensor, MQ-2, raspberry pi
{"title":"Fast Tracking of Detection Offenders Smoking Zone Menggunakan Sensor MQ-2 Berbasis Internet of Things","authors":"Fredy Susanto, Syafnidawati Syafnidawati","doi":"10.31937/sk.v10i1.749","DOIUrl":"https://doi.org/10.31937/sk.v10i1.749","url":null,"abstract":"With the increasing violations by smokers in free zone cigarettes, very affecting for human health cigarettes or not smokers. So that designed a supervision system to reduce the number of violations by smokers. The system is based on the aimed to detect and provide a warning to smokers that the room cannot be cigarettes if breaking will be imposed sanctions. This system is made up of hardware, consists of smoke sensor base their MQ2, Camera C270 and Raspberry pi. This system created by the language of Python programming technique. How this appliance if violations by smokers, when smoke is detected then the webcam will take pictures of the offenders and the results of the photo will be sent automatically to the email, if the results of the photo has been sent to email and alert sound alarm will be active and a notification that in the area cannot be cigarettes. The results of the design of this system is not only to detect and provide a notification only, but it also has been able to give a warning and evidence of who is a breach in the zone. \u0000Index Terms— Smoke sensor, MQ-2, raspberry pi","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126908807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data is one of the most important things in this information and information technology era that evolving now. Currently, the government still has not used the public data maximally for administrative purposes. Utilization of this big population data is the creation of a web service application system with REST API where this data will be open and accessible to those who have access. One of the institutions that use this service is the Manpower and Transmigration Service where this system can make the Dinas staff more efficient to create and register job search cards using available community data. This application is able to provide and facilitate many parties, such as data administrators to monitor data usage, registration employee in input data, and people able to register independently. Index Terms—Web service, API, Rest api, People data
{"title":"Pembangunan Web Service Data Masyarakat Menggunakan REST API dengan Access Token","authors":"Muhammad Iqbal Perkasa, E. Setiawan","doi":"10.31937/SK.V10I1.838","DOIUrl":"https://doi.org/10.31937/SK.V10I1.838","url":null,"abstract":"Data is one of the most important things in this information and information technology era that evolving now. Currently, the government still has not used the public data maximally for administrative purposes. Utilization of this big population data is the creation of a web service application system with REST API where this data will be open and accessible to those who have access. One of the institutions that use this service is the Manpower and Transmigration Service where this system can make the Dinas staff more efficient to create and register job search cards using available community data. This application is able to provide and facilitate many parties, such as data administrators to monitor data usage, registration employee in input data, and people able to register independently. \u0000Index Terms—Web service, API, Rest api, People data","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126507146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Menemukan tempat parkir kosong di tempat parkir dalam ruangan seperti pusat perbelanjaan menjadi kesulitan banyak pengemudi, terutama saat jam sibuk di kota-kota besar. Dalam makalah ini, sebuah sistem deteksi kekosongan tempat parkir dalam ruangan diusulkan, dengan menggunakan sistem kamera yang melibatkan OpenCV untuk mempercepat waktu dalam mencari tempat parkir bagi pengemudi kendaraan dengan memberi mereka informasi lokasi dan tempat parkir. Sistem ini menggunakan metode deteksi objek statis, yaitu Haar-Like Cascade Classifier yang dikombinasikan dengan Hough Line Detection untuk mengidentifikasi area parkir kosong dari gambar parkir yang diambil secara real time melalui kamera IP atau kamera USB. Sistem ini dirancang untuk disematkan dengan sistem manajemen parkir sebuah bangunan sebagai alat yang menyediakan tempat parkir untuk membantu pengemudi kendaraan memasuki area parkir. Index Terms—Haar-Like Cascade Classifier, Hough Line Detection, Sistem Maanajemen Parkir
{"title":"Pendeteksian Ruang Kosong Parkir di dalam Ruangan","authors":"Nunik Afriliana, R. Rosalina, Regina Valeria","doi":"10.31937/SK.V10I1.888","DOIUrl":"https://doi.org/10.31937/SK.V10I1.888","url":null,"abstract":"Menemukan tempat parkir kosong di tempat parkir dalam ruangan seperti pusat perbelanjaan menjadi kesulitan banyak pengemudi, terutama saat jam sibuk di kota-kota besar. Dalam makalah ini, sebuah sistem deteksi kekosongan tempat parkir dalam ruangan diusulkan, dengan menggunakan sistem kamera yang melibatkan OpenCV untuk mempercepat waktu dalam mencari tempat parkir bagi pengemudi kendaraan dengan memberi mereka informasi lokasi dan tempat parkir. Sistem ini menggunakan metode deteksi objek statis, yaitu Haar-Like Cascade Classifier yang dikombinasikan dengan Hough Line Detection untuk mengidentifikasi area parkir kosong dari gambar parkir yang diambil secara real time melalui kamera IP atau kamera USB. Sistem ini dirancang untuk disematkan dengan sistem manajemen parkir sebuah bangunan sebagai alat yang menyediakan tempat parkir untuk membantu pengemudi kendaraan memasuki area parkir. \u0000Index Terms—Haar-Like Cascade Classifier, Hough Line Detection, Sistem Maanajemen Parkir","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131126074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Employee is a part of the company's most important asset in its efforts to maintain survival, growth, ability to compete and profit. At this time the process of assessment of employees in Jakarta Smart City is still in the form of manual and the decision only from one party only, so the process is still not accurate. So it takes the methods that must be able to replace that system. For that reason, a Decision Support System (SPK) was created to determine the best employees in Jakarta Smart City. In the system implemented the method of Entropy and TOPSIS. Entropy method can be trusted in determining the weight of the criteria to be used. And TOPSIS method can quickly perform the ranking process. Criteria to be used are quality and quantity of work, obedience, cooperation, morale, and work discipline. The index of satisfaction level of respondents to the decision support system ranges from 70% -80%, meaning that the assessment of the system created gives results at a fairly good level. Index Terms—employee, nter key words or phrases in alphabetical order, separated by commas
{"title":"Implementasi Metode Entropy dan Topsis Dalam Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik","authors":"Mitha Anggreani Rupang, Adhi Kusnadi","doi":"10.31937/SK.V10I1.887","DOIUrl":"https://doi.org/10.31937/SK.V10I1.887","url":null,"abstract":"Employee is a part of the company's most important asset in its efforts to maintain survival, growth, ability to compete and profit. At this time the process of assessment of employees in Jakarta Smart City is still in the form of manual and the decision only from one party only, so the process is still not accurate. So it takes the methods that must be able to replace that system. For that reason, a Decision Support System (SPK) was created to determine the best employees in Jakarta Smart City. In the system implemented the method of Entropy and TOPSIS. Entropy method can be trusted in determining the weight of the criteria to be used. And TOPSIS method can quickly perform the ranking process. Criteria to be used are quality and quantity of work, obedience, cooperation, morale, and work discipline. The index of satisfaction level of respondents to the decision support system ranges from 70% -80%, meaning that the assessment of the system created gives results at a fairly good level. \u0000Index Terms—employee, nter key words or phrases in alphabetical order, separated by commas","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134282150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since 2012 until 2017, culinary business in Indonesia has increased by an average 7% to 14% per year. Nowadays, application technology such as Zomato, helps consumers to find information about restaurant’s promos, advantages and disadvantages of a restaurant, and variations of the menu their provided. People who owned the culinary business can interact directly with consumers through social media such as LINE. LINE has 90 million users that communicate with each other by using features that LINE’s provided, such as stickers, news portals, voice and video calls, and LINE Message API service. With 90 million LINE’s users in Indonesia and growing culinary business, developing a restaurant recommendation system in LINE will provide solutions to many people, which inspired the author to develop this system. Data of restaurant it’s taken using Zomato API. Developing this system needs a method of AHP (Analytic Hierarchy Process) and VIKOR (VIsektriterijumsko KOmpromisno Rangiranje), where the application will be built using PHP language. The AHP method is used to assign a weighting value to criteria, and the VIKOR method is used to sort the best alternative option. Based on research through questionnaires, this system’s design and implementation has reached 71,13 value of usability, which mean that system is useful to help people to find restaurant their looking for. Index Terms - Culinary, Zomato API, LINE Message API, AHP, VIKOR
{"title":"Rancang Bangun Sistem Rekomendasi Restoran Menggunakan Metode AHP dan VIKOR pada Platform LINE","authors":"Andre Utomo Martliong, nizamul iswari","doi":"10.31937/SK.V10I1.847","DOIUrl":"https://doi.org/10.31937/SK.V10I1.847","url":null,"abstract":"Since 2012 until 2017, culinary business in Indonesia has increased by an average 7% to 14% per year. Nowadays, application technology such as Zomato, helps consumers to find information about restaurant’s promos, advantages and disadvantages of a restaurant, and variations of the menu their provided. People who owned the culinary business can interact directly with consumers through social media such as LINE. LINE has 90 million users that communicate with each other by using features that LINE’s provided, such as stickers, news portals, voice and video calls, and LINE Message API service. With 90 million LINE’s users in Indonesia and growing culinary business, developing a restaurant recommendation system in LINE will provide solutions to many people, which inspired the author to develop this system. Data of restaurant it’s taken using Zomato API. Developing this system needs a method of AHP (Analytic Hierarchy Process) and VIKOR (VIsektriterijumsko KOmpromisno Rangiranje), where the application will be built using PHP language. The AHP method is used to assign a weighting value to criteria, and the VIKOR method is used to sort the best alternative option. Based on research through questionnaires, this system’s design and implementation has reached 71,13 value of usability, which mean that system is useful to help people to find restaurant their looking for. \u0000Index Terms - Culinary, Zomato API, LINE Message API, AHP, VIKOR","PeriodicalId":325284,"journal":{"name":"Jurnal ULTIMA Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114255762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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