Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285490
M. Wahab, Sulistyaningsih, Y. P. Saputera, E. Amin
In this paper, the research and development on display software for a radar detector that has an ability to receive and process data from Ultra-Wide Band (UWB) signals with a frequency range of 2–18 GHz is presented. This software design consists of three parts: processing module software, data logging module software, and data flow module software. The radar detector is able to extract the primary parameter information from the received signal: frequency, pulse width, TOA (time of arrival), direction of arrival (DOA), level, and modulation type.
{"title":"Software development for ultra wide band radar detector","authors":"M. Wahab, Sulistyaningsih, Y. P. Saputera, E. Amin","doi":"10.1109/ICITISEE.2017.8285490","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285490","url":null,"abstract":"In this paper, the research and development on display software for a radar detector that has an ability to receive and process data from Ultra-Wide Band (UWB) signals with a frequency range of 2–18 GHz is presented. This software design consists of three parts: processing module software, data logging module software, and data flow module software. The radar detector is able to extract the primary parameter information from the received signal: frequency, pulse width, TOA (time of arrival), direction of arrival (DOA), level, and modulation type.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126983672","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285523
B. Sugiarto, E. Prakasa, R. Wardoyo, R. Damayanti, Krisdianto, L. M. Dewi, H. Pardede, Y. Rianto
Forest areas in Indonesia covered about 2/3 of total land areas which has about 4000 wood species. Wood identification plays a key role in wood utilization not only for determining appropriate use but also for supporting legal timber trade. However, the identification process requires high expertise and complex method which can be done in the laboratory. In order to simplify the identification process, we develop wood identification using computer vision by using Histogram of Oriented Gradient (HOG) to extract the species of wood and Support Vector Machines (SVM) to classify wood species. These methods combination will improve the accuracy of wood identification process. The result showed that the HOG method can extract the texture of woods and SVM classifier can generate the boundary decision after executing the training process. By doing the testing process of SVM classifier, the result showed that the accuracy from the identification is 70.5% for using positive testing image and 77.5% for using negative testing image. This accuracy value can be reached because the texture for each training image has different texture pattern especially the number and location of vessels.
{"title":"Wood identification based on histogram of oriented gradient (HOG) feature and support vector machine (SVM) classifier","authors":"B. Sugiarto, E. Prakasa, R. Wardoyo, R. Damayanti, Krisdianto, L. M. Dewi, H. Pardede, Y. Rianto","doi":"10.1109/ICITISEE.2017.8285523","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285523","url":null,"abstract":"Forest areas in Indonesia covered about 2/3 of total land areas which has about 4000 wood species. Wood identification plays a key role in wood utilization not only for determining appropriate use but also for supporting legal timber trade. However, the identification process requires high expertise and complex method which can be done in the laboratory. In order to simplify the identification process, we develop wood identification using computer vision by using Histogram of Oriented Gradient (HOG) to extract the species of wood and Support Vector Machines (SVM) to classify wood species. These methods combination will improve the accuracy of wood identification process. The result showed that the HOG method can extract the texture of woods and SVM classifier can generate the boundary decision after executing the training process. By doing the testing process of SVM classifier, the result showed that the accuracy from the identification is 70.5% for using positive testing image and 77.5% for using negative testing image. This accuracy value can be reached because the texture for each training image has different texture pattern especially the number and location of vessels.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126806989","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285493
A. Pratama, R. Munadi, Ratna Mayasari
In this paper, we build the prototype system using Wireless Sensor Network (WSN) for flood detector for flooding area. In a flooding area, power consumption and reliability of network become an important thing. Therefore, the performance of devices and algorithm of this system must work properly. The system is created using Fuzzy Logic to calculate the output, in order to make the system work properly. With Zigbee technology, WSN can be useful for monitoring a small area with many nodes. WSN can be combined with another application, e.g. cloud, android, virtual private network, etc. The objective of this paper is to design flood detector system with WSN on two scenarios that are single hop and multi hop, then find two of these which the best. Single hop means no router node between coordinator node and end node and multi hop means there is router node between coordinator node and end node. After some test, this system has a maximum range in single hop at a distance of 95.1 meters and 185.5 meters when using multi hop's scenario. Error for fuzzy logic compare between manual calculation and prototype system is 3.04417493% and error overall system for its result is 5%. In the examination of the quality of the network, values of throughput obtained fairly stable but the result of delay values is unstable, the further the distance the higher the values of delay, on the contrary values of throughput getting lower. The power consumption is only 0.083 Watt/hour when the system in single hop and 0.06525 Watt/hour when the system in multi hop.
{"title":"Design and implementation of flood detector using wireless sensor network with mamdani's fuzzy logic method","authors":"A. Pratama, R. Munadi, Ratna Mayasari","doi":"10.1109/ICITISEE.2017.8285493","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285493","url":null,"abstract":"In this paper, we build the prototype system using Wireless Sensor Network (WSN) for flood detector for flooding area. In a flooding area, power consumption and reliability of network become an important thing. Therefore, the performance of devices and algorithm of this system must work properly. The system is created using Fuzzy Logic to calculate the output, in order to make the system work properly. With Zigbee technology, WSN can be useful for monitoring a small area with many nodes. WSN can be combined with another application, e.g. cloud, android, virtual private network, etc. The objective of this paper is to design flood detector system with WSN on two scenarios that are single hop and multi hop, then find two of these which the best. Single hop means no router node between coordinator node and end node and multi hop means there is router node between coordinator node and end node. After some test, this system has a maximum range in single hop at a distance of 95.1 meters and 185.5 meters when using multi hop's scenario. Error for fuzzy logic compare between manual calculation and prototype system is 3.04417493% and error overall system for its result is 5%. In the examination of the quality of the network, values of throughput obtained fairly stable but the result of delay values is unstable, the further the distance the higher the values of delay, on the contrary values of throughput getting lower. The power consumption is only 0.083 Watt/hour when the system in single hop and 0.06525 Watt/hour when the system in multi hop.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131497674","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285566
D. Effendy, Kusrini Kusrini, Sudarmawan Sudarmawan
Intrusion Detection System (IDS) is made as one of the solutions to handle security issues on the network in order to remain assured free of attack. IDS's work is developed by 2 models that using signature-based detection, how it works is limited to the pattern of attack behavior that has been defined in the database. The next is the Anomaly-based IDS model. It works by detects unusual activity of network in the normal conditions, but this model gives a lot of false positiv messages. Several previous studies have shown that the IDS approach with machine learning techniques can provide high accuracy results. The first step that must be done in the application of mechine learning technique is preprocessing the selection of features / attributes to optimize the performance of learning algorithms. In this study, intrusion detection system with mechine learning classification technique is proposed by using naivebayes algorithm with NSL-KDD dataset. The processes in this reseach start from normalization of data, discretization features continuous variables with k-means method and the selection of features using Information Gain algorithm. The result of this reseach shows that the application of k-means clustering method for continuous variabe discretization and feature selection can optimize the performance of naivebayes algorithm in classifying intrusion types.
{"title":"Classification of intrusion detection system (IDS) based on computer network","authors":"D. Effendy, Kusrini Kusrini, Sudarmawan Sudarmawan","doi":"10.1109/ICITISEE.2017.8285566","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285566","url":null,"abstract":"Intrusion Detection System (IDS) is made as one of the solutions to handle security issues on the network in order to remain assured free of attack. IDS's work is developed by 2 models that using signature-based detection, how it works is limited to the pattern of attack behavior that has been defined in the database. The next is the Anomaly-based IDS model. It works by detects unusual activity of network in the normal conditions, but this model gives a lot of false positiv messages. Several previous studies have shown that the IDS approach with machine learning techniques can provide high accuracy results. The first step that must be done in the application of mechine learning technique is preprocessing the selection of features / attributes to optimize the performance of learning algorithms. In this study, intrusion detection system with mechine learning classification technique is proposed by using naivebayes algorithm with NSL-KDD dataset. The processes in this reseach start from normalization of data, discretization features continuous variables with k-means method and the selection of features using Information Gain algorithm. The result of this reseach shows that the application of k-means clustering method for continuous variabe discretization and feature selection can optimize the performance of naivebayes algorithm in classifying intrusion types.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114255231","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285542
Rifki Sadikin, Andria Arisal, Rofithah Omar, N. Mazni
Next-Generation Sequencing in bioinformatics produce a massive amount of data volume. Big data technologies are needed to reduce computation time in data processing. In this paper, we implement Hadoop Map-Reduce framework for processing Next-Generation Sequencing using Hadoop-BAM library. Our implementation process a Binary Alignment Map (BAM) file which contains a reference sequence and many aligned/not-aligned reads by spitting the BAM file into Hadoop data blocks. To process the BAM file in a computer cluster, we implement a mapper and a reducer of Hadoop Map-Reduce framework. The mapper processes the BAM file to produce key value pairs. While, the reducer summary the key value pairs into a meaningful output. Here the mapper and reducer are created to summarize the number of bases in a BAM file. We conduct the experiment in a LIPI Hadoop cluster. The cluster consists of 96 CPU cores. The result of our experiments show that our map-reduce implementations are gaining speed-up compare to serial Next-Generation Sequencing with Picard tools.
{"title":"Processing next generation sequencing data in map-reduce framework using hadoop-BAM in a computer cluster","authors":"Rifki Sadikin, Andria Arisal, Rofithah Omar, N. Mazni","doi":"10.1109/ICITISEE.2017.8285542","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285542","url":null,"abstract":"Next-Generation Sequencing in bioinformatics produce a massive amount of data volume. Big data technologies are needed to reduce computation time in data processing. In this paper, we implement Hadoop Map-Reduce framework for processing Next-Generation Sequencing using Hadoop-BAM library. Our implementation process a Binary Alignment Map (BAM) file which contains a reference sequence and many aligned/not-aligned reads by spitting the BAM file into Hadoop data blocks. To process the BAM file in a computer cluster, we implement a mapper and a reducer of Hadoop Map-Reduce framework. The mapper processes the BAM file to produce key value pairs. While, the reducer summary the key value pairs into a meaningful output. Here the mapper and reducer are created to summarize the number of bases in a BAM file. We conduct the experiment in a LIPI Hadoop cluster. The cluster consists of 96 CPU cores. The result of our experiments show that our map-reduce implementations are gaining speed-up compare to serial Next-Generation Sequencing with Picard tools.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114595231","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285505
Giovani Ardiansyah, D. Setiadi, C. A. Sari, E. H. Rachmawanto
Public networks such as the Internet are becoming more sophisticated, faster, and cheaper, so that more and more used for information exchange. This may increase the likelihood of confidential information from being stolen and exploited by unauthorized persons. This study proposed a combination of two Steganography domains coupled with Cryptography which aimed to make confidential information more secure and inaccessible to unauthorized persons. Messages are encrypted using the 3-DES method. On the other side of the cover image is decomposed into four subbands by using DWT. LH, HL, and HH subbands are chosen to embed encrypted message using LSB method. The last step, done Inverse DWT (IDWT) to get the stego image reconstruction. From the proposed method is then measured its quality with PSNR and MSE. As for message encryption results are measured using entropy. From the experiment results obtained PSNR results with a value of 55.30 dB for image messages size 64 ∗ 64 and 49.23 dB for messages size 128 ∗ 128. The extraction process can also be done perfectly with NC 1 and the average of Entropy of encrypted messages are 7.95754 for 64∗64 and 7.98904 for 128∗128.
{"title":"Hybrid method using 3-DES, DWT and LSB for secure image steganography algorithm","authors":"Giovani Ardiansyah, D. Setiadi, C. A. Sari, E. H. Rachmawanto","doi":"10.1109/ICITISEE.2017.8285505","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285505","url":null,"abstract":"Public networks such as the Internet are becoming more sophisticated, faster, and cheaper, so that more and more used for information exchange. This may increase the likelihood of confidential information from being stolen and exploited by unauthorized persons. This study proposed a combination of two Steganography domains coupled with Cryptography which aimed to make confidential information more secure and inaccessible to unauthorized persons. Messages are encrypted using the 3-DES method. On the other side of the cover image is decomposed into four subbands by using DWT. LH, HL, and HH subbands are chosen to embed encrypted message using LSB method. The last step, done Inverse DWT (IDWT) to get the stego image reconstruction. From the proposed method is then measured its quality with PSNR and MSE. As for message encryption results are measured using entropy. From the experiment results obtained PSNR results with a value of 55.30 dB for image messages size 64 ∗ 64 and 49.23 dB for messages size 128 ∗ 128. The extraction process can also be done perfectly with NC 1 and the average of Entropy of encrypted messages are 7.95754 for 64∗64 and 7.98904 for 128∗128.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115847188","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285532
Syechu Dwitya Nugraha, O. Qudsi, D. S. Yanaratri, Epyk Sunarno, I. Sudiharto
This paper presents the design of MPPT-current fed push-pull converter. Because of the high step-up transformer ratio and the transformer works at high frequencies, the converter is suitable for low voltage photovoltaic applications. Photovoltaic is a renewable energy that has several advantages, i.e., no pollution (no emissions), no noise, little maintenance and an abundant resource. The photovoltaic used in this study was 300Wp with a DC Bus of 400V. To optimize the working of photovoltaic used MPPT technique. The MPPT technique chosen is Perturbation and Observe. In the proposed converter, an inductor installed on the input side serves as a voltage boost so that the transformer ratio is not too high.
{"title":"MPPT-current fed push pull converter for DC bus source on solar home application","authors":"Syechu Dwitya Nugraha, O. Qudsi, D. S. Yanaratri, Epyk Sunarno, I. Sudiharto","doi":"10.1109/ICITISEE.2017.8285532","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285532","url":null,"abstract":"This paper presents the design of MPPT-current fed push-pull converter. Because of the high step-up transformer ratio and the transformer works at high frequencies, the converter is suitable for low voltage photovoltaic applications. Photovoltaic is a renewable energy that has several advantages, i.e., no pollution (no emissions), no noise, little maintenance and an abundant resource. The photovoltaic used in this study was 300Wp with a DC Bus of 400V. To optimize the working of photovoltaic used MPPT technique. The MPPT technique chosen is Perturbation and Observe. In the proposed converter, an inductor installed on the input side serves as a voltage boost so that the transformer ratio is not too high.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126576590","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285499
E. S. Wahyuni
This research addresses a challenging issue that is to recognize spoken Arabic letters, that are three letters of hijaiyah that have indentical pronounciation when pronounced by Indonesian speakers but actually has different makhraj in Arabic, the letters are sa, sya and tsa. The research uses Mel-Frequency Cepstral Coefficients (MFCC) based feature extraction and Artificial Neural Network (ANN) classification method. The result shows the proposed method obtain a good accuracy with an average acuracy is 92.42%, with recognition accuracy each letters (sa, sya, and tsa) prespectivly 92.38%, 93.26% and 91.63%.
{"title":"Arabic speech recognition using MFCC feature extraction and ANN classification","authors":"E. S. Wahyuni","doi":"10.1109/ICITISEE.2017.8285499","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285499","url":null,"abstract":"This research addresses a challenging issue that is to recognize spoken Arabic letters, that are three letters of hijaiyah that have indentical pronounciation when pronounced by Indonesian speakers but actually has different makhraj in Arabic, the letters are sa, sya and tsa. The research uses Mel-Frequency Cepstral Coefficients (MFCC) based feature extraction and Artificial Neural Network (ANN) classification method. The result shows the proposed method obtain a good accuracy with an average acuracy is 92.42%, with recognition accuracy each letters (sa, sya, and tsa) prespectivly 92.38%, 93.26% and 91.63%.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124986144","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285561
Sandy Kosasi, Vedyanto, I. Yuliani
The business success of Micro, Small, and Medium Enterprises (MSMEs) is determined by capital assets and capabilities to adopt innovation of social media technology to formulate digital marketing strategy improving organizational agility. The vastly developing content of social media becomes an opportunity ensuring more agile organizations in the accessibility of target markets. Problems of this research proposal are formulated (a) to propose a new research model on influences of innovation adoption of social media technology on digital marketing strategy in improving organizational agility of MSMEs and (b) to design hypothetical tests to cognize the influence of each latent variable. The research aims to identify and analyze to what extent digital marketing strategy can improve organizational agility of MSMEs in Pontianak, Indonesia. The combination of a convergent triangulation model and a follow-up, explanatory design is used. The sample including 55 MSMEs is determined by using Slovin Formula and a simple random sampling technique. 5 informants are selected at a sampling site by using a purposive sampling technique. The novelty of this research is on influences of antecedent variables aiming to improve organizational agility of businesses of MSMEs digitally.
{"title":"Improving organizational agility of micro, small, and medium enterprises through digital marketing strategy","authors":"Sandy Kosasi, Vedyanto, I. Yuliani","doi":"10.1109/ICITISEE.2017.8285561","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285561","url":null,"abstract":"The business success of Micro, Small, and Medium Enterprises (MSMEs) is determined by capital assets and capabilities to adopt innovation of social media technology to formulate digital marketing strategy improving organizational agility. The vastly developing content of social media becomes an opportunity ensuring more agile organizations in the accessibility of target markets. Problems of this research proposal are formulated (a) to propose a new research model on influences of innovation adoption of social media technology on digital marketing strategy in improving organizational agility of MSMEs and (b) to design hypothetical tests to cognize the influence of each latent variable. The research aims to identify and analyze to what extent digital marketing strategy can improve organizational agility of MSMEs in Pontianak, Indonesia. The combination of a convergent triangulation model and a follow-up, explanatory design is used. The sample including 55 MSMEs is determined by using Slovin Formula and a simple random sampling technique. 5 informants are selected at a sampling site by using a purposive sampling technique. The novelty of this research is on influences of antecedent variables aiming to improve organizational agility of businesses of MSMEs digitally.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123175158","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}
Pub Date : 2017-11-01DOI: 10.1109/ICITISEE.2017.8285551
S. Yusoh, Sureena Matayong
This paper aims to evaluate usability factors of online satisfaction survey system for public healthcare service. The evaluation was performed to analyze issues of usability factors, which is relevant to user interface design by applying Analysis Hierarchy Process (AHP) to prioritize their level of challenges. The study focuses on 10 Jakob Nielsen's heuristics principles as main usability factors. Based on main factors, 43 sub-factors are determined. Relevant data was collected through questionnaires by surveying 24 persons, including programmers, system analyst, students, lecturers, and general users. Next, researchers calculated values of data by using Expert Choice. The result shows the first 5 levels of usability factors that are challenges in a form of percentage rate respectively. The factors of recognition rather than recall (81%); help users recognize, diagnose, and recover from errors (78%); match between system and real world (77%); user control and freedom (76%) and consistency and standards (74%). The challenge rate of all usability factors reveal 72% while non-challenge rate is only 28%. From the result of this study we can conclude that existing online applications of satisfaction survey system for public healthcare service need to be improved. The improvement can be taken by prioritizing the usability factors based on level of challenges that found in this study.
{"title":"Heuristic evaluation of online satisfaction survey system for public healthcare service: Applying analytical hierarchical process","authors":"S. Yusoh, Sureena Matayong","doi":"10.1109/ICITISEE.2017.8285551","DOIUrl":"https://doi.org/10.1109/ICITISEE.2017.8285551","url":null,"abstract":"This paper aims to evaluate usability factors of online satisfaction survey system for public healthcare service. The evaluation was performed to analyze issues of usability factors, which is relevant to user interface design by applying Analysis Hierarchy Process (AHP) to prioritize their level of challenges. The study focuses on 10 Jakob Nielsen's heuristics principles as main usability factors. Based on main factors, 43 sub-factors are determined. Relevant data was collected through questionnaires by surveying 24 persons, including programmers, system analyst, students, lecturers, and general users. Next, researchers calculated values of data by using Expert Choice. The result shows the first 5 levels of usability factors that are challenges in a form of percentage rate respectively. The factors of recognition rather than recall (81%); help users recognize, diagnose, and recover from errors (78%); match between system and real world (77%); user control and freedom (76%) and consistency and standards (74%). The challenge rate of all usability factors reveal 72% while non-challenge rate is only 28%. From the result of this study we can conclude that existing online applications of satisfaction survey system for public healthcare service need to be improved. The improvement can be taken by prioritizing the usability factors based on level of challenges that found in this study.","PeriodicalId":130873,"journal":{"name":"2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125526233","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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