A. Pramono, M. A. Febriantono, I. Agustina, Ida Bagus Ananta Wijaya, Tiara Ika Widia Primadani, S. Budiman
{"title":"Manufacturing a Smart Locker Security System for Public Spaces using E-KTP as a Primary Access","authors":"A. Pramono, M. A. Febriantono, I. Agustina, Ida Bagus Ananta Wijaya, Tiara Ika Widia Primadani, S. Budiman","doi":"10.1109/ICISS55894.2022.9915146","DOIUrl":"https://doi.org/10.1109/ICISS55894.2022.9915146","url":null,"abstract":"Everyone requires protection of belongings, especially security in public spaces such as locker rooms. Several locations in public areas keep hiring conventional security systems based on keys and padlocks, while others provide merely keyless lockers guarded by personnel. As a result, the user must ensure that the goods deposited with the locker storage officer are adequately secured. Numerous technologies have been used in conventional security systems, ranging from the difficult-to-imitate shape of keys and padlocks to the use of a padlock combination of numbers. The security system for storage places is also a purpose of information technology. This research aims to provide information on security systems in public spaces, especially shared access lockers. This project employs an experimental approach to create a prototype in the form of a smart locker that incorporates information technology. The lockers were constructed utilising plywood with an HPL finish on the exterior and PVC sheets on the interior. The dimensions of the locker were determined using the standard sizes of small and large luggage. Additionally, the approach to materials is addressed to minimise production waste. This research employs RFID technology that runs on the Arduino Nano to supplement the locker security system. Numerous RFID cards, including E-Toll cards and E-KTP, have been tested as the principal access method for opening and closing the smart locker's door.","PeriodicalId":125054,"journal":{"name":"2022 International Conference on ICT for Smart Society (ICISS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125260275","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}
{"title":"Evaluation Host-to-Host Data Integration Implementation Project Case Study: PT Jasa Raharja","authors":"Dwi Ria Nugraha, A. Hidayanto, T. Raharjo","doi":"10.1109/ICISS55894.2022.9915134","DOIUrl":"https://doi.org/10.1109/ICISS55894.2022.9915134","url":null,"abstract":"One of the most important business needs is centralized data; data that has been centralized will add value and increase efficiency for the company. To create a centralized data system, data integration between information sources is required. Data integration, on the other hand, is not cheap and takes time to implement. As a result, data integration in a company must have a significant impact on the company by adding value in terms of operational convenience or business requirements. This research use methode Qualitative analysis, data were gathered through case studies and semi-structured and phased interviews with representatives from a variety of stakeholders, The results of the evaluation of the data integration project at PT. Jasa Raharja, which has several obstacles and solutions that have been implemented and proven successful, as well as the impact on the company's operational activities, corporate image, and benefits for the management of PT. Jasa Raharja, are presented in this research.","PeriodicalId":125054,"journal":{"name":"2022 International Conference on ICT for Smart Society (ICISS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125632185","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}
{"title":"Effect of Overall Brand Equity and Perceived Value on The Purchase Intention of Smart Home Appliances in Indonesia","authors":"L. Sanny, Audrey Halim, Ivana Wijaya","doi":"10.1109/ICISS55894.2022.9915054","DOIUrl":"https://doi.org/10.1109/ICISS55894.2022.9915054","url":null,"abstract":"The primary purpose of smart home appliances is to improve the quality of life and comfort at home. Smart home appliance users are not just looking for functional value, but the product brand is also one of the considerations. The aims of this research to analyze impact of brand equity of smart home appliances and perceived value of the product on the purchase intention of smart home appliances specially in Indonesia. This study is done by conducting a cross-sectional survey of 430 users of smart home appliances in Indonesia. This research can help company to know the business opportunity for smart home appliances in Indonesia. Based on the research results, overall brand equity, perceived value of smart home appliance, and also brand preference of the smart home product have a significant and positive effect on purchase intention. Data processing results in this research show that the overall brand equity variable has the most significant influence from other variables. Therefore, the smart home appliance industry increases the Overall Brand Equity for smart home appliances products. However, the smart home appliances industry still needs to pay attention to the Perceived Value and product brand preference factors, which still encourage purchase intentions.","PeriodicalId":125054,"journal":{"name":"2022 International Conference on ICT for Smart Society (ICISS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127415655","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}
Afdhal Afdhal, N. Nasaruddin, Z. Fuadi, S. Sugiarto, Hammam Riza, Khairun Saddami
{"title":"Evaluation of Benchmarking Pre-Trained CNN Model for Autonomous Vehicles Object Detection in Mixed Traffic","authors":"Afdhal Afdhal, N. Nasaruddin, Z. Fuadi, S. Sugiarto, Hammam Riza, Khairun Saddami","doi":"10.1109/ICISS55894.2022.9915248","DOIUrl":"https://doi.org/10.1109/ICISS55894.2022.9915248","url":null,"abstract":"In the next few years, the new generation of Autonomous Vehicles (AVs) promises an advanced level of self-driving experiences. One of the most challenging topics in AVs development is the readiness of object detection models in complex urban environments. Mixed traffic is a complex urban environment that contains much uncertainty and is composed of heterogeneous objects. Therefore, this paper evaluates benchmarking the pre-trained CNN model for object detection in a mixed traffic environment. The evaluation is conducted for five modern algorithms and architecture of neural networks, including Faster RCNN, SSD, YOLOv3, YOLOv4, and EfficientDet. Then, we provide a new dataset in the mixed traffic environment under night conditions for more accurate object detection. Moreover, we conduct the simulation by considering the performance parameters that are recall, precision, and F measure. The performance of our dataset is also compared to the MS-COCO dataset. The result shows that the average precision value of Faster RCNN, SSD, YOLOv3, YOLOv4, and EfficientDet is 16.70%, 8.90%, 19.67%, 43.90%, and 55.56% respectively. It shows that YOLOv4 and EfficientDet provide better object detection accuracy than other CNN models.","PeriodicalId":125054,"journal":{"name":"2022 International Conference on ICT for Smart Society (ICISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121723476","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}