Data Prosiding - Tahun 2023
Menampilkan 120 dari 128 dataKlik pada judul artikel untuk melihat detail data
Implementation Of The Visual Identity Of Gandrung Dance In Branding Activities, Banyuwangi Regency, East Java, Indonesia
Author
Abstrak
-
Nama Prosiding
-
Volume 0 Nomor -
URL
-
DOI
-
A Discourse Analysis Of Interpersonal Metafunction In Vladimir Putin’s Speech Regarding Russia’s Invasion Of Ukraine
Author
Muhammad Rayhan Bustam, S.S., M.Hum.
Abstrak
-
Nama Prosiding
-
Volume 0 Nomor -
URL
DOI
-
Enhancing Aspect Detection Using Blstm And Random Oversampling In Marketplace Application Review
Author
Nelly Indriani Widiastuti, M.T. Kania Evita Dewi, S.Pd., M.Si
Abstrak
-
Nama Prosiding
-
Volume 0 Nomor -
URL
-
DOI
-
Geographic Information System For Situ Gunung Tourism With An Android-Based Design
Author
Prof. Dr. Lia Warlina, M.Si, Ir
Abstrak
-
Nama Prosiding
-
Volume 0 Nomor -
URL
-
DOI
-
Forest Fire Detection System Using Wireless Sensor Network
Author
Sri Nurhayati, MT Susmini Indriani Lestariningati, S.T, M.T
Abstrak
-
Nama Prosiding
-
Volume 0 Nomor -
URL
-
DOI
-
New Approach Of Covid-19 Prevention By Implemented Combination Of Decision Support System Algorithm
Author
Dr. Yeffry Handoko Putra, S.T, M.T Prof. Dr. Ir. H. Eddy Soeryanto Soegoto, MT Assoc. Prof. Dr. Rahma Wahdiniwaty, Dra.,M.Si.
Abstrak
Indonesia and Malaysia from 2020 to 2021 were exposed to COVID-19 pandemic. Both countries implemented a policy of restricting entry areas based on almost the same criteria, In Indonesia namely as PPKM which applying some level of exposure to those infected with covid-19. The determination of this level was all based on the growth in numbers exposed to covid-19, but on pandemic cases, the number of people who do not suffer from COVID-19 disease but have the same symptoms as the symptoms of COVID-19 also need to be considered as the pandemic agent to their environment. We named it as Precaution Covid-19 Pandemic (PCP) Level. The current level of the COVID-19 pandemic has not been fully determined by this idea. So, the idea of this research is to determine the pre-pandemic or precaution level of covid-19 in an area interfere by surrounding area. PCP level was not based on the growth of those infected with the covid-19 disease, but influenced by the number of patients whose have the symptoms similar to the dominant symptoms of the covid-19. The PCP Level determination can be used for precaution policy and support the previous Level Pandemic Methods. To accomplish this idea, three algorithms are used, they are K-Mean algorithm as a pattern clustering and the AHP algorithm as a level determination of the Covid-19 pandemic, While the relationship of candidate symptom pairs to Covid-19 transmission is carried out using the Naïve Bayes algorithm. The results of this study show that the combination of the three proposed algorithms provides and using data symptoms closely to dominant covid-19 symptoms can give an alternative for precaution level of covid-19 pandemic. The model for determining Covid-19 transmission based on four candidate symptoms has 89% precision and 85% accuracy.
Nama Prosiding
Seventh International Conference on Informatics and Computing (ICIC)
Volume 7 Nomor 1
URL
https://ieeexplore.ieee.org/abstract/document/10006989
DOI
Measurement Of Maturity Model Using The Service Operation Of Siakba In Itil V3 At Kpu
Author
Irfan Dwiguna Sumitra, S.Kom., M.Kom. Ph.D
Abstrak
The General Election Commission (KPU) is utilizing the advancing information technology (IT) to construct an Information System for KPU and the Ad hoc Board members known as SIAKBA. This IT system is progressively becoming more sophisticated as it undergoes further development. This study aims to assess the maturity model of the information system developed by the KPU and the Ad hoc Agency, employing the ITIL framework and adopting a Service Operation methodology. This study employs pertinent facts and information to assess the maturity of the information system. The research methodology employed in this study encompasses the utilization of questionnaires administered to relevant stakeholders, employing the RACI framework, as well as quantitative analysis to assess practices and procedures within the respective domain. Moreover, many metrics are utilized to assess performance within the KPU and Ad hoc Agency information systems. These metrics include incident resolution time, problem management effectiveness, change success rate, and service availability. The findings from the study on the KPU Information System and the ad hoc agency indicate a maturity level of 2.36, explicitly corresponding to level 2 as per the repeating table. Hence, it is imperative to conduct additional identification processes for the KPU to enhance its operational capabilities and deliver high-quality IT services.
Nama Prosiding
Informatics Engineering, Science & Technology (INCITEST)
Volume 1 Nomor 1
URL
https://ieeexplore.ieee.org/document/10396859
DOI
-
Smart Farming Based Low-Cost And Energy Efficient On Wireless Sensor Networks
Author
Irfan Dwiguna Sumitra, S.Kom., M.Kom. Ph.D
Abstrak
The plant maintenance system includes watering, fertilizing, and applying pesticides, whereas the system is able to determine the output according to the input parameters that have been prepared. A system created in this study is a wireless sensor network-based low-cost and efficient energy sensors that can assist farmers in managing and monitoring chili plants from planting seeds until they are ready to harvest. The tool uses spray-type sprinkler water to control output more efficiently. The system to be built is expected to provide accurate watering orders according to plant needs, where input parameters are obtained from a capacitive soil moisture sensor, temperature sensor, humidity sensor, and GPS to determine the precise location and OLED screens to display real-time information. The system aims to make plants grow healthy and produce quality vegetables. The WSN board used as a microcontroller is an ESP8266. The board has the ability to transmit data in real-time. This study involved collecting data from several sensors to enable farmers to monitor chili gardens' status effectively.
Nama Prosiding
Informatics Engineering, Science & Technology (INCITEST)
Volume 1 Nomor 1
URL
https://ieeexplore.ieee.org/document/10396946
DOI
-
The Implementation Of Supervised Learning Recommender System To Enhance Reading Interest Of Visitors In Regional Libraries
Author
Irfan Dwiguna Sumitra, S.Kom., M.Kom. Ph.D
Abstrak
In the era of digitization, regional libraries face challenges in sustaining the reading interest of their visitors. One solution that could be implemented to enhance the reading interest of visitors in regional libraries is by applying the supervised learning recommender system method based on the profiling of previous book borrowers. This study aims to implement this method on the borrowing history of books by visitors to regional libraries in order to recommend books that align with their reading interests, thereby increasing the number of borrowed books, facilitating visitors in finding the books they need, and providing the best service such as user experience to the visitors. The method used in this research is item-based collaborative filtering with the K-Nearest Neighbor (K-NN) algorithm and cosine similarity distance to find similar book titles based on the titles previously borrowed by book borrowers. The visitor’s borrowing history data in this study consists of Bibliographic Data from book borrowers in 2022 at regional libraries. The data underwent preprocessing to enhance accuracy, resulting in quantitative data comprising attributes such as borrower ID, book ID, and result. The model evaluation method used a confusion matrix on the training data compared to the testing data to determine the accuracy, precision, recall, and f-measure values generated by the created K-Nearest Neighbor (K-NN) model. The result of this study is a recommender system model that shows the top 10 book titles based on the borrowing history of previous book titles entered by the visitor. The performance measurements of the recommendation model yield the following results: the model’s accuracy stands at 68.53%, signifying its ability to accurately classify all samples. Precision is recorded at 99.79%, indicating that the model tends to have minimal false positives (FP). The recall rate is 68.61%, suggesting that the model excels at detecting positive samples compared to negative ones. The F-measure registers at 81.32%, showcasing a fairly effective trade-off between precision and recall. The implementation of this model can be used as a reference for regional libraries in providing book recommendations favored by visitors and assisting visitors in selecting books aligned with their interests based on the profiling of previous borrowers, thus increasing the number of books borrowed.
Nama Prosiding
International Conference of Signal Processing and Intelligent Systems (ICSPIS)
Volume 1 Nomor 1
URL
https://ieeexplore.ieee.org/document/10402673
DOI
-
Integration Of Wireless Sensor Network And Iot For Enhanced Broiler Closed-House Monitoring: A Case Study At Broiler Teaching Farm
Author
Irfan Dwiguna Sumitra, S.Kom., M.Kom. Ph.D
Abstrak
The monitoring system is an essential component for broiler closed-house farmers. This design aims to implement an efficient monitoring system using Wireless Sensor Network (WSN) technology and the Internet of Things (IoT). This system system enhances chicken coop monitoring and supports online learning at Broiler Teaching Farm. It comprises six sensor nodes and one controller node (gateway). Each sensor node is equipped with a DHT22 sensor for temperature and humidity, an MQ-135 sensor for NH3 gas concentration, and anemometers for wind speed monitoring. Communication between nodes is facilitated by NRF24L01 modules, with the primary node employing an ESP32 and each sensor node using an ATmega328P. The data collected, including temperature, humidity, NH3 gas levels, and wind speed, is wirelessly transmitted to the controller node via the WSN. The controller node then forwards this data to a web-based service using the HTTP protocol. The information is presented in a user-friendly, real-time web platform, offering valuable insights. Moreover, the system can maintain weekly performance records and coop administration records. Furthermore, this implementation represents a significant contribution to the field of animal farming and serves as a foundation for future research and development of livestock monitoring systems. The system offers operators real-time data for prompt decisions on the chicken coop’s status. It’s integrated with an online poultry farming course at Broiler Teaching Farm, allowing students to gain insights into the latest technology in broiler chicken farming. This integration should improve broiler closed-house monitoring, enhancing education quality and environmental management for students and instructors.
Nama Prosiding
International Conference of Signal Processing and Intelligent Systems (ICSPIS)
Volume 1 Nomor 1
URL
https://ieeexplore.ieee.org/document/10402746
DOI
-