2020 8th International Conference on Information and Communication Technology (ICoICT)最新文献

Academic Expert Finding in Indonesia using Word Embedding and Document Embedding: A Case Study of Fasilkom UI 利用词嵌入和文档嵌入在印尼寻找学术专家:以Fasilkom用户界面为例

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166249

Theresia V. Rampisela, E. Yulianti

引用次数: 10

Micro-Climate Control for Hydroponics in Greenhouses 温室水培的小气候控制

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166237

B. Erfianto, A. Rakhmatsyah, Endro Ariyanto

{"title":"Micro-Climate Control for Hydroponics in Greenhouses","authors":"B. Erfianto, A. Rakhmatsyah, Endro Ariyanto","doi":"10.1109/ICoICT49345.2020.9166237","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166237","url":null,"abstract":"Greenhouse is a building which one of them functions for cultivation. Greenhouse can help the plant growth process, but there can be differences climate that affect plant growth. By knowing the distribution of temperature and humidity, it can help the cultivation process. The next problem is how to control greenhouse conditions or commonly called micro-climate so that temperature and humidity can be maintained. To solve these problems, a system is used to determine the temperature and humidity distribution in a greenhouse and generate it in the form of a two-dimensional distribution map in the form of heatmap so that users can know the spread of temperature and humidity through the image. Based on temperature and humidity data can be used to control the micro-climate in a greenhouse so that the temperature and humidity of the greenhouse are maintained according to the needs of the plant. This system is built using a sprinkler to reduce the temperature and increase the humidity in the greenhouse, where the micro-climate control uses Fuzzy logic controller. The main results of this experiment are the temperature and humidity of the greenhouse can be controlled according to the needs of the plant.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116169054","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}

引用次数: 4

Designing NB-IoT (Internet of Things) Network for Public IoT in Batam Island 巴淡岛公共物联网NB-IoT网络设计

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166321

Shelasih Winalisa, M. I. Nashiruddin

{"title":"Designing NB-IoT (Internet of Things) Network for Public IoT in Batam Island","authors":"Shelasih Winalisa, M. I. Nashiruddin","doi":"10.1109/ICoICT49345.2020.9166321","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166321","url":null,"abstract":"One of the most widely use of IoT network connectivity technologies is Narrow Band Internet of Things (NB-IoT). This technology has advantages, such as faster and simpler deployment using the existing cellular network, wide coverage area, low cost, ten years battery life, and supported by 3GPP global standard. However, it is scarce for scholars to explore the NB-IoT network for multiple use cases as public IoT. This research explored NB-IoT network planning and simulation for public IoT services in Batam Island, as the representative of the urban area and special economic zone in Indonesia. The NB-IoT network planning methods used network capacity and coverage planning analysis, meanwhile, the network deployment simulations were carried out using the Forsk Atol 3.2.2 software. It is found that to serve a public IoT network in Batam Island, 11 NB-IoT gateways are needed. The coverage prediction simulation results in the average of best signal level received is -54.4 dBm, and the Radio Signal Strength Indicator (RSSI) value at the receiver is -65.67 dBm. While the Signal to Noise Ratio (SNR) simulation generated the average SNR level of 11.19 dB. It indicates that the design of the network meets the requirements.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114061598","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}

引用次数: 3

Adaptive Attention Generation for Indonesian Image Captioning 印尼语图像字幕的自适应注意力生成

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166244

Made Raharja Surya Mahadi, A. Arifianto, Kurniawan Nur Ramadhani

{"title":"Adaptive Attention Generation for Indonesian Image Captioning","authors":"Made Raharja Surya Mahadi, A. Arifianto, Kurniawan Nur Ramadhani","doi":"10.1109/ICoICT49345.2020.9166244","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166244","url":null,"abstract":"Image captioning is one of the most widely discussed topic nowadays. However, most research in this area generate English caption while there are thousands of language exist around the world. With their language uniqueness, there’s a need of specific research to generate captions in those languages. Indonesia, as the largest Southeast Asian country, has its own language, which is Bahasa Indonesia. Bahasa Indonesia has been taught in various countries such as Vietnam, Australia, and Japan. In this research, we propose the attention-based image captioning model using ResNet101 as the encoder and LSTM with adaptive attention as the decoder for the Indonesian image captioning task. Adaptive attention used to decide when and at which region of the image should be attended to produce the next word. The model we used was trained with the MSCOCO and Flick30k datasets besides. Both datasets are translated manually into Bahasa by human and by using Google Translate. Our research resulted in 0.678, 0.512, 0.375, 0.274, and 0.990 for BLEU-1, BLEU-2, BLEU-3, BLEU-4, and CIDEr scores respectively. Our model also produces a similar score for the English image captioning model, which means our model capable of being equivalent to English image captioning. We also propose a new metric score by conducting a survey. The results state that 76.8% of our model’s caption results are better than validation data that has been translated using Google Translate.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"12 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114025939","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}

引用次数: 8

Implementation of Data Mining for Drop-Out Prediction using Random Forest Method 基于随机森林方法的辍学预测数据挖掘实现

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166276

Meylani Utari, B. Warsito, R. Kusumaningrum

{"title":"Implementation of Data Mining for Drop-Out Prediction using Random Forest Method","authors":"Meylani Utari, B. Warsito, R. Kusumaningrum","doi":"10.1109/ICoICT49345.2020.9166276","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166276","url":null,"abstract":"Accreditation is one of the quality measurements for a University. Some elements of these measurements are students and graduate students. Prevention of students to drop out is a problem that is considered very important for the university itself. High levels of drop out students will have a bad impact on the university, such as bad reputation or low-grade accreditation. This research presenting the results of a case study analysis in educational data, by analyzing the data using the data mining technique. The author using the classification method, that focuses on drop-out prediction of undergraduate and diploma students at the ABC Faculty at XYZ University. To predict drop-out classification, academic data are needed. The raw data are student’s academic data that enroll in university from 2008 to 2012. The raw data preprocessing then carried out to handle imbalanced data. This research uses synthetic minority oversampling technique (SMOTE) to handle imbalance dataset and random forest algorithm to predict drop-out within 2492 data. As a research result, the random forest algorithm accompanied by SMOTE can provide the best accuracy results by 93.43%. The main results of this research can be used to reduce drop-out levels by predicting potential drop out students and identifying potential factors related to drop out students.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134060646","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}

引用次数: 13

Analysis of Web Content Quality Information on the Koseeker Website Using the Web Content Audit Method and ParseHub Tools 利用Web内容审计方法和ParseHub工具分析Koseeker网站的Web内容质量信息

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166396

Deandra Abiantoro, D. S. Kusumo

{"title":"Analysis of Web Content Quality Information on the Koseeker Website Using the Web Content Audit Method and ParseHub Tools","authors":"Deandra Abiantoro, D. S. Kusumo","doi":"10.1109/ICoICT49345.2020.9166396","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166396","url":null,"abstract":"Content Quality is one of the most critical dimensions of Website Quality. There are seven indicators to check the quality of the content. Content that has low quality can be determined with these indicators. To facilitate quality checking of the website content, the authors used a content audit method. However, there are currently not many standards that can be used for content auditing. So in this study, the authors proposed to use the website auditing framework and combine it with content quality indicators. With these methods, the authors can assess content by following the indicators of content quality. Complete information about the website was needed to conduct an audit. The authors used web scraping using Parsehub to get all these data. In this research, the case taken for quality checking was Koseeker Website. After conducting the content audit in Koseeker, the results showed that Koseeker has a quality that was not yet maximum on three of seven indicators, namely, Timely, Relevant, and Authority. After doing the test, it can be seen that the proposed web content audit can assess the quality of Koseeker website content.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061505","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}

引用次数: 0

WSN Based Agricultural Bird Pest Control with Buzzer and a Mesh Network 基于蜂鸣器和网状网络的无线传感器网络农业鸟类病虫害防治

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166304

Achmad Ramadhan, M. Abdurohman, Aji Gautama Putrada

引用次数: 6

Melanoma Classification Using Combination of Color and Shape Feature 结合颜色和形状特征的黑色素瘤分类

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166300

Dimas Agusta Wiranata, Ema Rachmawati, D. Q. Utama

引用次数: 0

Sea Level Prediction by Using Seasonal Autoregressive Integrated Moving Average Model, Case Study in Semarang, Indonesia 基于季节自回归综合移动平均模式的海平面预测，以印尼三宝垄为例

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166423

Ronald Tulus, D. Adytia, N. Subasita, D. Tarwidi

{"title":"Sea Level Prediction by Using Seasonal Autoregressive Integrated Moving Average Model, Case Study in Semarang, Indonesia","authors":"Ronald Tulus, D. Adytia, N. Subasita, D. Tarwidi","doi":"10.1109/ICoICT49345.2020.9166423","DOIUrl":"https://doi.org/10.1109/ICoICT49345.2020.9166423","url":null,"abstract":"Sea level prediction system is an important tool for many coastal engineering applications, such as for designing of engineering structures in coastal or in offshore, routing of vessels, predicting and preventing flood in low land coastal areas, etc. One classical method to predict sea level is by using the Tidal Harmonic Analysis, in which the sea level is approximated by summation of tidal components. The method needs long historical time series data, and it cannot predict non-tidal component or sealevel anomaly. In this paper, we propose a sea level prediction by using the Autoregressive Integrated Moving Average (ARIMA) and the Seasonal Autoregressive Integrated Moving Average (SARIMA) to predict sea level. Here, we choose a study case in Tanjung Mas Harbour in Semarang, Indonesia. Several input combinations for the ARIMA and the SARIMA are investigated for finding the best fit parameters. Results of prediction by using both methods are compared with the classical Tidal Harmonic Analysis. The accuracy of each method is investigated by calculating the RMSE and R-squared value. Despite of the seasonal data that is used in this paper, the ARIMA method gives the best prediction.","PeriodicalId":113108,"journal":{"name":"2020 8th International Conference on Information and Communication Technology (ICoICT)","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133617835","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}

引用次数: 3

Analysis of Feature Correlation for Music Genre Classification 音乐体裁分类的特征相关性分析

2020 8th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2020-06-01 DOI: 10.1109/ICoICT49345.2020.9166333

Manuel Theodore Leleuly, P. H. Gunawan

引用次数: 1