2019 7th International Conference on Information and Communication Technology (ICoICT)最新文献

Price Prediction of Chili in Bandung Regency Using Support Vector Machine (SVM) Optimized with an Adaptive Neuro-Fuzzy Inference System (ANFIS) 基于自适应神经模糊推理系统(ANFIS)优化支持向量机(SVM)的万隆县辣椒价格预测

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-11-26 DOI: 10.1109/ICoICT.2019.8835367

Asma Hasifa Nurcahyono, F. Nhita, D. Saepudin, A. Aditsania

{"title":"Price Prediction of Chili in Bandung Regency Using Support Vector Machine (SVM) Optimized with an Adaptive Neuro-Fuzzy Inference System (ANFIS)","authors":"Asma Hasifa Nurcahyono, F. Nhita, D. Saepudin, A. Aditsania","doi":"10.1109/ICoICT.2019.8835367","DOIUrl":"https://doi.org/10.1109/ICoICT.2019.8835367","url":null,"abstract":"The price fluctuation of chili is one of the economic problems faced by every chili-producing country in the world, including in Indonesia. Chili is a vegetable that is consumed almost every day by the people of Indonesia. In Bandung district area, chili has been experiencing price fluctuations in the last four years, according to data obtained from the Bandung Regency Area Trade and Industry Service. Many factors cause the price of chili to fluctuate—one of them being the weather. This is because chili is a plant that is easily damaged if exposed to too much water. This research predicts chili prices in Bandung Regency using the Support Vector Machine (SVM) algorithm, which is optimized by an Adaptive Neuro-Fuzzy Inference System (ANFIS) and based on weather factors. The average accuracy of training and testing data was 94.07%; the training and testing data using the SVM algorithm produced 89.90% average accuracy and the average accuracy of training and testing data using the ANFIS algorithm was 92.68%.","PeriodicalId":439440,"journal":{"name":"2019 7th International Conference on Information and Communication Technology (ICoICT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122425938","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: 2

Rainfall Forecasting using the Classification and Regression Tree (CART) Algorithm and Adaptive Synthetic Sampling (Study Case: Bandung Regency) 基于分类回归树(CART)算法和自适应综合抽样的降雨预报(以万隆县为例)

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-11-26 DOI: 10.1109/ICoICT.2019.8835308

Siti Nur Lathifah, F. Nhita, A. Aditsania, D. Saepudin

引用次数: 9

C5.0 Algorithm and Synthetic Minority Oversampling Technique (SMOTE) for Rainfall Forecasting in Bandung Regency 万隆县降雨预报的C5.0算法与合成少数派过采样技术(SMOTE

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-10-18 DOI: 10.1109/ICoICT.2019.8835324

Erwin Kurniawan, F. Nhita, A. Aditsania, D. Saepudin

引用次数: 8

Clustering Synonym Sets in English WordNet 英语WordNet中同义词集的聚类

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-10-18 DOI: 10.1109/ICoICT.2019.8835313

Jentrisi Priyatno, M. Bijaksana

引用次数: 4

Generating Image Description on Indonesian Language using Convolutional Neural Network and Gated Recurrent Unit 用卷积神经网络和门控循环单元生成印尼语图像描述

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-09-04 DOI: 10.1109/ICoICT.2019.8835370

A. A. Nugraha, A. Arifianto, Suyanto

引用次数: 28

Forecasting Portfolio Optimization using Artificial Neural Network and Genetic Algorithm 基于人工神经网络和遗传算法的投资组合预测优化

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-07-24 DOI: 10.1109/ICoICT.2019.8835344

Mohammad Maholi Solin, A. Alamsyah, B. Rikumahu, Muhammad Apriandito Arya Saputra

{"title":"Forecasting Portfolio Optimization using Artificial Neural Network and Genetic Algorithm","authors":"Mohammad Maholi Solin, A. Alamsyah, B. Rikumahu, Muhammad Apriandito Arya Saputra","doi":"10.1109/ICoICT.2019.8835344","DOIUrl":"https://doi.org/10.1109/ICoICT.2019.8835344","url":null,"abstract":"Investment has an important role in the economic growth of a country. The higher investment value obtained by a country, the faster the country is able to develop their prosperity. However, the investor faces some obstacle in investment activity to have a reasonable return and acceptable risk. In stock investments area, investors could increase chance of getting higher returns by making predictions and diversifying by forming a stock portfolio. Previous studies have stated that Artificial Neural Network (ANN), which are one of the machine learning models inspired by the activity of human brain cells have more advantages to predict the stock future value in terms of speed, accuracy, and the amount of data that can be processed compared to other stock prediction models. Diversification is a method of dividing investment funds into different index stocks, with the aim of reducing the investment risk. With thousands of stocks in the market, deciding which portfolio should be chosen is difficult. This study extends the scope of several previous studies, which are only limited to perform predictions using ANN or GA without forming an optimal stock portfolio. The objective of this study is to predict future stock values using ANN, then form those optimal stock portfolios using GA with aims to get the best optimization of maximal return and minimal risk value. The results of this study show, the implementation of GA as an alternative to the Single Index Model (SIM) method show better optimization index.","PeriodicalId":439440,"journal":{"name":"2019 7th International Conference on Information and Communication Technology (ICoICT)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124826683","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: 6

Analyzing Tourism Mobile Applications Perceived Quality using Sentiment Analysis and Topic Modeling 基于情感分析和主题建模的旅游移动应用感知质量分析

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-07-24 DOI: 10.1109/ICoICT.2019.8835255

Riefvan Achmad Masrury, Fannisa, A. Alamsyah

{"title":"Analyzing Tourism Mobile Applications Perceived Quality using Sentiment Analysis and Topic Modeling","authors":"Riefvan Achmad Masrury, Fannisa, A. Alamsyah","doi":"10.1109/ICoICT.2019.8835255","DOIUrl":"https://doi.org/10.1109/ICoICT.2019.8835255","url":null,"abstract":"Mobile application is one of the most important information platforms for international tourists. Millions of tourists use mobile applications to find information and make transactions. Two popular Online Travel Agent (OTA) mobile applications for travel-related activities providers are Traveloka and Tiket.com. These applications certainly must meet travelers’ needs to achieve satisfaction. Such satisfaction related to application Mobile Application Service Quality (MappSql) dimensions can be traced from thousands of their comments on the Google Play Store. From a set of reviews, information about the perception of mobile application quality can be obtained. Knowledge on user perceptions is very useful for company’s consideration in creating effective business and app features to increase users’ satisfaction. We propose Text Mining models to bring up hidden information regarding users’ verdict. The selected text analysis methods for this research are Sentiment Analysis and Topic Modeling. We find that positive or negative sentiments towards MappSql dimensions of online travel agent applications qualities can be revealed using sentiment analysis method. Topic Modeling method is used to bring up groups of important words of topics related to each mobile application service quality dimensions.","PeriodicalId":439440,"journal":{"name":"2019 7th International Conference on Information and Communication Technology (ICoICT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124525379","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: 11

Smart Light Recommending System Using Artificial Neural Network Algorithm 基于人工神经网络算法的智能灯光推荐系统

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-07-24 DOI: 10.1109/ICoICT.2019.8835192

Muchammad Ferdian Akbar, Aji Gautama Putrada, M. Abdurohman

{"title":"Smart Light Recommending System Using Artificial Neural Network Algorithm","authors":"Muchammad Ferdian Akbar, Aji Gautama Putrada, M. Abdurohman","doi":"10.1109/ICoICT.2019.8835192","DOIUrl":"https://doi.org/10.1109/ICoICT.2019.8835192","url":null,"abstract":"This paper proposes smart light recommending system based on sleep monitoring data using Artificial Neural Network (ANN) algorithm. lights are one of the biggest contributors to the power consumption of electrical equipment. The effort to reduce the use of lights is related to not using them when they are not in use. One of the moments when the lights are not used is when we are sleeping but some user sleep styles keep the lights on even when they are sleeping so the idea is how to turn off the lights after the user sleeps. To realize this idea, it is necessary to detect sleep which can be derived from the detection of heart rate by certain sensors. The sensors that are needed are those already embedded in Fitbit, a bracelet-shaped device that can detect various kinds of conditions in the human body. However, Fitbit cannot directly provide the sleep condition to the user or the lamp, but it can provide information in the form of logs, so that the lamp settings cannot be instantaneous. To overcome this problem a learning method can be applied to know sleep patterns that appear in logs produced by Fitbit. This paper applies ANN back propagation to learn the sleep patterns of users, especially sleep start time and sleep end time. Nine ANN models made from user sleep data are applied to 60 days of testing. From these models, the best results were given by the model which gave 82.27% accuracy for sleep start time and 98.28% for sleep end time. Accuracy is largely determined by the user's sleep style.","PeriodicalId":439440,"journal":{"name":"2019 7th International Conference on Information and Communication Technology (ICoICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127881530","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

On the Capacity of Full-Duplex Diamond Relay Networks Using NOMA 基于NOMA的全双工菱形中继网络容量研究

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-07-24 DOI: 10.1109/ICoICT.2019.8835280

M. Uddin, Md. Fazlul Kader, S. Shin

引用次数: 2

Outage Analysis of NOMA Exploited Coordinated Direct and Relay assisted Uplink Transmission NOMA利用协调直、中继辅助上行传输的中断分析

2019 7th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2019-07-24 DOI: 10.1109/ICoICT.2019.8835317

Jae Oh Kim, Mohammed Belal Uddin, S. Shin

引用次数: 1