JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)最新文献

MACHINE LEARNING FOR PREDICTING SPREAD OF COVID-19 IN INDONESIA 用机器学习预测科维-19 在印度尼西亚的传播

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-05-07 DOI: 10.33480/jitk.v9i2.5174

Nur Hayati, Eri Mardiani, Fauziah Fauziah, Toto Haryanto, Viktor Vekky Ronald Repi

{"title":"MACHINE LEARNING FOR PREDICTING SPREAD OF COVID-19 IN INDONESIA","authors":"Nur Hayati, Eri Mardiani, Fauziah Fauziah, Toto Haryanto, Viktor Vekky Ronald Repi","doi":"10.33480/jitk.v9i2.5174","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.5174","url":null,"abstract":"In previous research, we carried out an analysis using the FBProphet model to predict the COVID-19 outbreak in Indonesia. The application of the FBProphet model to time series data is considered quite good because it produces a MAPE of 22.60% with a linear distribution. Additionally, based on the pattern in the previous dataset and the total number of active cases currently stands at 2,606, in this research we tried to use the Linear Regression (LR) model as a comparison with the FBProphet model by using additional data from the same data source, KAWALCOVID19 website. Data collection started from March 2, 2020 to December 19, 2021. The aim of this research is the same as previous research, namely predicting the spread of COVID-19. The analysis process is carried out by preprocessing the data by validating missing data and validating the format of the data variables. Then carry out descriptive analysis and data visualization so that it can be seen that in this 657 data there is a fluctuates data that non-periodically from July to August 2021. Next, model analysis is carried out using FBProphet and LR and validating the results of each model. The research results are in the form of evaluation metrics where the LR model gets better RMSE, MAE and MAPE values compared to FBProphet, namely 292.91; 178, 81 and 12.79%.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"22 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141005960","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

WEB-BASED INFORMATION SYSTEM PREDICTION OF VEHICLE THEFT VULNERABILITY IN JAYAPURA USING REGRESSION ANALYSIS 基于网络的信息系统利用回归分析预测贾亚普拉车辆失窃的可能性

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-29 DOI: 10.33480/jitk.v9i2.4194

F. Y. Wattimena, Johan Minggus Loly, Halomoan Edy Manurung

{"title":"WEB-BASED INFORMATION SYSTEM PREDICTION OF VEHICLE THEFT VULNERABILITY IN JAYAPURA USING REGRESSION ANALYSIS","authors":"F. Y. Wattimena, Johan Minggus Loly, Halomoan Edy Manurung","doi":"10.33480/jitk.v9i2.4194","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.4194","url":null,"abstract":"Vehicle theft in Jayapura Regency is quite high and there is no application to assist the police in making estimates or predictions of the number of theft cases that will occur in the next year. In 2022, cases of theft in Jayapura district will start to increase. to make these predictions the authors designed and built a system that can predict the number of these cases in building this application the authors use the Regression Analysis method this process can help the police predict the number of cases in the coming year. The development method used is SDLC, linear regression analysis and using the PHP programming language, the database uses MYSQL, Sublime Text. This research was conducted because there was no system that could assist the staff of the Resort Police (Polres) of Jayapura Regency. From this research, a system for predicting the level of vulnerability to motorized vehicle theft has been successfully built at the Jayapura District Police with data processed for attendance data using face region, reporting data using barcodes, queue data using counters and digital archive data helping the police store important documents.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"3 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140412482","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

OPTIMIZATION OF LIVESTOCK MONITORING SYSTEM IN OUTDOOR BASED ON INTERNET OF THINGS (IOT) 基于物联网（IOT）的户外牲畜监测系统优化

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-29 DOI: 10.33480/jitk.v9i2.5312

Andi Chairunnas, Agung Prahujana Putra

{"title":"OPTIMIZATION OF LIVESTOCK MONITORING SYSTEM IN OUTDOOR BASED ON INTERNET OF THINGS (IOT)","authors":"Andi Chairunnas, Agung Prahujana Putra","doi":"10.33480/jitk.v9i2.5312","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.5312","url":null,"abstract":"Livestock businesses are often underestimated by the public because they are associated with less hygienic working environments. However, the demand for livestock products such as meat and milk is increasing, providing significant business opportunities. Several obstacles, such as livestock loss and the capital required for cage construction, are barriers to starting a livestock business. Livestock losses, especially in outdoor farms, often occur because of the lack of proper monitoring and data collection. Therefore, technology is required to overcome this problem. The application of IoT technology is an effective solution for overcoming this problem. By utilizing sensors, such as GPS, temperature, and heart rate, farmers can monitor farm animals remotely using Android applications. In this study, a U-blox Neo6m GPS sensor was used to track the location of farm animals, a temperature sensor was used to monitor the temperature conditions of farm animals, and a heart rate sensor was used to determine the health of farm animals that had been tested. The use of a 1500 mAh LI-ION LITHIUM battery as a power source proved to be sufficient for 7 h. The results showed that this IoT-based Outdoor Livestock Monitoring System can provide information on the last location of livestock as well as real-time heart rate and temperature data in the database. This innovation opens opportunities for farmers to improve livestock management and monitoring efficiently, minimize losses, and increase the productivity of their livestock business","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"27 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140411854","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

HERBAL LEAF CLASSIFICATION USING DEEP LEARNING MODEL EFFICIENTNETV2B0 利用深度学习模型进行草本植物叶片分类 efficientnetv2b0

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-29 DOI: 10.33480/jitk.v9i2.5119

Rakha Pradana Susilo Putra, Christian Sri Kusuma Aditya, G. Wicaksono

引用次数: 0

E-GOVERNMENT MATURITY ANALYSIS USING THE LAYNE AND LEE, HILLER AND BELANGER, AND SPBE MODELS 利用 layne 和 lee 模型、hiller 和 belanger 模型以及 spbe 模型进行电子政务成熟度分析

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-28 DOI: 10.33480/jitk.v9i2.5110

Eltyasar Putrajati Noman, Andi Wahju Rahardjo Emanuel

{"title":"E-GOVERNMENT MATURITY ANALYSIS USING THE LAYNE AND LEE, HILLER AND BELANGER, AND SPBE MODELS","authors":"Eltyasar Putrajati Noman, Andi Wahju Rahardjo Emanuel","doi":"10.33480/jitk.v9i2.5110","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.5110","url":null,"abstract":"This research aims to analyze the level of e-government maturity in Kupang City using the Layne and Lee and Hiller and Belanger models and combine them with the SPBE model to provide a more comprehensive approach. The method used to develop an audit model involves a literature study to understand the e-government maturity model, identification of specific objectives for analysis of the Kupang City Population and Civil Registration Service (DUKCAPIL) website, determination of scope based on the SPBE model, determination of design audit criteria and benchmarks, collection and data synthesis from the Kupang City DUKCAPIL e-Government site, as well as analysis of audit findings, and using the GT Metrix tool for performance analysis and evaluation of the Kupang City DUKCAPIL website. The research results show that the lowest rating is F out of six, which indicates poor service performance. The Layne and Lee Model assessment gives a score of 18, indicating the technology's lack of integration and complexity. Hiller and Belanger's Model assessment gives a value of 13, indicating an immature level. These findings highlight significant gaps between the models evaluated. Recommendations based on research are to increase citizen participation by improving the Kupang City DUKCAPIL website based on a maturity model and the need for regular audits and ongoing evaluations to improve public services in Kupang City in e-government maturity. In conclusion, this research provides a new contribution to the field of e-government by highlighting the need for audits using several e-government maturity models to improve public services in Kupang City.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"8 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140418150","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

AN INNOVATIVE LEARNING ENVIRONMENT: G-MOOC 4D TO ENHANCE VISUAL IMPAIRMENTS LEARNING MOTIVATION 创新的学习环境：G-MOOC 4D增强视觉障碍者的学习动力

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-19 DOI: 10.33480/jitk.v9i2.5037

Rujianto Eko Saputro, Berlilana Berlilana, Wiga Maaulana Baihaqi, Sarmini Sarmini, Y. Purwati, F. S. Utomo

{"title":"AN INNOVATIVE LEARNING ENVIRONMENT: G-MOOC 4D TO ENHANCE VISUAL IMPAIRMENTS LEARNING MOTIVATION","authors":"Rujianto Eko Saputro, Berlilana Berlilana, Wiga Maaulana Baihaqi, Sarmini Sarmini, Y. Purwati, F. S. Utomo","doi":"10.33480/jitk.v9i2.5037","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.5037","url":null,"abstract":"The proliferation of visual impairment among school-age children in Indonesia has prompted the need for specialized online learning solutions. The G-MOOC 4D platform, a novel Learning Management System (LMS), is designed to address this need by leveraging gamification and artificial intelligence to enhance accessibility for visually impaired users. This study reports on the development and testing of two AI models within the G-MOOC 4D framework: a facial recognition model for secure user authentication and a voice command model for interactive learning. User Acceptance Testing (UAT), conducted with expert users, namely teachers at a special needs school, showed high approval rates for the platform's features. The results show that all metrics, accuracy, precision, and recall reach their optimal values at a distance of 40 cm for face detection. The respective metric scores at that distance, precision: 100%, accuracy: 98%, and recall: 97%. Additionally, the voice command functionality tested achieved a 100% recognition rate, reflecting the platform’s potential to significantly ease the learning process for visually impaired students. The findings underscore the importance of integrating assistive technologies into educational platforms to ensure all students have equal access to learning opportunities.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"137 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140451869","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

IMPROVING TRAFFIC DENSITY PREDICTION USING LSTM WITH PARAMETRIC ReLU (PReLU) ACTIVATION 利用带有参数再路（PReLU）激活功能的 LSTM 改进交通密度预测

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-01 DOI: 10.33480/jitk.v9i2.5046

Nur Alamsyah, Titan Parama Yoga, Budiman Budiman

引用次数: 0

DEEP LEARNING FOR POLYCYSTIC OVARIAN SYNDROME CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK 利用卷积神经网络进行多囊卵巢综合征分类的深度学习

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2024-02-01 DOI: 10.33480/jitk.v9i2.4575

Odi Nurdiawan, Heliyanti Susana, Ahmad Faqih

{"title":"DEEP LEARNING FOR POLYCYSTIC OVARIAN SYNDROME CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK","authors":"Odi Nurdiawan, Heliyanti Susana, Ahmad Faqih","doi":"10.33480/jitk.v9i2.4575","DOIUrl":"https://doi.org/10.33480/jitk.v9i2.4575","url":null,"abstract":"Polycystic Ovarian Syndrome (PCOS) is the main cause of infertility in women. This condition results in abnormal hormone levels. Women who experience this syndrome will have irregular hormone levels and experience irregular menstrual cycles as well, thereby affecting the reproductive system. Symptoms that arise as a result of the increase in these hormones can be seen from the growth of hair on the legs, weight gain which results in not being ideal, irregular menstruation, unusual acne growth, and oily skin. The problem of Polycystic Ovarian Syndrome can cause disturbances in ovulation and cause infertility in women. Urgency This research requires a classification that has good accuracy in diagnosing early to minimize the rate of pregnancy failure. The aim of the research is to be able to model early detection of Polycystic Ovarian Syndrome with high accuracy so that it can help the health team in detecting Polycystic Ovarian Syndrome or not having Polycystic Ovarian Syndrome. The research stage has 3 stages including the first stage of identifying problems and collecting datasets from Telkom University dataverse in the form of images and literature reviews of various sources. The second stage is Pre Processing of image data, Data Training, modeling design by managing image data and classifying using the Convolutional Neural Network Algorithm deep learning model and testing. The third stage is evaluating the test results and discussing the results of accuracy in determining the status of Normal Polycystic Ovarian Syndrome or PCOS. The results of training and validation on the ovarian xray image dataset using the CNN architecture that has been made, 40 iterations (epochs), and 4 step_per_epochs show an accuracy value of 0.8947 or 89.47% and a loss value of 0.2684.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"51 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139686852","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

SKYLINE QUERY BASED ON USER PREFERENCES IN CELLULAR ENVIRONMENTS 基于蜂窝环境中用户偏好的Skyline查询

JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Pub Date : 2023-08-31 DOI: 10.33480/jitk.v9i1.4192

Ruhul Amin, Taufik Djatna, Annisa Annisa, Imas Sukaesih Sitanggang

{"title":"SKYLINE QUERY BASED ON USER PREFERENCES IN CELLULAR ENVIRONMENTS","authors":"Ruhul Amin, Taufik Djatna, Annisa Annisa, Imas Sukaesih Sitanggang","doi":"10.33480/jitk.v9i1.4192","DOIUrl":"https://doi.org/10.33480/jitk.v9i1.4192","url":null,"abstract":"The recommendation system is an important tool for providing personalized suggestions to users about products or services. However, previous research on individual recommendation systems using skyline queries has not considered the dynamic personal preferences of users. Therefore, this study aims to develop an individual recommendation model based on the current individual preferences and user location in a mobile environment. We propose an RFM (Recency, Frequency, Monetary) score-based algorithm to predict the current individual preferences of users. This research utilizes the skyline query method to recommend local cuisine that aligns with the individual preferences of users. The attributes used in selecting suitable local cuisine include individual preferences, price, and distance between the user and the local cuisine seller. The proposed algorithm has been implemented in the JALITA mobile-based Indonesian local cuisine recommendation system. The results effectively recommend local cuisine that matches the dynamic individual preferences and location of users. Based on the implementation results, individual recommendations are provided to mobile users anytime and anywhere they are located. In this study, three skyline objects are generated: soto betawi (C5), Mie Aceh Daging Goreng (C4), and Gado-gado betawi (C3), which are recommended local cuisine based on the current individual preferences (U1) and user location (L1). The implementation results are exemplified for one user located at (U1L1), providing recommendations for soto betawi (C5) with an individual preference score of 0.96, Mie Aceh Daging Goreng (C4) with an individual preference score of 0.93, and Gado-gado betawi (C3) with an individual preference score of 0.98. Thus, this research contributes to the field of individual recommendation systems by considering the dynamic user location and preferences.","PeriodicalId":475197,"journal":{"name":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135991416","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