Edutran Computer Science and Information Technology最新文献

Development of the Information System for the Studies Program Information Engineering at USN Papua 为巴布亚美国海军信息工程研究计划开发信息系统

Edutran Computer Science and Information Technology Pub Date : 2024-07-19 DOI: 10.59805/ecsit.v2i1.109

Fadil Rahman, Emy. L. Tatuhey

引用次数: 0

Organization Cooperative Mapping Information System-based GIS 基于地理信息系统的组织合作制图信息系统

Edutran Computer Science and Information Technology Pub Date : 2024-06-07 DOI: 10.59805/ecsit.v1i2.98

April Lia Hananto, Baenil Huda, Fitria Nurapriani, Tarmuji

引用次数: 0

Implementation Of Goal-Directed Design in the Development of the Jogja Tourist Travel Planning Website Application 在开发 Jogja 旅游规划网站应用程序中实施目标导向设计

Edutran Computer Science and Information Technology Pub Date : 2024-01-05 DOI: 10.59805/ecsit.v1i2.95

Danny Sebastian, Galen Riandito, I. Kadek, Dendy Senapartha

{"title":"Implementation Of Goal-Directed Design in the Development of the Jogja Tourist Travel Planning Website Application","authors":"Danny Sebastian, Galen Riandito, I. Kadek, Dendy Senapartha","doi":"10.59805/ecsit.v1i2.95","DOIUrl":"https://doi.org/10.59805/ecsit.v1i2.95","url":null,"abstract":"Jogja is one of the most popular tourist destinations in Indonesia. Tourists who come to Jogja are mostly backpackers, family tourists, and tour groups. Jogja is indeed famous for its popular tourist attractions, such as Prambanan Temple, Malioboro, and Mount Merapi. However, tourists who do not know much about tourism in Jogja will find it difficult to design their travel plans. Therefore, the existence of Jogja travel planning website application will help tourists in planning their trip. This Jogja travel itinerary website application is designed using the Goal-directed design method because tourists have different types and characteristics so that their tourist interests will be different. This research will focus on the goals and needs of users with the stages of research, modeling, requirements, framework, design refinement, interface implementation, and usability testing. From the results of usability testing on the Jogja travel planning website application, we obtained an effectiveness value with a success rate of 100%, efficiency with the longest average time-based efficiency value T1, namely 0.016 goal/sec and the fastest time-based efficiency, namely T5 with a value of 0.093 goal/sec, as well as satisfaction with an average value of 80.7, which means it is acceptable with a good rating and a rating scale of C.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"42 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139382483","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

Support Vector Machine Application for Classification of Tempe Fermentation Maturity with Information Gain Selection Feature 基于信息增益选择特征的支持向量机在坦贝发酵成熟度分类中的应用

Edutran Computer Science and Information Technology Pub Date : 2023-08-29 DOI: 10.59805/ecsit.v1i2.40

Muhammad Irfak, Istiadi, Aviv Yuniar Rahman

{"title":"Support Vector Machine Application for Classification of Tempe Fermentation Maturity with Information Gain Selection Feature","authors":"Muhammad Irfak, Istiadi, Aviv Yuniar Rahman","doi":"10.59805/ecsit.v1i2.40","DOIUrl":"https://doi.org/10.59805/ecsit.v1i2.40","url":null,"abstract":"Tempe is one of the ingredients of traditional Indonesian cuisine. In making tempe, a soybean fermentation process is needed which is generally still carried out in an open environment so that the maturity time becomes slow and erratic. Therefore, in the tempe fermentation process, a detector is needed to find out optimal maturity in tempe. This detection effort makes it possible to use image processing by utilizing various feature extractions through the classification process. This research utilizes a variety of image features, namely texture features using the GLCM method and various color features, namely RGB, HSV, LAB, CMYK, YUV, HIS, HCL, LCH. However, with so many features, it causes a high computational load, so that in this study the Information Gain approach was used to select features. Furthermore, the classification process is carried out using the Support Vector Machine (SVM) method with variations of linear, polynomial, gaussian and sigmoid kernels. Tempe objects in the fermentation process are divided into unripe, ripe and rotten classes with a total of 410 images as a dataset. The test results (SVM+IG) on the Sigmoid kernel produce the fastest time accuracy with a computational result of 2.18 seconds on a 30:70 split ratio, the longest split ratio is 80:20 which is 2.50 seconds on a Linear kernel and produces the highest accuracy of 96 ,74%. Furthermore, in the SVM test without using Information Gain on the gaussian kernel, it produced the fastest time accuracy of 2.28 seconds, and the longest at a split ratio of 40:60, namely 3.00 seconds in the polynomial kernel. Thus the result of using SVM+IG is that the average level of accuracy when using (SVM+IG) is faster than the SVM process without IG which obtains slower computation time. Based on the description above, this study aims to apply the SVM method to classify tempe fermented images with feature selection using Information Gain.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720697","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

Implementation Of Linear Regression Algorithm And Support Vector Regression In Building Prediction Models Fish Catches Of Fishermen In Ciparagejaya Village 线性回归算法与支持向量回归在建立预测模型中的应用

Edutran Computer Science and Information Technology Pub Date : 2023-03-14 DOI: 10.59805/ecsit.v1i1.15

Fiqri Mahendra, Amril Mutoi Siregar, Kiki Ahmad Baihaqi, B. Priyatna, Lila Setyani

{"title":"Implementation Of Linear Regression Algorithm And Support Vector Regression In Building Prediction Models Fish Catches Of Fishermen In Ciparagejaya Village","authors":"Fiqri Mahendra, Amril Mutoi Siregar, Kiki Ahmad Baihaqi, B. Priyatna, Lila Setyani","doi":"10.59805/ecsit.v1i1.15","DOIUrl":"https://doi.org/10.59805/ecsit.v1i1.15","url":null,"abstract":"Fish catch is one of the indicators affecting the economic growth of coastal communities including the Ciparagejaya Village Community, fish catches recorded by the Fish Auction Place (TPI) vary every month, this is due to the unpredictable condition of the fish caught, for fishermen caught from sea fish are the main source of income, so a reference is needed to anticipate a decrease in fish catches in determining a strategy for sharing the results of savings that are deducted every day from fishermen's catches. The purpose of this study was to create a prediction model with the Linear Regression Algorithm and Support Vector Regression (SVR) from data recorded by TPI Ciparagejaya Village, the data consisting of 33 types of fish caught in 2021. The method used in this research is an analytical method using Linear Regression Algorithm and SVR. This research produces a Prediction Model which will be a reference in the process of calculating data accuracy values where in this study the Root Mean Squared Error (RMSE) method is used. Tests were carried out using Microsoft excel and python with the smallest RMSE value from Microsoft excel calculations of 0.577735, and from python calculations, the smallest RMSE value is 0.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132571483","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

Data Management System Design Website-Based Waste Bank (Case study: DLHK Karawang Regency) 基于网站的废物银行数据管理系统设计(以DLHK Karawang Regency为例)

Edutran Computer Science and Information Technology Pub Date : 2023-03-14 DOI: 10.59805/ecsit.v1i1.23

Vikri Khoerul, B. Priyatna, Baenil Huda, Fitria Nurapriyani, Dudi Awalludin

引用次数: 0

Decision Support System Determining Leading Class Using The Web-Based Analytical Hierarchy Process Method (Case Study: Smp It Al Huda) 基于web的层次分析法的决策支持系统领导阶层确定(案例研究:Smp It Al Huda)

Edutran Computer Science and Information Technology Pub Date : 2023-03-14 DOI: 10.59805/ecsit.v1i1.24

Candra Zonyfar, Yusron Hasbulloh, Arif Maulana Yusuf

引用次数: 0

Work Process Efficiency With Goods Arrival Predictions Against Production Plans Using Linear Regression Algorithms 根据生产计划使用线性回归算法预测货物到达的工作流程效率

Edutran Computer Science and Information Technology Pub Date : 2023-03-13 DOI: 10.59805/ecsit.v1i1.5

Bramandito Yusuf Rizqi Affandi, Y. Cahyana, Dwi Sulistya Kusumaningrum, April Lia Hananto, Fitri Marisa

{"title":"Work Process Efficiency With Goods Arrival Predictions Against Production Plans Using Linear Regression Algorithms","authors":"Bramandito Yusuf Rizqi Affandi, Y. Cahyana, Dwi Sulistya Kusumaningrum, April Lia Hananto, Fitri Marisa","doi":"10.59805/ecsit.v1i1.5","DOIUrl":"https://doi.org/10.59805/ecsit.v1i1.5","url":null,"abstract":"This study discusses how an algorithm can produce predictions used as a reference for implementing work efficiency using the Linear Regression Algorithm. Linear Regression Algorithm is an algorithm that allows to calculate the linear relationship between the dependent and independent variables to make predictions. In his observations, the researcher used one sample which is data on the arrival of goods in the Production Control department of PT XYZ Indonesia with a total IN part of 9055551, part OUT of 332037. The results of predictions made using the Linear Regression Algorithm in (February-May) in 2022 are 4981165 and on the results of testing the prediction results using the MAPE (Mean Absolute Percentage Error) method produces an error of 6% where 6% is still in category A <10% which is very accurate. The results of this prediction produce Man Power, Space and Shuttle efficiency with a reduction of 1 Man Power, 500m2 space and 5 shuttles with a total profit of Rp. 1,897,670,000 per year and can meet the demand for new suppliers to fill the warehouse area. Researchers can conclude that researchers can find out the stages, processes, and results in applying the Linear Regression Algorithm by an average of 90% from previous studies which can predict the arrival of goods and produce work efficiency.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132881442","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

Decision Support System for Performance Assessment in Raising Teacher Salaries Using the SAW Method at MA'ARIF Vocational School 基于SAW方法的MA’arif职业学校教师加薪绩效评估决策支持系统

Edutran Computer Science and Information Technology Pub Date : 2023-03-13 DOI: 10.59805/ecsit.v1i1.39

Anjas Tryana, Anisa Agustianie

{"title":"Decision Support System for Performance Assessment in Raising Teacher Salaries Using the SAW Method at MA'ARIF Vocational School","authors":"Anjas Tryana, Anisa Agustianie","doi":"10.59805/ecsit.v1i1.39","DOIUrl":"https://doi.org/10.59805/ecsit.v1i1.39","url":null,"abstract":"The Decision Support System is a specialized information system designed to aid management in making effective and efficient decisions on semi-structured problems; it does not replace conventional decision-making procedures. The system that is currently running at the Cicalengka Integrated Ma'arif Vocational School has deficiencies: The process of determining teacher salary increases at the Cicalengka Integrated Ma'arif Vocational School takes more time due to the difficulty of finding data; It's easy to make mistakes because the salary increase process is done manually; It's easy to lose the raise process file. The decision-making function increase in teacher salaries at SMK Ma'arif Terpadu Cicalengka. This thesis uses a Decision Support System with the SAW (Simple Additive Weighting) method then the system development method uses OOAD (object-oriented analysis and design) with the RUP (Rational Unified Process) model. Rational Unified Process (RUP) is a software engineering technique created by compiling the software development industry's best practices. RUP is object-oriented, with activities centered on model development utilizing the Unified Modeling Language (UML). The final result of the Thesis and the making of applications and Decision Support Systems Assessing Performance for Salary Increases/Teachers at SMK Ma'arif Terpadu Cicalengka is a website-based application that can facilitate the process of evaluating performance for salary increases at SMK Ma' Arif Integrated Cicalengka, The Decision Support System built using the SAW method is expected to make it easier for schools to evaluate performance for teacher/manager salary increases; The Decision Support System that is built can minimize errors that occur from the performance appraisal process for teacher/manager salary increases; Can reduce the loss of archives at Integrated Cicalengka Ma'arif Vocational High School.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114207544","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

Sentiment Analysis Of Vaccination Using The K-Nearest Neighbor Algorithm 基于k近邻算法的疫苗接种情感分析

Edutran Computer Science and Information Technology Pub Date : 2023-03-13 DOI: 10.59805/ecsit.v1i1.6

F. Aryanto, Ahmad Fauzi, Anis Fitri Nur Masruriyah, April Lia Hananto, Darmansyah

引用次数: 0