Journal of Dinda : Data Science, Information Technology, and Data Analytics最新文献

Classification of Sleep Disorders Using Random Forest on Sleep Health and Lifestyle Dataset 基于睡眠健康和生活方式数据集的随机森林睡眠障碍分类

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-08-07 DOI: 10.20895/dinda.v3i2.1215

Idfian Azhar Hidayat

引用次数: 0

Classification of Drug Types using Decision Tree Algorithm 基于决策树算法的药物类型分类

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-08-04 DOI: 10.20895/dinda.v3i2.1203

Alissiyah Putri, Dani Azka Faz, Felis Tigris Hafizhulloh

{"title":"Classification of Drug Types using Decision Tree Algorithm","authors":"Alissiyah Putri, Dani Azka Faz, Felis Tigris Hafizhulloh","doi":"10.20895/dinda.v3i2.1203","DOIUrl":"https://doi.org/10.20895/dinda.v3i2.1203","url":null,"abstract":"The accurate classification of drugs plays a crucial role in various areas of pharmaceutical research and development. In recent years, machine learning techniques have emerged as powerful tools for drug classification tasks. This paper presents a study on drug classification using machine learning techniques implemented in Python. The objective of this research is to explore the effectiveness of different machine learning algorithms in accurately classifying drugs based on their molecular properties and characteristics. The dataset used in this study consists of a diverse collection of drug compounds with annotated class labels. Several popular machine learning algorithms, including decision trees are implemented and evaluated using Python's extensive libraries such as scikit-learn. The dataset is pre-processed to handle missing values, normalize features, and reduce dimensionality using appropriate techniques. Experimental results demonstrate the performance of each algorithm in terms of accuracy, precision, recall, and F1-score. The findings of this study highlight the potential of machine learning techniques in accurately classifying drugs and provide valuable insights into the selection and optimization of algorithms for drug classification tasks. The Python implementation serves as a practical guide for researchers and practitioners interested in applying machine learning for drug classification purposes.","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129302899","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

The Descriptive Analysis of Perceptions of ITTP Data Science Students regarding Face-to-Face Learning Plans ITTP数据科学学生对面对面学习计划看法的描述性分析

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-07-31 DOI: 10.20895/dinda.v3i2.1028

Wahyu Nouval Aghniya, Lutfhi Rakan Nabila, Rizky Ananda Putra

{"title":"The Descriptive Analysis of Perceptions of ITTP Data Science Students regarding Face-to-Face Learning Plans","authors":"Wahyu Nouval Aghniya, Lutfhi Rakan Nabila, Rizky Ananda Putra","doi":"10.20895/dinda.v3i2.1028","DOIUrl":"https://doi.org/10.20895/dinda.v3i2.1028","url":null,"abstract":"The case of Covid-19 which has been going up and down has forced educational units to think about what learning methods will be applied in the future and also have to pay attention to the responses that students will say. Remember, some students have various arguments, including students who can think maturely in assessing something related to their future interests. This research was conducted with the aim of knowing student perceptions regarding face-to-face learning plans during the pandemic at IT Telkom Purwokerto. In knowing each student's perception, there are several variables that can influence the results of their perception. For the population in this study, all undergraduate students of the IT Telkom Purwokerto Faculty of Informatics in 2021 with judgment/expert sampling as the sampling technique. The instrument used is a questionnaire or questionnaire. The data analysis method used in this research is descriptive quantitative analysis method. Based on the research that has been done, the results show that there were 37 answers (56.1%) who strongly agreed with the question regarding facilities & infrastructure, for Regarding service quality, there were 45 answers (68.2%) who strongly agreed, then for questions regarding student perceptions, there were 17 answers (25.8%) who felt strongly agreed. And obtained results of less than 15% and even up to 0% in each variable for answers that do not agree. So, most students agree with face-to-face learning and attending lectures. Likewise with the parents of each student who agreed to the plan.","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132276605","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

Dominant Requirements for Student Graduation in the Faculty of Informatics using the C4.5 Algorithm 基于C4.5算法的信息学专业学生毕业优势要求

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-07-31 DOI: 10.20895/dinda.v3i2.1040

Alvina Tahta Indal Karim, Sudianto Sudianto

{"title":"Dominant Requirements for Student Graduation in the Faculty of Informatics using the C4.5 Algorithm","authors":"Alvina Tahta Indal Karim, Sudianto Sudianto","doi":"10.20895/dinda.v3i2.1040","DOIUrl":"https://doi.org/10.20895/dinda.v3i2.1040","url":null,"abstract":"Graduating on time is one of the indicators in the achievement and ranking of educational institutions. The achievement of graduating on time in educational institutions is essential to balance incoming and graduating students. The problem that occurs, the attributes for graduating on time have varying weightings, so the determinants of the attributes for passing on time need to be known so that the anticipation of achieving graduation on time can be met. The purpose of this study is to find out the dominant attributes in the prediction of graduating on time for students. The attributes used are credit scores (Semester Credit Units), GPA scores (Grade Point Average), and English scores (TOEFL). The method used is the C4.5 Algorithm which is one of the classification methods in data mining. The data used was 262 data, split randomly with a composition of training and testing data of 80:20. Data is processed using the data mining process by creating decision trees. The decision tree results using the C4.5 Algorithm show that the GPA value is the most influential attribute in predicting a student's graduation time. In addition, predictions based on the decision tree of the C4.5 Algorithm with criterion = 'gini' and max_depth = 5 showed an accuracy result of 77%.","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125347955","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

Minimalist DCT-based Depthwise Separable Convolutional Neural Network Approach for Tangut Script 基于dct的极简深度可分卷积神经网络切线脚本算法

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-07-31 DOI: 10.20895/dinda.v3i2.1106

Agi Prasetiadi, Julian Saputra, Imada Ramadhanti, Asti Dwi Sripamuji, Risa Riski Amalia

引用次数: 0

Comparison of C4.5 and Naive Bayes Algorithm Methods in Prediction of Student Graduation on Time (Case Study: Information Systems Study Program) C4.5与朴素贝叶斯算法在学生按时毕业预测中的比较(以信息系统研究项目为例)

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-02-04 DOI: 10.20895/dinda.v3i1.782

Disty Dikriani, Alvina Tahta Indal Karim

{"title":"Comparison of C4.5 and Naive Bayes Algorithm Methods in Prediction of Student Graduation on Time (Case Study: Information Systems Study Program)","authors":"Disty Dikriani, Alvina Tahta Indal Karim","doi":"10.20895/dinda.v3i1.782","DOIUrl":"https://doi.org/10.20895/dinda.v3i1.782","url":null,"abstract":"In tertiary institutions, students become one of the important parameters in the evaluation of study program organizers. Prediction of student graduation is a special concern to know, early identification for students is needed as an important action. Information processing to predict student graduation is by implementing data mining. The implementation of data mining can be applied if a university, especially a study program, does not yet have an early classification in achieving student graduation on time. The ITTP Information System study program is one of the study programs that does not have an early identification of student graduation on time. Determination of graduation for SI ITTP Study Program students includes GPA, TOEFL scores, and total credits. The purpose of this research is to find out which attributes have the most influence in predicting graduation of ITTP IS Study Program students. The method used in this prediction is by using the classification of the C4.5 Algorithm and Naïve Bayes. The classification is used to determine which attributes have an effect on predicting student graduation on time and to compare the two classification methods. The results obtained are the training set size 70% which has the best accuracy when compared to other training set sizes. Comparing the accuracy between the two methods, it is known that the C4.5 algorithm has good accuracy when training set size is 70% and Naïve Bayes has higher accuracy when training set size is 75%. Decision tree C4.5 interprets that the most influential attribute is the GPA as the root of the decision tree to predict student graduation on time. The research is expected to be used as a reference for the ITTP IS Study Program in formulating student graduation policies on time and as a reference for further researchers in predicting in the same field.","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391980","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: 1

Cluster Analysis of Covid-19 in Indonesia Using K-means Method 基于K-means方法的印度尼西亚Covid-19聚类分析

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-02-02 DOI: 10.20895/dinda.v3i1.822

Claudia Larasvaty, S. Khomsah, R. Sa

引用次数: 0

Utilization of Google Trends in Knowing Public Attention to Diabetes in Indonesia in 2018 利用谷歌趋势了解2018年印度尼西亚公众对糖尿病的关注

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-02-02 DOI: 10.20895/dinda.v3i1.765

Guruh Dewa Prataba, Aida Devanty Putri, Lalu Moh. Arsal Fadila

{"title":"Utilization of Google Trends in Knowing Public Attention to Diabetes in Indonesia in 2018","authors":"Guruh Dewa Prataba, Aida Devanty Putri, Lalu Moh. Arsal Fadila","doi":"10.20895/dinda.v3i1.765","DOIUrl":"https://doi.org/10.20895/dinda.v3i1.765","url":null,"abstract":"Diabetes is one of the four non-communicable diseases that are prioritized because of the sufferer’s number and the increasing prevalence rate. The results of the 2018 Basic Health Research shows an iceberg phenomenon where there are far more people living with diabetes who have not been diagnosed than those who live with diabetes and know their condition. The public's desire to find out in advance the disease that may be suffered on Google opens up opportunities of research in public concern about diabetes. This research with descriptive analysis aims to describe the public's attention to diabetes based on Google Trends data. The results show that the development of public attention in 2018 tends to fluctuate with the highest index on World Diabetes Day. Then there are provinces that need attention with high diabetes prevalence values but still have a low volume of diabetes-related searches. Most topics related to diabetes are about the drugs, causes, and symptoms of diabetes. So it is necessary to socialize diabetes literacy, especially in areas with low public attention","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128338477","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

Comparison Analysis of Native Database Design with Object Oriented Design 本机数据库设计与面向对象设计的比较分析

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-02-01 DOI: 10.20895/dinda.v3i1.707

Muhamad Fernandy, Khevien Rizkhi Darmawan, Daniel Kristiyanto

引用次数: 0

Design and Creation of Online Attendance Systems in Web-Based Higher Education Institutions 基于网络的高等院校在线考勤系统的设计与实现

Journal of Dinda : Data Science, Information Technology, and Data Analytics Pub Date : 2023-02-01 DOI: 10.20895/dinda.v3i1.771

Heldiansyah Heldiansyah, Muchtar Salim, Rustaniah Rustaniah

引用次数: 0