Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika最新文献

Application of the Naive Bayes Classifier Method and Fuzzy Analytical Hierarchy Process in Determining Books Eligible for Publishing 应用 Naive Bayes 分类法和模糊分析层次法确定符合出版条件的图书

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.6677

Mochamad Denny Irwansyah, Teguh Puja Negara, Erniyati Erniyati, Puspa Citra

引用次数: 0

Recommender Systems using Hybrid Demographic and Content-Based Filtering methods for UMKM Products 针对 UMKM 产品使用人口统计学和内容过滤混合方法的推荐系统

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.8991

Salsa Nadira Putri, Tjut Awaliyah Zuraiyah, Dinar Munggaran Akhmad

{"title":"Recommender Systems using Hybrid Demographic and Content-Based Filtering methods for UMKM Products","authors":"Salsa Nadira Putri, Tjut Awaliyah Zuraiyah, Dinar Munggaran Akhmad","doi":"10.33751/komputasi.v21i1.8991","DOIUrl":"https://doi.org/10.33751/komputasi.v21i1.8991","url":null,"abstract":"Marketing digitization such as e-commerce is needed by micro, small and medium enterprises (UMKM) in Bogor City and Regency so that the products are more easily accessible to consumers. One of the digital marketing that is commonly used by consumers is an e-commerce website. The Recommendation System is implemented into e-commerce websites to increase consumer convenience in online shopping. The recommendation systems method applied is Demographic Filtering and Content-based Filtering. Demographic Filtering uses IMDB Weighted Rating calculations which generate recommendations globally and give recommendations based on each product's IMDB Weighted score. Content-based Filtering uses Cosine Distance calculations which generate personal recommendations and give recommendations based on the score cosine distance of each product in the form of a presentation of the similarity of products that have been purchased with other products. This research uses 107 UMKM fashion and craft product data that was obtained from Bogor City Regional Craft Center which sells various kinds of UMKM products from Bogor City and Regency. Data preprocessing is then carried out on the raw data, with the Data Cleaning, Data Transforming and Data Splitting stages which divide the data in a ratio of 80:20. The accuracy of Demographic Filtering Recommendation System reaches 82.7% and Content-based Filtering Recommendation System reaches 100%.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"30 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140489536","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

Spatial Clustering Using Generalized LASSO on the Gender and Human Development Index in Papua Island in 2022 利用广义 LASSO 对 2022 年巴布亚岛的性别和人类发展指数进行空间聚类

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.9268

Ahdan Darul Mutaqin, S. Rahardiantoro, Mohammad Masjkur

{"title":"Spatial Clustering Using Generalized LASSO on the Gender and Human Development Index in Papua Island in 2022","authors":"Ahdan Darul Mutaqin, S. Rahardiantoro, Mohammad Masjkur","doi":"10.33751/komputasi.v21i1.9268","DOIUrl":"https://doi.org/10.33751/komputasi.v21i1.9268","url":null,"abstract":"Equitable development from a gender perspective needs attention. Based on data from the World Economic Forum (WEF), gender equality in Indonesia has increased. Even so, the island of Papua is still very low on gender equality. It can be seen from the Gender Development Index (IPG) from the Central Bureau of Statistics (BPS), there is a considerable gap between the Papua Island IPG and the National. IPG is a comparison between the Human Development Index (IPM) for Men and Women. Based on these conditions, this study aims to classify GPI, Male IPM, and Female IPM by region using the spatial clustering method in 2022. One of the analytical methods that can overcome these conditions is Generalized LASSO. Generalized LASSO can be used on data that only has a response variable (y) for clustering. Generalized LASSO clustering uses a penalty matrix D. The formation of the D matrix is formed by giving values -1 and 1 for areas that intersect or are adjacent and a value of 0 for other areas. The best clustering for IPG uses KNN with K = 3 and the number of clusters formed is 2 clusters. The best clustering for male HDI uses KNN with K = 2 and the number of clusters formed is 8. The best clustering for female HDI uses KNN with K = 2 and the number of clusters formed is 10 clusters.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"18 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140487799","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

Chaos CSPRNG Design As a Key in Symmetric Cryptography Using Logarithmic Functions 混沌 CSPRNG 设计作为使用对数函数的对称密码学密钥

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.9265

Hizkia Nathanael, Alz Danny Wowor

引用次数: 0

Apriori Algorithm Application for Consumer Purchase Patterns Analysis Apriori 算法在消费者购买模式分析中的应用

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.9260

B. H. Situmorang, Ali Isra, Dhatu Paragya, David Aulia Akbar Adhieputra

引用次数: 0

Linear Kernel Optimization of Support Vector Machine Algorithm on Online Marketplace Sentiment Analysis 在线市场情感分析中支持向量机算法的线性核优化

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.9266

Fiki Andrianto, A. Fadlil, Imam Riadi

{"title":"Linear Kernel Optimization of Support Vector Machine Algorithm on Online Marketplace Sentiment Analysis","authors":"Fiki Andrianto, A. Fadlil, Imam Riadi","doi":"10.33751/komputasi.v21i1.9266","DOIUrl":"https://doi.org/10.33751/komputasi.v21i1.9266","url":null,"abstract":"Twitter is a short message platform commonly used as a means of news information, commentary, and social interaction. One of the utilization of twitter is to analyze the sentiment of the online marketplace which can be used to determine the service, quality of goods, and delivery of goods on a product, service or application. This research aims to categorize the reviews or responses of the Indonesian people, especially to the online marketplace using the linear Support Vector Machine (SVM) algorithm. In order to make continuous improvements to the role of the Indonesian online marketplace in the future, sentiment analysis is needed. The analysis research tweets used were 4165 datasets using the python programming language. Sentiment analysis research stages include data collection, preprocessing, labeling, tf-idf weighting, split data, SVM model analysis and result evaluation. The data is then divided into 80% training data and 20% testing data, 50% training data and 50% testing data, 20% training data and 80% testing data. The results of the svm algorithm testing scenario obtained the highest optimization with an accuracy value of 97%, F1-score value on positive labels 88% and negative 98%, also obtained a positive recall value of 80% and negative 100% precision value on positive labels 98% and negative 97%, on 80% training data and 20% testing. It can be concluded that in this case, the linear svm algorithm is able to work to recognize models with a high level of accuracy so that in the future it can be used in similar cases.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"47 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140487566","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

Message Encryption in Digital Images using the Zhang LSB Imange Method 使用张式 LSB Imange 方法对数字图像中的信息进行加密

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2024-01-29 DOI: 10.33751/komputasi.v21i1.9314

Asep Saepulrohman, Agus Ismangil, L. Heliawati

引用次数: 0

C4.5 Algorithm Implementation to Predict Student Satisfaction Level of Lecturer’s Performance in the Covid-19 Pandemic 用 C4.5 算法预测学生对 Covid-19 大流行病中讲师表现的满意程度

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2023-07-26 DOI: 10.33751/komputasi.v20i2.8284

Juan Rizky Mannuel Ledoh, Ferdinandus Elfanto Andreas, Emerensye Sofia Yublina Pandie, Clarissa Elfira Amos Pah

{"title":"C4.5 Algorithm Implementation to Predict Student Satisfaction Level of Lecturer’s Performance in the Covid-19 Pandemic","authors":"Juan Rizky Mannuel Ledoh, Ferdinandus Elfanto Andreas, Emerensye Sofia Yublina Pandie, Clarissa Elfira Amos Pah","doi":"10.33751/komputasi.v20i2.8284","DOIUrl":"https://doi.org/10.33751/komputasi.v20i2.8284","url":null,"abstract":"Implementation of education during the emergency period of Covid-19 in Higher Education was carried out at home through online/distance learning. The lecturer is one of the key holders of success in the learning process. Lecturer performance is a main factor needed to improve education and service quality in online learning. In this study, the authors implemented the C4.5 algorithm using RapidMiner 9.10 app to predict student satisfaction with lecturer performance during the Covid-19 pandemic. The data in this study were obtained from a questionnaire distributed to active students in the Computer Science Study Program (class of 2016 - 2021) at the University of Nusa Cendana with 942 records. The attributes used in this study were the lecturer's age, gender, suitability of learning media (SLM), and the competencies of Pedagogic Competence (PeC), Professional Competence (PrC), Personal Competence (PsC), and social competence (SC), with the level of student satisfaction as the target class divided into two, namely Satisfied and Dissatisfied. The dataset is processed using RapidMiner and produces 11 decision rules which show that the attribute PeC has the most significant influence on the level of student satisfaction with lecturer performance during the Covid-19 pandemic and the test results of the decision tree model using cross-validation. The test results show that the C4.5 algorithm has a good performance in predicting levels of student satisfaction with an accuracy rate of 94.8%, precision for the prediction class Dissatisfied and Satisfied of 92.23 % and 95.52%, and recall of the actual Dissatisfied and Satisfied classes of 85.2% and 97.77%.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139354542","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 EDAS Method in the Selection of the Best Students with ROC Weighting 在利用 ROC 加权法选拔优秀学生中实施 EDAS 方法

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2023-07-23 DOI: 10.33751/komputasi.v20i2.7904

Dedi Darwis, H. Sulistiani, Dyah Ayu Megawaty, Setiawansyah Setiawansyah, Intan Agustina

引用次数: 0

Chatbot PTIPD Customer Care Center Service using Dialogfow 使用 Dialogfow 的聊天机器人 PTIPD 客户服务中心服务

Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Pub Date : 2023-07-22 DOI: 10.33751/komputasi.v20i2.8281

Arlan Joliansa Ndruru, Muhammad Fikry, Yusra

{"title":"Chatbot PTIPD Customer Care Center Service using Dialogfow","authors":"Arlan Joliansa Ndruru, Muhammad Fikry, Yusra","doi":"10.33751/komputasi.v20i2.8281","DOIUrl":"https://doi.org/10.33751/komputasi.v20i2.8281","url":null,"abstract":"Chatbot research is a unique innovation in the development of Artificial Intelli- gence and has promising prospects in the field of Education. One form of information service available at the university is the Customer Care Center (C3) PTIPD UIN Suska Riau, which is responsible for handling problems submitted by students. However, with so many questions or problems submitted to the PTIPD Customer Care Center, it is difficult for the PTIPD Cus- tomer Care Center to respond to student questions submitted, the service becomes ineffective and the response to the answers to the problems submitted becomes late. To overcome this problem, chatbot development was carried out for PTIPD UIN Suska Riau Customer Care Center Services using Dialogflow to improve services and overcome existing problems. Di- alogflow as conversation development platform that uses natural language processing (NLP) to understand and interpret user intent in conversations. Through User Acceptance Test (UAT) testing, the chatbot managed to achieve an acceptance rate of 84% overall. This shows that users, in this case, students respond positively to the use of chatbots in PTIPD Customer Care Center services. In addition, Usability Testing was also conducted to evaluate the level of usability of the chatbot. Based on this test, the chatbot achieved a score of 76, which indicates a good level of usability in interaction with users. The test results illustrate that the chatbot at the Customer Care Center PTIPD UIN Suska Riau has provided a positive user experience.","PeriodicalId":339673,"journal":{"name":"Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139356566","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