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Survival Analysis of Kasturi Tobacco Plants in Jember District using the Stratified Cox and Extended Cox Models

MethodsX 2025年

作者： Angga Iryanto Pratama Dwi Rantini Ratih Ardiati Ningrum Arip Ramadan Fazidah Othman Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Research Group of Data-Driven Decision Support System Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia

In 2022, tobacco was the top export commodity, generating $106.3 million in sales. East Java Province contributes significantly to Indonesia's tobacco production, with an annual output of 188.6 thousand tons. Jember Regency is the area in East Java Province which is a Kasturi tobacco cultivation area. The productivity of Kasturi tobacco continues to decrease due to several factors that can affect the survival of the tobacco. This study aims to analyze the survival of Kasturi tobacco by creating stratified Cox and extended Cox models in order to handle factors that cannot fulfill the proportional hazard assumption. Based on the results of the analysis, the stratified Cox model is the best model with AIC and BIC values of 798.108 and 805.5748 respectively, while the extended Cox has AIC and BIC values of 840.2186 and 850.1732 respectively. Variables that can significantly affect the survival of Kasturi tobacco are the variable concentration of ZA fertilizer, pesticide concentration. The addition of ZA fertilizer must be appropriate, because if excessive it can cause poisoning of tobacco plants. Likewise with pesticides, if excessive it will cause damage to the leaves. This policy can increase the productivity of Kasturi tobacco. Then, Jember Regency contributes greater export capacity. • This paper aims to determine the factors that affect the survival of Kasturi tobacco plants in Jember • By using the extended Cox model, the best one is obtained using the Heaviside function with AIC and BIC values of 840.2186 and 850.1732, respectively • The stratified Cox model is better than the extended Cox model, which has AIC and BIC values of 798.108 and 805.5748, respectively

关键词： Productive Agriculture Cox Proportional Hazard Stratified Cox Extended Cox Kasturi Tobacco

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Profile of Students' Technological Content Knowledge in School Mathematics 1

Profile of Students' Technological Content Knowledge in Scho...

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1st International Conference on Computer, Science, Engineering and technology, ICComSET 2018

作者： Mulyanti, Yanti Rahmat, Dadan Darhim Mathematics Education Study Program FKIP UMMI Indonesia Information Technology Education Study Program FKIP UMMI Indonesia

This study aims to find out the technological content knowledge profile of Mathematics Education Students of Teacher Training and Education Faculty, Universitas Muhammadiyah Sukabumi who have completed courses in Mathematics Capita Selecta III. The research method used is descriptive with quantitative approach. Data is collected by survey method, using a questionnaire instrument whose statement is based on the component of technological content knowledge. The results showed that students' technological content knowledge was in a good category with an means 3.52 which means that students of Mathematics Education understood how to integrate technology and material in learning school mathematics. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Students

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Web Browser Extension Development of Structured Query Language Injection Vulnerability Detection Using Long Short-Term Memory Algorithm 4

Web Browser Extension Development of Structured Query Langua...

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4th IEEE International Conference of Computer Science and information technology, ICOSNIKOM 2022

作者： Turnip, Togu Novriansyah Aruan, Hotma Siagian, Anita Lasmaria Siagian, Leonardo Institut Teknologi Del Information Technology Study Program Toba Indonesia

ISBN: (纸本)9798350399073

Structured Query Language Injection (SQLi) is a client-side application vulnerability that allows attackers to inject malicious SQL queries with harmful intents, including stealing sensitive information, bypassing authentication, and even executing illegal operations to cause more catastrophic damage to users on the web application. According to OWASP, the top 10 harmful attacks against web applications are SQL Injection attacks. Moreover, based on data reports from the UK's National Fraud Authority, SQL Injection is responsible for 97% of data exposures. Therefore, in order to prevent the SQL Injection attack, detection SQLi system is essential. The contribution of this research is securing web applications by developing a browser extension for Google Chrome using Long Short-Term Memory (LSTM), which is a unique kind of RNN algorithm capable of learning long-term dependencies like SQL Injection attacks. The results of the model will be deployed in static analysis in a browser extension, and the LSTM algorithm will learn to identify the URL that has to be injected into Damn Vulnerable Web Application (DVWA) as a sample-tested web application. Experimental results show that the proposed SQLi detection model based on the LSTM algorithm achieves an accuracy rate of 99.97%, which means that a reliable client-side can effectively detect whether the URL being accessed contains a SQLi attack or not. © 2022 IEEE.

关键词： Long short-term memory

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Method for modelling the number of HIV and AIDS cases using least square spline Biresponse nonparametric negative binomial regression

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MethodsX 2025年 14卷 103336页

作者： Ramadan, Arip Chamidah, Nur Budiantara, I Nyoman Lestari, Budi Aydin, Dursun Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Information System Study Program Department of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Statistics Department Faculty of Science and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences The University of Jember Jember 68121 Indonesia Department of Statistics Faculty of Science Muğla Sıtkı Koçman University Muğla 48000 Turkey Research Scholar at Department of Mathematics University of Wisconsin Oshkosh Algoma Blvd Oshkosh 54901 WI United States

We propose a new statistical modeling method to analyze functional relationship between predictor variables and correlated response variables, and apply it for modeling the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users. The proposed method is LS-Spline BNNBR that is a Biresponse Nonparametric Negative Binomial Regression (BNNBR) based on least squares spline (LS-Spline). To validate the proposed method, we compare it with classical method, namely Ordinary Least Square Biresponse Parametric Negative Binomial Regression (OLS-BPNBR). The results show that the LS-Spline BNNBR method provided deviance value of 7.542334 which is smaller than that of OLS-BPNBR method, namely 7.993935. Thus, the proposed method has better prediction fit than the classical method. • This study discusses new statistical modeling method for the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users where the response variables are correlated with each other. • The model estimation results show that the number of HIV and AIDS cases in Indonesia will decrease if the early-age marriages percentage increases and the contraceptive users percentage decreases. • The results are useful to provide a scientific basis for making policies to control the number of HIV and AIDS cases in Indonesia. © 2025 The Authors

关键词： AIDS BLSSNNBR model Contraceptive user Early-age marriage HIV Least square spline

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Finding the Best Techniques for Predicting Term Deposit Subscriptions (Case study UCI Machine Learning Dataset) 4

Finding the Best Techniques for Predicting Term Deposit Subs...

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4th International Conference on Sustainable Engineering and Creative Computing, ICSEC 2022

作者： Setiyani, Lila Indahsari, Ayu Rosalina Wansen, Tjong President University Master of Science Information Technology Study Program Bekasi Indonesia President University Informatics Study Program Bekasi Indonesia

ISBN: (纸本)9798350322002

Knowing a lot about attributes, such as bank client data, marketing campaigns, social and economic context, and so on, is necessary to predict which bank customers are likely to sign up for time deposits. The direct marketing campaigns dataset for the bank institution was made available by the UCI machine learning repository. This dataset had previously been used in studies to forecast customers who would sign up for time deposits, but the outcomes of the two studies were different. The purpose of this study is to determine which machine learning methods are most effective for predicting customers who will sign up for time deposits. In this study, researchers used machine learning methods like random forests, K-nearest neighbors, decision trees, naive bayes, logistic regression, SVM, and XGBoost to uncover the truth. Results showed that XGBoost had the highest accuracy (91.73%), followed by the DT classifier (88.79%), LR classifier (91.2%), NB classifier (84.78%), KNN classifier (90.6%), SVM (89.6%), and XGBoost (91.44%). © 2022 IEEE.

关键词： Forecasting

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Monitoring System of Greenhouse Based on WSN and Auto Flushing Sensor Mechanism 6

Monitoring System of Greenhouse Based on WSN and Auto Flushi...

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6th International Conference on information technology, information Systems and Electrical Engineering, ICITISEE 2022

作者： Yuliandoko, Herman Panduardi, Farisqi Holik, Abdul Politeknik Negeri Banyuwangi Information Technology Program Study Banyuwangi Indonesia Politeknik Negeri Banyuwangi Agrobusiness Program Study Banyuwangi Indonesia

ISBN: (纸本)9798350399615

Indonesia is an agricultural country with agriculture as one of the mainstays of state income. However, the competition for agricultural production is currently very high, so it requires innovations in agricultural technology to increase the competitiveness of Indonesian food production. One of the latest agriculture technologies is Greenhouse. With Greenhouse, it is possible to adjust temperature conditions, room humidity and other plant parameters. In Indonesia, this technology has begun to be widely used but is still very limited due to technological constraints and high costs. In a greenhouse, some tools monitor plant parameters to support plant growth, such as water pumps, sensors, dynamos, and sprays. However, currently, there are still many greenhouses that operate these tools conventionally. This causes greenhouse operations to take a long time and a lot of labor, so greenhouse operations are expensive and complicated. Therefore, Greenhouse innovation is needed with a flexible, easy and efficient system. In this research, innovation will be carried out with a Greenhouse monitoring system by implementing the WSN (Wireless Sensor Network). In addition, the use of sensors with auto flushing is done to prevent encrustation on the sensor surface. Using WSN will increase the flexibility of data transmission and minimize energy use so that it can be applied in remote areas. Room temperature is also connected with a blower as an automation mechanism to maintain wind circulation in Greenhouse. The monitoring of plan nutrition in the Greenhouse is very important that why this research also study it. © 2022 IEEE.

关键词： Flushing Greenhouse Monitoring Sensor WSN

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Development of Ikigai instructional method to cultivate computational thinking of millennial generations

Development of Ikigai instructional method to cultivate comp...

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Seminar on Advances in Mathematics, Science and Engineering for Elementary School, SAMSES 2018

作者： Hikmawan, R. Sari, D.P. Majid, N.A. Ridwan, T. Nuriyah, W. Aprilia, L. Diani, D. Study Program of System and Information Technology Education Universitas Pendidikan Indonesia Indonesia

Digitalization in industrial revolution 4.0 era has many impacts towards all aspects of life. Massive technology advancement shifts industrial demands in Indonesia from quantitative to qualitative demands. These qualitative demands can be interpreted that today's industry workforce not only need technique competencies but also must have good Computational Thinking (CT) which is the pillar of collaboration, communication, creativity, and problem-solving skills. This issue did not balance with the enhancement of cognitive skills of Indonesians, especially youth or millennial generation. Millennial generation required to overcome multilevel challenges to improve thinking skills particularly on individual level. The low level of intrinsic motivation in using computational thinking to solve its problem became one of millennial culture characteristics. One of the solutions is cultivate student's intrinsic motivation to use CT by utilize Ikigai concept on teaching and learning activities from early grade. The Ikigai role as motivation template has been endure for millennia and proven, if used properly, to be most important factor that help eastern culture people achieve self-actualization. This study aims to develop instructional design that include Ikigai concept to support the achievement of intellectual competencies. Product development is done by Research and Development (R&D) Method with Akker procedure scheme. Product expected to improve students CT in accordance to standard needed in industrial 4.0 era. At this point, we currently at Empirical Testing phase. As expected, we got good response from teacher for product's ease of use and provide clear assessment of students CT Skills. Student that can be described as skilled programmer often have poor communication or collaboration skills with societies. However, when the students have clear life-goal, those lack of social skills are gradually improved. Otherwise, student with good social skills but has poor technique (

关键词： Students

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Multidocument Summarization using GloVe Word Embedding and Agglomerative Cluster Methods 2

Multidocument Summarization using GloVe Word Embedding and A...

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2nd International Conference on Sustainable Engineering and Creative Computing, ICSECC 2020

作者： Rosalina Huda, Rafiqul Sahuri, Genta Faculty of Computing Information Technology Study Program President University Bekasi Indonesia

ISBN: (纸本)9781728175881

This paper explores the method of extracting multi-document summary terminology that enhances single document summary methods using the information related to the document and perhaps even the relation between the documents. In the problems of fragmentation, density, duplication and selection of passages, the summarization of several documents ranges from the summarization of single documents to the creation of efficient summaries. Our approach addresses these issues by using Agglomerative cluster sentence, GloVe, TextRank, Cosine Similarity. In addition, this research also use NLTK as library filter word such as stopwords, numeric, punctuation, multiple_whitespaces, short_words in order Vectorizing the sentence when using GloVe. The result of this paper was evaluated using ROUGE;41% for unigram, 17% for bigram, 57% for trigram. © 2020 IEEE.

关键词： Cluster analysis

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Evaluation model of students learning outcome using k-means algorithm 2

Evaluation model of students learning outcome using k-means ...

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2nd International Conference on Computer, Science, Engineering, and technology, ICComSET 2019

作者： Henderi Sunarya, Abas Zakaria Nurmika, Sri Linggawati Asmainah, Nur Master of Information Technology Study Program Faculty of Science and Technology Raharja University Tangerang Indonesia

The progress of students learning outcomes have to evaluated and make monitor. Student learning outcomes were indicated by score of the exam. Educational institutions can determine the ability of students' knowledge and competences based on student exam scores. For this reason, the goals of this research is develops an evaluation model of student learning outcomes. The model was developed using k-means algorithm and it has functions to analyze the student learning outcomes. The model was tested by conducted using 50 data exam of students, rapid manner software, and has implemented by the Python 3.0 programming language. The testing the evaluation model of student learning outcomes that were developed resulted: there are 3 clusters of student learning outcomes that are good, satisfying, and lacking. The tested results also showed that 40% of students had good learning outcomes, 44% of students were satisfactory, and 16% of other students had poor learning outcomes. The results of testing the student learning evaluation model can be used by the parties concerned to make decisions related to work programs or formulate steps that need to be taken to improve student learning outcomes. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Determinants of Continuance Intention to Use Mutual Fund Investment Apps: The Changing of User Behavior during the Pandemic Crisis 9

Determinants of Continuance Intention to Use Mutual Fund Inv...

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9th IEEE International Conference on Behavioural and Social Computing, BESC 2022

作者： Puspitasari, Ira Utami, Farida Raharjana, Indra Kharisma Universitas Airlangga Faculty of Science and Technology Information System Study Program Surabaya Indonesia

ISBN: (数字)9798350398144

ISBN: (纸本)9798350398144

The COVID-19 pandemic and the implementation of large-scale social restrictions have caused economic and social disruptions globally, including in Indonesia. These difficult situations have shifted the financial attitudes, especially among the working-age group in Indonesia, to be more focused on saving and investing. One of the popular options among new investors is mutual fund investment because it requires a lower cost than other options, offers diversified holdings, and supports a variety of risk profiles. New investors primarily use an investment app, such as a mutual fund investment application, to manage their investment portfolios safely and seamlessly. In line with the rapid growth of mutual fund investors, the number of mutual fund investment apps in Indonesia has increased to more than 80 providers in 2022, resulting in fiercer competition between service providers. Therefore, retaining and increasing the apps' investment usage is crucial to providers' business success. This study investigates factors affecting the investor's continuance intention to use mutual fund investment apps by adapting the expectation-confirmation model (ECM) with other key constructs, i.e., perceived security, trust, and self-efficacy. The collected data from 384 participants were analyzed using Structural Equation Modelling. The results indicate that perceived usefulness, trust, and user satisfaction positively affect the continuance use of mutual fund investment apps. Based on findings, this study proposes practical strategies to retain the application usage, such as implementing security measures, personalized investment courses and advisories based on the user's profile risks and preferences, and recommendations on achieving the user's investment goals based on machine learning solutions. Digital solutions, such as financial and investment apps, may contribute to expanding access to banking, financial services, and financial inclusion in the Indonesian population. © 2022 IEEE

关键词： Investments

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