cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Deden Istiawan
Contact Email
deden.istiawan@itesa.ac.id
Phone
+6282229161672
Journal Mail Official
lppm@itesa.ac.id
Editorial Address
Jl. Prof. Dr. Hamka Km. 01 Ngaliyan Semarang
Location
Kota semarang,
Jawa tengah
INDONESIA
Journal of applied statistics and data mining
Published by Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang
ISSN : ""     EISSN : 27210332     DOI : -
Core Subject : Economy, Science, Social,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences
Journal of applied statistics and data mining provide open access, which in principle makes research open and freely available to the public so that it becomes a means of global knowledge exchange. Published twice a year, in June and December. This journal publishes scientific articles as research results, case studies, or literature reviews on various aspects of statistics, data mining and its applications. Such as Computing, Time Series, Multivariate, Biostatistics, Survival Analysis, Econometrics, Spatial Analysis, Actuarial, Quality Control, Bayesian Analysis, Development Research in Statistics, Natural Language Processing, Applied Mathematics, and Applied Statistics. The editor does not rule out other topics in statistics and data mining.
Arjuna Subject : Matematika - Matematika Komputer
Articles 6 Documents
 1 
Search results for , issue "Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining" : 6 Documents clear
Analysis of the Influence of Influencers and the Word of Mouth System on Purchasing Decisions XX Cosmetic Products Safaat Yulianto; Afifah Oktafiyani, Eka
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.83

Abstract

Background: Products that are currently needed by most women are cosmetics. One of Local cosmetics that are now on the rise and are heading to the global market are products XX. One of XX's marketing strategies is to entrust on Celebrity Endorsers. Objective:  This study aims to determine the effect of influencer and word of mouth on the decision to purchase XX's products from the students of the Institute of Technology Statistics and Business of Muhammadiyah Semarang using the Structural Equation Modeling–Partial Least Square (SEM-PLS). Respondents in this study as many as 44 active D3 Statistics ITESA Muhammadiyah Semarang who had purchased XX’s products. Methods: Structural Equation Modeling (SEM) method is a development of path analysis and multiple regression, which are both forms of multivariate analysis model. One of the methods that can be used for analysis between variables and indicators is to use Structural Equation Modeling (SEM). Results: The results of the SEM-PLS analysis show that as many as 58% of purchasing decisions for product XX among D3 Statistics students are influenced by the role of influencers and the word of mouth system. Conclusion: In addition to interactions with celebrity endorsers, word communication of mouth has also been shown to have an effect on the use and purchase of a product.
The Benefits of Sharia Insurance for MSMEs at PT Zurich Asuransi Indonesia Tbk Putri Ardelia, Nova; Arista Fitri Diana; Zakaria Bani IKhtiyar
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.91

Abstract

Background: Islamic insurance in Indonesia has grown significantly into a modern financial institution capable of competing with conventional insurance. In this context, the micro, small, and medium enterprises (MSMEs) sector is among the major beneficiaries, as Islamic insurance offers protection aligned with the values and needs of the Muslim community. The Indonesian government continues to promote the development of Islamic microinsurance as part of its strategy to strengthen the halal industry and support the economic resilience of MSMEs. Objective: This study aims to examine in depth the benefits of Islamic insurance for MSMEs in Indonesia, with a particular focus on PT Zurich Asuransi Indonesia Tbk as a provider of Islamic insurance products designed to support the MSME sector.t did you want to find out? Methods: This research uses a literature review methodology by analyzing various academic sources, government policies, and industry reports related to the development and implementation of Islamic insurance for MSMEs in Indonesia. Results: The findings show that Islamic insurance provides various benefits to MSMEs, including protection against operational risks, natural disasters, and economic uncertainty. Innovative and effectively managed Islamic microinsurance products enable MSMEs to access affordable protection. PT Zurich Asuransi Indonesia Tbk plays an active role in offering insurance products that are compliant with sharia principles and tailored to the specific needs of MSMEs. Conclusion: This study concludes that Islamic insurance is an important instrument in supporting the sustainability and growth of MSMEs in Indonesia. The protection it offers serves not only as a financial safety net but also as a driver of a sharia-based economy. Future research should explore the empirical impact of Islamic insurance products on the long-term resilience and development of MSMEs.
Sharia Insurance: An Islamic-Based Financial Protection Solution Muhamad Ibnu Hajar; Arista Fitri Diana; Lathifatul Aulia
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.93

Abstract

Background: In Indonesia, Sharia Financial Institutions continue to develop, including in addition to banking companies, such as Sharia Insurance Institutions, Sharia Capital Markets, Sharia Pawnshops, Sharia Financial Institution Pension Fund (DPLK), Sharia Cooperatives, Waqf Agencies, Amil Zakat Agencies, BMT (Baitu al-Mâl wa at-Tamwil) and others. Although sharia insurance continues to develop, public interest is still lacking. This is based on a lack of literacy and socialization related to sharia insurance. Objective: This article aims to review more deeply matters related to sharia insurance, such as its definition, law, history, development, types of contracts, principles, differences between sharia and conventional insurance, premiums, and sharia insurance claims. The goal is to improve public understanding and confidence in sharia insurance. Methods: The method used in this study is a literature review. Results: This study provides a comprehensive synthesis of existing literature related to sharia insurance. Although no new empirical data is presented, the discussion highlights key aspects to address the public's lack of understanding and interest in sharia insurance. Conclusion: The study is expected to help the public better understand sharia insurance so that they become more confident and willing to take out insurance. Further research could focus on evaluating the effectiveness of educational or socialization programs to increase public literacy and participation in sharia insurance.
Implementation of Text Mining for Grouping Thesis Titles Using the K-Harmonic Means Method Sukowati; Lisna Zahrotun
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.85

Abstract

Background: A thesis is a course required for completing a Bachelor's degree (S-1). Thesis documents are typically collected in a library file. This data will be more useful if subjected to in-depth analysis. One such analysis is identifying trends in student thesis topics using clustering techniques. Objective: To analyze and group thesis titles from the years 2012 to 2017 using text mining techniques, with the aim of identifying topic trends through clustering with the K-Harmonic Means method. Methods: The method used in this study is K-Harmonic Means clustering. The stages carried out include tokenization, filtering, stemming, TF-IDF, grouping using K-Harmonic Means, and testing using purity. Results: The result of this research is an application that can process thesis titles into trend groups of thesis titles. From the test conducted using purity obtained a value of 0.63 which means the K-Harmonic method is quite good in grouping. The results of the analysis show that the topic of Multimedia and soft computing became a trend for 3 years, namely 2012, 2013 and 2014, while the topic of mobile applications and web programming became a trend in 2013 and 2015. Conclusion: The results of grouping using the K-Harmonic Means method show a sufficient accuracy value of 0.63. This proves that the K-Harmonic Means method is quite suitable for carrying out the process of grouping text-based data.
Comparison of Feature Extraction for Sentiment Analysis using Support Vector Machine Algorithm Waldi Darmansyah; Herman Yuliansyah 
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.86

Abstract

Background: The Directorate General of Customs and Excise (DJBC), as the regulator of goods at airports, frequently receives passenger complaints about baggage inspections. A recent study (2023) showed a 25% increase in complaints via social media, but no research has compared feature extraction techniques for this specific sentiment analysis. Objective: This study aims to compare the performance of the BoW and TF-IDF methods in sentiment analysis of DJBC inspection complaints, develop an SVM model for sentiment classification, and identify passenger sentiment patterns from Twitter data. Methods: This quantitative research analyzed 4,215 tweets about DJBC from January to June 2023. The stages included: text preprocessing, feature extraction (BoW and TF-IDF), classification with SVM, and evaluation using accuracy, precision, recall, and F1-score. Results: The TF-IDF model achieved 91.3% accuracy (91% precision, 89% recall, and 90% F1-score), while the BoW model achieved 91.1% accuracy (92% precision, 90% recall, and 91% F1-score). The analysis showed that the BoW model was superior in capturing the nuances of complaints. Conclusion: Despite minimal accuracy differences, BoW was more effective for sentiment analysis of DJBC audit complaints. These findings recommend improving officer training on the most frequently complained-about aspects. Further research could test combinations with word embedding or transformers.
Twitter Sentiment Analysis on the Relocation of Indonesia's Capital City Using the Convolutional Neural Network Algorithm Ramadhani Ari Putra; Herman Yuliansyah
Journal of Applied Statistics and Data Mining Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v6i1.90

Abstract

Background: The relocation of the Indonesian capital (IKN) has become a hot topic on social media, particularly Twitter, with diverse public opinions. Sentiment analysis is necessary to comprehensively understand public perception. Objective:  This study aims to analyze public sentiment on Twitter regarding the relocation of the IKN using the CNN algorithm to identify tendencies of positive, negative, or neutral opinions. Methods: Data was obtained through Twitter crawling, followed by preprocessing, automatic labeling with VADER, and resampling (oversampling). Text features were extracted using pre-trained Word2Vec and classified with CNN. Testing was conducted with varying epochs (25, 50, 100) and data splits (70:30 and 80:20). Conclusion: The highest accuracy was achieved with the 70:30 scheme with 100 epochs, namely 83.2% (precision 83.8%, recall 83.2%, and F1-score 83.0%). The analysis shows a dominant positive sentiment regarding the new capital city as a future solution and hope for Indonesia, although there are also negative criticisms.

Page 1 of 1 | Total Record : 6

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 6 No. 1 (2025): Journal Applied Statistics and Data Mining Vol. 5 No. 2 (2024): Journal Applied Statistics and Data Mining Vol. 5 No. 1 (2024): Journal Applied Statistics and Data Mining Vol. 4 No. 2 (2023): Journal Applied Statistics and Data Mining Vol. 4 No. 1 (2023): Journal Applied Statistics and Data Mining Vol. 3 No. 2 (2022): Journal Applied Statistics and Data Mining Vol. 3 No. 1 (2022): Journal Applied Statistics and Data Mining Vol. 2 No. 2 (2021): Journal Applied Statistics and Data Mining Vol. 2 No. 1 (2021): Journal Applied Statistics and Data Mining Vol. 1 No. 2 (2020): Journal Applied Statistics and Data Mining Vol. 1 No. 1 (2020): Journal Applied Statistics and Data Mining More Issue