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HENGKI TAMANDO SIHOTANG
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Jurnal Mantik
Published by Institute of Computer Science
ISSN : -     EISSN : 26854236     DOI : -
Core Subject : Economy, Science, Education,
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media
Jurnal Mantik (Manajemen, Teknologi Informatika dan Komunikasi) is a scientific journal in information systems/informati containing the scientific literature on studies of pure and applied research in information systems/information technology,Comptuer Science and management science and public review of the development of theory, method and applied sciences related to the subject. Jurnal Mantik Penusa is published by Institute of Computer Science (IOCS). Editors invite researchers, practitioners, and students to write scientific developments in fields related to information systems/information technology,Comptuer Science and management science). Jurnal Mantik is issued 4 (FOUR) times a year.
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Articles 2,110 Documents
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Understanding the motivation of purchase decision making of KPOP Seventeen’s merchandise in Weverse Shop Alexandrina, Elke; Ramonita, Latifa; Anindita, Arnika
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5191

Abstract

In the midst of society and the economy gradually recovering after COVID-19, there is one group that seems to be continuing to strengthen: Korean Idol lovers. In Jakarta alone, the Blackpink concert which was held on March 11-12, 2023, was a huge success, including other K-Idol concerts. Fans not only chase the concert tickets, but also buy up all available merchandise. Gaon Music Chart data sales on the katadata page even record sales of K-Pop physical albums reaching 53.73 million albums in 2021. This is the first-time physical album sales have exceeded 50 million since 2011. Weverse Shop currently is the largest e-commerce intermediary business, selling K-Pop-themed merchandise through applications and websites, based in South Korea. This shop is the go-to place for fans who want to collect merchandise from K-Pop artists, especially those under Pledis Entertainment, one of which is “Seventeen”. The pattern of purchases by fans is so massive, that they are willing to pre-order because they want to be the first to have the merchandise. Several production errors and merchandise delivery problems that had occurred with Seventeen's merchandise did not reduce the number of buyers, instead they were still sold out.  The theory used in this study is the ERG Theory from Clayton Alderfer which states that motivation is based on three needs, namely Existence, Relatedness, and Growth
Understanding sales person turnover intention: relationship between job stress, workload and job satisfaction Trisnawati, Asih; Wiwoho, Gunarso
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5193

Abstract

Sales person becomes one of the assets and important factors in the company. What often happens in connection with the problem of sales person at the company is the employee's desire to leave his job (turnover intention) which ultimately requires the company to recruit employees. This research aims to find out the effect of job stress and workload on turnover intention mediated by job satisfaction. The data collection was carried out by disseminating questionnaires to 66 sales persons at PT Mitra Bisnis Keluarga Ventura Banyumas. The analytical tool used is SmartPLS 4 (Partial Least Squares) with structural equation modeling (SEM). The results of the study revealed the following: Job Stress (X1) has a negative and significant effect on Job Satisfaction (Z), Workload (X2) has a negative and significant effect on Job Satisfaction (Z), Job stress (X1) has a positive and significant effect on Turnover Intention (Y), Workload (X2) has a positive & significant effect on Turnover Intention (Y), Job Satisfaction (Z) has a negative and significant effect on Turnover Intention (Y), Job Stress (X1) has a positive & significant effect on Turnover Intention (Y) mediated by Job Satisfaction (Z) and Workload (X2) has a positive & significant effect on Turnover Intention (Y) mediated by Job Satisfaction (Z).
Impact of Palestine-Israel conflict on multinational stock prices use neural network and support vector machine comparison Andriani, Wresti; Gunawan, Gunawan; Wahyuning Naja, Naella Nabila Putri
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5196

Abstract

One form of prolonged geopolitical event is the conflict between Palestine and Israel, which has complex historical, political, and religious roots in the Middle East. This research aims to determine whether this conflict influences the share prices of the companies Unilever, McDonald's, and KFC. These three large companies are known as allies of one of the disputing countries. The method used by the Neural Network is compared with Support Vector Machine to find the best accuracy using RMSE and MAE. The greater the error value, the more affected the company is by this geopolitical factor. As a result, the accuracy of the SVM method is better than NN; the company most affected is KFC, with the RMSE value of 0.111, MAE of 0.020, followed by Unilever with RMSE 0.034, MAE 0.025 then McDonald's with RMSE 0.026 and MAE 0.116, is expected to help investors choose to invest in the company McDonald’s then Unilever.
Analysis of precious metal (gold) investment management at pt. antam tbk from a sharia economic perspective Madani Amir, Moch. Sayyid Salsabila; Wazin, Wazin; Peristiwo, Hadi
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5197

Abstract

Investment is a commitment to save a certain amount of funds to obtain a certain amount of profit in the future. Thus, the aim of this research is how to manage precious metal investment and how precious metal investment is viewed from an Islamic perspective. The approach taken in this research uses a qualitative approach with the library research method. The data sources in this research use primary and secondary sources. Primary includes journal articles, E-Books, and other internet media. While secondary such as online proceedings, magazines, newspapers, and word press. Meanwhile, the data collection technique in this research is collecting from the sources that have been mentioned and then classifying them to conclude. The analysis technique used is descriptive analysis. The results of this research show that explaining sharia principles in investing is important as a guide for society. investment activities explicitly or implicitly in a number of verses of the Koran and the sunnah of the Prophet Muhammad saw. who has been in business and has been Mecca's financial support partner for a long time. The conclusion of this research explains that based on the DSN MUI Fatwa Number 77/DSN-MUI/IV/2010 concerning non-cash buying and selling of gold, it is decided that if there is a non-cash buying and selling of gold, either through murabahah or through regular buying and selling, the law is permissible. only, as long as the gold is not an official medium of exchange
Testing posketanmu website with google penetration testing and OWASP Top 10 Sebrina, Aida Fitriya; Junaidi, Achmad; Sihananto, Andreas Nugroho
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5204

Abstract

Data integrity has become vital in the quickly evolving digital era, pushing cybersecurity to a critical concern. Securing cybersecurity is crucial for systems such as the Posketanmu website in Mojokerto Regency, as it is responsible for safeguarding sensitive personal information. The objective of this research is to detect, evaluate, and exploit on any security weaknesses present on the Posketanmu website. The methodology combines the Google Penetration Testing strategy with the latest OWASP Top 10 2021 criteria. The penetration testing procedure comprises five distinct steps: Initially, the process involves collecting data and comprehending the platform by utilizing several programs such as Nmap, Nslookup, Wappalizer, Whatweb, Whois, and Google Hacking. Furthermore, the process involves utilizing ZAP to do vulnerability scanning, resulting in the creation of thorough reports. Furthermore, doing a vulnerability assessment, which involves manual testing and classification according to OWASP standards. Furthermore, effectively capitalizing on all eleven identified vulnerabilities. Ultimately, the task involves adhering to the OWASP Top 10 2021 standards by documenting, reporting, and suggesting solutions for any identified issues. This investigation found and resolved four significant security vulnerabilities on the Posketanmu website: stored XSS, unset CSP header, unset Strict-Transport-Security header, and open redirect. The implementation of Google Penetration Testing and adherence to the OWASP Top 10 2021 criteria have greatly improved the security of the Posketanmu website, ensuring the protection of Mojokerto Regency citizens' data.
Performance evaluation of single moving average and exponential smoothing in shallot production prediction Santoso, Aisyach Aminarti; Surorejo, Sarif; Kurniawan, Rifki Dwi; Gunawan, Gunawan
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5205

Abstract

Shallots are a strategic commodity that has significant health benefits, including its ability to prevent cancer. The commodity also plays an important role in the agricultural economy, especially in Indonesia, where high demand in domestic and international markets contributes greatly to farmer’s income. However, fluctuations in shallot production often lead to price instability, which has a negative impact not only on consumers but also on the sustainability of farmers' income. This research aims to develop a forecasting model that can assist in more effective planning of shallot production. To achieve this goal, the study tested and compared two forecasting methods: Single Moving Average (SMA) and Single Exponential Smoothing (SES), which are known for their ease of implementation and accuracy in predicting time series data. Using a dataset of shallot production from Brebes Regency over the period 2020-2023, the study found that Single Exponential Smoothing consistently provided more accurate results than Single Moving Average. SES performance is more responsive to recent changes in production data, which is particularly important given the rapid fluctuations that often occur in the agricultural sector. The findings suggest that the application of the SES method in shallot production forecasting can facilitate more informed decision-making in production management and distribution planning, potentially stabilizing market prices and improving farmers' economic conditions
The impact of customer satisfaction on repurchase intention in e-commerce: a study in indonesia Afinia, Shevila
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5206

Abstract

The rapid growth of e-commerce in Indonesia has transformed the digital economy landscape, becoming a key driver of economic development. This study aims to investigate the relationship between customer satisfaction and repurchase intention in the context of e-commerce in Indonesia. Specifically, the research focuses on understanding how customer satisfaction impacts the likelihood of customers to repurchase products or services from online platforms. The research employs a quantitative approach, utilizing a sample of 90 respondents in Semarang, Indonesia, selected through purposive sampling. Data collection is conducted through structured questionnaires, with Likert scales used to assess customer responses. Statistical analysis, including validity testing and multiple linear regression, is performed using SPSS software to examine the relationship between customer satisfaction, trust, electronic word-of-mouth, and repurchase intention. The results indicate a significant and positive relationship between customer satisfaction and repurchase intention in e-commerce. Statistical tests reveal that both customer satisfaction and trust have a significant impact on repurchase intention, with p-values of 0.023 and 0.019, respectively. In conclusion, the findings highlight the importance of prioritizing customer satisfaction in e-commerce operations to enhance customer loyalty and drive repeat purchases. E-commerce platforms in Indonesia should focus on building trust, delivering quality service, and fostering positive customer experiences to increase repurchase intention and sustain long-term success in the competitive market
Analysis of marketing strategies for home industry MSMEs on consumer behaviour Fitriany, Fitriany
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5207

Abstract

Within the MSME sector, home industries stand out as one of the pillars that drive the local economy. Despite their small scale, home industries have great potential to grow and contribute more to the national economy if managed with the right marketing strategy. Therefore, the main challenge is how MSMEs can convince themselves to adopt digital technology as part of their marketing strategy. Marketing is a key element in business success, including for home industry MSMEs. The purpose of this research analysis is carried out because it departs from one of the main challenges for home industry MSMEs in implementing marketing strategies is limited funds. Therefore, marketing strategies must be designed in such a way as to be effective but still cost-effective or in accordance with the capacity of the business. The research method is qualitative with the design used in this research is a descriptive method with a type of case study. The data collection technique using observation provides direct data from the field and interviews provide insight from the resource person's perspective. The results showed that Fatur Bakery has great potential by utilising strengths and overcoming weaknesses. Market opportunities can be maximised with advanced marketing strategies and improved management. Threats of competition and market changes are anticipated by innovation and rapid adaptation, increasing customer satisfaction and loyalty.
Application of machine learning for short-term climate prediction in Indonesia Gunawan, Gunawan; Andriani, Wresti; Aimar Akbar, Aminnur
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5215

Abstract

This study explores the Application of Machine Learning for Short-Term Climate Prediction in Indonesia, focusing on enhancing forecast accuracy through advanced computational models. The primary objective was to develop and validate Random Forest and Support Vector Machine (SVM) models to predict short-term climate conditions accurately across ten major Indonesian cities. Employing a quantitative approach, the study utilized experimental design, rigorous data analysis, and model validation using historical weather data from April 2024 provided by the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG). The results indicate that both Random Forest and SVM significantly outperform traditional climate prediction models, with Random Forest achieving an average accuracy of 87.5% and SVM 85.2%. These findings underscore the potential of machine learning to revolutionize short-term climate predictions in regions with complex meteorological dynamics like Indonesia, offering substantial implications for disaster preparedness, agricultural planning, and urban management. Future research can expand upon these models by incorporating real-time data and exploring deep learning techniques to enhance predictive reliability further
Optimizing the viola-jones algorithm for robust face recognition in variable lighting and orientation conditions Gunawan, Gunawan; Aisyah, Nur; Santoso, Nugroho Adhi
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5220

Abstract

Facial recognition is a critical technology in digital security, driven by significant advances in computer vision. This research focuses on optimizing the Viola-Jones algorithm to improve the accuracy and speed of face detection by adjusting parameters and integrating more sophisticated image processing techniques. Facing challenges such as suboptimal lighting and variations in face orientation, the study adopted a rigorous experimental design, in-depth quantitative analysis, and robust model validation. Of the ten facial images collected, all were intensively processed using Haar-like features to identify significant patterns and adjust algorithm parameters in Python. This optimization process increased performance from 7 identified faces to 9 post-optimization identified faces and a substantial decrease in detection time from 0.0065 seconds to 0.0017 seconds per image. The comprehensive evaluation showed an increase in accuracy from 70% to 90%, recall from 70.0% to 90.0%, Precision remained constant at 100.0%, and F1-score from 82.35% to 94.74%. These results show that the optimization has increased the algorithm's sensitivity to changes in light intensity and face orientation and improved the effectiveness of facial recognition systems in complex and dynamic security scenarios while providing concrete evidence of the benefits of using Haar-like features in the Viola-Jones algorithm

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