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Articles 974 Documents
Implementation Of The Support Vector Machine Method In Predicting Student Graduation Abdillah, Syakira; Juni Yanris, Gomal; Sihombing, Volvo
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.1265

Abstract

Student graduation is an important indicator of the quality of education at a higher education institution. A high graduation rate not only indicates success in the learning process but also has a positive impact on the reputation of the institution. Conversely, a low graduation rate can be a signal of problems that require special attention. Various factors, both academic and non-academic, influence higher education institutions in ensuring timely student graduation. Therefore, we need a method that can accurately predict student graduation to carry out early intervention. This study aims to apply the support vector machine method in predicting student graduation. We chose this method due to its capacity to classify complex data. We use historical student data, such as Semester Achievement Index scores, as input variables to build a prediction model. We evaluate the model using precision, recall, and f1-score metrics. According to the study's findings, the support vector machine model's accuracy level is 71.20%. This method is good at predicting students who graduate with a precision of 95%, recall of 72%, and f1-score of 82%. However, the model's performance in predicting students who failed was less than satisfactory, with a precision of only 17%, a recall of 62%, and an f1-score of 26%. The imbalance in data between passed and failed students contributed to this result. The Support Vector Machine method effectively predicts student graduation for the majority class (passed), but requires special handling of the data imbalance to enhance the accuracy of predictions for the minority class (failed). Universities expect to use the results of this study to carry out early intervention and increase student graduation rates.
Comparison Of Support Vector Machine And Naïve Bayes Algorithms For Analyzing Public Interest In Espresso Coffee Rita, Sano; Halmi Dar, Muhammad; Nirmala Sari Hasibuan, Mila
International Journal of Science, Technology & Management Vol. 5 No. 4 (2024): July 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.814

Abstract

Given its increasing popularity, public interest in buying espresso coffee is an important concern for coffee industry players. To understand and predict this buying interest, the use of classification algorithms in data analysis is crucial. This study was conducted to compare the performance of two popular classification algorithms, namely Support Vector Machine and Naïve Bayes, in analyzing public interest in buying espresso coffee. This research problem is based on the need for an accurate predictive model in the coffee industry to aid in strategic decision-making related to marketing and sales. The proposed solution is to implement two different classification algorithms and assess their performance using a variety of performance evaluation metrics. The purpose of this study is to determine which algorithm is superior in terms of accuracy, precision, recall, and f1-score. The research method entails collecting data on public interest in purchasing espresso coffee, preprocessing data, implementing both algorithms, and evaluating each algorithm's performance. The results show that Naïve Bayes consistently outperforms Support Vector Machine in all performance evaluation metrics. Naïve Bayes achieved 94.00% accuracy, 91.40% precision, 100% recall, and 95.51% F1-Score, compared to Support Vector Machine, which achieved 90.00% accuracy, 88.60% precision, 96.90% recall, and 92.56% F1-Score. The conclusion of this study is that the Naïve Bayes classifier is more effective and efficient in predicting people's purchasing interest in espresso coffee compared to support vector machines. This advantage can be attributed to the ability of Naïve Bayes to handle data that may have non-normal distributions or independent variables.
Analysis of Rewards and Punishment on the Performance of State-Owned Enterprise Employees in Medan Region Suwarno, Bambang; Harahap, Arman
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i4.1199

Abstract

Motivating workers through the use of rewards and punishments, the management control system places an emphasis on output. Any decent employee will follow the rules set out by their employer and will push for their coworkers to do the same. Finding out whether company rewards and punishments have an effect on employee performance in a State-Owned Enterprise is the main objective of this study. Quantitative studies employ non-probability purposive sampling and associative causality studies. With the aid of SmartPLS, descriptive statistics were applied to 100 questionnaires. All of the study's variables were found to have a positive and statistically significant effect. With a t-statistic value of 4.218, employees believe that the company's performance reviews can positively affect their pay, benefits, and advancement opportunities. The company's punisment motivate employees to perform well in order to avoid pay cuts and promotion delays (t-statistic value 4.861). When workers' expectations regarding company assessments and reward are satisfied, their performance improves (t-statistic value 3.900). Therefore, it is reasonable to assume that, with proper implementation of evaluation and sanctions, staff performance will improve. While punishments are the most powerful incentive for improving performance, this study's original finding is that positive reinforcement in the form of awards can inspire loyalty and good conduct.
The Deformation Responses As The Resulted Of The Tectonics In Apaumagida (Apowo), Enarotali And Legare Mountain Area of Papua Province Gultom, Maran; Dandy Waromi, Doodle; Abdurrachman, Mirzam; Yaner Ayomi , Iwan; Steven Wetipo, Yafet; Disti Mambrasar , Ela
International Journal of Science, Technology & Management Vol. 5 No. 6 (2024): November 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i6.1212

Abstract

The deformation phenomenon in Central Mountain of Papua Province is very complex, isn’t there the uniformity of geology structure pattern (folds, joints, faults) as resulted of tectonics or reactivations of the geology structure of the lately rock to the upper early rock?. Therefore, measuring the geology structure had to be done with the surface geological mapping and the measured section traverse in the field. The research area distributed in three boundaries of tectonics in coordinate 135° 00’ 00” East - 136° 30’ 00” East and 3° 00’ 00” South - 4° 40’ 00” South. There are three research areas namely the Apaumagida area represent the Permian – Triassic Periods in coordinate 135°18’11,88” East - 135°43’20,14” East and 3°56’17,59” South - 4°8’28,44” South, the Enarotali area represent the Cretaceous – Paleocene Periods in coordinate 136°18’45,08” East - 136°29’42,00” East and 3°53’34,75” South - 4°5’16,03” South, and the Legare Mountain area represent the Tertiary – Quaternary Periods in coordinate 135° 28’ 54,87” East - 135° 47’ 16,80” East and 3° 25’ 31,17” South - 3° 6’ 6,25” South. According to the result and discussion, conclusioned that the direction of folds, jonts, faults were different between the oldest periods to the youngest periods, indicated by the direction diffrent of principal stress on N 5° – 27°E in Permian Period, N 349° - 358°E in Triassic Period, N 15° – 32°E in Cretaceous period, N 45° 54° E in Paleocene Period, N52° – 74°E in Tertiary Period N74°-78° E in Quarternary. Therefore, there were general pattern in the diffrent of folds, joints and faults from Permian – Triassic and Cretaceous – Paleocene but there’s conformity from the Tertiary – Quarternary. The general conclusion that the tectonic is actively roled for the geology structure developing in Central M.ountain area since Paleozoic to Quaternary.
The Effect of Rainfall Anomalies on the Productivity of Clove Plants (Syzygium aromaticum) and Management Strategies in Southeast Sulawesi Ardiansa, Feling; Sabaruddin, Laode; Alam, Syamsu
International Journal of Science, Technology & Management Vol. 6 No. 1 (2025): January 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i1.1219

Abstract

Climate change has caused rainfall anomalies that have an impact on decreasing the productivity of clove plants (Syzygium aromaticum). This study aims to analyze extreme rainfall anomalies in North Buton Regency and Kolaka Regency, assess its impact on the productivity of clove plants (Syzygium aromaticum), and formulate management strategies that can be applied to increase crop yields. The method used is a quantitative descriptive approach with linear regression analysis to determine the relationship between rainfall and clove productivity. The research population is clove farmers in North Buton Regency and Kolaka Regency, with a sample of three farmers in each village where the research is located. Rainfall data was obtained from the Betoambari Bau-Bau Meteorological Station and the Sangia Nibandera Kolaka Meteorological Station during the 2009–2023 period, while clove crop productivity data was obtained from farmer surveys and reports from the Central Statistics Agency. The results of the study show that North Buton Regency has an average annual rainfall of 1,971 mm with slightly wet climate characteristics (Type C), while Kolaka Regency has an average annual rainfall of 1,973 mm with wet climate characteristics (Type B). Based on the evaluation of the suitability of the rainfall land, it is included in the S1 category (very suitable). Regression analysis showed that rainfall had a less significant relationship with the productivity of clove plants. The results of the regression analysis showed that the determination coefficient (R2) of North Buton Regency was 12.59% and Kolaka Regency was 14.21%. Recommended management strategies to deal with rainfall anomalies in Kolaka Regency include improving drainage systems, soil management and conservation, and environmental sanitation. Meanwhile, in North Buton Regency, it includes the provision of irrigation, the use of mulch and the provision of organic matter.
The Influence of Product Quality, Price and Exchange Rate towards Export Volume On SME’s Creative Sculpture Industry in Mojokerto Setia Pratama, Ade; Sudarmiatin, Sudarmiatin
International Journal of Science, Technology & Management Vol. 6 No. 2 (2025): March 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i2.1237

Abstract

The aim of carrying out this research is to determine the influence of production concepts, prices and exchange rates on the export volume of the creative sculpture craft industry in Mojokerto, East Java, Indonesia. Research includes research with a quantitative approach. Primary data was collected using a questionnaire during the period February 2025. Based on the data that was collected, the total amount of data that can be used is sixty SME’s. The results show a simultaneous influence, the three independent variables used jointly influence the dependent variable. Partially, it was found that production did not have a significant influence, while international prices and exchange rates had a significant influence. It is hoped that the results of this data processing will have implications for creative sculpture industry producers in Indonesia in general to be able to improve quality in order to increase export volume so that it has a significant impact on economic growth and social welfare.
Cybersecurity with Quantum Cryptography: An Analysis of Current Techniques and Future Trends Omol, Edwin; Kibuku, Rachael; Abuonji, Paul
International Journal of Science, Technology & Management Vol. 6 No. 2 (2025): March 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i2.1269

Abstract

Using a systematic literature review methodology comprising the following stages: Identification of Relevant Literature, Screening and Selection, Data Extraction and Synthesis, Qualitative Analysis, and SWOT Analysis, this paper explores the role of quantum cryptography in enhancing cybersecurity. The analysis begins with an introduction to the vulnerabilities of classical cryptography in the context of quantum computing advancements. It delves into Quantum Key Distribution (QKD) protocols such as BB84 and E91, Quantum Random Number Generators (QRNGs), and post-quantum cryptography algorithms in detail. Real-world case studies are presented to illustrate the practical applications and advancements in quantum cryptographic techniques. Additionally, the paper addresses the challenges associated with implementing quantum cryptography and proposes strategies for its integration with existing cybersecurity frameworks. The discussion on future trends highlights anticipated technological advancements, potential applications in quantum internet and blockchain security, suggested research directions, and policy implications. The significance of quantum cryptography in securing sensitive data and establishing trust in critical sectors is thoroughly emphasized.
The Transformative Impact of Innovative Work Behavior on Entrepreneurial Orientation and Organizational Performance Anak Agung Ketut, Sriasih; I Made Hedy , Wartana; I Ketut , Yudana Adi; I Putu Bagus , Suthanaya
International Journal of Science, Technology & Management Vol. 6 No. 2 (2025): March 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i2.1278

Abstract

Innovative work behavior, entrepreneurial orientation, and organizational performance are central to achieving competitive advantage and resilience in dynamic business environments. This study examines how innovative work behavior affects organizational performance within firms. The study also explores the critical role of entrepreneurial orientation as both a direct influence on organizational performance and as a mediator in the relationship between innovative work behavior and organizational performance. This research was conducted on small & medium enterprise in the Province of Bali, Indonesia. Data were collected by 396 questionnaires from managers representing small & medium enterprise as research respondents and analysis was carried out using structural equation modelling. Results indicate that innovative work behavior has a positive impact on organizational performance, though its effect is enhanced significantly when mediated by entrepreneurial orientation. Specifically, the analysis reveals a strong relationship between innovative work behavior and entrepreneurial orientation, demonstrating that organizations fostering innovative behaviors are more likely to develop a proactive and risk-oriented culture. entrepreneurial orientation, in turn, shows a substantial direct positive effect on organizational performance, confirming its role as a critical driver of organizational success. Importantly, the mediation analysis suggests that entrepreneurial orientation partially mediates the relationship between innovative work behavior and organizational performance, channeling innovation efforts toward strategic objectives for optimal performance gains. The study contributes to the fields of innovation and entrepreneurship by elucidating the synergistic relationship between innovative work behavior and entrepreneurial orientation in driving organizational performance. The findings highlight the importance of fostering an entrepreneurial organizational culture that directs individual innovation toward strategic outcomes. This research provides valuable implications for organizational leaders aiming to enhance performance through integrated innovation and entrepreneurship strategies, and it sets the stage for future research exploring additional mediating factors and varied industry applications.
Determinants of Financial Literacy, Digital Literacy and Consumer Confidence Level Mediated by Fintech Literacy on Retail Industry Growth in Indonesia Sapta Rini, Anggarwati; Mukti Soma, Abdul
International Journal of Science, Technology & Management Vol. 6 No. 2 (2025): March 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i2.1280

Abstract

This study evaluates how financial literacy, digital literacy, and consumer confidence influence retail industry growth in Indonesia, emphasizing the mediating role of fintech literacy. In the era of industry 4.0, technology, especially fintech, has transformed conventional financial business models into digital ones, accelerating transactions and financial inclusion. The Covid-19 pandemic has further driven digitalization, although it has posed major challenges for the retail industry. This study aims to determine the actual impact of the development of fintech applications including the influence of financial literacy, digital literacy and consumer confidence levels on the development or growth of retail in Indonesia. This study uses a quantitative method with a focus on analysing the relationship between financial literacy, digital literacy, and consumer confidence levels on the growth of the retail industry, both directly and through fintech literacy mediation. The data used are primary data that include information on financial literacy, digital literacy, consumer confidence levels, fintech literacy, and retail growth. Data collection uses a Likert scale questionnaire with a scale of one to five for each variable. The analysis was carried out using multiple linear regression to identify direct relationships between variables and structural equation modelling (SEM) to comprehensively evaluate the influence of fintech mediation. This study shows that financial literacy has a positive and significant influence on retail growth without fintech literacy mediation. However, it does not have a significant effect on retail growth with fintech literacy mediation. In contrast to digital literacy, where digital literacy has a significant and positive effect on retail growth with fintech literacy mediation. While without fintech literacy, this variable does not have a significant effect on retail growth. The level of consumer confidence has a positive and significant effect on retail growth directly and with fintech literacy mediation.
Analysis of Public Satisfaction Levels Towards Hospital Services Using The K-Nearest Neighbors Method (Case Study: XYZ Regional Public Hospital) Ramadani Sibutar-Butar, Novia; Halmi Dar, Muhammad; Nirmala Sari Hasibuan, Mila
International Journal of Science, Technology & Management Vol. 6 No. 2 (2025): March 2025
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v6i2.1284

Abstract

The level of public satisfaction with health services is an important indicator that reflects the quality of services provided by a hospital. XYZ Hospital, as one of the main health service providers, strives to continuously improve the quality of its services by understanding and evaluating the level of patient satisfaction. However, challenges arise when it comes to accurately identifying and predicting patient satisfaction, given the diverse characteristics of patients and the complexity of the services provided. Therefore, this study aims to analyze the level of public satisfaction with XYZ Hospital services using the K-Nearest Neighbors method. This study employs a quantitative approach by utilizing patient satisfaction data obtained through a survey. We then analyze the data using the K-Nearest Neighbors method, known for its effectiveness in classifying based on data proximity. We carry out the model performance evaluation process through an evaluation matrix that includes accuracy, precision, recall, and F1-score. The results of the study show that the K-Nearest Neighbors model is able to classify patient satisfaction with an accuracy value of 94%, precision of 97.67%, recall of 95.45%, and F1-Score of 96.55%. These results indicate that the K-Nearest Neighbors model is not only accurate in predicting patient satisfaction but also consistent in classifying patients who are satisfied and dissatisfied. The study's conclusion is that the K-nearest neighbors method is very effective in analyzing and predicting the level of patient satisfaction at XYZ Hospital. This study makes a significant contribution by utilizing the K-Nearest Neighbors model as a potent predictive tool for assessing patient satisfaction, a tool hospitals can employ to enhance service quality. We hope that further development will enable the larger-scale implementation of this model, thereby enhancing the quality of health services across various hospitals.