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International Journal Of Science, Technology & Management (IJSTM)
Published by CV. Inara
ISSN : -     EISSN : 27224015     DOI : doi.org/10.46729
Core Subject : Science, Education, Agriculture, Engineering,
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation
International Journal of Science, Technology & Management (IJSTM) is an international scholarly refereed research journal which aims to promote the theory and practice of science, technology, innovation, engineering and management.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 1,077 Documents
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Effect Of Online Tracking System And Delivery Timeliness On Customer Satisfaction (Case Study On J & T Express Sampit) Oetama, Seanewati; Susanto, Hari; Rizwannur, Wahyu
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.v5i4.1157

Abstract

The title of this study is the effect of Online tracking system and Keteptan delivery time on customer satisfaction (Case Study on J&T Express Sampit). This study was conducted at J & T Express Sampit which is located at Jalan MT. Haryono No. 095, Mentawa Baru Hulu, District. Mentawa Baru Ketapang, East Kotawaringin Regency, Central Kalimantan. This study was conducted on customers who use the services of J & T Express Sampit with accidental sampling technique. And the data were tested using validity test, reliability test, hypothesis test and analysis of research data using descriptive analysis, multiple linear regression analysis, correlation coefficient analysis and determination analysis. Based on the results of the hypothesis test in this study is a T-test for online tracking system variables (X1) IE t count 3.146 > t table 2.00324 and a significant level of 0.001 < 0.05 then H0 rejected and Ha accepted. This means that there is a significant influence of Online tracking systems on customer satisfaction. As for the T-test for variable timeliness of delivery (X2) is t count 4.763 > t table 2.00324 and a significant level of 0.000 < 0.05 then H0 rejected and Ha accepted. This means that there is a significant influence between the timeliness of delivery to customer satisfaction. Then for the F-test, namely F count 25.098 > F table 3.16 and a significant level of 0.000 < 0.05 means that simultaneously the Online tracking system and delivery timeliness have a significant effect on customer satisfaction. R number of 0.690 shows the relationship / correlation between customer satisfaction with the independent variable is strong (significant). Adjust R Square of 0.552 means that 55.20% of customer satisfaction variable (Y) can be explained by Online Tracking System variables (X1) and delivery timeliness (X2). While the remaining 44.8% were influenced by other variables that were not included in this study. Based on the results of multiple linear regression test obtained by the equation Y = 1.233+ 0.407 (X1) + 0.580 (X2) means that the score/value of the constant ( ? ) shows that if there is no increase in the variables of the online tracking system and the accuracy of delivery time then the value of customer satisfaction is equal to 1.233. And each addition of one score / variable value of the online tracking system provides an increase of 0.407 to customer satisfaction with fixed X2 conditions and each addition of one score/variable value of delivery timeliness provides the same increase of 0.580 to customer satisfaction with fixed X1.
The Influence Of Brand Experience And Brand Image On Brand Loyalty With Brand Trust As A Mediation Variable (Case Study Of FCL Modest In Pekanbaru City) Sundari, Laisitha; Djunita Pasaribu, Rina; Sugiat, Maria
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.v5i6.1160

Abstract

Famys Circle Label (FCL) is a modest fashion brand that offers thousands of articles from well-known local modest brands in Indonesia and is the only brand in Pekanbaru, giving it a strong competitive edge in the modest fashion market due to its ability to attract a variety of customer groups with diverse tastes and fashion styles. This study aims to examine the effect of brand experience and brand image on brand loyalty, with brand trust as a mediating variable.The research uses a quantitative method with a descriptive approach to illustrate the characteristics of a group, such as the characteristics of users or products, estimate product users' characteristics, and understand users' perceptions of a product. The study uses non-probability sampling, with 384 respondents who are FCL consumers. The data was processed and analyzed using Structural Equation Modeling (SEM) with SmartPLS3 software.The study results show a partial positive and significant effect of brand experience and brand image on brand loyalty and brand trust. Simultaneous testing also showed the same results, where the independent variables had a positive and significant effect on the dependent variable, brand loyalty, mediated by the intervening variable brand trust among FCL consumers in Pekanbaru City.
The Role of Virtualization Technology to Increase Operational Cost Efficiency of Indonesian SMEs: Case Study of Internet Service Providers Iswara Sanantagraha, Arnastya; Puspitaloka Mahadewi, Erlina
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1161

Abstract

This research investigates the role of virtualization technology in enhancing operational cost efficiency for Indonesian Small and Medium-sized Enterprises (SMEs), specifically Internet Service Providers (ISPs). A quantitative approach, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) version 2.0, was employed to analyze data collected from 68 respondents representing 216 Indonesian SME ISPs. The study focused on the relationship between virtualization technology planning, adaptation capability, server consolidation services, and operational cost effectiveness. The findings demonstrate that adaptability to virtualization technology is the most significant factor influencing operational cost efficiency. Effective implementation requires careful planning and a proactive approach to adapting to the technology's demands. Server consolidation services play a crucial role in optimizing resource utilization and reducing costs while virtualization technology offers substantial benefits, SMEs should carefully assess their specific needs and resources before implementation. Factors such as infrastructure, skills, and business objectives should be evaluated to ensure successful adoption and maximize cost savings. This research provides a foundation for further exploration into the impact of virtualization technology on SMEs. Future studies could investigate the applicability of these findings in different contexts, such as other industry sectors or regions. Additionally, examining the long-term effects of virtualization technology adoption and the potential for scalability could offer valuable insights. Further research could also focus on the challenges and opportunities associated with virtualization technology adoption in SMEs with varying sizes and resources.
The Effect Addition of Soil Amandments and PGPR (Plant Growth Promoting Rhizobacteria) on the Growth and Yield of Cotton Plants Intercropped with Corn Plants in Dry Land of North Lombok Regency of Indonesia Siti Rohmaniati, Baiq; Sarjan, M.; Suwardji, Suwardji
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1162

Abstract

This research investigates the effect of soil amendments in the form of cow, form goat manures and PGPR biofertilizer on cotton plants intercropped with corn in the dry lands of North Lombok Regency. The research aims is to determine the growth and yield response of cotton plants due to the application of soil amendments and PGPR in an intercropped system with corn in dryland areas. The research was conducted from December 2023 to June 2024 in Andalan Village, Bayan District, North Lombok Regency. The method used is an experimental method with field trials. The design used was Randomized Block Design (RBD), incorporating two factors: soil amendment treatment (P) as the main plot and PGPR (K) concentration treatments as the subplot. Soil amendments consisted of three levels: P0 (no cow manure and no goat manure), P1 (20 tons/ha cow manure), P2 (20 tons/ha goat manure). PGPR concentration consisted of four levels: K0 (without PGPR), K1 (20 ml/liter PGPR application), K2 (30 ml/liter PGPR application), and K3 (40 ml/liter PGPR application). The research results indicated that the application of 20 tons/ha of goat manure (P2) produced the highest average across all observed parameters (plant height, number of leaves, branch number, stem diameter, and plant yield). Similarly, the application of 40 ml/liter PGPR produced the highest average for these observed parameters. Based on the results of the land equivalent ratio (LER) analysis, this integration system shows highly suitable and relevant to be applied in the dry lands of North Lombok.
Comparison of Machine Learning Algorithms in Public Sentiment Analysis of TAPERA Policy Sihombing, Eklesia; Halmi Dar, Muhammad; Aini Nasution, Fitri
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1164

Abstract

The rapid development of information technology has changed the way people interact and express their opinions on public policies, including the People's Housing Savings (Tapera) policy in Indonesia. People now primarily express their views openly on social media platforms like Twitter, generating a substantial amount of text data for analysis to understand public sentiment. However, the main challenge in this sentiment analysis is determining the most effective machine learning algorithm for classifying public opinion with high accuracy. This study aims to compare the performance of three machine learning algorithms, namely Naïve Bayes, Support Vector Machine, and Random Forest, in analyzing public sentiment towards the Tapera policy. This study analyzes public comment data obtained from Twitter. We measure the accuracy of each algorithm to determine its optimal performance in sentiment classification. The research method consists of several stages, starting with data collection, text preprocessing to clean and prepare data, and then applying the three algorithms to analyze sentiment. The results showed that Naïve Bayes had the highest accuracy of 69.17%, followed by Support Vector Machine with an accuracy of 68.42%, and Random Forest with an accuracy of 66.17%. This shows that Naïve Bayes is the most effective algorithm to use in sentiment analysis of public comments related to the Tapera policy, especially in the context of complex text data from social media. The conclusion of this study is that Naïve Bayes is superior in classifying public sentiment towards the Tapera policy compared to Support Vector Machine and Random Forest. As a result, this study makes a significant contribution to selecting the most appropriate machine learning algorithm for public sentiment analysis towards public policy, which in turn can help the government understand and respond to public perceptions more effectively.
The Influence of Workload and Work Environment on the Turnover Intention of Employees in PT. XYZ Rahmansyah, Ezra; Indiyati, Dian
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1165

Abstract

This research aims to investigate the impact of workload and work environment on employee turnover intention at PT. XYZ. High turnover intentions can disrupt workforce stability and result in significant costs for the company. Two factors often associated with turnover intention are workload and work environment. Excessive workload can cause stress and fatigue, while an unsupportive work environment can reduce employee satisfaction and commitment. The study uses a quantitative approach, distributing questionnaires to 107 employees and sampling using the saturated sample method. Data analysis was conducted using SEM-PLS software. The hypothesis test tested the influence of workload and work environment on employee turnover intention. The results showed that workload variable (X1) is in the high category, work environment variable (X2) is in the bad category, and turnover intention (Y) is in the medium category. Quantitative data analysis with SEM-PLS showed that workload variables do not have a significant influence on turnover intention, while work environment variables have a significant influence. The research aims to evaluate company management's attention to workload and work environment conditions, with one variable showing a significant positive influence on employee turnover intention
The Effect of E-WOM on Social Media Marketing on Purchase Intention (Case Study: Gallery Vinna) Rizka Utami, Fany; Ariyanti, Maya; Millanyani, Heppy
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1166

Abstract

This study aims to determine the effect of social media marketing through online word of mouth on purchase intention on the Tiktok Gallery Vinna platform as the object of research. The research method used is quantitative method, using an online survey by collecting 155 respondents. The data collected was analyzed with Smart PLS software to test the research hypothesis. The results showed that respondents' responses to Tiktok Gallery Vinna's social media received a good response, and respondents felt that the uploaded content could provide interesting and easy-to-understand information. Then, e-WOM has a significant effect on buying interest, and social media has the most influence on buying interest. The results also show that providing the latest information by utilizing social media can expand the network to attract buying interest in consumers. Therefore, this study examines the Tiktok platform which expands knowledge about the factors that influence attitudes and purchase intentions towards consumers through e-WOM, as well as the use of social media that have an impact on consumer purchase intentions. This research provides insight for SMEs who want to improve marketing strategies using social media.
Factors Analysis Of Digital Transformation Challenges In Alfamart Company Zaimah Nabila, Farah; Noviaristanti, Siska
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1167

Abstract

Technological advancements occur continuously without our notice, requiring us to adapt to them in all aspects of life. Most firms now recognize the importance of digital transformation as a strategy for improving services and business efficiency. Alfamart, a minimarket company in Indonesia's retail industry, is facing a technological transformation. Alfamart offers a range of product categories to accommodate diverse family requirements. The acceleration of digital transformation in Indonesia necessitates the application of digital technology as a digital platform that serves as the foundation for the Industry 4.0 ecosystem by including technologies such as IoT, big data, artificial intelligence, and augmented reality. This study uses quantitative and descriptive approaches to identify the characteristics that challenge digital transformation at PT Sumber Alfaria Trijaya, Tbk (Alfamart), particularly in the International Business & Technology division. The research employs two-factor analyses: CFA (Confirmatory Factor Analysis) and EFA (Exploratory Factor Analysis). According to the research results, 4 (four) factors influencing Alfamart's digital transformation, particularly in the International Business & Technology section, shape the company's digital transformation issues. These challenges include IT, digitalization, digital business, and digital skills.
Study On The Implementation Of Accreditation Status And Regional Public Service Agencies As A Strategic Model For Improving The Management Of Community Health Centers (Puskesmas) Alesa, Nelly; Kamaludin, Kamaludin; Suthia Hayu, Rina; Agustina Ekaputri, Retno
International Journal of Science, Technology & Management Vol. 4 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i5.1168

Abstract

Indonesia still has public health centre (Puskesmas) health care issues. The data from Bengkulu is comparable to those from the national level. It shows that Puskesmas has not maximised gatekeeping. We need responsible Puskesmas management and high-quality, sustainable health care to address these problems. Puskesmas' accreditation and Regional Public Service Agency status help the government improve Puskesmas administration. We need an improvement strategic model by synchronization because we still implement accreditation and BLUD separately. Given the current situation, this study explores potential synchronization strategies between accreditation and BLUD to enhance Puskesmas management. The study describes the condition of accredited and BLUD Puskesmas, identifies the problems, investigates the role capabilities of the parties involved, seeks to synchronise Puskesmas management, and formulates a strategy to improve management. This qualitative descriptive research uses a case study approach with purposive sampling to examine Puskesmas, an accredited and BLUD school in Bengkulu Province. Researchers conduct in-depth interviews, observations, library studies, and documentation. Researchers analyse data through collection, reduction, presentation, and verification or conclusion. They also triangulate data, sources, and procedures for data validity analysis. This research created a Puskesmas Management Improvement Strategy Model as a Novelty.
Comparative Analysis of K-Nearest Neighbors and Decision Tree Methods in Determining Students’ Purchase Interest in MacBook Laptops Fadilla Hasibuan, Intan; Irmayani, Deci; Sihombing, Volvo
International Journal of Science, Technology & Management Vol. 5 No. 5 (2024): September 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i5.1169

Abstract

In the context of increasingly competitive technology markets, companies need to know consumer preferences accurately to optimize product offerings and increase sales. Two classification methods that are often used in data mining, namely K-Nearest Neighbors and Decision Tree, have their own advantages and disadvantages. This study proposes a solution that involves processing student data using both classification methods to identify the most accurate and effective method for identifying purchase intentions. This study aims to compare the performance of the two methods in determining student purchase intentions for MacBook laptops. The research methodology includes collecting data from 100 students covering various factors such as user experience, design and portability, technical specifications, price, and security. This data is then classified using the K-Nearest Neighbors and Decision Tree methods. Furthermore, a confusion matrix is used to provide a more detailed picture of the performance of the two methods. The results of the study show that the Decision Tree method has a higher accuracy (91%) compared to K-Nearest Neighbors (88%). In addition, Decision Tree excels in other metrics such as precision (87.18% vs. 85.71%), recall (89.47% vs. 85.71%), specificity (91.94% vs. 89.66%), and F1-Score (88.31% vs. 85.71%). The decision tree also has a higher NPV value and lower FPR and FNR rates than K-Nearest Neighbors, indicating that it is superior in avoiding misclassification. The study's conclusion is that the Decision Tree method is more effective and accurate than K-Nearest Neighbors in determining students' purchase intentions for MacBook laptops. The decision tree shows better performance in almost all evaluation metrics, making it a more reliable method to use in consumer data analysis. The results of this study are expected to help companies choose a more appropriate and effective analysis method for their marketing strategies, as well as provide a basis for further research in the field of consumer purchase intention classification.

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