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Arman Harahap
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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 974 Documents
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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.
The Internal and External Factors in Prevention of Procurement Fraud in Goods and Services Based on E-Procurement Mansyuri, M. Ikhwan; Ramadhan, Muh. Syahru
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.v5i5.1170

Abstract

The process of goods and services procurement within the government environment still has vulnerabilities to fraud, which necessitates proper handling. This study aims to identify the factors that can influence efforts to prevent fraud in the procurement of goods and services using an e-procurement system. The data for this research was obtained through the distribution of questionnaires to employees at the Procurement Services Unit (ULP) and the Regional Financial and Asset Management Agency (BPKAD) Office of Dompu Regency. The sampling method used in this study is purposive sampling. Furthermore, the research data were tested using multiple regression analysis. This study demonstrates that the variables of technology utilization, e-procurement, internal control systems, organizational culture, employee ethics, and religiosity can influence the prevention of fraud in the procurement of goods and services. The research findings can serve as a reference for evaluating the use of information technology through e-procurement and the application of internal control systems for optimal results. Additionally, it is important to consider human resources, specifically employees, in maintaining organizational culture, good ethics, and religious values as a foundation for actions in the workplace to avoid various deviant or unlawful behaviors.
The Influence of Safety Leadership and Working Condition on Safety Behavior: A Systematic Literature Review Narendra, Made Diksi; Dudija, Nidya
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.v5i5.1171

Abstract

This systematic literature review aims to evaluate the influence of safety leadership dan working condition on safety behavior. The methodology involved a comprehensive search and selection of peer-reviewed articles published between 2017 and 2023. This research succeeded in reviewing 14 studies originating from 10 different countries and having topics related to safety leadership, working conditions and safety behavior. The results also indicate that safety leadership and working condition have a significant influence on safety behavior, both directly and indirectly. The review also highlights the critical role of organizational support in mitigating work accident rate. The study concludes that addressing safety behavior through strategic interventions and leadership development to enhance safety leadership and working condition related program can prevent work accident. By recognizing and addressing these issues, it is hoped that management will gain a better and more comprehensive understanding of issues related to safety behavior to give organizational support in order to correctly determine safety programs.
Development Of Strategy Map And Measuring Corporate Performance With Sustainability Balanced Scorecard Approach (Case Study On Renewable Energy Consultant Services Company Pt Xyz) Destianissa, Marsha; Pasaribu, Rina Djunita
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.v5i5.1172

Abstract

This study aims to develop a Strategy Map of PT XYZ based on the company's vision, mission, strategic goals and analyze the company's performance as measured using the Sustainability Balanced Scorecard (SBSC) method. The research method used is qualitative, which involves conducting in-depth interviews and analyzing company documents. According to the research results, the PT XYZ Strategy Map consists of a vision, mission, 17 company strategic goals and 34 measurement indicators. The company performance of PT XYZ in 2021 and 2022, measured by the 5 SBSC perspectives can be indicated as sufficient performance, which obtained a total scorecard of 0. Based on 34 measurement indicators, 13 obtained a good assessment, 13 obtained a poor assessment, 3 obtained a sufficient assessment, and 5 could not be calculated because the company did not have related numerical documents. In the future, PT XYZ needs to increase its efforts to improve company performance and improve company data management so that it is easier to identify the company's achievements or performance to a measurable extent. Further, PT XYZ needs to integrate sustainability goals that become the company's vision into the company's business strategy, one of which is using SBSC as a company performance measurement tool. In addition, PT XYZ needs to integrate its vision of contributing to sustainability development into the company's business strategy, one of which is the use of SBSC as a corporate performance measurement tool.

Page 82 of 98 | Total Record : 974

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