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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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Implementation of the K-Means Clustering Method in Clustering Poor Population in Bandar Kumbul Village, Labuhanbatu Regency Maharani, Aulia; Juni Yanris, Gomal; Aini Nasution, Fitri
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.v6i1.1209

Abstract

Poverty is one of the crucial social problems in rural areas. The problem of poverty in rural areas is increasingly in the spotlight because of its broad impact on the community's economic and social sustainability. The varying levels of poverty require an appropriate analytical approach to design effective intervention programs. In an effort to understand and address this problem, this study uses the K-Means Clustering method to group the poor population. We use K-Means clustering to identify and group hamlets based on their poverty levels. This study aims to categorize the hamlets in Bandar Kumbul Village into multiple clusters according to their poverty levels, thereby identifying which hamlets necessitate more focused attention. The research methods used include collecting data on the number of poor people from 2013 to 2022 in each hamlet, data preprocessing, applying the Elbow method to determine the optimal number of clusters, and applying the K-Means Clustering algorithm to group the hamlets. The results of the study show that there are three main clusters with different characteristics. Cluster 0 includes Hutaimbaru and Mailil Julu hamlets with high poverty levels. Cluster 1 only includes the Pasir Sidimpuan hamlet, which has medium poverty levels. Cluster 2 includes Aek Mardomu, Bandar Kumbul, Mailil Jae, Sidodadi, and Singga Mata hamlets with low poverty levels. Variations in distance from the cluster center indicate significant differences in the distribution of poverty in each hamlet. The K-Means Clustering method is effective in identifying and grouping hamlets based on poverty levels, providing useful insights for the government and stakeholders to design more targeted intervention programs. Clusters with high poverty levels require immediate intervention, while clusters with medium and low poverty levels require maintenance and support to prevent an increase in poverty. This study provides a strong foundation for decision-making and policies to reduce poverty levels in Bandar Kumbul Village more effectively and sustainably.
Web-based Palm Oil Seedling Sales Information System (Case Study: CV. XYZ) Ramadhani, Siska; Sihombing, Volvo; Juni Yanris, Gomal
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.v6i1.1213

Abstract

Oil palm seedling sales are one of the important aspects of the agricultural industry in Indonesia. However, conventional sales processes often encounter various obstacles, such as limited access to information for consumers, difficulties in inventory management, and low operational efficiency. To overcome these problems, this study aims to develop a Web-based Oil Palm Seedling Sales Information System at CV. XYZ. We designed this system to offer a comprehensive solution for sales management, encompassing stock recording and real-time transaction processing. This study uses a system development method with the waterfall method, in which the development stages include requirements, system design, implementation, verification, and maintenance. We collected data through direct observation at CV XYZ, interviews with management and customers, and related literature studies. Users then tested the prototype to identify potential problems and gather feedback for system improvement. According to the study's findings, the implementation of this web-based information system has resulted in increased efficiency in sales and inventory management. Users can easily access product information, place orders, and track the status of their orders. In addition, this system also allows integration with payment gateways, so that the transaction process becomes faster and safer. This system simplifies customer data management, sales recording, and financial report analysis from a management standpoint. At CV. XYZ, the development of the Web-based Palm Oil Seedling Sales Information System positively impacted operational efficiency and effectiveness. This system not only increases customer satisfaction by providing faster and more transparent services, but it also helps management make more accurate decisions based on available data. We need to add more advanced data analysis features to forecast sales trends and market demands, and integrate the system with e-commerce platforms to broaden our market reach.
Rhizobacteria as Biological Agents in Enhancing the Viability and Vigor of Rice Seeds (Oryza sativa L.) Kadek Pande Prasetia Wiguna, I; Ayu Kade Sutariati, Gusti; Corina Rakian, Tresjia
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.v6i1.1263

Abstract

This study aims to examine the effectiveness of rhizobacteria in stimulating plant growth and acting as a biofertilizer that can enhance the viability and vigor of rice (Oryza sativa L.) seeds. The research was conducted at the Agronomy Unit Laboratory, Faculty of Agriculture, Halu Oleo University, from September to October 2024. The study was designed based on a randomized block design (RBD), consisting of 11 test isolates and 1 control. These isolates were tested for their effectiveness in improving the viability and vigor of rice (Oryza sativa L.). The test was carried out by soaking seeds in a rhizobacteria suspension, then germinating the seeds using a standard germination procedure. The observed variables included germination capacity, vigor index, seed uniformity, relative growth rate, and T50. The results showed that seed treatment with rhizobacteria significantly increased the viability and vigor of rice seeds (Oryza sativa L.), as seen in the variables of germination capacity, vigor index, T50, and relative growth rate. From this study, 2 isolates were selected that have the potential as growth promoters for rice seeds, namely DMW 4 and DSS 3. Further research is needed to test the effectiveness of these isolates in improving the growth and yield of rice (Oryza sativa L.) under field conditions.
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.

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