Jurnal Politeknik Negeri Batam (PoliBatam)
Not a member yet
3001 research outputs found
Sort by
Comparative Study of the ARIMA Method and Multiple Linear Regression in Metro City Population Growth Projections
No full textThis study aims to compare the effectiveness of the ARIMA (Autoregressive Integrated Moving Average) method and multiple linear regression in projecting population growth in Metro City, Lampung. The analysis utilizes population data from 2010 to 2022, sourced from the Central Statistics Agency and the Population and Civil Registration Office. The methodologies employed include ARIMA modelling and multiple linear regression, with model evaluation conducted using metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The findings indicate that the multiple linear regression model predicts an average population growth of 2,200 individuals per year, resulting in a total projection of 185,032 by 2030. In contrast, the ARIMA (2,1,1) model forecasts a total population of 169,500 for the same year. The conclusion drawn from this research suggests that while both methods possess distinct advantages, ARIMA is more effective in capturing seasonal patterns and long-term trends, whereas multiple linear regression offers greater interpretability. This study recommends the complementary use of both methods to enhance the accuracy of population growth projections.This study aims to compare the effectiveness of the ARIMA (Autoregressive Integrated Moving Average) method and multiple linear regression in projecting population growth in Metro City, Lampung. The analysis utilizes population data from 2010 to 2022, sourced from the Central Statistics Agency and the Population and Civil Registration Office. The methodologies employed include ARIMA modelling and multiple linear regression, with model evaluation conducted using metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The findings indicate that the multiple linear regression model predicts an average population growth of 2,200 individuals per year, resulting in a total projection of 185,032 by 2030. In contrast, the ARIMA (2,1,1) model forecasts a total population of 169,500 for the same year. The conclusion drawn from this research suggests that while both methods possess distinct advantages, ARIMA is more effective in capturing seasonal patterns and long-term trends, whereas multiple linear regression offers greater interpretability. This study recommends the complementary use of both methods to enhance the accuracy of population growth projections
Implementation of K-Means Clustering in Grouping Sales Data at Zura Mart
No full textThe efficiency of inventory management and targeted marketing strategies relies on understanding sales patterns and stock levels dynamically. This study proposes a K-Means Clustering-based approach combined with a real-time stock monitoring system to classify products adaptively. The dataset consists of 87 products with variables including total sales, average sales, and remaining stock. The analysis process begins with data normalization to standardize parameter scales, followed by the application of the Elbow Method, which determines the optimal number of clusters as three. The clustering results indicate that Cluster C0 (21 products) has high sales but low stock, Cluster C1 (59 products) has stable sales with moderate stock, and Cluster C2 (7 products) has low sales but abundant stock. These findings not only provide strategic insights for inventory optimization but also serve as the foundation for developing an automated recommendation system that links clustering results with adaptive promotional strategies and restock prediction. Thus, this study contributes to enhancing Zura Mart\u27s business efficiency through the integration of data-driven decision-making in inventory management and marketing.The efficiency of inventory management and targeted marketing strategies relies on understanding sales patterns and stock levels dynamically. This study proposes a K-Means Clustering-based approach combined with a real-time stock monitoring system to classify products adaptively. The dataset consists of 87 products with variables including total sales, average sales, and remaining stock. The analysis process begins with data normalization to standardize parameter scales, followed by the application of the Elbow Method, which determines the optimal number of clusters as three. The clustering results indicate that Cluster C0 (21 products) has high sales but low stock, Cluster C1 (59 products) has stable sales with moderate stock, and Cluster C2 (7 products) has low sales but abundant stock. These findings not only provide strategic insights for inventory optimization but also serve as the foundation for developing an automated recommendation system that links clustering results with adaptive promotional strategies and restock prediction. Thus, this study contributes to enhancing Zura Mart\u27s business efficiency through the integration of data-driven decision-making in inventory management and marketing
Comparison of K-Nearest Neighbors and Naive Bayes Classifier Algorithms in Sentiment Analysis of 2024 Election in Twitter (X)
No full textThis study compares the performance of the K-Nearest Neighbors (K-NN) and Naive Bayes Classifier (NBC) algorithms in sentiment analysis of the 2024 Regional Election (Pilkada) based on Indonesian local data sourced from platform X. A total of 1,187 tweets were collected through crawling, followed by extensive preprocessing and manual sentiment labeling by a professional linguist to ensure data validity and reliability. The study highlights NBC\u27s superior accuracy (81.05%) compared to K-NN (75.26%), largely due to the characteristics of short-text social media data that align with NBC\u27s independence assumptions. Key terms identified through TF-IDF analysis include “pilkada”, “2024”, and “damai” in positive sentiment, while “mahkamah konstitusi” and “kalah” dominated negative sentiment. The results imply that although public discourse largely supports the election process, critical sentiments toward election dispute issues persist. These findings offer practical implications for election authorities, policymakers, and digital campaign strategists, particularly in optimizing public communication strategies, early detection of potential conflicts, and designing public opinion monitoring systems based on real-time sentiment analysis. By leveraging high-quality labeled local data, this study makes a significant contribution to modeling public opinion dynamics in Indonesia during political events.This study compares the performance of the K-Nearest Neighbors (K-NN) and Naive Bayes Classifier (NBC) algorithms in sentiment analysis of the 2024 Regional Election (Pilkada) based on Indonesian local data sourced from platform X. A total of 1,187 tweets were collected through crawling, followed by extensive preprocessing and manual sentiment labeling by a professional linguist to ensure data validity and reliability. The study highlights NBC\u27s superior accuracy (81.05%) compared to K-NN (75.26%), largely due to the characteristics of short-text social media data that align with NBC\u27s independence assumptions. Key terms identified through TF-IDF analysis include “pilkada”, “2024”, and “damai” in positive sentiment, while “mahkamah konstitusi” and “kalah” dominated negative sentiment. The results imply that although public discourse largely supports the election process, critical sentiments toward election dispute issues persist. These findings offer practical implications for election authorities, policymakers, and digital campaign strategists, particularly in optimizing public communication strategies, early detection of potential conflicts, and designing public opinion monitoring systems based on real-time sentiment analysis. By leveraging high-quality labeled local data, this study makes a significant contribution to modeling public opinion dynamics in Indonesia during political events
Comparison of Random Forest and Support Vector Machine Methods in Sentiment Analysis of Student Satisfaction Questionnaire Comments at ITB STIKOM Bali
No full textITB STIKOM Bali is one of the higher education institutions in Bali that focuses on academic activities, particularly in the field of Information Technology. To maintain its educational quality, the Quality Assurance Department collaborates with the Center for Information and Communication (Puskom) to distribute a student satisfaction questionnaire at the end of each semester. In evaluating student satisfaction with campus facilities, the comment section is one of the key indicators, featuring the question: “Based on your experience, please describe which AAK services you found disappointing and in need of improvement.” This study compares the performance of the Random Forest and Support Vector Machine (SVM) methods in conducting sentiment analysis on historical student satisfaction comments. The research involved several stages, including literature review, data collection, preprocessing, transformation, data mining, evaluation, and visualization. The results demonstrate strong accuracy, precision, recall, and F1-scores for both methods using an 80:20 data split. Before applying the SMOTE technique, the best result was achieved by the Support Vector Machine method with a score of 0.90, while the Random Forest method yielded an accuracy of 0.81, precision of 0.85, recall of 0.81, and F1-score of 0.76. After applying SMOTE, both methods achieved an improved and equal score of 0.90. The study also produced an excellent classification result based on the ROC curve. It is expected that this research can serve as an additional reference for the assessment of student satisfaction at ITB STIKOM Bali at the end of each academic semester.ITB STIKOM Bali is one of the higher education institutions in Bali that focuses on academic activities, particularly in the field of Information Technology. To maintain its educational quality, the Quality Assurance Department collaborates with the Center for Information and Communication (Puskom) to distribute a student satisfaction questionnaire at the end of each semester. In evaluating student satisfaction with campus facilities, the comment section is one of the key indicators, featuring the question: “Based on your experience, please describe which AAK services you found disappointing and in need of improvement.” This study compares the performance of the Random Forest and Support Vector Machine (SVM) methods in conducting sentiment analysis on historical student satisfaction comments. The research involved several stages, including literature review, data collection, preprocessing, transformation, data mining, evaluation, and visualization. The results demonstrate strong accuracy, precision, recall, and F1-scores for both methods using an 80:20 data split. Before applying the SMOTE technique, the best result was achieved by the Support Vector Machine method with a score of 0.90, while the Random Forest method yielded an accuracy of 0.81, precision of 0.85, recall of 0.81, and F1-score of 0.76. After applying SMOTE, both methods achieved an improved and equal score of 0.90. The study also produced an excellent classification result based on the ROC curve. It is expected that this research can serve as an additional reference for the assessment of student satisfaction at ITB STIKOM Bali at the end of each academic semester
The Influence of Work Flexibility on Job Satisfaction and Performance of Generation Z
No full textThis study examined the influence of work flexibility and job satisfaction on performance among Generation Z employees at the Indonesian Ministry of Defense Office. This study comprised a saturated sample of 107 participants. This paper utilized a quantitative analysis using survey methodology, questionnaires, and structural analysis techniques with Smart-PLS. The study’s findings indicated that Work Flexibility has a significant positive effect on Job Satisfaction. Work flexibility significantly affects employees\u27 assessment of their level of satisfaction. Flexible work arrangements allow individuals to optimize their time management and increase job satisfaction. Job satisfaction will inherently improve employee performance
Evaluation of Managers\u27 Entrepreneurial Skills and Their Impact on Organizational Productivity in Selected Retail Store in Bulacan Philippines
No full textThe comparative study between manager’s entrepreneurial skills and organizational productivity perceives a situation as fair when they obtain equivalent results for similar inputs, in accordance with the equity idea. The study aimed to assess the manager’s entrepreneurial skills towards organizational productivity of selected convenience store in Bulacan and used correlation with descriptive – quantitative design. Findings revealed that there were more female, 51.0 percent, more were in the age from 14 to 60 years old with 58.0 percent, in married category with 60.0 percent, with educational attainment College Graduates with 48.0 percent, in line managers has 52.0 percent. Data showed the average mean of all factors of work performance was 3.47 (SD = 0.52) facing as very highly skilled. The organizational productivity with an overall mean of 3.45, (SD = 0.51), with an interpretation of Very High Productive. This result will be guided that will provide continuous service and implementing flexible working policies to accommodate themselves to competition, often apply different working status together to achieve targets
A STUDY OF ENTERPRISE VALUE IN INDONESIAN MANUFACTURING FIRMS: EVIDENCE FROM IDX-LISTED COMPANIES
No full textThe research study examined the influence debt policy, profitability, company performance, and investment decisions on the value of enterprises within the manufacturing sectors which listed on the Indonesia Stock Exchange (IDX) from 2018 into 2022. We included 15 companies in the sample and conducted the analysis using multiple linear regression with SPSS 25. The findings indicated that the debt policy (DER) had a significant negative impact on firm value, evidenced by a t count of -3.178 and a significance level of 0.002. The impact of profitability (ROE) on firm value is notably positive, as evidenced by a t amount of 9.110 and a significance level 0.000. The company performance, measured by ROA, had a significantly negative impact on enterprise value, evidenced by a t count of -0.3288 and a significance level 0.002. In the meantime, investment decisions (CAPBVA) do not significantly influence enterprise value, as indicated by a t count of 1.991 and a corresponding significance level. This study offers investors and company management a deeper understanding of the elements that contribute to firm value in the manufacturing industry.Penelitian dilakukan untuk melakukan kajian mengenai nilai sebuah perusahaan bidang manufaktur terigistrasi pada Bursa Efek Indonesia (BEI) periode 2018-2022 dengan variebel prediktor kebijakan hutang, profitabilitas, kinerja perusahaan, dan keputusan investasi. Jumlah sampel yang digunakan sebannyak 15 perusahaan dengan Metode regresi linear berganda yang diolah menggunakan SPSS 25. Penelitian ini menunjukkan bahwa kebijakan hutang (DER) memiliki pengaruh signifikan negatif terhadap nilai perusahaan dengan t hitung -3,178 dan nilai signifikansi 0,002. Profitabilitas (ROE) berpengaruh signifikan positif terhadap nilai perusahaan dengan t hitung 9,110 dan nilai signifikansi 0,000. Kinerja perusahaan (ROA) berpengaruh signifikan negatif terhadap nilai perusahaan dengan t hitung -0,3288 dan nilai signifikansi 0,002. Sementara itu, variable keputusan investasi (CAPBVA) tidak berpengaruh secara signifikan terhadap nilai perusahaan manufaktur. dengan t hitung 1,991 dan nilai signifikansi 0,050. Studi ini menawarkan pemahaman yang mendalam bagi investor dan manajemen perusahaan mengenai elemen-elemen yang berkontribusi terhadap nilai perusahaan dalam industri manufaktur
TAX AVOIDANCE: PROFITABILITAS, LIKUIDITAS DAN FINANCIAL DISTRESS PERAN UKURAN PERUSAHAAN SEBAGAI MODERASI
No full textThe purpose of this study is to empirically test the effect of profitability, liquidity and financial distress on tax avoidance by adding company size as a moderating variable in energy sector companies listed on the IDX during the period 2021-2023. In this study, the Random Effect Model (REM) is the selected testing model using the Eviews program. This study uses a quantitative approach. The sample selection method uses purposive sampling, which produces 40 companies as samples. The results of the study show that profitability and liquidity have no effect on tax avoidance, while financial distress has an effect on tax avoidance. In addition, company size is unable to moderate the effect of profitability and liquidity on tax avoidance, while company size is able to moderate the effect of financial distress on tax avoidance.Tujuan dari penelitian Ini adalah untuk menguji secara empiris pengaruh profitabilitas, likuiditas dan financial distress terhadap tax avoidance dengan menambahkan ukuran perusahaan sebagai variabel moderasi pada perusahaan sector energy yang terdaftar di BEI selama periode 2021-2023. Dalam penelitian ini Random Effect Model (REM) menjadi model pengujian yang terpilih menggunakn program Eviews. Penelitian ini menggunakan pendekatan kuantitatif. Metode pemilihan sampel menggunakan purposive sampling, yang menghasilkan 40 perusahaan sebagai sampel. Hasil penelitian menunjukkan profitabilitas dan likuiditas tidak berpengaruh terhadap tax avoidance, sedangkan financial distress memiliki pengaruh terhadap tax avoidance. Selain itu ukuran perusahaan tidak mampu memoderasi pengaruh profitabilitas dan likuiditas terhadap tax avoidance, sedangkan ukuran perusahaan mampu memoderasi pengaruh financial distress terhadap tax avoidance
Applying the Diffusion of Innovation Theory to Address the Challenges of Implementing PSAK 55 in Rural Banks
No full textThis study aims to provide recommendations for addressing the challenges that arise in the implementation of PSAK 55 in Rural Banks (BPR). The research employs a descriptive qualitative approach using interview techniques, analyzed with NVivo12 Pro software through content analysis, thematic analysis, and constant comparative methods. The findings reveal several key obstacles, including limited human resource competence in calculating the fair value of collateral and estimating future cash flows, both of which are essential for determining CKPN (Allowance for Impairment Losses). These challenges are further exacerbated by doubts among many BPR practitioners regarding the effectiveness of PSAK 55 in reducing credit risk losses, as the standard has never been implemented in the BPR sector before. In response to these barriers, this study offers strategic recommendations based on the Diffusion of Innovation Theory, including enhanced dissemination of information about PSAK 55, strengthened collaboration among BPRs through peer support mechanisms—such as initiatives by BPRKU 3 to assist BPRKU 1 and 2 by providing CKPN calculation templates and technical training and active regulatory involvement in promoting broader acceptance of the standard. Accordingly, this research contributes conceptually by applying the Diffusion of Innovation Theory to explain the adoption process of PSAK 55 within the practical context of BPRs. It also provides practical contributions by offering actionable recommendations that can be used by professional associations to design training and outreach programs, and by BPRs to prepare internal strategies for more effective implementation of PSAK 55.This study is examined and provide recommendation about challenges the implementation of PSAK 55 in Rural Banks (BPR). This research utilizes a descriptive qualitative approach. Data were collected through interviews and subsequently analyzed using NVivo12 Pro, employing content analysis, thematic exploration or analysis and the constant comparative method. Additionally, this study refers to the Diffusion Theory of Innovation to analyze and provide recommendations regarding the challenges in implementing PSAK 55 in BPRThis study identifies several potential obstacles in implementing PSAK 55, including the limited capacity of human resources to evaluate and interpret objective indicators of asset impairment, difficulties in determining the market value of collateral, projecting future cash flows, and system limitations in calculating impairment allowances (CKPN). These issues are rooted in skepticism among practitioners about the practical effectiveness of PSAK 55 in mitigating losses from Non-Performing Loans (NPL), given that the standard has not previously been applied within BPR, despite the recognition that the current PPAP (Provision for Productive Asset Write-Off) method is suboptimal. In response, the study offers strategic recommendations grounded in the Diffusion of Innovation Theory to help address and overcome these barriers. These include enhancing knowledge dissemination, fostering peer-to-peer support such as BPRKU 3 providing calculation templates and educational assistance to BPRKU 1 and 2 and encouraging regulatory reinforcement to reduce resistance and improve the adoption process of PSAK 55 across different BPR levels
PERAN ORANG TUA DAN SIKAP MATERIALISME MEMPENGARUHI KEPUTUSAN MENABUNG GEN-Z: LITERASI KEUANGAN SEBAGAI VARIABEL INTERVENING
No full textThis research aims to study the factors that influence gen-z\u27s saving decisions, focusing on financial literacy, the role of parents, and materialism. The research respondents were 340 students majoring in Management and Business at Batam State Polytechnic. This research uses a quantitative approach which consists of several stages, such as data collection, data processing using SmartPLS 3, outer and inner tests, hypothesis testing, and drawing conclusions. The research results reveal the significant role of parents in shaping the financial literacy and saving decisions of Gen-Z. Financial literacy also has a positive and significant effect on gen-z\u27s saving decisions. The interesting finding that the materialism variable, which was previously considered negative, has a positive influence on Gen-Z\u27s saving decisions, highlights the complexity of financial behavior. This research provides an important theoretical contribution by applying the Theory of Planned Behavior (TPB) to financial literacy, the role of parents, and materialism in saving decisions. Practically, this research provides a clear view for gen- z and parents regarding the factors that influence saving decisions, with the hope that gen-z can develop positive and sustainable saving habits, providing a positive impact on their financial stability in the future.Penelitian ini bertujuan untuk mempelajari faktor-faktor yang memengaruhi keputusan menabung gen-z, dengan memfokuskan pada literasi keuangan, peran orang tua, dan materialisme. Responden penelitian adalah 340 mahasiswa jurusan Manajemen dan Bisnis di Politeknik Negeri Batam. Penelitian ini menggunakan pendekatan kuantitatif yang terdiri atas beberapa tahapan, seperti pengumpulan data, pengolahan data dengan menggunakan SmartPLS 3, uji outer dan inner, pengujian hipotesis, dan penarikan kesimpulan. Hasil penelitian mengungkapkan peran signifikan orang tua dalam membentuk literasi keuangan dan keputusan menabung gen-z. Literasi keuangan juga berpengaruh positif dan signifikan terhadap keputusan menabung gen-z. Temuan menarik pada variabel materialisme, yang sebelumnya dianggap negatif, memiliki pengaruh positif terhadap keputusan menabung gen-z, menyoroti kompleksitas perilaku keuangan. Penelitian ini memberikan kontribusi teoritis penting dengan menerapkan Theory of Planned Behavior (TPB) pada literasi keuangan, peran orang tua, dan materialisme dalam keputusan menabung. Secara praktis, penelitian ini memberikan pandangan yang jelas bagi gen-z dan orang tua mengenai faktor-faktor yang memengaruhi keputusan menabung, dengan harapan gen-z dapat mengembangkan kebiasaan menabung yang positif dan berkelanjutan, memberikan dampak positif pada stabilitas finansial mereka di masa depan