Jurnal Politeknik Negeri Batam (PoliBatam)
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The Influence of Trust and Habit on Users’ Intention to Keep Using Facebook Reels for Economic Purposes
Get PDFSocial media now plays a crucial role in supporting economic activities. Facebook Reels, for instance, as a short video feature, offers economic opportunities for its users. However, understanding the factors that encourage continued usage remains limited. This study aims to explore the influence of trust and habit on users’ intention to keep using Facebook Reels for economic purposes (N=174 active users). We integrated the Technology Continuance Theory (TCT) applied Partial Least Squares Structural Equation Modelling (PLS-SEM) for the analysis. The results show that both factors significantly influence continuance intention (R² = 78.7%), although they do not directly affect user attitude. Attitude is influenced only by reciprocal benefits (R² = 62%). These findings indicate that in regions with limited digital infrastructure such as West Papua, the success of digital platforms strongly depends on building user trust and encouraging consistent usage habit. This study offers valuable insights for platform developers and policymakers in designing strategies to help users continue using the platform over time and support the growth of the local digital economy
International Business Strategy Formulation for the African Market of Copy Paper Company
Get PDFThis study examines strategic entry into the African market by a copy paper manufacturing company through internal and external business environment analysis. Using PESTEL, Porter’s Five Forces, SWOT, and VRIN frameworks, the research identifies key opportunities and risks. An Analytical Hierarchy Process (AHP) evaluates six strategic criteria: product standardization, pricing competitiveness, cost efficiency, regulatory compliance, adaptability, and cultural fit. Findings support a hybrid strategy combining transnational and multidomestic approaches to balance scale efficiency and local responsiveness. The study recommends phased market entry, regional partnerships, localized facilities, and improved market intelligence. These insights contribute to international business strategy by offering an evidence-based roadmap for firms targeting emerging markets in Africa
Enhancing Business Accountability through Effective Pension Fund Accounting and Reporting
No full textThe purpose of this study was to describe the implementation of PSAK No. 18 accounting and reporting of retirement benefit programs at DAPENBUN Regional 2 Medan. This research is qualitative in nature using observation, in-depth interviews with various parties in DAPENBUN, and documentation studies of the financial statements for 2023-2024. The data were analyzed descriptively based on four aspects of PSAK No.18, namely recognition, measurement, presentation, and disclosure. The conclusion shows that most of the provisions have been implemented, but there are some obstacles in disclosing financial risks, membership details, and the identity of the independent actuary. These findings are expected to be the basis for improving pension fund reporting in the future. This research contributes through a comprehensive implementation that not only assesses formal compliance but also accountability to pension funds. The findings and recommendations can be used as a reference for improving the reporting and management of pension funds in accordance with PSAK No.18. This research only covers one pension fund institution and has not examined a wider range of stakeholders or cross institutional comparisons
Evaluasi Efektivitas Promosi Makanan Cepat Saji Menggunakan Pendekatan Hibrida Metode Non-Parametrik Robust dan Simulasi Monte Carlo Berdasarkan Segmentasi Ukuran Pasar
No full textThe fast food industry is highly competitive, requiring effective promotional strategies to drive sales and maintain customer loyalty. This study evaluates the effectiveness of fast food promotions using a hybrid approach combining robust non-parametric methods, Random Forest, and Monte Carlo simulation. The analysis focuses on segmenting the market by Market Size (Large, Medium, Small) to identify the most impactful promotional strategies for each segment. Non-parametric A/B testing using the Kruskal-Wallis test revealed significant differences in sales across promotions, with Promotion 1 emerging as the most effective overall. The Random Forest model highlighted LocationID as the most critical factor influencing sales, particularly in Large markets. Monte Carlo simulation further demonstrated that Promotion 1 yields the highest Expected Monetary Value (EMV), making it the optimal choice for long-term sales growth. The findings emphasize the importance of tailoring promotional strategies to specific market segments, considering factors such as location, timing, and store history. This study provides actionable insights for businesses to optimize promotional campaigns, enhance sales performance, and achieve sustainable growth in the fast food industry.Industri makanan cepat saji sangat kompetitif, sehingga memerlukan strategi promosi yang efektif untuk mendorong penjualan dan mempertahankan loyalitas pelanggan. Studi ini mengevaluasi efektivitas promosi makanan cepat saji menggunakan pendekatan hibrida yang menggabungkan metode nonparametrik yang kuat, Random Forest, dan simulasi Monte Carlo. Analisis difokuskan pada segmentasi pasar berdasarkan Ukuran Pasar (Besar, Sedang, Kecil) untuk mengidentifikasi strategi promosi yang paling berdampak bagi setiap segmen. Pengujian A/B nonparametrik menggunakan uji Kruskal-Wallis mengungkapkan perbedaan yang signifikan dalam penjualan di seluruh promosi, dengan Promosi 1 muncul sebagai yang paling efektif secara keseluruhan. Model Random Forest menyoroti LocationID sebagai faktor paling penting yang memengaruhi penjualan, khususnya di pasar Besar. Simulasi Monte Carlo selanjutnya menunjukkan bahwa Promosi 1 menghasilkan Nilai Moneter yang Diharapkan (EMV) tertinggi, menjadikannya pilihan yang optimal untuk pertumbuhan penjualan jangka panjang. Temuan tersebut menekankan pentingnya menyesuaikan strategi promosi dengan segmen pasar tertentu, dengan mempertimbangkan faktor-faktor seperti lokasi, waktu, dan riwayat toko. Studi ini memberikan wawasan yang dapat ditindaklanjuti bagi bisnis untuk mengoptimalkan kampanye promosi, meningkatkan kinerja penjualan, dan mencapai pertumbuhan berkelanjutan dalam industri makanan cepat saji
Financial Performance Efficiency: Determinants of Return on Invested Capital
Get PDFWith the growth of the capital market in Indonesia, stocks are an attractive investment option. The healthcare sector plays a strategic role in supporting public health services, which makes it much sought after by investors. Inconsistency results from the fact that much previous research has created a knowledge gap in this field. This study aims to determine the effect of capital structure on the efficiency of financial performance partially and simultaneously in healthcare sector companies from 2019 to 2021. Based on the Eviews statistical analysis and testing results, the partial Self-Financing Ratio, Long-Term Asset Ratio, and Financial Leverage Ratio have an insignificant effect on financial performance efficiency. The Fixed Asset Ratio variable partially and significantly affects financial performance efficiency. The test results simultaneously show that the variables Self-Financing Ratio, Long-Term Asset Ratio, Financial Leverage Ratio, and Fixed Asset Ratio significantly affect financial performance efficiency. Novelty in this research is using the capital structure, which is proxied by the Self-financing Ratio (SFR), Long-term Asset Ratio (LAR), Financial Leverage Ratio (FLR), and Fixed Asset Ratio (FAR) across different company sectors and periods of panel data. The implication from this analysis of these ratios and industry benchmarks can provide a more comprehensive picture of a company’s financial health and ability to generate sustainable returns on its invested capital.Penelitian ini bertujuan untuk mengetahui pengaruh Capital Structure terhadap Financial Performance secara parsial dan simultan pada perusahaan sektor healthcare yang terdaftar di IDX dari tahun 2019-2021. Jenis penelitian yang dilakukan adalah penelitian kuantitatif dengan data yang digunakan dalam penelitian ini merupakan data sekunder, yaitu data yang diperoleh secara tidak langsung dari perusahaan sektor healthcare yang terdaftar di IDX. Berdasarkan hasil pengujian analisis statistik secara parsial Self-Financing Ratio, Long-Term Asset Ratio, dan Financial Leverage Ratio berpengaruh tidak signifikan terhadap Financial Performance. Sedangkan secara parsial variabel Fixed Asset Ratio berpengaruh signifikan terhadap Financial Performance. Hasil pengujian secara simultan menunjukkan bahwa variabel Self-Financing Ratio, Long-Term Asset Ratio, Financial Leverage Ratio, dan Fixed Asset Ratio berpengaruh signifikan terhadap Financial Performance
Pelatihan Internet Of Things (IoT) Untuk Meningkatkan Kompetensi Digital Siswa Di Smk Negeri Jorlang Hataran
Get PDFThe purpose of this community service activity is to enhance digital competency skills at SMK Negeri I Jorlang Hataran. The method used in the implementation of this activity is training through the delivery of materials, practical training on the assembly and programming of IoT devices, and a question-and-answer session. The participants of this activity consist of 37 students from the 11th grade RPL (Software Engineering) major. The instruments used in this activity include participant feedback and activity documentation. The results of the implementation show that the participants\u27 responses to the basic computer training were overall in the good category. The percentage of student responses reached 98.20%, which falls into the very good category.Tujuan kegiatan pengabdian kepada masyarakat ini adalah untuk meningkatkan kemampuan kompetensi digital di SMK Negeri I Jorlang Hataran. Metode yang digunakan dalam pelaksanaan kegiatan ini adalah pelatihan melalui penyampaian materi, pelatihan praktis tentang perakitan dan pemrograman perangkat IoT dan sesi tanya jawab. Peserta kegiatan ini terdiri dari 37 siswa kelas XI Jurusan RPL ( Rekayasa Perangkat Lunak). Instrument yang diguanakn dalam kegiatan ini meliputi tanggapan peserta dan dokumentasi kegiatan. Hasil pelaksanaan menunjukkan bahwa tanggapan peserta terhadap pelatihan komputer dasar secara keseluruhan berada pada kategori baik. Rerarta persentase tanggapan siswa mencapai 98,20 %, yang termasuk dalam kategori sangat baik
Analisis Variasi Polaritas Shield Metal Arc Welding Dan Build-Up Root Gap Terhadap Diskontinuitas, Metalografi, Dan Nilai Ketangguhan Pada Material Baja SS400 Untuk Struktur Bangunan Kapal
Get PDFDalam fabrikasi struktur bangunan kapal, root gap yang terlalu lebar sering ditemukan saat pengelasan, umumnya akibat kesalahan pemotongan pelat. Untuk memenuhi dimensi desain, perbaikan diperlukan. Metode build-up, penambahan lapisan logam las untuk memperkecil gap menjadi solusi. Dalam penelitian ini metode build-up menggunakan variasi layer sebanyak 2 sampai 4 layer serta perbedaan polaritas pada pengelasan SMAW menggunakan AC dan DC+ agar mendapatkan lelehan deposit las yang besar dan penetrasi dangkal sehingga ketebalan layer yang direncanakan terpenuhi. Akibat dari metode build-up material terkena heat input secara berulang yang dapat mempengaruhi struktur dan sifat mekanisnya sehingga penelitian ini bertujuan untukmengetahui diskontinuitas, metalografi, dan ketangguhan akibat proses tersebut. Hasilnya menunjukkan area build-up tidak terdapat diskontinuitas dan cacat. Struktur mikro menunjukkan perbedaan jumlah kandungan pearlite dan batas butir, dengan jumlah paling banyak hingga paling sedikit yaitu di daerah logam las, build-up, HAZ, dan logam dasar yang tidak banyak berubah. Uji makro menunjukkan HAZ melebar hingga 1 mm seiring penambahan lapisan, namun variasi polaritas tidak berpengaruh signifikan. Ketangguhan tertinggi terjadi pada polaritas AC sebesar 116,16 J dan paling rendah dengan polaritas DC sebesar 85,66 J akibat perbedaan heat input dan travel speed, sementara peningkatan jumlah layer build-up menurunkan ketangguhan.Dalam fabrikasi struktur bangunan kapal sering ditemukan terjadi root gap yang sangat lebar pada saat pengelasan material. Hal ini disebabkan kesalahan saat melakukan pemotongan pelat sehingga diperlukan adanya perbaikan agar dimensi desain terpenuhi. Metode build-up dapat digunakan untuk menambah ketebalan yang dilakukan dengan penambahan lelehan logam las baik pada satu sisi maupun kedua sisi material dengan harapan memperkecil over root gap. Dalam penelitian ini metode build-up menggunakan variasi layer dan polaritas pada pengelasan SMAW menggunakan AC dan DC+ agar mendapatkan lelehan deposit las yang besar serta penetrasi dangkal sehingga ketebalan layer yang direncanakan terpenuhi. Akibat dari metode build-up material terkena heat input secara berulang yang dapat mempengaruhi struktur dan sifat mekanisnya sehingga penelitian ini bertujuan untuk mengetahui ketangguhan, metalografi, dan diskontinuitas akibat proses tersebut. Hasil metode build-up menunjukkan tidak ada diskontinuitas pada area build-up. Struktur mikro menunjukkan perbedaan jumlah kandungan pearlite dan batas butir, dengan jumlah paling banyak hingga paling sedikit yaitu logam las, build-up, HAZ, dan logam dasar yang tidak signifikan. Uji makro menunjukkan pelebaran HAZ hingga 1 mm seiring peningkatan layer build-up, namun variasi polaritas tidak berpengaruh signifikan. Ketangguhan tertinggi terjadi pada polaritas AC akibat perbedaan heat input dan travel speed, sementara peningkatan jumlah layer build-up menurunkan ketangguhan
Comparison of ResNet-50, EfficientNet-B1, and VGG-16 Algorithms for Cataract Eye Image Classification
Get PDFCataract is a leading cause of blindness worldwide, emphasizing the need for an effective early detection approach. This study evaluates the capabilities of three widely-used deep learning models—ResNet-50, EfficientNet-B1, and VGG-16—in classifying visual data. The analysis was conducted on a dataset of 2,112 images, comprising 1,074 normal cases and 1,038 cataract cases. The findings reveal that ResNet-50 achieved the best accuracy at 98.61%, followed by EfficientNet-B1 at 96.64% and VGG-16 at 93.82%. In comparison, previous research using Convolutional Neural Network (CNN) techniques reported an accuracy of 92.93%. These results highlight ResNet-50\u27s superior potential for image classification tasks in this domain. This study contributes significantly to the selection of robust models for building an automated cataract detection framework
Twitter Sentiment Analysis on Digital Payment in Indonesia Using Artificial Neural Network
Get PDFIn the rapid development of technology, the need for big data processing is increasingly important, especially in the context of digital transactions such as e- wallets in Indonesia. On the other hand, sentiment analysis of digital payment platforms via Twitter requires fast and accurate data processing, but often faces challenges in managing big data and optimal classification quality. This study uses the Term TF-IDF method for text preprocessing and Artificial Neural Network (ANN) for sentiment classification. The preprocessing process includes case folding, removing numbers and punctuation, tokenization, filtering, and stemming. For classification, ANN is used which is optimized with the Backpropagation and K-fold Cross Validation algorithms to improve the accuracy of the model in grouping positive and negative sentiments from tweets about digital payment platforms. Through this approach, the study produces a sentiment classification model in analyzing big data. The results in this study are Gopay gets a positive value and gets the first value in sentiment assessment with an accuracy rate of 72% using ANN. Of the 5 digital payments that received a negative value and ranked last, namely Link Aja with an achievement rate of 43%. Based on these results, it shows that this approach contributes to identifying consumer sentiment towards e-wallet platforms, which is useful for developing digital marketing strategies. The contribution given is in improving sentiment analysis of digital payment platforms by utilizing Big Data processing technology and machine learning, so that it can be used to improve services and marketing strategies based on user data.In the rapid development of technology, the need for big data processing is increasingly important, especially in the context of digital transactions such as e- wallets in Indonesia. On the other hand, sentiment analysis of digital payment platforms via Twitter requires fast and accurate data processing, but often faces challenges in managing big data and optimal classification quality. This study uses the Term TF-IDF method for text preprocessing and Artificial Neural Network (ANN) for sentiment classification. The preprocessing process includes case folding, removing numbers and punctuation, tokenization, filtering, and stemming. For classification, ANN is used which is optimized with the Backpropagation and K-fold Cross Validation algorithms to improve the accuracy of the model in grouping positive and negative sentiments from tweets about digital payment platforms. Through this approach, the study produces a sentiment classification model in analyzing big data. The results in this study are Gopay gets a positive value and gets the first value in sentiment assessment with an accuracy rate of 72% using ANN. Of the 5 digital payments that received a negative value and ranked last, namely Link Aja with an achievement rate of 43%. Based on these results, it shows that this approach contributes to identifying consumer sentiment towards e-wallet platforms, which is useful for developing digital marketing strategies. The contribution given is in improving sentiment analysis of digital payment platforms by utilizing Big Data processing technology and machine learning, so that it can be used to improve services and marketing strategies based on user data
Application of Naive Bayes and Forward Chaining Methods in a Web-Based Expert System for Stunting Diagnosis in Toddlers
Get PDFThe high rate of stunting in toddlers shows the need for accurate early diagnosis to prevent long-term impacts on children\u27s growth and development. One of the main obstacles to early diagnosis is parents\u27 lack of knowledge about the early symptoms of stunting, so treatment is often delayed. To overcome this problem, a web-based expert system was developed that applies the Naïve Bayes and Forward Chaining methods in diagnosing stunting in toddlers. The Naïve Bayes method is used to calculate the possibility of stunting based on the symptoms experienced by toddlers. This method is a probability-based algorithm that is used to classify the possibility of a condition based on existing symptoms. The process begins by calculating the probability of each symptom of stunting disease based on historical data that has been collected from experts. Then, using Bayes\u27 Theorem, the system calculates the greatest probability of a disease based on the symptoms selected by the user. The final output is the diagnosis that has the highest probability, along with the recommended solution. Meanwhile, Forward Chaining is used to trace the rules that lead to a diagnosis conclusion. The Naïve Bayes method focuses more on calculating probabilities to determine a diagnosis with a certain level of confidence, while the Forward Chaining method works by matching rules to obtain conclusions based on the facts provided. The combination of these two methods allows the expert system to make a more accurate diagnosis by considering the probabilities and rules set by the expert. The web-based system built using these two methods aims to help parents detect stunting in toddlers early, so they can immediately take appropriate preventive or treatment steps. The results of the research show that it is found that the symptoms experienced by children are likely to be diagnosed as Not Stunting with the highest value of 0.5192 or around 51.9% with the solution being that children who do not experience stunting show growth and development appropriate to their age. The system developed is able to provide diagnoses in accordance with expert evaluations, so that it can be used as a tool to assist parents in providing