Jurnal Politeknik Negeri Batam (PoliBatam)
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Determine of Employee Performance Study Case PT Interplex Precision Batam
Get PDFThis research aims to determine the effect of work discipline and motivation on employee performance. Using a descriptive quantitative approach and processed with the SPSS version 20 application, the research involved 48 employees of PT Interplex Precision Batam as samples. The primary data collection method uses a questionnaire with the application of quantitative multiple regression analysis. The results of this research, both work discipline and motivation, have a significant partial and simultaneous positive influence on employee performance. Discipline and work motivation factors are able to explain around 61.9% of the variation in employee performance, while the remaining 38.1% is influenced by other variables not in this study, such as leadership and work environment conditions and others
ANALISA PERBANDINGAN KEMAMPUAN KARBON AKTIF SEKAM PADI DAN KARBON AKTIF BATOK KELAPA DALAM ALAT FILTRASI AIR
Get PDFDalam instalasi alat filtrasi air terdapat tiga jenis material yang umum dipakai sebagai media filtrasi yaitu Zeolit, Silika dan Karbon. Karbon aktif dapat dibuat menggunakan arang dari limbah hasil pertanian. Di Indonesia limbah sekam padi kebanyakan hanya di bakar atau diolah untuk tambahan pakan ternak. Batok kelapa kebanyakan digunakan untuk bahan untuk produksi briket. Penelitian ini dilakukan untuk membandingkan kemampuan karbon dari limbah sekam padi dan batok kelapa dalam meningkatkan kinerja alat filrasi air saat menyaring zat pencemar. Langkah-langkah dalam pembuatan karbon aktif dari limbah sekam padi dan batok kelapa ini yaitu melakukan proses pretreatment, proses dehidrasi, proses karbonisasi, proses pengaktifan secara fisika dan kimia. Kualitas air dilakukan pengujian menggunakan metode fisika dan kimia dengan mengacu standar kualitas air dari PP Republik Indonesia No 22 Tahun 2021 tentang Penyelenggaraan Perlindungan dan Pengelolaan Lingkungan Hidup. Hasil pengujian menunjukan air yang dihasilkan dari alat filtrasi menggunakan karbon aktif sekam padi berada pada baku mutu kelas 1 sedangkan air yang dihasilkan dari alat filtrasi menggunakan karbon aktif batok kelapa berada pada baku mutu kelas 2. Hal ini menunjukan penggunaan karbon aktif dari sekam padi dapat meningkatkan kinerja alat filrasi air dalam menyaring zat pencemar apabila dibandingkan dengan penggunaan karbon aktif dari batok kelapa.Dalam instalasi alat filtrasi air terdapat tiga jenis material yang umum digunakan yaitu Pasir Zeolit, Pasir Silika dan Karbon Aktif. Karbon aktif dapat dibuat menggunakan arang dari limbah hasil pertanian. Di Indonesia limbah sekam padi kebanyakan hanya di bakar atau diolah untuk tambahan pakan ternak. Batok kelapa kebanyakan digunakan untuk bahan baku pembuatan briket. Penelitian ini bertujuan untuk membandingkan kemampuan karbon dari limbah sekam padi dan batok kelapa dalam meningkatkan kinerja alat filrasi air dalam menyaring zat pencemar. Langkah-langkah dalam pembuatan karbon aktif dari limbah sekam padi dan batok kelapa ini yaitu melakukan proses pre-treatment, proses dehidrasi, proses karbonisasi, proses pengaktifan secara fisika dan kimia. Hasil pengujian kualitas air menggunakan metode fisika dan kimia dengan mengacu standar baku mutu air dari Peraturan Pemerintah Republik Indonesia Nomor 22 Tahun 2021 tentang Penyelenggaraan Perlindungan dan Pengelolaan Lingkungan Hidup. Hasil pengujian menunjukan bahwa air yang dihasilkan dari alat filtrasi menggunakan karbon aktif sekam padi berada pada baku mutu kelas 1 sedangkan air yang dihasilkan dari alat filtrasi menggunakan karbon aktif batok kelapa berada pada baku mutu kelas 2. Hal ini menunjukan penggunaan karbon aktif dari sekam padi dapat meningkatkan kinerja alat filrasi air dalam menyaring zat pencemar apabila dibandingkan dengan penggunaan karbon aktif dari batok kelapa
Video Edukasi Animasi 2d Tentang Pemilu 2024 Untuk Perum Lkbn Antara Biro Kepulauan Riau
Get PDFFirst-time voters play a significant role in the 2024 elections in Batam City, necessitating engaging and accessible information media to enhance audience engagement. Therefore, a 2D animated educational video was developed as a platform for socialization and disseminated through digital platforms. The design method used was the Multimedia Development Life Cycle (MDLC), which consists of six main stages: Concept, Design, Material Collection, Assembly, Testing, and Distribution. Testing was conducted using the EPIC Model, which encompasses four aspects: Empathy, Persuasion, Impact, and Communication. The 2D animated video proved effective in educating first-time voters in Batam about the 2024 elections, combining visual elements and narrative information to reinforce the message.Pemilih pemula memiliki kontribusi besar dalam Pemilu 2024 di Kota Batam, sehingga diperlukan media informasi yang menarik dan mudah diakses untuk meningkatkan keterlibatan audiens. Sehingga dibutuhkan video edukasi animasi 2D sebagai media sosialisasi yang disebarkan melalui platform digital. Metode perancangan yang digunakan adalah Multimedia Development Life Cycle (MDLC) yang terdiri dari enam tahapan utama; Concept, Design, Material Collecting, Assembly, Testing, dan Distribution. Pengujian dilakukan menggunakan EPIC Model yang mencakup empat aspek; Empathy, Persuasion, Impact, dan Communication. Video animasi 2D menjadi media yang efektif untuk mengedukasi pemilih pemula di Batam tentang Pemilu 2024, dengan perpaduan elemen visual dan narasi yang memperkuat informasi
Implementation of BERTopic for Topic Modeling Analysis of the Free Nutritious Meal Program Based on YouTube Comments
Get PDFThe Free Nutritious Meal Program (Makan Bergizi Gratis), represents a significant national effort aimed at mitigating stunting rates in Indonesia, having commenced its operations in January 2025. As the program progressed, public sentiment towards it evolved, resulting in a diverse array of opinions that were extensively debated on various social media platforms, notably YouTube. This study was conducted with the objective of examining the perceptions of the public regarding Makan Bergizi Gratis through a topic modeling methodology employing the BERTopic approach, which analyzed 19,843 comments from YouTube. The analytical framework entailed several stages, including data preprocessing, sentence-based embedding representation, dimensionality reduction via UMAP, clustering through HDBSCAN, and topic interpretation grounded in c-TF-IDF. The findings indicate that public commentary is categorizable into ten primary themes, encompassing issues such as the involvement of political figures, concerns over budget transparency, the program\u27s educational benefits, and the need for equitable access in underserved regions. Evaluation results show that BERTopic outperformed the traditional LDA model, with a coherence score of 0.46 compared to 0.39 and topic diversity of 76 percent compared to 71 percent. This analysis reveals that public perception of Makan Bergizi Gratis is multifaceted, shaped by social experience, political context, and economic expectations. These insights may serve as a valuable foundation for a more comprehensive understanding of public opinion, thereby supporting more targeted and responsive policy development.The Free Nutritious Meal Program (Makan Bergizi Gratis), represents a significant national effort aimed at mitigating stunting rates in Indonesia, having commenced its operations in January 2025. As the program progressed, public sentiment towards it evolved, resulting in a diverse array of opinions that were extensively debated on various social media platforms, notably YouTube. This study was conducted with the objective of examining the perceptions of the public regarding Makan Bergizi Gratis through a topic modeling methodology employing the BERTopic approach, which analyzed 19,843 comments from YouTube. The analytical framework entailed several stages, including data preprocessing, sentence-based embedding representation, dimensionality reduction via UMAP, clustering through HDBSCAN, and topic interpretation grounded in c-TF-IDF. The findings indicate that public commentary is categorizable into ten primary themes, encompassing issues such as the involvement of political figures, concerns over budget transparency, the program\u27s educational benefits, and the need for equitable access in underserved regions. Evaluation results show that BERTopic outperformed the traditional LDA model, with a coherence score of 0.46 compared to 0.39 and topic diversity of 76 percent compared to 71 percent. This analysis reveals that public perception of Makan Bergizi Gratis is multifaceted, shaped by social experience, political context, and economic expectations. These insights may serve as a valuable foundation for a more comprehensive understanding of public opinion, thereby supporting more targeted and responsive policy development
Clustering of the Air Pollution Standard Index (ISPU) in the Province of DKI Jakarta Using the CLARANS Algorithm
Get PDFAir pollution has become a serious global issue. According to IQAir\u27s 2024 report, DKI Jakarta ranked 10th among cities with the worst air quality worldwide, indicating that air pollution in DKI Jakarta has reached a concerning level. This research uses the CLARANS algorithm to cluster daily air quality in DKI Jakarta based on pollution parameters. CLARANS is chosen due to its advantages in terms of big data processing efficiency, outlier resistance, and medoid search capability. The novelty of this research lies in the application of CLARANS to overcome the limitations of clustering algorithms in previous research. This research comprises several stages, including data understanding, data preprocessing, building the CLARANS model, and evaluation using the silhouette score. The CLARANS clustering result using the most optimal parameter combination and k = 3 demonstrates well-separated cluster boundaries, with an overall average silhouette score across all regions and years of 0.6398. The analysis results indicate that air pollution in DKI Jakarta tends to worsen in 2024. Jakarta Barat and Jakarta Pusat are predominantly affected by PM10, CO, and O₃ pollution, whereas Jakarta Selatan and Jakarta Utara are more influenced by SO₂ and NO₂ pollution. On the other hand, air pollution in East Jakarta shows a balanced dominance from both pollutant categories
Pembuatan Motion Comic Chibi Sebagai Media Informasi Pendaftaran Pemberangkatan Haji Di Kantor Kementerian Agama Kota Batam
No full textPenelitian ini mengembangkan motion comic bergaya chibi sebagai mediainformasi pendaftaran haji di Kantor Kemenag Kota Batam. Media cetakdinilai kurang efektif, terutama bagi generasi Z yang lebih akrab denganmedia digital. Menggunakan pendekatan art basic research kualitatif, karyaini dibuat dalam bentuk animasi terbatas berdurasi 3 menit 15 detik,menampilkan alur informasi melalui karakter ilustratif. Hasil evaluasi daridua ahli menunjukkan motion comic ini cukup informatif, namun masihperlu perbaikan pada intro-outro, transisi, font, dan visual panel. Gaya chibi,pewarnaan, dan karakter dinilai sesuai dengan target audiens. Secarakeseluruhan, motion comic ini berpotensi sebagai media informasi yangmenarik dan mudah dipahami, terutama bagi generasi muda.Penelitian ini mengembangkan motion comic bergaya chibi sebagai mediainformasi pendaftaran haji di Kantor Kemenag Kota Batam. Media cetakdinilai kurang efektif, terutama bagi generasi Z yang lebih akrab denganmedia digital. Menggunakan pendekatan art basic research kualitatif, karyaini dibuat dalam bentuk animasi terbatas berdurasi 3 menit 15 detik,menampilkan alur informasi melalui karakter ilustratif. Hasil evaluasi daridua ahli menunjukkan motion comic ini cukup informatif, namun masihperlu perbaikan pada intro-outro, transisi, font, dan visual panel. Gaya chibi,pewarnaan, dan karakter dinilai sesuai dengan target audiens. Secarakeseluruhan, motion comic ini berpotensi sebagai media informasi yangmenarik dan mudah dipahami, terutama bagi generasi muda
Innovative Mobile Application UI/UX for Gestari Waste Bank Administration Using Activity-Centered Design
No full textBank Sampah Gestari, located in Dusun Gesikan, Panggungharjo, Sewon, Bantul, runs a routine household waste sorting program every “Minggu Legi.” In its operation, administrative officers still rely on manual data recording using notes and books, leading to data accumulation and inefficient recap processes, especially with the growing number of customers. The absence of a digital system to support the recording process presents a major challenge in achieving optimal administration. This study aims to design the User Interface (UI) and User Experience (UX) of a mobile-based administrative system for Bank Sampah Gestari using the Activity Centered Design approach. The approach focuses on the core activities performed by users during administrative tasks. The design process was informed by observations and interviews with administrative staff and was used to develop application flows and interfaces aligned with user needs and the bank’s business processes. The prototype was evaluated through two usability testing iterations, measuring five usability aspects: learnability, efficiency, memorability, errors, and satisfaction. Results showed notable improvements in all aspects. Learnability increased from 78% to 94%, efficiency from 0.0155 to 0.0440 goals/sec, memorability from 2.75 to 3.85, error rate decreased from 0.44 to 0.12, and satisfaction rose from 25.5 to 84.5. In conclusion, the proposed interface design significantly enhances ease of use, operational efficiency, and user satisfaction. The design can serve as a recommendation for developing a more structured, effective, and user-friendly digital administrative system for Bank Sampah Gestari.Bank Sampah Gestari, located in Dusun Gesikan, Panggungharjo, Sewon, Bantul, runs a routine household waste sorting program every “Minggu Legi.” In its operation, administrative officers still rely on manual data recording using notes and books, leading to data accumulation and inefficient recap processes, especially with the growing number of customers. The absence of a digital system to support the recording process presents a major challenge in achieving optimal administration. This study aims to design the User Interface (UI) and User Experience (UX) of a mobile-based administrative system for Bank Sampah Gestari using the Activity Centered Design approach. The approach focuses on the core activities performed by users during administrative tasks. The design process was informed by observations and interviews with administrative staff and was used to develop application flows and interfaces aligned with user needs and the bank’s business processes. The prototype was evaluated through two usability testing iterations, measuring five usability aspects: learnability, efficiency, memorability, errors, and satisfaction. Results showed notable improvements in all aspects. Learnability increased from 78% to 94%, efficiency from 0.0155 to 0.0440 goals/sec, memorability from 2.75 to 3.85, error rate decreased from 0.44 to 0.12, and satisfaction rose from 25.5 to 84.5. In conclusion, the proposed interface design significantly enhances ease of use, operational efficiency, and user satisfaction. The design can serve as a recommendation for developing a more structured, effective, and user-friendly digital administrative system for Bank Sampah Gestari
Prediction of Tuberculosis Treatment Outcomes in Indonesia Using Support Vector Machine and Random Forest
No full textTuberculosis (TB) remains a global health challenge, particularly in developing countries such as Indonesia, which ranks third worldwide in the number of TB cases. This study aims to evaluate the performance of Support Vector Machine (SVM) and Random Forest (RF) algorithms in predicting TB patient recovery rates based on clinical data obtained from healthcare facilities in Indonesia. Evaluation results indicate that the model achieved very high precision scores (100%) for the "Deceased," "Transferred," and "Default" categories; however, these findings require critical interpretation due to the likely class imbalance in those categories. In contrast, for the "Recovered" and "Completed" categories—where data instances were more numerous—the model exhibited lower precision and recall values (below 90%), reflecting challenges in accurately predicting majority classes. These results suggest that despite seemingly high numerical performance, model predictions can be biased if class distribution is not appropriately considered. The main contribution of this research lies in providing a comparative analysis of two widely used machine learning algorithms in predicting TB recovery outcomes, while emphasizing the importance of addressing data imbalance issues in clinical predictive modeling. The findings provide a practical basis for integrating predictive algorithms into clinical workflows, enabling more accurate monitoring of patient recovery and timely adjustments of TB treatment plans in Indonesia.Tuberculosis (TB) remains a global health challenge, particularly in developing countries such as Indonesia, which ranks third worldwide in the number of TB cases. This study aims to evaluate the performance of Support Vector Machine (SVM) and Random Forest (RF) algorithms in predicting TB patient recovery rates based on clinical data obtained from healthcare facilities in Indonesia. Evaluation results indicate that the model achieved very high precision scores (100%) for the "Deceased," "Transferred," and "Default" categories; however, these findings require critical interpretation due to the likely class imbalance in those categories. In contrast, for the "Recovered" and "Completed" categories—where data instances were more numerous—the model exhibited lower precision and recall values (below 90%), reflecting challenges in accurately predicting majority classes. These results suggest that despite seemingly high numerical performance, model predictions can be biased if class distribution is not appropriately considered. The main contribution of this research lies in providing a comparative analysis of two widely used machine learning algorithms in predicting TB recovery outcomes, while emphasizing the importance of addressing data imbalance issues in clinical predictive modeling. The findings provide a practical basis for integrating predictive algorithms into clinical workflows, enabling more accurate monitoring of patient recovery and timely adjustments of TB treatment plans in Indonesia
Optimizing Digital Transformation Through AI and Cloud Technology Integration for Innovation in Big Data-Driven Information Systems
No full textDigital transformation has become critical for SMEs in emerging economies, yet integrated studies combining AI, cloud computing, and human factors remain scarce. This study addresses this gap by developing a holistic framework for Indonesian SMEs through a systematic literature review. Using PRISMA protocol, we analyzed 46 peer-reviewed articles (2020-2025) from Scopus, IEEE Xplore, and Google Scholar, with thematic synthesis in NVivo 12. The proposed framework reveals three interdependent dimensions: (1) technological integration (AI-cloud-big data synergy), (2) process optimization (automation and analytics), and (3) human-digital leadership (competency and cultural readiness). Case studies show 35% operational efficiency gains but highlight infrastructure and skill gaps. This study contributes a novel integration of TOGAF and DCMM theories, offering policymakers a roadmap for SME digitalization while cautioning against one-size-fits-all solutions.Digital transformation has become critical for SMEs in emerging economies, yet integrated studies combining AI, cloud computing, and human factors remain scarce. This study addresses this gap by developing a holistic framework for Indonesian SMEs through a systematic literature review. Using PRISMA protocol, we analyzed 46 peer-reviewed articles (2020-2025) from Scopus, IEEE Xplore, and Google Scholar, with thematic synthesis in NVivo 12. The proposed framework reveals three interdependent dimensions: (1) technological integration (AI-cloud-big data synergy), (2) process optimization (automation and analytics), and (3) human-digital leadership (competency and cultural readiness). Case studies show 35% operational efficiency gains but highlight infrastructure and skill gaps. This study contributes a novel integration of TOGAF and DCMM theories, offering policymakers a roadmap for SME digitalization while cautioning against one-size-fits-all solutions
Clustering Coastal Areas Based on Aquaculture Productivity in North Aceh Regency Using K-Means Algorithm
No full textThis study aims to cluster coastal subdistricts in North Aceh Regency based on the productivity of seven key aquaculture commodities milkfish, vannamei shrimp, tiger shrimp, tilapia, mojarra, grouper, and crab using the K-Means algorithm. The dataset, sourced from 15 coastal subdistricts, was normalized using the Z-Score method. The optimal number of clusters was determined using the Elbow Method, and clustering performance was evaluated with the Silhouette Score, yielding a value of 0.5293, indicating a moderately well-defined structure. The resulting clusters reflect distinct productivity levels: Cluster 0 (low), Cluster 1 (moderate), and Cluster 2 (high). A two-dimensional PCA plot was used to visualize the clusters, showing clear separations among them. These findings offer valuable insights for regional planners and policymakers in developing targeted aquaculture strategies and optimizing resource allocation, particularly for underperforming areas