Politeknik Negeri Jember

Introduction: A complete medical record is defined as one that is fully completed by Healthcare Professionals (HCPs) within ≤ 24 hours after the patient is discharged. In the third quarter of 2022, X Regional Hospital recorded the highest percentage of incomplete inpatient medical records in October, totaling 465 incomplete records (32.68%). This study aims to analyze the factors contributing to the incompleteness of inpatient medical record documentation at the hospital using Lawrence Green's behavioral theory, focusing on predisposing, enabling, and reinforcing factors.Methods: This qualitative study employed data collection techniques such as observation, documentation, and interviews to nine informants, comprising one head of the medical records department, four attending physicians, three nurses, and one head of the inpatient ward. The data were analyzed through data reduction, data presentation, and conclusion drawing, followed by providing improvement recommendations.Results: The findings indicate predisposing factors include limited staff knowledge about medical record documentation. Enabling factors involve an insufficient number of computers, incomplete training attendance, and unawareness of Standard Operating Procedures (SOP) on medical record completeness. Reinforcing factors include the absence of punishment for non-compliance.Conclusion: Improvement efforts include conducting regular socialization, monitoring, and evaluation of SOP implementation for medical record completeness; proposing additional computers; organizing seminars and training on medical record documentation for medical record staff and HCPs; and implementing a reward and punishment system to enhance HCP performance in completing inpatient medical records.

Introduction: The estimated maternal mortality ratio in Indonesia from 2016 to 2020 was 249 maternal deaths per 100,000 live births. Currently, this ratio remains relatively high. One effort to reduce maternal mortality is to provide regular antenatal care during pregnancy. This study aimed to analyse the urban–rural differences in the incompleteness of antenatal care coverage in Indonesia. Methods: This cross-sectional study used data from Indonesian Basic Health Research 2018. A total of 64,399 women aged 15–49 years, including 26,792 and 37,607 women from urban and rural areas, respectively, were included. Univariate (percentage), bivariate (chi-square statistics) and multivariate (logistic regression statistics) analyses were conducted. Results: Approximately 18.2% and 26.4% of the urban and rural participants received incomplete antenatal care, respectively. Secondary and primary education, lack of health insurance, home-based antenatal care, parity greater than 2, travel time to health facilities exceeding 15 min, absence of abortion history, undesired pregnancy and absence of pregnancy complications were associated with incomplete antenatal care in rural areas. Secondary and primary education, home-based antenatal care, travel time to health facilities exceeding 15 min, parity greater than 2 and undesired pregnancy were associated with incomplete antenatal care in urban areas. Conclusion: Incomplete antenatal care coverage is more prevalent in rural areas than in urban areas, influenced by distinct socio-demographic and healthcare access factors. Strengthening health insurance programmes, improving healthcare facility access and promoting antenatal care education are critical to reducing disparities and ensuring better maternal health outcomes in both urban and rural areas.

Coffee is known for its flavor and antioxidant effects. Roasting may change the characteristics of caffeic, chlorogenic, ferulic, and sinapic acids. While temperature and time are key factors affecting coffee’s aroma, flavor, and taste, airflow during roasting also significantly impacts bean quality and antioxidant content. This study examined the effects of roasting parameters like temperature, time, and airflow on Robusta coffee beans’ physicochemical qualities (phenols, tannins, flavonoids, and chlorogenic acid) and antioxidant activity. The best roasting parameters refer to the combination of temperature, time, and airflow that produces the most favorable qualities in the coffee beans, such as optimal flavor, aroma, and antioxidant content. Beans were roasted at 190°C, 210°C, and 230°C for 11, 14, and 17 minutes, with airflow settings of 1/4, 2/4, and 3/4. Response Surface Methodology (RSM) and Design Expert software optimized roasting conditions for optimal antioxidant content. The best roasting settings for antioxidant activity and physicochemical content were 190°C, 11 minutes, and 3/4 damper opening. These findings emphasize the importance of correctly managing temperature, time, and air movement during coffee roasting to maximize its health benefits. This approach helps produce functional beverages with better antioxidant capabilities for sensory pleasure and health advantages.

BACKGROUND Nowadays, there is increasing interest in optimizing the beneficial effects on egg quality and production by investigating various levels and sources of Se. METHODS Data of various forms, sources and levels of Se were analyzed using a meta‐analysis approach in terms of their effects on production, antioxidant activity and egg Se deposition of laying hens by using 81 peer‐reviewed publications. RESULTS Overall, laying hens' performance and egg quality attributes were not affected by Se supplementation, except for minor changes in egg weight and eggshell thickness in response to higher Se levels in diets. Noticeable effects were found on antioxidant activities where organic Se outperformed the inorganic form. Strong linear relationships between Se levels in the diet and Se content of whole egg, egg yolk and egg albumen were found where Se in the form of selenomethionine (SM) exhibited a stronger relationship with Se content in whole egg (R² = 0.954), egg yolk (R² = 0.972) and egg albumen (R² = 0.926) than other forms of organic Se and inorganic Se (sodium selenite). Also observed was a Se preferential deposition in egg yolk compared with egg albumen especially for SM, indicating a higher bioavailability and deposition rate of SM than other Se sources. CONCLUSION Various forms of Se could be safely supplemented to diets at high doses of up to 5 mg kg⁻¹ without adversely affecting hens' performance while enhancing antioxidant status. Supplementation with SM could be the most effective strategy to improve egg Se status among other forms of Se which may be beneficial for consumers. © 2025 Society of Chemical Industry.

Sugar is a vital commodity in Indonesia, serving as a staple ingredient in households and industries. The interplay of supply and demand significantly impacts sugar production, influencing prices, farmer incomes, and national food security. Comprehending these factors assists policymakers and stakeholders in devising strategies for a stable and sustainable sugar industry. Sugar is a staple foods that plays an important role in the Indonesian economy because Indonesia is one of the countries that produces granulated sugar, but still imports it every year. among the staple food that holds a significant role in the Indonesian economy since Indonesia is one of the countries that produce granulated sugar but still import it annually. This study aims to: (1) determine the demand trend for granulated sugar in Indonesia, (2) ascertain the supply trend of granulated sugar in Indonesia, (3) identify the gap between supply and demand trends for granulated sugar in Indonesia, (4) analyze the factors influencing demand for granulated sugar in Indonesia, and (5) examine the factors affecting the supply of granulated sugar in Indonesia. This study employs descriptive methods, cause and effect analysis, and a quantitative approach utilizing secondary data. The study was intentionally conducted in Indonesia, considering that Indonesia is among the countries that produce granulated sugar but still import it annually. The data utilized is secondary data sourced from various channels. The analysis methods employed include trend analysis and multiple analyses of the Cobb-Douglas model. The results of the study concluded that: (1) the trend of demand for granulated sugar in Indonesia is increasing, (2) the trend of supply of granulated sugar in Indonesia is increasing, (3) the trend of the gap between supply and demand for granulated sugar in Indonesia is increasing, (4) factors that significantly influence the demand for granulated sugar in Indonesia are the price of granulated sugar, the price of tea, the price of ground coffee, while factors that do not significantly influence are the price of brown sugar, population, per capita income. (5) Factors that significantly influence the supply of granulated sugar in Indonesia are the farmer's benchmark price, the price of granulated sugar, and the price of SP-36 fertilizer.

Fokus penelitian adalah mengembangkan mekanika dan dinamika pada robot edukasi berbasis IoT dan ESP32. Selain juga untuk memperkenalkan robotika sebagai media yang efektif dalam pembelajaran. Robot ini memiliki sistem penggerak diferensial dan lengan pengangkat yang mirip dengan sistem forklift. Robot ini dikontrol menggunakan mikrokontroler ESP32 dan terhubung ke aplikasi Android melalui basis data cloud Firebase. Dengan memanfaatkan platform IoT, pelatihan dapat dilakukan secara daring, yang memungkinkan siswa untuk mengendalikan robot dari jarak jauh saat robot berada di lokasi pelatihan. Robot pengangkut dirancang untuk memberikan pengalaman belajar robotika yang interaktif dan langsung, yang memungkinkan siswa untuk memahami konsep dasar dalam robotika, pemrograman, dan sistem kontrol. Sistem penggerak diferensial menawarkan kemampuan manuver yang sangat baik, sementara lengan pengangkat memungkinkan robot untuk melakukan tugas-tugas seperti mengangkat dan memindahkan objek, yang menambahkan aspek fungsional pada proses pembelajaran. Hasil pengujian menunjukkan bahwa robot bekerja dengan baik di bawah kendali daring, dengan respons yang cepat dan akurat terhadap perintah dari aplikasi Android. Penggunaan Firebase memastikan komunikasi yang stabil dan waktu nyata antara robot dan aplikasi. Implementasi ini tidak hanya meningkatkan aksesibilitas pelatihan robotika tetapi juga memungkinkan pengembangan keterampilan dengan cara yang lebih fleksibel dan terjangkau. Studi ini menyimpulkan bahwa robot transporter berbasis ESP32 dengan kontrol daring melalui aplikasi Android dan basis data cloud Firebase dapat menjadi alat pembelajaran yang efektif dan inovatif. Ini mendukung pengembangan keterampilan teknis dan pemahaman praktis siswa tentang robotika, menyediakan landasan yang kuat untuk studi lebih lanjut dalam teknologi dan teknik. Kinerja robot yang menjanjikan dalam pengaturan kontrol daring menyoroti potensinya sebagai sumber daya pendidikan yang berharga dalam lingkungan pembelajaran modern

Fokus penelitian adalah mengembangkan mekanika dan dinamika pada robot edukasi berbasis IoT dan ESP32. Selain juga untuk memperkenalkan robotika sebagai media yang efektif dalam pembelajaran. Robot ini memiliki sistem penggerak diferensial dan lengan pengangkat yang mirip dengan sistem forklift. Robot ini dikontrol menggunakan mikrokontroler ESP32 dan terhubung ke aplikasi Android melalui basis data cloud Firebase. Dengan memanfaatkan platform IoT, pelatihan dapat dilakukan secara daring, yang memungkinkan siswa untuk mengendalikan robot dari jarak jauh saat robot berada di lokasi pelatihan. Robot pengangkut dirancang untuk memberikan pengalaman belajar robotika yang interaktif dan langsung, yang memungkinkan siswa untuk memahami konsep dasar dalam robotika, pemrograman, dan sistem kontrol. Sistem penggerak diferensial menawarkan kemampuan manuver yang sangat baik, sementara lengan pengangkat memungkinkan robot untuk melakukan tugas-tugas seperti mengangkat dan memindahkan objek, yang menambahkan aspek fungsional pada proses pembelajaran. Hasil pengujian menunjukkan bahwa robot bekerja dengan baik di bawah kendali daring, dengan respons yang cepat dan akurat terhadap perintah dari aplikasi Android. Penggunaan Firebase memastikan komunikasi yang stabil dan waktu nyata antara robot dan aplikasi. Implementasi ini tidak hanya meningkatkan aksesibilitas pelatihan robotika tetapi juga memungkinkan pengembangan keterampilan dengan cara yang lebih fleksibel dan terjangkau. Studi ini menyimpulkan bahwa robot transporter berbasis ESP32 dengan kontrol daring melalui aplikasi Android dan basis data cloud Firebase dapat menjadi alat pembelajaran yang efektif dan inovatif. Ini mendukung pengembangan keterampilan teknis dan pemahaman praktis siswa tentang robotika, menyediakan landasan yang kuat untuk studi lebih lanjut dalam teknologi dan teknik. Kinerja robot yang menjanjikan dalam pengaturan kontrol daring menyoroti potensinya sebagai sumber daya pendidikan yang berharga dalam lingkungan pembelajaran modern

Background Coccidiosis caused by Eimeria species (spp.) is a significant global health concern in goats leading to gastrointestinal illness. This condition causes clinical manifestations, including weight loss and diarrhea, resulting in worldwide economic losses. Subclinical symptoms can manifest during Eimeria infection. Neglecting this disease can lead to severe morbidity and mortality. Therefore, addressing caprine coccidiosis is imperative. Aim This study aimed to determine the prevalence and molecular identification related to the natural infection of Eimeria spp. in domestic goats originating from Java Island, Indonesia. Methods In total, fecal samples from 289 domestic goats were obtained across five provinces on Java Island, Indonesia: East Java, Central Java, D. I. Yogyakarta, West Java, and Banten. Morphological examinations were performed using the modified Whitlock method and saturated sugar flotation. Molecular assays targeting the 18S ribosomal ribonucleic acid have been employed for spp.-specific confirmation. Statistical analysis was performed using the Wilson binomial proportion and chi-square methods implemented in the online software. Results A total of 92.7% (268/289) of fecal samples tested positive for Eimeria spp. Phylogenetic tree analysis demonstrated that Eimeria christenseni and Eimeria arloingi closely resembled the reference sequences from China, Australia, and other countries. Conclusion This study identified E. christenseni and E. arloingi as the goat-infecting spp. of Eimeria present on Java Island. The specific and accurate molecular identification conducted in this study will contribute to improved coccidiosis control and the development of effectiveness.

Background and Aim The inclusion of Leucaena leucocephala leaf meal (LLM) in poultry feed is often limited due to its high crude fiber and mimosine content. This study investigates the potential of fermented LLM (FLM) to enhance nutrient intake, egg production, and egg quality in laying quails by reducing anti-nutritional factors through fermentation. Materials and Methods Two hundred 42-day-old laying quails were assigned to five dietary treatments: T0 (control) = 100% basal diet (BD), T1 = 98% BD + 2% FLM, T2 = 96% BD + 4% FLM, T3 = 94% BD + 6% FLM, and T4 = 92% BD + 8% FLM. Parameters including nutrient intake (energy, protein, fat, calcium, phosphorus), feed conversion ratio (FCR), egg production, egg weight, eggshell thickness, Haugh unit, and yolk color were measured over a 28-day trial. Data were analyzed using a one-way analysis of variance, followed by Duncan’s test for significant differences (p ≤ 0.05). Results FLM supplementation significantly improved energy, protein, fat, calcium, and phosphorus intake while reducing FCR. At 4% FLM inclusion, significant enhancements in egg production, eggshell thickness, Haugh unit, and yolk color were observed. Conversely, fiber intake and overall feed intake remained unaffected across treatments. The highest egg production (56.43%) and best yolk color (8,95) were observed in the 8% FLM group. Conclusion Incorporating FLM into the diets of laying quails effectively enhances nutrient utilization and improves egg production and quality without increasing feed intake. The optimal inclusion level for maximizing benefits appears to be 4-8% FLM.

Edge computing, a distributed computing paradigm that places small yet capable computing devices near data sources and IoT sensors, is gaining widespread adoption in various real-world applications, such as real-time intelligent drones, autonomous vehicles, and robotics. Object detection (OD) is an essential task in computer vision. Although state-of-the-art deep learning-based OD methods achieve high detection rates, their large model size and high computational demands often hinder deployment on resource-constrained edge devices. Given their limited memory and computational power, edge devices like the Jetson Nano (J. Nano), Jetson Orin Nano (Orin Nano), and Raspberry Pi 4B (Raspi4B) require model optimization and compression techniques in order to deploy large OD models such as YOLO. YOLOv4 is a widely used OD model with a backbone for image feature extraction and a prediction layer. Originally, YOLOv4 was designed to use CSPDarkNet53 as its backbone, which requires significant computational power. In this paper, we propose replacing its backbone with a smaller model, such as MobileNetV2 and RepViT. In order to ensure the strong backbone performance, we perform knowledge distillation (KD), using CSPDarknet53 as the teacher and the smaller model as the student.We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. According to our experiments, Contrastive Representation Distillation (CRD) yields MobileNetV2 and RepViT with an acceptable accuracy drop. We consider both accuracy drop and model size to choose either MobileNetV2 or RepViT model to replace CSPDarknet53 in the modified YOLOv4 named M-YOLO-CRD and RV-YOLO-CRD. Our evaluation results demonstrate that RV-YOLO-CRD reduces 30% of model size and achieves better mean average precision (mAP) than M-YOLO-CRD. Our experiments show that the M-YOLO-CRD significantly reduces model size (from 245.5 MB to 35.76 MB) and inference time (6× faster on CPU, 4× faster on J. Nano, and 2.5× faster on Orin Nano. While the precision decreased slightly (less than 4%) , the model still performs well on edge devices. The M-YOLO-CRD achieved latency per frame at around 37 ms on Orin Nano, 168 ms on J. Nano, and 1310 ms on Raspi4B.

Digital Twin (DT) is a technology that creates a digital replica of a physical object or system, enabling virtual monitoring, simulation, and testing. DT technology integrates historical and real-time data to predict future situations, proving advantageous in areas with high-value assets. In the maritime industry, DT plays a crucial role in the development of autonomous vessels, predictive maintenance, energy management, and port operations. DT facilitates the simulation of maritime environmental conditions and the monitoring of vessel health, hence improving operating efficiency and mitigating hazards. The main challenges in DT implementation encompass sufficient information technology infrastructure, data integrity, security, and interoperability. By tackling these difficulties, DT possesses significant potential to transform the marine sector, enhancing data-driven decision-making and promoting more efficient and environmentally sustainable vessel management.

It is common for individuals to seek information online when facing health and nutritional problems, particularly those with lower education level and nutritional knowledge ⁽¹⁾ . One way to access such information is through search engines, with Google being the most popular, currently used by 92% of the world’s population, with an average of 85.59 billion monthly visits ⁽²⁾ . Google Trends is a tool provided by Google, freely accessible, allowing users to observe patterns in internet searches ⁽³⁾ . The aim of this study is to identify patterns to predict trends related to weight loss at specific times. Data were extracted from Google Trends over the past 20 years, from 2004 to 2024, using the keywords “weight loss” and “diet.” In Google Trends, users may input a keyword consisting of words or phrases that are relevant to the chosen issue or cases. The duration of time that users wish to examine can be specified. Furthermore, users can explore geographical regions or search worldwide. Figures generated represent search interest based on the highest points on the graph for specific regions and times. The popularity of search terms is relative and depends on the category: search term or topic. Data is normalised and presented on a scale from 0-100, where each point on the graph is divided by the highest point, or 100. A value of 100 indicates peak popularity, 50 indicates half popularity, and 0 indicates insufficient data for the term. Over the past 20 years, there has been an increasing trend in searches for websites using the keyword “weight loss,” with an average interest score of 31. This differs from the keyword “diet,” which has shown a tendency towards stagnation in popularity, although it briefly peaked with a score of 100 in early 2014 and has an average interest score of 53. Both keywords exhibit similar search patterns, reaching their highest peaks each year in January and lowest points in December. For the keyword “weight loss,” the most searches were from South Africa (100), Romania (96), and Vietnam (91), while the lowest were from Italy (4), Japan (5), and the Netherlands (9). For the keyword “diet,” the most searches were from Poland (100), Kuwait (87), and Greece (85), while the lowest were from Japan (2), Thailand (7), and France (11). Users also searched for other related topics or queries including ozempic and intermitten fasting. Our data indicates a consistent increasing trend in searches for weight loss over the last 20 years via Google Trends. New Year resolutions may be linked to peak searches which occur in January. While this data may prove useful for researchers and policymakers, further validation of its validity and reliability is necessary.

Mealybug is a renowned pest known to attack agricultural products from the field to the post-harvest process, such as on the seed rhizomes of Curcuma aeruginosa. Therefore, this study aimed to examine and identify the species of mealybug on the seed rhizomes of C. aeruginosa based on morphological and molecular characteristics. Fifty mealybugs were collected from the seed rhizomes of C. aeruginosa in the storage room in Bogor (Indonesia) using a soft brush. They were transferred to new C. aeruginosa rhizomes without any other insects present. Morphological identification based on observation of mounted specimens of 10 female adults and six for molecular identification. The primer pair that amplified the mitochondrial cytochrome oxidase I (COI) gene was used to study the molecular characteristics and was continued with direct sequencing and sequence analysis. The results showed that the morphological characteristics of the mounted specimen were close to those of Pseudococcus jackbeardsleyi. Amplification of the COI gene yielded DNA bands measuring 490 base pairs (bp), while homology and phylogeny analysis confirmed the morphological identification. Based on BLAST analysis, the similarity of COI genes of mealybugs in this study was above 99% with other P. jackbeardsleyi. The study specimen was identified as P. jackbeardsleyi on the seed rhizomes of C. aeruginosa by comparing the morphological features of insect specimens and results of the species available in GeneBank. This result represented the first documented report about the presence of the species in storage.

The coffee production process typically generates sub-grade coffee beans, accounting for approximately 10%–20% of total production, with a significant defect rate of 39.54% due to broken beans. Although these beans have a low market value and can negatively impact quality and flavor, they still contain various beneficial compounds. Increasing the economic value of sub-grade coffee beans can be achieved through diversification, such as blending them with chocolate to enhance flavor. To ensure product sustainability, development efforts must prioritize quality. Consumer perceptions of quality, which encompass emotional, sensory, and safety aspects, greatly influence satisfaction. Thus, analyzing consumer impressions is crucial to aligning product development with customer expectations. Kansei words capture and measure emotional impressions based on customer requirements (CRs), while Fuzzy Quality Function Deployment (QFD) systematically translates these desires into measurable product attributes. The study identified 11 technical responses to meet consumer expectations, with the top three being the selection of high-quality raw materials (4.26), the determination of appropriate processing techniques (3.90), and securing permits to ensure health safety (2.63). These technical responses are prioritized to fulfill consumer desires. Subsequently, specific efforts related to these technical responses are determined to detail the steps needed to meet consumer expectations and enhance satisfaction.

Energi merupakan bagian terpenting dalam kehidupan kita sehari-hari karena sebagian besar aktivitas dan kebutuhan manusia selalu membutuhkan energi. Pengembangan teknologi dibidang energi untuk pembangkit listrik menggunakan energi terbarukan di Indonesia sangat berpotensi dimana Indonesia merupakan negara tropis yang terekspos sinar matahari hampir sepanjang tahun. Namun, hanya digunakan untuk kegiatan praktikum dan masih belum terkoneksi dengan beban yg optimal Pembangkit Listrik Tenaga Surya (PLTS) sebesar 4 kW telah terinstal pada rooftop lantai 6 Gedung Teknik Politeknik Negeri Jember. Penelitian ini bertujuan untuk mengetahui performa PLTS rooftop yang telah terpasang dengan cara mengintegrasikan ke jaringan listrik di Gedung Teknik. Integrasi PLTS di Gedung Teknik Lantai 6 telah berhasil dilakukan untuk mensuplai lampu penerangan di Gedung Teknik Lantai 3 sebanyak 25 unit lampu dengan total konsumsi daya adalah 964 watt. Sistem PLTS diinstal secara offgrid rangkaian AC coupling yang terdiri dari 12 unit panel surya masing-masing berkapasitas daya 360 watt, 1 unit inverter 5000 watt, dan 8 unit baterai 12 volt 105 Ah.