Analisis Sentimen pada Komentar Sosial Media Instagram Layanan Kesehatan BPJS Menggunakan Naïve Bayes Classifier

Abstrak - Instansi Pelayan Kesehatan Pemerintah seperti BPJS Kesehatan membutuhkan feedback dari masyarakat yang merupakan sumber informasi untuk meningkatkan kinerja. Umpan balik yang didapatkan dari masyarakat tidak hanya yang bersifat positif, melainkan juga bersifat negatif. Tujuan penelitian ini adalah menganalisis sentimen berdasarkan komentar masyarakat terhadap akun sosial media pemerintahandengan mengklasifikasikan secara otomatis menggunakan algoritma naïve bayes classifier. Hasil implementasi dapat membantu pemilih akun menganalisis respon masyarakat terhadap suatu postingan berupa respon positive, negative atau netral. Metode klasifikasi berbasis pencocokan teks boyer moore berhasil diimplementasikan untuk melakukan klasifikasi teks komentar di postingan instagram. Metode yangdiusulkan memiliki performa baik dengan akurasi mencapai 73 persen.Kata Kunci: Instagram, Text Mining, Sentiment Analysis, Naïve Baye

STEP: extraction of underlying physics with robust machine learning

A prevalent class of challenges in modern physics are inverse problems, where physical quantities must be extracted from experimental measurements. End-to-end machine learning approaches to inverse problems typically require constructing sophisticated estimators to achieve the desired accuracy, largely because they need to learn the complex underlying physical model. Here, we discuss an alternative paradigm: by making the physical model auto-differentiable we can construct a neural surrogate to represent the unknown physical quantity sought, while avoiding having to relearn the known physics entirely. We dub this process surrogate training embedded in physics (STEP) and illustrate that it generalizes well and is robust against overfitting and significant noise in the data. We demonstrate how STEP can be applied to perform dynamic kernel deconvolution to analyse resonant inelastic X-ray scattering spectra and show that surprisingly simple estimator architectures suffice to extract the relevant physical information

Spatial estimation of groundwater quality, hydrogeochemical investigation, and health impacts of shallow groundwater in Kabul city, Afghanistan

The management of groundwater in densely populated areas with no centralized water treatment is critical for the prevention of diseases and maintaining sanitation. Here, we determine the bacteriological and chemical characteristics of groundwater in Kabul city, a resource that 4.1 million individuals rely on. Groundwater samples were analyzed from 41 newly established piezometric wells across Kabul, and data were compared with the last detailed study, undertaken in 2007, to understand contamination trends in an area that has undergone significant development and social changes. Piper diagrams, Gibbs diagrams, correlation analysis, and bivariate plots examine the hydrogeochemical and natural occurring processes of groundwater. The average concentration of cations followed the order Na+  > Mg2+  > Ca2+  > K+, and anions HCO3− > NO3− > Cl− > SO42− > F with Gibbs diagrams indicating mainly rock-weathering influence groundwater chemistry. An increase in nitrate (NO3−) and E. coli indicates anthropogenic activities impacting the shallow groundwater quality, with significantly elevated nitrate (over 50 mg/L) and E. coli (up to 250 CFU/100 mL). The increasing presence of E. coli and NO3− in the shallow groundwater of Kabul city in turn suggests problematic links to the prevalence of waterborne diseases. Additionally, the water quality index (WQI) was used to assess groundwater quality, and rank its suitability for drinking purposes. The WQI analysis showed that less than 35% of shallow groundwater samples had good water quality. The findings of this study are crucial for the development and sustainable management of groundwater in the city. In short term, we propose interventions such as point-of-use (POU) water purification which may offer temporary respite for waterborne disease prevention. Kabul city requires immediate attention to developing sustainable groundwater management policies, expansion of the water supply network, groundwater quality monitoring, and wastewater management

Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game

While Large Language Models (LLMs) are increasingly being used in real-world applications, they remain vulnerable to prompt injection attacks: malicious third party prompts that subvert the intent of the system designer. To help researchers study this problem, we present a dataset of over 126,000 prompt injection attacks and 46,000 prompt-based "defenses" against prompt injection, all created by players of an online game called Tensor Trust. To the best of our knowledge, this is currently the largest dataset of human-generated adversarial examples for instruction-following LLMs. The attacks in our dataset have a lot of easily interpretable stucture, and shed light on the weaknesses of LLMs. We also use the dataset to create a benchmark for resistance to two types of prompt injection, which we refer to as prompt extraction and prompt hijacking. Our benchmark results show that many models are vulnerable to the attack strategies in the Tensor Trust dataset. Furthermore, we show that some attack strategies from the dataset generalize to deployed LLM-based applications, even though they have a very different set of constraints to the game. We release all data and source code at https://tensortrust.ai/pape

Comparing single-best-answer and very-short-answer questions for the assessment of applied medical knowledge in 20 UK medical schools: Cross-sectional study.

OBJECTIVES: The study aimed to compare candidate performance between traditional best-of-five single-best-answer (SBA) questions and very-short-answer (VSA) questions, in which candidates must generate their own answers of between one and five words. The primary objective was to determine if the mean positive cue rate for SBAs exceeded the null hypothesis guessing rate of 20%. DESIGN: This was a cross-sectional study undertaken in 2018. SETTING: 20 medical schools in the UK. PARTICIPANTS: 1417 volunteer medical students preparing for their final undergraduate medicine examinations (total eligible population across all UK medical schools approximately 7500). INTERVENTIONS: Students completed a 50-question VSA test, followed immediately by the same test in SBA format, using a novel digital exam delivery platform which also facilitated rapid marking of VSAs. MAIN OUTCOME MEASURES: The main outcome measure was the mean positive cue rate across SBAs: the percentage of students getting the SBA format of the question correct after getting the VSA format incorrect. Internal consistency, item discrimination and the pass rate using Cohen standard setting for VSAs and SBAs were also evaluated, and a cost analysis in terms of marking the VSA was performed. RESULTS: The study was completed by 1417 students. Mean student scores were 21 percentage points higher for SBAs. The mean positive cue rate was 42.7% (95% CI 36.8% to 48.6%), one-sample t-test against ≤20%: t=7.53, p<0.001. Internal consistency was higher for VSAs than SBAs and the median item discrimination equivalent. The estimated marking cost was £2655 ($3500), with 24.5 hours of clinician time required (1.25 s per student per question). CONCLUSIONS: SBA questions can give a false impression of students' competence. VSAs appear to have greater authenticity and can provide useful information regarding students' cognitive errors, helping to improve learning as well as assessment. Electronic delivery and marking of VSAs is feasible and cost-effective

The World Health Organization was born as a normative agency: Seventy-five years of global health law under WHO governance

The World Health Organization (WHO) was born as a normative agency and has looked to global health law to structure collective action to realize global health with justice. Framed by its constitutional authority to act as the directing and coordinating authority on international health, WHO has long been seen as the central actor in the development and implementation of global health law. However, WHO has faced challenges in advancing law to prevent disease and promote health over the past 75 years, with global health law constrained by new health actors, shifting normative frameworks, and soft law diplomacy. These challenges were exacerbated amid the COVID-19 pandemic, as states neglected international legal commitments in national health responses. Yet, global health law reforms are now underway to strengthen WHO governance, signaling a return to lawmaking for global health. Looking back on WHO’s 75th anniversary, this article examines the central importance of global health law under WHO governance, reviewing the past successes, missed opportunities, and future hopes for WHO. For WHO to meet its constitutional authority to become the normative agency it was born to be, we offer five proposals to reestablish a WHO fit for purpose: normative instruments, equity and human rights mainstreaming, sustainable financing, One Health, and good governance. Drawing from past struggles, these reforms will require further efforts to revitalize hard law authorities in global health, strengthen WHO leadership across the global governance landscape, uphold equity and rights at the center of global health law, and expand negotiations in global health diplomacy

Elevated Cocaine-and Amphetamine-Regulated Transcript Immunoreactivity in the Circulation of Patients with Neuroendocrine Malignancy

Context: Cocaine-and amphetamine-regulated transcript (CART) codes for a peptide widely distributed in nervous and endocrine tissues. CART immunoreactivity (CART-LI) has been detected in human insulinomas. Objective: The objective of the study was to investigate the measurement of plasma CART-LI as a tumor marker of neuroendocrine malignancy. Design and Subjects: Plasma CART-LI levels were measured in 401 patients with a range of diagnoses: neuroendocrine malignancy (n ϭ 131), after removal of neuroendocrine malignancy (n ϭ 27), without any form of tumor or renal impairment (n ϭ 192), with renal impairment (n ϭ 17) and with nonneuroendocrine tumors (n ϭ 34). Chromatography methods were used to investigate CART-LI circulating in human plasma. Results: The upper limit of normal calculated for CART-LI was 150 pmol/liter. Mean circulating plasma CART-LI among neuroendocrine tumor patients was 440 pmol/liter, 56% of subjects having levels greater than 150 pmol/liter. Measuring CART-LI in addition to chromogranin (Cg)-A improved the sensitivity for neuroendocrine malignancy from 85 to 91%, whereas combined use of CgA and CgB had a joint sensitivity of 89%. Of 38 patients with pancreatic neuroendocrine tumors, 71% had plasma CART-LI levels greater than 150 pmol/liter, increasing to 95% in those classified with progressive disease (n ϭ 20, mean CART-LI 625 pmol/liter), compared with 80% for CgA. Chromatographic analysis suggests that circulating CART-LI is present as one major form, which may correspond to CART (62-102) or another unknown form. Conclusions: We demonstrate CART-LI as a specific tumor marker in patients with a range of neuroendocrine tumors. Used in combination with CgA, CART-LI measurement has the potential to improve sensitivity in diagnosis and follow-up of neuroendocrine tumors, in particular progressive pancreatic neuroendocrine tumors

Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit

Resonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe$_2$O$_3$, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds

Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit

Resonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe2O3, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds

Using prescribing very short answer questions to identify sources of medication errors:a prospective study in two UK medical schools

Objective To assess the utility and ability of the novel prescribing very short answer (VSA) question format to identify the sources of undergraduate prescribing errors when compared with the conventional single best answer (SBA) question format and assess the acceptability of machine marking prescribing VSAs. Design A prospective study involving analysis of data generated from a pilot two-part prescribing assessment. Setting Two UK medical schools. Participants 364 final year medical students took part. Participation was voluntary. There were no other inclusion or exclusion criteria. Outcomes (1) Time taken to mark and verify VSA questions (acceptability), (2) differences between VSA and SBA scores, (3) performance in VSA and (4) SBA format across different subject areas and types of prescribing error made in the VSA format. Results 18 200 prescribing VSA questions were marked and verified in 91 min. The median percentage score for the VSA test was significantly lower than the SBA test (28% vs 64%, p<0.0001). Significantly more prescribing errors were detected in the VSA format than the SBA format across all domains, notably in prescribing insulin (96.4% vs 50.3%, p<0.0001), fluids (95.6% vs 55%, p<0.0001) and analgesia (85.7% vs 51%, p<0.0001). Of the incorrect VSA responses, 33.1% were due to the medication prescribed, 6.0% due to the dose, 1.4% due to the route and 4.8% due to the frequency. Conclusions Prescribing VSA questions represent an efficient tool for providing detailed insight into the sources of significant prescribing errors, which are not identified by SBA questions. This makes the prescribing VSA a valuable formative assessment tool to enhance students’ skills in safe prescribing and to potentially reduce prescribing errors