Reading Errors Research Articles

Rancang Bangun Purwarupa Monitoring Arus Bocor Pada Kabel Grounding Trafo Incoming 20 KV di Gardu Induk Nusa Dua Berbasis Internet Of Things

Failure of the grounding isolation on the 20 kV transformer incoming cable, resulting in leakage current. The leakage current on the grounding cable can change periodically, so an accurate and real-time monitoring system is required to protect the power transformer equipment and facilitate responsive handling. Therefore, an Internet of Things-based monitoring device is needed that can detect the magnitude of the leakage current present on the 20 kV secondary side of the transformer using an ESP8266 microcontroller and Arduino UNO R3 as the brain of the monitoring system, which controls and processes data from the input to output components. The SCT-013 current sensor is used to measure the AC current on the transformer incoming 20 kV grounding cable without requiring cable cutting, and the Arduino IDE is used to configure the program on the ESP8266 microcontroller to work according to the desired configuration. The results of the prototype testing using the ESP826 and Arduino UNO R3 microcontrollers and the SCT-013 current sensor have shown that the system can work well and the monitoring has been successfully implemented with real-time current monitoring using the Thinkspeak and Blynk platforms. The testing also proved that the SCT-013 current monitoring device can provide a comparison of the test results and measurements with a Tang Ampere, and the data obtained shows that the real-time SCT-013 current monitoring device is accurate, with an average reading error of less than 3% from the SCT-013 non-linearity specification, with a total reading error percentage of 2.0%. Additionally, the current monitoring device is precise, with the lowest standard deviation value of 0.046.

An action research to overcome reading difficulties encountered after the Covid-19 pandemic

This study aimed to overcome the reading problems of a student who had reading difficulties due to the effect of distance education during the Covid-19 pandemic with reading fluency strategies. For this purpose, the study was conducted with a 5th grade student studying in Turkey. The study was conducted with action research, one of the qualitative research patterns. Texts appropriate to the student's age and reading level, as well as researcher and student diaries were used as data collection tools. The student's reading errors were determined and presented with descriptive data, and a reading action plan was prepared for the low-performing student. Over 18 lesson hours, a reading program incorporating strategies such as repetitive reading, paired reading, guided reading, word repetition, and word box techniques was implemented. Post-intervention evaluation revealed that the student’s reading level improved from the concern level to the instructional level, with notable progress in reading deficiencies. This study contributes to the literature by demonstrating that students with reading difficulties can enhance their reading skills through appropriate methods and techniques, mitigating the adverse effects of the pandemic period.

Organic Nonvolatile 2T Memory Cell Employing a NOT-Gate-Like Architecture Toward Binary Output Level With Enhanced Noise Tolerance.

Organic nonvolatile memory has been considered a low-cost memory technology for flexible electronics and Internet-of-things (IoT). However, a major concern is the nonuniformity of memory units, which is primarily caused by random grain boundaries, interface defects, and charge traps, making it difficult to develop high-density reliable memory arrays. This nonuniformity problem would induce read error, which is directly caused by the narrow distribution margin of memory states and low noise tolerance in conventional organic memory cells. To break this limitation, a novel 2T memory cell employing a NOT-gate-like architecture achieving self-enhancing noise tolerance is presented. This unique cell consists of a pair of commonly-gated memory transistors with contradictory "write-and-erase" features. It functions as a voltage divider, producing a well-distinguished binary voltage output capability. The concept and design model of this brand-new 2T memory cell is thoroughly discussed. It is originally characterized by noise-tolerant memory cells irrespective of device nonuniformity. The noise tolerance range of this 2T memory cell is also investigated. The binary voltage-readable memory state with a large noise tolerance range is obtained. Moreover, the conceptual design of the 1T2T FeRAM cell is further developed for low-cost voltage-readable memory technology in wearable electronic applications.

Resolving the problem of surface dyslexia in Italian through inflection of irregular verbs.

Surface dyslexia and dysgraphia are considered diagnostic features of semantic variant primary progressive aphasia (svPPA) and are useful signs in English, a language whose attributes afford numerous opportunities to observe these phenomena. This, however, is not the case in many languages, including Italian, that have high transparency between orthography and phonology, making surface reading and spelling errors scarce. This creates a problem in applying the diagnostic recommendations for svPPA in such languages. Surface dyslexia and dysgraphia are examples of 'regularization' errors in which semantic knowledge loss leads to a failure to recognize exceptions that do not follow standard rules of pronunciation. Another form of regularization involves the incorrect inflection of irregular verbs using the rules that govern regular verbs. Unlike irregularly pronounced words, Italian, as with many languages, has numerous irregular verbs. The Italian Verb Inflection Test (IVIT) was developed to test the hypothesis that svPPA would regularize irregular verbs when inflecting them into two Italian past tenses. Results confirmed that people with svPPA made a significantly greater proportion of regularization errors compared to people with typical Alzheimer's disease or logopenic variant PPA. Without recourse to the other diagnostic features of PPA subgroups, the IVIT on its own could separate svPPA from these other two groups with 70% sensitivity and ~ 80% specificity. Regularization of irregular verb inflection offers a solution to the problem of applying the surface dyslexia/dysgraphia criterion for svPPA diagnosis in Italian.

Metode Pengumpulan Data Debit Air Pada Saluran Distribusi Air PDAM Makassar Berbasis IoT

Water is an important resource for human survival as well as various economic sectors. PDAM is responsible for providing water supply to the community. One of the major challenges faced in managing water supply is the problem of water loss or leakage. This research aims to overcome this problem by designing an innovative method to collect water discharge data on the distribution channel of PDAM Makassar using Internet of Things (IoT) technology. This method uses the ESP32-CAM to take images of the water meter on the main pipe and save it to a database. Optical Character Recognition (OCR) technology is used to convert the image into text that can be processed. The test results show that the average error in meter readings is 0.215% with an average accuracy rate of 98%. Overall the system works well in reading digital meters and is reliable in monitoring water consumption visually and in real-time. Thus, this method can be an effective solution in detecting water leaks and improving the efficiency of water supply management by PDAMs, as well as saving resources and operational costs.

Ultra-compact dual-channel integrated CO2 infrared gas sensor

Expiratory CO2 concentrations can directly reflect human physiological conditions, and their detection is highly important in the treatment and rehabilitation of critically ill patients. Existing respiratory gas analyzers suffer from large sizes and high power consumption due to the limitations of the internal CO2 sensors, which prevent them from being wearable to track active people. The internal and external interference and sensitivity limitations must be overcome to realize wearable respiratory monitoring applications for CO2 sensors. In this work, an ultra-compact CO2 sensor was developed by integrating a microelectromechanical system emitter and thermopile detectors with an optical gas chamber; the power consumption of the light source and ambient temperature of the thermally sensitive devices were reduced by heat transfer control; the time to reach stabilization of the sensor was shortened; the humidity resistance of the sensor was improved by a dual-channel design; the light loss of the sensor was compensated by improving the optical coupling efficiency, which was combined with the amplitude trimming network to equivalently improve the sensitivity of the sensor. The minimum size of the developed sensor was 12 mm × 6 mm × 4 mm, and the reading error was <4% of the reading from −20 °C to 50 °C. The minimum power consumption of the sensor was ~33 mW, and the response time and recovery time were 10 s (@1 Hz), and the sensor had good humidity resistance, stability, and repeatability. These results indicate that the CO2 sensor developed using this strategy has great potential for wearable respiratory monitoring applications.

Integrated Artificial Neural Network with Trainable Activation Function Enabled by Topological Insulator-Based Spin-Orbit Torque Devices.

Nonvolatile memristors offer a salient platform for artificial neural network (ANN), yet the integration of different function and algorithm blocks into one hardware system remains challenging. Here we demonstrate the brain-like synaptic (SOT-S) and neuronal (SOT-N) functions in the Bi2Te3/CrTe2 heterostructure-based spin-orbit torque (SOT) device. The SOT-S unit exhibits highly linear and symmetrical long-term potentiation/depression process, resulting in a fast-training of the MNIST data set with the classification accuracy above 90%. Meanwhile, the Sigmoid-shape transition curve inherited in the SOT-N cell replaces the software-based activation function block, hence reducing the system complexity. On this basis, we employ a serial-connected, voltage-mode sensing ANN architecture to enhance the vector-matrix multiplication signal strength with low reading error of 0.61% while simplifying the peripheral circuitry. Furthermore, the trainable activation function of SOT-N enables the implementation of the Batch Normalization algorithm and activation operation within one clock cycle, which bring about improved on/off-chip training performance close to the ideal baseline.

The Effect of Display Polarity on Reading Speed and Reading Error Among Young Adults

Objective: The widespread adoption of digital devices has surged, particularly since the coronavirus disease 2019 (COVID-19) pandemic. Nearly everyone now owns devices like laptops, tablets, or smartphones, offering options for light mode (positive polarity) and dark mode (negative polarity) to suit individual preferences. This study examines how display polarity affects reading performance among young adults. Material and Methods: Thirty participants engaged in a 15-minute reading task on a laptop with randomly assigned display polarities, followed by a 15-minute break before repeating the task. Results: Reading speed, measured in words per minute (wpm), differed significantly between polarities, with negative polarity yielding higher speeds (136.27±25.58 wpm) compared to positive polarity (128.42±19.98 wpm), Z=-2.355, p-value&lt;0.05. However, no significant polarity-related differences were found in reading errors, including mispronunciation (p-value=0.193) or omission (p-value=0.113). Conclusion: Negative polarity displays enhanced reading performance by increasing reading speed; while reading errors remained unaffected.

Nanopore strand-specific mismatch enables de novo detection of bacterial DNA modifications.

DNA modifications in bacteria present diverse types and distributions, playing crucial functional roles. Current methods for detecting bacterial DNA modifications via nanopore sequencing typically involve comparing raw current signals to a methylation-free control. In this study, we found that bacterial DNA modification induces errors in nanopore reads. And these errors are found only in one strand but not the other, showing a strand-specific bias. Leveraging this discovery, we developed Hammerhead, a pioneering pipeline designed for de novo methylation discovery that circumvents the necessity of raw signal inference and a methylation-free control. The majority (14 out of 16) of the identified motifs can be validated by raw signal comparison methods or by identifying corresponding methyltransferases in bacteria. Additionally, we included a novel polishing strategy employing duplex reads to correct modification-induced errors in bacterial genome assemblies, achieving a reduction of over 85% in such errors. In summary, Hammerhead enables users to effectively locate bacterial DNA methylation sites from nanopore FASTQ/FASTA reads, thus holds promise as a routine pipeline for a wide range of nanopore sequencing applications, such as genome assembly, metagenomic binning, decontaminating eukaryotic genome assemblies, and functional analysis for DNA modifications.

RANCANG BANGUN PRODUK SUBSTITUSI SISTEM DATA LOGGER ALIRAN DAN TEKANAN AIR PADA ALIRAN PIPA TERTUTUP MENGGUNAKAN KOMUNIKASI LoRaWAN

The availability of data loggers as data acquisition is still limited to sensor levels and the data loggers have not been produced in Indonesia. This makes it difficult for monitors to obtain data such as water pressure and water discharge data. The solution to this problem is to reduce the import cost of purchasing data loggers from abroad by developing data loggers that are able to take data on water level, water pressure. This study aims to determine how the design and performance of data logger system substitution products flow and water pressure using LoRa WAN communication. The test results show that the Water Flow and Pressure Data logger System functions according to the design that has been made with error readings from the itron cyble sensor of ?? and a pressure sensor reading error of 20.66%. The Packet Loss value of sending data from the data logger device is directly proportional to the distance where the smallest packet loss value is 13% at a distance of 50m and 80% at a distance of 2800m.

Estimating the rate of failure to notice functionword errors in natural reading.

Skilled readers sometimes fail to notice seemingly obvious errors in text, such as the repetition or omission of a function word or the transposition of two words, suggesting that linguistic knowledge can override bottom-up input at either a perceptual or postperceptual level. The present study investigates the role of this top-down process of error correction in natural reading of extended texts. In previous research, critical sentences have been presented one at a time, and subjects were explicitly tasked with detecting errors. In the present study, each participant read a full newspaper article or pair of articles, with their comprehension tested by multiple choice questions. As a secondary task, participants were also instructed that they should make a mouse click on any errors in the text, without any instruction as to the frequency or nature of any such errors. Each article contained nine intentionally inserted errors involving function words: three repetitions, three omissions, and three transpositions. After removing subjects who did not click on the text at all (leaving n = 165), the median subject made seven clicks, but detected only one of the nine inserted errors. Neither error type nor article type (highly professional vs. amateur) clearly modulated the rate of error detection, though subjects clicked more often overall on the amateur articles. We conclude that previous research has dramatically underestimated the rate at which readers fail to notice these function word errors; in natural reading, they are noticed only rarely. No existing reading model can account for this phenomenon.

Efficiency of phonics-based instruction in developing reading, spelling, and pronunciation fluency among Yemeni EFL primary learners

In Yemen, there is a scarcity of research and a lack of application for phonics-based instruction. Hence, the present study aimed to explore EFL teachers' perspectives on the efficiency of phonics instruction in developing reading, spelling and pronunciation fluency among Yemeni EFL learners at primary schools. The study sample comprised 33 EFL teachers from six schools in Dhamar City, Yemen. The participants were asked to give their views and share their experiences on the efficacy of phonics-based instruction in developing the above-mentioned language skills. The participants were selected based on the convenient sampling technique and asked to respond to a questionnaire consisting of 15 statements. The data obtained were analyzed using the SPSS program version 22.0 to display descriptive statistics quantitatively. The results revealed that teaching phonics is so crucial for the development and improvement of learners' reading fluency, spelling mastery, and pronunciation proficiency. In addition, phonics teaching contributes to reducing and/or eliminating the learners' errors in spelling, reading, and pronunciation. The findings highlighted the importance of integrating phonics teaching into the curricula of English in the early stages at Yemeni schools.

Examining the Smart-Prepaid Metering Systems in Ghana: Implications for Policy Reform

This study examined Smart-Prepaid Metering System deployed by ECG and NEDCo from the technical point of view. The analysis revealed that smart meters are far advantageous compared to traditional postpaid meters that are error prone- reading errors, generate a lot of system losses, and can be bypassed by power theft. The high losses that utility companies make because of non- payment of bills could be reduced to the barest minimum. The resistance to smart-prepaid meter adoption is due to the high bills consumers are experiencing. The rising bills were caused by the use of energy consuming appliances like electric stove, dryers, washers coupled with rise in tariff. The study recommends mass education using various fora like community engagement and electronic media to teach consumers the added values of the new meters and how to use them efficiently. Also, these meters should installed at all government institutions and private industries that have been persistently defaulting in bill payment.

Perceptual inference corrects function word errors in reading: Errors that are not noticed do not disrupt eye movements

Both everyday experience and laboratory research demonstrate that readers often fail to notice errors such as an omitted or repeated function word. This phenomenon challenges central tenets of reading and sentence processing models, according to which each word is lexically processed and incrementally integrated into a syntactic representation. One solution would propose that apparent failure to notice such errors reflects post-perceptual inference; the reader does initially perceive the error, but then unconsciously ’corrects’ the perceived string. Such a post-perceptual account predicts that when readers fail to explicitly notice an error, the error will nevertheless disrupt reading, at least fleetingly. We present a large-scale eyetracking experiment investigating whether disruption is detectable in the eye movement record when readers fail to notice an omitted or repeated two-letter function word in naturalistic sentences. Readers failed to notice both omission and repetition errors over 36% of the time. In an analysis that included all trials, both omission and repetition resulted in pronounced eye movement disruption, compared to reading of grammatical control sentences. But in an analysis including only trials on which readers failed to notice the errors, neither type of error disrupted eye movements on any measure. Indeed, there was evidence in some measures that reading was relatively fast on the trials on which errors were missed. It does not appear that when an error is not consciously noticed, it is initially perceived, and then later corrected; rather, linguistic knowledge influences what the reader perceives.

Identification of Insertion and Deletion (InDel) Markers for Chickpea (Cicer arietinum L.) Based on Double-Digest Restriction Site-Associated DNA Sequencing.

Enhancing the marker repository and the development of breeder-friendly markers in chickpeas is important in relation to chickpea genomics-assisted breeding applications. Insertion-deletion (InDel) markers are widely distributed across genomes and easily observed with specifically designed primers, leading to less time, cost, and labor requirements. In light of this, the present study focused on the identification and development of InDel markers through the use of double-digest restriction site-associated DNA sequencing (ddRADSeq) data from 20 chickpea accessions. Bioinformatic analysis identified 20,700 InDel sites, including 15,031 (72.61%) deletions and 5669 (27.39%) insertions, among the chickpea accessions. The InDel markers ranged from 1 to 25 bp in length, while single-nucleotide-length InDel markers were found to represent the majority of the InDel sites and account for 79% of the total InDel markers. However, we focused on InDel markers wherein the length was greater than a single nucleotide to avoid any read or alignment errors. Among all of the InDel markers, 96.1% were less than 10 bp, 3.6% were between 10 and 20 bp, and 0.3% were more than 20 bp in length. We examined the InDel markers that were 10 bp and longer for the development of InDel markers based on a consideration of the genomic distribution and low-cost genotyping with agarose gels. A total of 29 InDel regions were selected, and primers were successfully designed to evaluate their efficiency. Annotation analysis of the InDel markers revealed them to be found with the highest frequency in the intergenic regions (82.76%), followed by the introns (6.90%), coding sequences (6.90%), and exons (3.45%). Genetic diversity analysis demonstrated that the polymorphic information content of the markers varied from 0.09 to 0.37, with an average of 0.20. Taken together, these results showed the efficiency of InDel marker development for chickpea genetic and genomic studies using the ddRADSeq method. The identified markers might prove valuable for chickpea breeders.

Primed and ready: nanopore metabarcoding can now recover highly accurate consensus barcodes that are generally indel-free

BackgroundDNA metabarcoding applies high-throughput sequencing approaches to generate numerous DNA barcodes from mixed sample pools for mass species identification and community characterisation. To date, however, most metabarcoding studies employ second-generation sequencing platforms like Illumina, which are limited by short read lengths and longer turnaround times. While third-generation platforms such as the MinION (Oxford Nanopore Technologies) can sequence longer reads and even in real-time, application of these platforms for metabarcoding has remained limited possibly due to the relatively high read error rates as well as the paucity of specialised software for processing such reads.ResultsWe show that this is no longer the case by performing nanopore-based, cytochrome c oxidase subunit I (COI) metabarcoding on 34 zooplankton bulk samples, and benchmarking the results against conventional Illumina MiSeq sequencing. Nanopore R10.3 sequencing chemistry and super accurate (SUP) basecalling model reduced raw read error rates to ~ 4%, and consensus calling with amplicon_sorter (without further error correction) generated metabarcodes that were ≤ 1% erroneous. Although Illumina recovered a higher number of molecular operational taxonomic units (MOTUs) than nanopore sequencing (589 vs. 471), we found no significant differences in the zooplankton communities inferred between the sequencing platforms. Importantly, 406 of 444 (91.4%) shared MOTUs between Illumina and nanopore were also found to be free of indel errors, and 85% of the zooplankton richness could be recovered after just 12–15 h of sequencing.ConclusionOur results demonstrate that nanopore sequencing can generate metabarcodes with Illumina-like accuracy, and we are the first study to show that nanopore metabarcodes are almost always indel-free. We also show that nanopore metabarcoding is viable for characterising species-rich communities rapidly, and that the same ecological conclusions can be obtained regardless of the sequencing platform used. Collectively, our study inspires confidence in nanopore sequencing and paves the way for greater utilisation of nanopore technology in various metabarcoding applications.

Analysis of Goals Conceded by Goalkeepers in Two FIFA World Cups

&lt;p&gt;目的：探討兩屆世足賽中守門員各時段、傷停補時、球衣顏色對失球因素分布情形，並提供相關實務建議與策略。方法：以影像觀察法為主，透過電腦網路影片，經由慢速播放記錄各項失球因素與FIFA官方數據加以反覆交叉核對，分析兩屆世足賽守門員失球因素共128場。研究方法以利用卡方檢定、描述性研究以及比較百分比來進行研究分析守門員各項失球數據。結果：一、失球時間分析：兩屆世足賽皆為下半場102球與101球 (占61.4%與60.1%) 高於上半場64球與67球 (占38.6%與39.9%)。二、傷停補時分析：兩屆世足賽皆為下半場20球與15球 (占87.0%與75%) 高於上半場3球與5球 (占13.0%與25%)。三、球衣顏色分析：兩屆世足賽中發現守門員皆身穿橘色球衣時失球時間較快。結論：一、失球時間：下半場失分上升涵蓋多種因素，包含球員與守門員脫水、體能耗盡、比賽節奏加快、球隊戰術改變、觀察與判斷能力下降、注意力不集中、防守失誤等。二、傷停補時分析：此時段應特別留意球員的壓力和身心狀態，球隊可根據比分情況採取不同策略，藉此提高比賽勝算。三、球衣顏色分析：教練在選擇球衣顏色時應多加留意，球員們藉由身穿不同顏色的球衣進行視覺訓練來強化對視覺的感知與適應力，以降低失球風險。&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;Purposes: This study aimed to analyze the distribution of factors contributing to goals conceded by goalkeepers in two FIFA World Cups, incorporating considerations of distinct time periods, additional time, and jersey colors. Methods: Employing observational methods, the research utilized internet video clips, slow-motion replays, and cross-verification with official FIFA data to analyze 128 games from two World Cups. The data were analyzed using Chi-Square tests, descriptive studies, and comparative percentages to scrutinize various factors influencing goals conceded by goalkeepers. Results: a) Goal concession time analysis: across both World Cups, a higher number of goals were conceded in the second half, accounting for 61.4% and 60.1%, compared to the first half with 38.6% and 39.9%, respectively; b) Additional time analysis: the analysis indicates that more goals were conceded during the second half, constituting 87.0% and 75% in the two World Cups, as opposed to the first half with 13.0% and 25%, respectively; c) Jersey color analysis: goalkeepers wearing orange jerseys were found to concede goals more frequently in both World Cups. Conclusion: The study identifies significant insights, a) Factors contributing to increased goals in the second half encompass player and goalkeeper dehydration, physical exhaustion, heightened game tempo, tactical adjustments, diminished game reading, decreased concentration, and defensive errors; b) Coaches are advised to closely monitor players’ stress levels, physical and mental conditions during additional time. Adopting and adjusting strategies during this period can enhance a team’s chances of success; c) Coaches should exercise caution in selecting jersey colors, as goalkeepers wearing orange jerseys exhibited a higher susceptibility to conceding goals. Players can enhance visual perception and adaptability through training with jerseys of diverse colors, mitigating the risk of conceding goals.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

QRGB+: Advanced QR Code Generator with RGB Color Method in Python to Expand Data Capacity

The present work entitled QRGB, consists of the development of an application in Python for the generation of QR codes using the additive color generation (RGB) method. This innovative method allows increasing the density of information stored in QR codes by using three color layers (red, green and blue), each representing a different set of data. QRGB offers an efficient and secure solution for storing and transmitting large amounts of information in limited spaces, significantly improving the capabilities of traditional black and white QR codes. By using three layers of colors, QRGB codes can store up to three times more information in the same space. This technique not only increases storage capacity but also improves information security, making it difficult to forge or manipulate the code. The overlay of multiple data layers allows redundancy to be implemented, increasing the robustness of the code against damage or reading errors. QRGBs are especially useful in applications that require the transmission of large amounts of data in limited spaces, such as in the packaging industry, digital business cards, and interactive advertising. Additionally, they have great potential in areas such as document and banknote security, where the authenticity and integrity of information are crucial. These points provide a solid foundation for understanding the innovation and advantages of colored QR codes (QRGB) compared to traditional QR codes, highlighting their applicability and potential in various sectors. This article presents a novel method for encoding and decoding information using a QRGB code, which involves the generation of three independent QR codes and their superimposition according to the additive color system (RGB). The research highlights the challenges encountered during the encoding and decoding processes due to the lack of specific libraries in Python, which required the creation of a custom solution using open source tools. The implementation takes advantage of Python and its libraries: qrcode[pil] to generate QR codes with the Pillow dependency for image manipulation, Pillow to open, manipulate and save different image formats, and opencv-python to perform tasks such as image processing and object detection. Despite facing issues with color mixing and accurate information retrieval, the proposed method demonstrates a significant increase in data density within a single QR code. Future work will focus on optimizing the algorithm and exploring potential applications in data security and high-density information storage. This Python script is designed to generate and decode QR codes with a logo overlay using a graphical user interface (GUI) built with Tkinter. The script combines several functionalities, such as creating QR codes, overlaying a logo, combining QR images of different colors, and manually decoding combined QR codes.

Analysis of Difficulty in Solving Story Problems Based on Newman Error Analysis on Flat Building Material in Grade IV Elementary School

This study aims to analyze the difficulties students experience based on errors in solving story problems related to flat shapes using Newman’s Error Analysis procedure. The method used in this research is descriptive analysis. The subjects of the study are fourth-grade students at SDN Sindangkasih. Data was collected through tests and interviews. The results of the data analysis using the Newman procedure reveal that student errors include reading errors at 0.51%, comprehension errors at 2.5%, transformation errors at 16.24%, process skill errors at 39.5%, and encoding errors at 41.63%. The increase in the percentage of errors from reading to encoding is due to students' inability to solve problems correctly after encountering difficulties at the initial stage.

Designing a Real-Time DataLogger Using the Internet of Things for a Basic Imple Home Kwh Meter Capable of 1300 VA

Researchers want to make a kWh meter monitoring tool with estimated usage costs so that the tools made can help people to minimize costs in electricity usage. The purpose of this research is the creation of an IoT-based kWh meter monitoring tool that has the ability to read current, voltage, frequency, power factor and power usage that flows and shows the use of costs that have been used in real time with the display results on the LCD and also on the user's smartphone. In the reading results of usage costs (Rp) on the tool and PLN there is also a difference of Rp. 12,000, where the reading results on the tool are also lower than the results of the payment slip provided by PLN. The cost reading error rate on the tool is 4.4% with a reading accuracy rate of 95.6%.