KAJIAN DAN PEMANFAATAN BUBUR KULIT PISANG RAJA (Musa Sapientum) SEBAGAI BAHAN PEMBUATAN BROWNIES DISUBSTITUSI DENGAN TEPUNG BIJI NANGKA (Artocarpus Heterophyllus Lamk) DITINJAU DARI ANALISIS ORGANOLEPTIK DAN KANDUNGAN GIZI

ABSTRACTThis study aimed to study the effect of substitution of jackfruit seed flour and the addition of plantain peel on organoleptic assessment and nutritional value of brownie products. This study used a completely randomized design. The first factor was the substitution of jackfruit seed flour in wheat flour with levels of 0%:100% (T1), 15%:85% (T2), and 30%:70% (T3). The second factor was the addition of plantain peel pulp with levels of 0% (P0), 5% (P1), and 10% (P2). The data were analyzed using the Analysis of Variances (ANOVA). The results with a significant effect then followed by the Duncan's Multiple Range Test (DMRT) test at the 95% confidence level (α = 0.05). The results show that the organoleptic assessment selected by the panelists was the sample with 30% jackfruit seed flour substitution with 5% plantain peel pulp addition. The hedonic assessment scores of color, aroma, texture, and taste reached 4.46 (like), 4.26 (like), 4.00 (like), and 4.20 (like), respectively. Meanwhile, the average descriptive assessment scores of color, aroma, texture, and taste reached 4.16 (bright), 4.13 (fragrant), 4.26 (soft), and 4.46 (good), respectively. The nutrient content of the selected sample shows that it had 27.58% water, 1.89% ash, 13.79% protein, 22.58% fat, and 34.16% carbohydrate. The moisture content of brownies did not meet the national standard, while the ash, fat, protein, and carbohydrate contents met the national standard.Keywords: Brownies cake, jackfruit seed flour, plantain skins porridge, flour.ABSTRAKPenelitian ini bertujuan untuk mempelajari pengaruh substitusi tepung biji nangka dan penambahan kulit pisang raja terhadap penilaian organoleptik dan nilai gizi produk brownies. Penelitian ini menggunakan Rancangan Acak Lengkap. Faktor pertama adalah substitusi tepung biji nangka pada tepung terigu dengan taraf 0% : 100% (T1), 15% : 85% (T2), dan 30% : 70% (T3). Faktor kedua adalah penambahan bubur kulit pisang raja dengan taraf, yakni 0% (P0), 5% (P1), dan 10% (P2). Data dianalisis dengan menggunakan Analyses of Variances (ANOVA), Hasil berpengaruh nyata dilanjutkan dengan uji Duncan’s Multiple Range Test (DMRT) pada taraf kepercayaan 95% (α=0,05). Hasil penelitian menunjukkan bahwa penilaian organoleptik terpilih oleh panelis terdapat pada substitusi tepung biji nangka 30% dengan penambahan bubur kulit pisang raja 5% dengan skor penilaian hedonik terhadap warna 4,46 (suka), aroma 4,26 (suka), tekstur 4,00 (suka), rasa 4,20 (suka), sedangkan skor penilaian deskriptif meliputi warna dengan rerata 4,16 (terang), aroma dengan rerata 4,13 (harum), tekstur dengan rerata 4,26 (lembut), dan rasa dengan rerata sebesar 4,46 (enak). Kandungan gizi meliputi kadar air 27,58 (%), kadar abu 1,89 (%), kadar protein 13,79 (%), kadar lemak 22,58 (%), dan kadar karbohidrat 34,16 (%). Kadar air brownies tidak memenuhi standar SNI, sedangkan kadar abu, lemak, protein, dan karbohidrat telah memenuhi standar SNI.Kata kunci: Kue brownies kukus, tepung biji nangka, bubur kulit pisang raja, tepung terigu.

Automatic Generation of German Translation Candidates for SNOMED CT Textual Descriptions

We present an approach called MTP (multiple translation paths) aiming at assisting human translation in SNOMED CT localisation projects based on free, web-based machine translation tools. For a chosen target language, MTP generates a scored output of translation candidates (TCs) for each input concept. This paper describes the basic idea of MTP, the distribution of its output TCs and discusses typical examples with German as target language. The MTP approach capitalises on combinatorial growth by the combination of input languages, support languages, and translation engines. We applied MTP on the SNOMED CT Starter Set, using Google Translator, DeepL and Systran, together with the four source languages English, Spanish, Swedish and French, and Danish, Dutch, Norwegian, Italian, Portuguese, Polish and Russian as support languages. The descriptive assessment of TC variety, together with an analysis of typical results is the focus of this paper. MTP defines, for each input concept, TPs by the combination of input languages, support languages and translation engines, resulting in 91 translation results with various degrees of co-incidence (cardinality). The most configurations produce an average number of TCs indicating that the same TC is often derived via different translation paths. Combinations of translation engines result in distributions with a higher number of distinct TCs per concept. We present work in progress on using machine translation (MT) for terminology translation, by leveraging several free MT tools fed by different languages and language combinations. A first qualitative analysis was promising and supports our hypothesis that a majority voting applied to many translation candidates yields higher quality results than from one single engine and input language.

Bureaucratic management style and workplace well-being of the Divine Word Colleges

This study aimed to determine the effect of bureaucratic management on the workplace well-being of the Divine Word Colleges. To establish the theoretical foundation of the study, related literature was reviewed. The study used descriptive assessment and correlational research design and the data were gathered through research questionnaires. To interpret the data, descriptive and inferential statistics were used, and therefore, weighted mean was used to determine the level of bureaucratic management, and workplace well-being. While Pearson r correlation was used to determine the correlation between bureaucratic management and workplace well-being. The finding of the study indicated that there is no correlation between bureaucratic management and workplace well-being. Therefore, the hypothesis of the study is rejected. The output of this study contributes to a complex discussion about the effect of bureaucratic management on workplace well-being.

Teachers’ Use of Descriptive Assessment in Primary School Mathematics Education in Iran

In many countries, assessment and curriculum reforms came into being in recent decades. In Iran, an important educational assessment reform took place called Descriptive Assessment (DA). In this reform, the focus of student assessment was moved from a more summative approach of providing grades and deciding about promotion to the next grade to a more formative approach of providing descriptive feedback aimed at improving student learning. In this study, we evaluated how seven fourth-grade mathematics teachers used the principles of DA. Data were collected by a questionnaire on assessment practices and beliefs, lesson observations, and interviews. Although the teachers varied in how they assess their students, in general their assessment practice is by and large in line with the DA guidelines. Nevertheless, in some respects we found differences. When assessing their students, the teachers essentially do not check the students’ strategies and when preparing the report cards, they still use final exams because they do not sufficiently trust the assessments methods suggested by DA. The guideline to use assessment results for adapting instruction is also not genuinely put into action. The article is concluded by discussing dilemmas the teachers may encounter when implementing DA.

Questions to the Article: Features Constituting Actionable COVID-19 Dashboards: Descriptive Assessment and Expert Appraisal of 158 Public Web-Based COVID-19 Dashboards (Preprint)

UNSTRUCTURED The recent article published on February 24 in 2021 is well-written but remains several questions that are required for clarifications, particularly for readers who hope to replicate this study to assess the 158 selected web-Based COVID-19 dashboards. We design a dashboard including the 158 selected COVID-19 and other prediction-involved dashboards that were neglected in the previous study. The 158 dashboards were downloaded from Multimedia Appendix 3 in the previous study. The other two dashboards regarding prediction COVID-19 were included in the study to understand the characteristic of prediction COIVD-19 cases using mathematical models. We observed that (1) all those 158 dashboards can be laid on Google Maps for better understanding the research than the previous study; (2) the prediction-COVID-19 dashboards can be applied with mathematical models to strengthening the previous study. The lack of predictive models in the pandemic likely stunted the use of those 158 dashboards. Predictive approaches to dashboard design should be involved in the previous study.

Features Constituting Actionable COVID-19 Dashboards: Descriptive Assessment and Expert Appraisal of 158 Public Web-Based COVID-19 Dashboards

Background Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. Objective The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (“why”), content and data (“what”), and analyses and displays (“how” they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. Methods We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. Results A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are “close to home”; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. Conclusions COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.