Universitas Ma Chung

This presents the assessment of a real estate bankruptcy risk, and the purpose of its consideration is to demonstrate the effectiveness in predicting companies in Indonesia that are vulnerable to bankruptcy during the pandemic. This is important to provide predictions of company bankruptcy during the pandemic period, and so far, no research has accommodated a similar selection. Empirical research analyzed financial data from 28 observations of real estate companies in Indonesia from 2019 to 2022. The time frame allows for identifying and assessing the effectiveness of early warning models, especially during pandemic turmoil. The analysis methods used are the Z-Score, S-Score, X-Score, G-Score, and O-Score. The best bankruptcy model in the real estate sector is the X-Score. The contribution of this research is that the type of bankruptcy model specification cannot be generally applied to various companies, specifically the real estate industry. We suggest using the X-Score to predict bankruptcy alarms as one of its instruments.

This study aimed to investigate the effects of Storytelling Narrated Videos (SNV) on students’ knowledge retention and transferability. A total of 56 students from a university in Indonesia were randomly assigned to a quasi-experimental research design exposed to SNV and to Lecture Narrated Videos (LNV). Two videos were created to deliver content on Bloom’s Taxonomy, one using a lecture-style format and the other adopting a storytelling approach. Data were collected through tests, questionnaires, and essays. The findings revealed that participants exposed to SNV had higher retention memory scores, indicating a positive impact on knowledge retention compared to those who watched LNV. Moreover, the storytelling videos facilitated cognitive skill progression, enhanced understanding through engaging visuals, and fostered a strong connection with a familiar narrator, resulting in a more dynamic and memorable learning experience. The study also examined knowledge transfer and found that participants who watched the storytelling videos performed better in applying Bloom’s Taxonomy concepts to planning teaching objectives in the essay test. This suggests that the incorporation of storytelling narration and promoting transfer knowledge activities can enhance students’ understanding, retention, and practical application of the learned material. Overall, the findings highlight the potential of incorporating storytelling in narrated videos to improve students’ knowledge retention, transferability, and engagement in educational settings.

Flipped classes can improve English language teaching and learning, especially reading outcomes, by enhancing student engagement and motivation through interactive and captivating educational materials. The goal of this study is to examine the effects of different schema activations in different English flipped class formats in pre-reading activities on the reading comprehension of students with different reading proficiency levels. A quasi-experimental research design was employed involving 30 first-year students from the first university and 28 first-year students from the second university in Surabaya, Indonesia, who were studying English as a general course at an intermediate level. The study used informed consent and two different formats, A and B, where pre-reading tasks were completed in class or asynchronously online, respectively. The study found that using video-based pre-reading activities in flipped class can improve comprehension and schema acquisition. Flipped classes can provide personalized learning experiences, but its effectiveness varies depending on the strategies and delivery methods used. While most students benefit from flipped classes, those who struggle with self-discipline and time management may find it challenging to adapt to the online component and may experience lower performance as a result.

This study aims to analyse and determine the effect of Big Data, the Internet of Things (IoT), and physical-cyber system variables on human factors in refinery industry operators and the influence of human factors and managerial initiatives on sustainable manufacturing. The method used in this study is a quantitative method using partial least square-structural equation modelling (PLS-SEM). The respondents in this study were workers of Indonesia's upstream oil and gas sector. The results of this study indicate that Big Data, IoT, and Physical Cyber Systems (PCS) have a positive and significant effect on the human factor. In addition, there is a significant relationship between human factors and sustainable manufacturing. Furthermore, it is also found that there is a relationship between managerial initiatives and sustainable manufacturing. However, the managerial initiative cannot moderate the human factor and sustainable manufacturing.

Viral replication inhibition strategies are needed to prevent pandemics through the latest therapeutic agent designs. A viral infection occurring over a wide area is called a pandemic. The strategy of inhibiting virus replication is used to tackle the pandemic Viruses can trigger negative regulation of apoptosis in host cells for viral survival. Apoptosis can reduce viral load and inhibit viral replication. Several types of viruses can evade the immune response through upregulation of various anti-apoptotic proteins, which allows this research to explore specific types of anti-apoptotic proteins in host cells for the design of candidate therapeutic agents.Medicinal plants from the Dayak Lundayeh tribe in North Kalimantan have potential for health, the antiviral potential of these plants has not been identified. This study aims to reveal the potential of the bioactive compounds from Bawang Ada' as antivirals with a molecular mechanism through apoptosis with an in silico approach.The in silico method used in this study consisted of ligand preparation, druglikeness analysis, pathway prediction, docking, and molecular interaction.Bawang Ada' acts as the best antiviral candidate through the activity of Erythrolaccin and Isoeleutherin compounds in inhibiting antiapoptotic proteins consisting of GSK3B and AKT1. We recommend the binding sites Val70, Leu132, Ile62, Leu188, Asp200, and Cys199 (GSK3B) and Leu210, Leu264, Tyr272, Asp292, Trp80, Lys 268, Val270, and Ser205 (AKT1) for further research as antiviral target development.

Predicting the performance of various infrastructure design options in complex federated infrastructures with computing sites distributed over a wide area network that support a plethora of users and workflows, such as the Worldwide LHC Computing Grid (WLCG), is not trivial. Due to the complexity and size of these infrastructures, it is not feasible to deploy experimental test-beds at large scales merely for the purpose of comparing and evaluating alternate designs. An alternative is to study the behaviours of these systems using simulation. This approach has been used successfully in the past to identify efficient and practical infrastructure designs for High Energy Physics (HEP). A prominent example is the Monarc simulation framework, which was used to study the initial structure of the WLCG. New simulation capabilities are needed to simulate large-scale heterogeneous computing systems with complex networks, data access and caching patterns. A modern tool to simulate HEP workloads that execute on distributed computing infrastructures based on the SimGrid and WRENCH simulation frameworks is outlined. Studies of its accuracy and scalability are presented using HEP as a case-study. Hypothetical adjustments to prevailing computing architectures in HEP are studied providing insights into the dynamics of a part of the WLCG and candidates for improvements.

Betalain is a water‐soluble pigment contained in Caryophyllales plants. It not only holds potential as a natural food colorant but also offers various health benefits, acting as an antioxidant. This study focused on analyzing the pH‐dependent stability of encapsulated betalain pigments extracted from red beetroot (Beta vulgaris L.) using methods such as absorption spectroscopy, HPLC, and LC–MS. The major pigments identified were vulgaxanthin I, betanin, isobetanin, and neobetanin, alongside minor components, including three betaxanthin species and a degradation product known as betalamic acid. Spectrophotometric analyses revealed that above pH 8, the betalain peak at 435 nm decreased and red‐shifted to a peak at 549 nm, a shift that could be reversed through neutral pH treatment. At pH 11, a new broad peak appeared at 410 nm and was identified as betalamic acid. To assess the pH‐dependency of each betalain, the targeted betalains were separated and quantified through HPLC after incubation across a wide pH range of 2–11 and during storage. After 3 days of storage in highly alkaline conditions (pH 10–11), major betalains, with the exception of neobetanin, underwent significant degradation. Conversely, these pigments displayed relative stability in acidic conditions. In contrast, neobetanin showed vulnerability to acidic conditions but exhibited tolerance to alkaline pH levels of 10–11. The degradation product, betalamic acid, demonstrated a similar susceptibility to alkaline pH as betanins. In conclusion, the significant stability decrease under highly alkaline conditions results not only from the hydrolytic reaction of betalains but also from the degradation of betalamic acid itself. Practical Application Encapsulation methods are used to enhance the stability of betalains against temperature variations; however, the effects of pH, especially when considering individual betalain species, are not well understood. Despite betalains exhibiting similar features and being suitable for a wide pH range from acid to alkaline conditions, they are significantly affected by alkaline pH levels exceeding 10, as well as by storage duration. This study demonstrated the application of encapsulation to pH‐dependent stability, and the findings offer valuable insights and a fresh perspective on betalains as red biocolorants, extending their potential application to a wide range of pH‐controlled food products.

English language learning is an integral part of basic education in Indonesia today. However, not all students have equal opportunities to learn English. Elementary school children in Kucur village, in particular, are among those who lack sufficient access to learning English outside the classroom due to their family circumstances. Fortunately, there is a Learning Center called Cakrawangsa managed by the local youth organization (Karang Taruna) in Krajan hamlet, Kucur village. This center provides educational assistance to students. However, the center lacks permanent human resources to support students in learning English. In 2021, the community engagement team from Ma Chung University conducted once-a-week fun English learning sessions. Based on the evaluation results of the program, the participants greatly enjoyed the fun learning approach delivered by the Ma Chung University community engagement team. However, some students still struggled to memorize English vocabulary and pronounce it accurately. Therefore, the proposing team suggests a supplementary English learning program using an enjoyable method that has the potential to enhance vocabulary mastery. Based on conducted studies, the proposing team has developed a relevant board game tailored to the students' environment as an engaging and effective tool to support English language teaching.

The environmental, social, and governance (ESG) integration finds itself in a transition with rapid developments worldwide, given that the pandemic incentivized companies and investors to focus on other social and governance measures such as ESG ratings. However, the divergence of ratings from the ESG and a lack of transparency lead the companies to report voluntary indicators without standardization. This study aimed to identify the ESG criteria and the most suitable set of key performance indicators (KPIs) in the airline industry after the impact of COVID-19. Furthermore, the second objective was to determine the appropriate weights and ranking of the identified criteria. The multi-criteria decision-making analytical hierarchical process was applied for this purpose. Additionally, the use of intuitionistic variables delivers a comprehensive model for rating the airlines according to their ESG performance. The most relevant criteria found in the study were critical risk management, greenhouse gas emissions, and systemic risk management. Regarding the KPIs, the top-3 weights were the number of flight accidents, jet fuel consumed and sustainable aviation used, and the number of digital transformation initiatives.

Food Small and Medium Enterprises (SMEs) in Indonesia have low competitiveness but receive less attention in innovation research. This study aims to analyze the relationship between innovation capability and competitiveness of food SMEs and to analyze the role of government policies in strengthening that relationship during the Covid-19 pandemic. Data were collected using an online questionnaire from food SMEs in Malang Regency. There were 162 returned and valid questionnaires for analysis. The results of the study prove that innovation capability was strongly related to the competitiveness of food SMEs. Government policies through training, credit, and marketing strengthen the relationship between product innovation and competitiveness, while it weakening the relationship between process innovation and the competitiveness of food SMEs. The Covid-19 pandemic is an externality factor that hinders resource mobility so that the production process is reduced which in turn has a negative impact on the competitiveness of food SMEs.

A marketing career entails a heavy burden and requires much originality and creativity, which can result in interpersonal friction. This situation influences employees' affective commitment and organizational citizenship behavior (OCB). Consequently, the purpose of this study is to investigate how affective commitment, work overload, and interpersonal conflict may impact OCB when combined with social interaction. This survey involved 61 personnel from the marketing and supply chain departments of an Indonesian state-owned enterprise. The data were analyzed using a quantitative method and partial least squares (PLS) approach. This study revealed that work overload and interpersonal conflict have a negative impact on positive behavior and actions, including OCB and affective commitment. In addition, the findings accentuate the importance of employees' affective commitment because it directly encourages employees to take on extra responsibilities. Furthermore, social interaction does not moderate the relationship between work overload and interpersonal conflict on affective commitment. This study broadened perspectives on OCB concerning work-related stressors and provided direction for the managerial team to cope with workload and conflict in the decision-making process.

Breast cancer is a condition where the cells in breast tissue lose control and multiply uncontrollably. In this study, MCF-7 breast cancer cells were tested for cytotoxic activity using the MTT assay and the active compound's interaction with the p53 protein was tested in silico. The most active fraction was found to be the ethyl acetate fraction, with an IC50 value of 1.730 μg/mL and a selectivity index of 2.485. However, the selectivity index was less than 3, and Vero cells showed changes in morphology with the addition of the ethyl acetate fraction. GC-MS was used to identify 19 compounds in the ethyl acetate fraction, and in-silico tests were performed on 5 potential anticancer compounds. Lipinski's Rule of Five test showed that only 3 of these compounds could undergo molecular docking. The results indicated that Anethole compound can interact with p53 protein, while Cinnamaldehyde, (E)-can interact with p21 protein.

Purpose: This study seeks to reveal the relationship between the triple helix innovation ecosystem and Small and Medium Enterprises (SMEs’) performance and the role of the SME community as the mediator between the triple helix innovation ecosystem and SMEs’ performance. Methodology/Approach: This study uses a quantitative approach. Data were collected using an online questionnaire from 386 SME managers who are members of the SME community in Malang Regency, East Java, Indonesia. SEM-PLS was used to analyse the data to examine the relationship of three latent variables: triple helix ecosystem, SME community, and SMEs’ performance. Findings: The triple helix ecosystem in this study was the collaboration of three agents, namely the government, large companies, and universities. This study proves that the triple helix ecosystem innovation is positively and significantly related to the performance of SMEs. Another important finding is that the SME community partially mediates the triple helix innovation ecosystem relationship and SME performance. The SME community has a strategic role in the triple helix agents intervention process to improve the performance of SMEs. Research Limitation/Implication: The data were collected through an online questionnaire so that it could not reveal the process of operational interventions of triple helix agents to improve SMEs’ performance. The performance of SMEs did not measure internal business processes, such as the presence of technology in processes, product development, and time savings. Originality/Value of paper: This research contributes to the literature through triple helix analysis as an ecosystem in improving the performance of SMEs.

Indonesian spices offer an avenue into a broad spectrum of knowledge covering history, geography, sciences, humanities, and medicine. During the COVID-19 pandemic, spices have been revisited for potentials to boost the immune system. However, this knowledge is often inaccessible to children, which leads to the risk of the nation losing local wisdoms related to its endemic plants. Therefore, this study aims to explore the writing of poetry on spices to educate elementary schools student about COVID-19 prevention. We reviewed literature and wisdom on Indonesian spices and proposed the formula of writing spice-themed poetry. Building on Sam Illingworth’s concept of poetry as a dialogue, we stipulated four guiding elements in writing spice-themed poetry for children, namely (1) facilitation-purpose, (2) science exposure, (3) communicative interaction, and (4) transformation based on Indonesian knowledge and culture. We argue that writing poetry on spices potentially strengthens children’s spice-related knowledge of natural sciences and Indonesian local wisdom.

Ardisia silvestris is a traditional medicinal herb used in Vietnam and several other countries. However, the skin-protective properties of A. silvestris ethanol extract (As-EE) have not been evaluated. Human keratinocytes form the outermost barrier of the skin and are the main target of ultraviolet (UV) radiation. UV exposure causes skin photoaging via the production of reactive oxygen species. Protection from photoaging is thus a key component of dermatological and cosmetic products. In this research, we found that As-EE can prevent UV-induced skin aging and cell death as well as enhance the barrier effect of the skin. First, the radical-scavenging ability of As-EE was checked using DPPH, ABTS, TPC, CUPRAC, and FRAP assays, and a 3-(4-5-dimethylthiazol-2-yl)-2-5-diphenyltetrazolium bromide assay was used to examine cytotoxicity. Reporter gene assays were used to determine the doses that affect skin-barrier-related genes. A luciferase assay was used to identify possible transcription factors. The anti-photoaging mechanism of As-EE was investigated by determining correlated signaling pathways using immunoblotting analyses. As-EE had no harmful effects on HaCaT cells, according to our findings, and As-EE revealed moderate radical-scavenging ability. With high-performance liquid chromatography (HPLC) analysis, rutin was found to be one of the major components. In addition, As-EE enhanced the expression levels of hyaluronic acid synthase-1 and occludin in HaCaT cells. Moreover, As-EE dose-dependently up-regulated the production of occludin and transglutaminase-1 after suppression caused by UVB blocking the activator protein-1 signaling pathway, in particular, the extracellular response kinase and c-Jun N-terminal kinase. Our findings suggest that As-EE may have anti-photoaging effects by regulating mitogen-activated protein kinase, which is good news for the cosmetics and dermatology sectors.

Transfer learning has been used in computer vision research, including in the health sector. In the health sector, the input image is generally an x-ray image or a microscopic image. In this study, transfer learning for models that have been trained using CNN to detect malaria parasites in red blood cell images. The deep CNN pre-trained model uses 3 architectures, namely ResNet50V2, EfficientNetB0, and InceptionV3. For each architecture, experiments will be carried out and compare which architecture is better in detecting malaria parasites. Based on experiments conducted without fine tune, the accuracy ranges from 0.76 – 0.81 for ResNet50v2, 0.76 – 0.80 for EfficientNetB0, and 0.77 – 0.82 for InceptionV3

p> Pigmen utama yang berperan penting pada fotosintesis, yaitu klorofil, karotenoid dan antosianin dapat dianalisis kandungannya untuk menentukan status kesehatan tanaman. Metode analisis kandungan pigmen yang dilakukan secara destruktif memerlukan penanganan khusus dan biaya yang tinggi. Fuzzy Piction adalah aplikasi Android yang telah dikembangkan sebelumnya untuk prediksi kandungan pigmen utama pada tanaman. Aplikasi tersebut mempunyai kemampuan untuk melakukan prediksi kandungan pigmen pada citra daun secara non-destruktif dengan menggunakan model Convolutional Neural Network (CNN) FP3Net. Namun, Fuzzy Piction masih belum invarian terhadap perbedaan kualitas citra yang dapat terjadi karena perbedaan kualitas atau spesifikasi kamera smartphone. Hal ini ditunjukkan dengan adanya perbedaan hasil prediksi kandungan pigmen pada beberapa smartphone untuk objek daun yang sama. Pada penelitian ini dikembangkan metode perbaikan citra dengan algoritma Partial Least Square Regression (PLSR) sebagai solusi atas permasalahan tersebut. Dengan penambahan metode perbaikan citra, aplikasi Fuzzy Piction dapat memberikan prediksi kandungan pigmen dengan tingkat presisi yang lebih baik. Aplikasi Fuzzy Piction difasilitasi dengan layanan cloud yang dikembangkan menggunakan Flask web service sehingga model perbaikan citra dan prediksi pigmen lebih mudah diperbarui. Hasil perbaikan warna oleh PLSR berhasil menyeragamkan warna citra serta dapat memberikan hasil prediksi kandungan pigmen dengan standar deviasi yang lebih kecil. Variasi prediksi kandungan pigmen dengan 3 jenis smartphone yang berbeda pada objek daun yang sama dapat diturunkan sebesar 87% setelah citra asal diperbaiki dengan PLSR. Abstract Chlorophyll, carotenoids, and anthocyanins are three main pigments that are important for photosynthesis process. Its content can be examined to determine the status of plants health. The destructive approach of evaluating pigment content is expensive and necessitates specialized handling. An Android based application called Fuzzy Piction could predict the content of those pigments nondestructively using the FP3Net, a Convolutional Neural Network (CNN) model. This application predicts the pigment content in plant leaf by its digital images. However, Fuzzy Piction is still not invariant to differences in image quality that can occur due to differences in smartphone camera specifications. This is indicated by the difference in the prediction results of the pigment content on several smartphones for the same leaf object. Therefore, the Partial Least Square Regression (PLSR) technique was used in this work as an image enhancement method to resolve the issue. Eventually, Fuzzy Piction may provide precise predictions of pigment content by embedding PLSR in it. A cloud service made with the Flask web service makes it easy to update the image enhancement and pigment prediction models for the Fuzzy Piction application. The results of color correction by PLSR succeeded in uniforming the color of the image and could provide predictive results of pigment content with a smaller standard deviation. The variation of pigment content prediction with 3 different smartphone types on the same leaf object can be reduced by 87% after the original image is corrected with PLSR. </p