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All Journal International Journal of Global Operations Research International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research International Journal of Mathematics, Statistics, and Computing International Journal of Linguistics, Communication, and Broadcasting
Suhaimi, Nurnisaa binti Abdullah
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Transportation Other

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Application of Fish Waste Processing for Sustainable Livestock Feed Production A Community Engagement Study in Garut Regency Lianingsih, Nestia; Suhaimi, Nurnisaa binti Abdullah; Prabowo, Agung
International Journal of Ethno-Sciences and Education Research Vol 4, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v4i3.719

Abstract

This community engagement study aimed to develop an application for processing fish waste into animal feed based in an incubator system in Garut Regency. The program was conducted from May to November 2023 with the primary objective of transferring technology in waste processing and animal feed production to partner groups. Methods included socialization, technical and non-technical training, and direct mentoring in animal feed pellet production. Results showed a significant improvement in the knowledge and skills of the groups in producing fish waste pellets, reducing feed production costs, and enhancing the sustainability of local livestock businesses. Challenges encountered included initial production limitations and consumer trust in new products. With in-depth scientific approaches and sustained support, the program successfully created positive impacts on the environment and community economic welfare.
Determination of Dominant Factors Affecting Lung Cancer Patients Using Principal Component Analysis (PCA) Amal, Moh Alfi; Suhaimi, Nurnisaa binti Abdullah; Yasmin, Arla Aglia
International Journal of Quantitative Research and Modeling Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i3.747

Abstract

The diagnosis of lung cancer is one of the most pressing health issues as the disease is often only detected at an advanced stage, leading to a poor prognosis for patients. Therefore, in an effort to detect, prevent, and manage the disease more effectively, this study utilized screening variables. Screening is an important endeavor in the early detection of diseases or abnormalities that are not yet clinically apparent using various tests, examinations, or procedures. The use of screening variables is very important in the early detection process because it can help in this study to understand the risk factors and causes of disease. The purpose of this study is to determine the dominant factors affecting people with lung cancer using Principal Component Analysis (PCA). Based on the results of the study, it was found that there are 20 dominant screening variables that have a considerable correlation to the formation of early detection of lung cancer with a total proportion of covariance variance of 100% when, the total variance obtained from the 20 screening variables is 100%. The final PCA results show that the factor loading values are used to determine which variables are most influential by comparing the magnitude of the correlation. As a result, the main factor causing lung cancer was Fatigue which had a factor loading of 7.87%, followed by the variables Age and Alcohol use with a factor loading of 6.02%. Other variables also showed certain factor loadings that indicated the cause of lung cancer. These findings are very important in efforts to improve early detection and management of lung cancer through more effective and targeted screening.
The Development of Atomic Structures by Dalton, Thomson Rutherford and Bohr, and their Mathematical Equations Suhaimi, Nurnisaa binti Abdullah; Cahyandari, Rini; Salih, Yasir
International Journal of Quantitative Research and Modeling Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i3.759

Abstract

Thomson's atom is a solid ball or billiard ball with a positive charge that contains several negatively charged particles or electrons. These electrons will be spread on the ball like raisins on bread. The main difference between Thomson's and Rutherford's atomic models is that Thomson's model does not contain information about the atomic nucleus, while Rutherford's model does. The theory of atomic structure helps scientists understand why elements behave in certain ways in chemical reactions. For example, electron configuration determines how elements bond and form compounds. In this paper, a literature review was conducted on the development of Thomson's atomic structure model. The study method was carried out to identify elements based on their atomic number, determine their reactivity based on the number of valence electrons, and understand how atoms unite to form molecules through chemical bonds. The results of the study, by studying atomic theory, can find out about the chemical and physical properties, as well as the uses of particles or substances that exist around the universe.
Sentiment Analysis of Tiktok App Reviews on Google Play using Several Machine Learning Methods Suhaimi, Nurnisaa binti Abdullah; Lestari, Mugi
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.343

Abstract

Sentiment analysis has become increasingly important in understanding user perceptions of digital platforms. This study focuses on analyzing TikTok application reviews from the Google Play Store in Indonesia using machine learning techniques. The research aims to investigate sentiment distribution and compare the performance of three popular machine learning models: Random Forest, Support Vector Machine (SVM), and Naive Bayes. The study employed a comprehensive methodology involving data collection, preprocessing, feature extraction, and model evaluation. A dataset of 10,000 TikTok reviews was collected and preprocessed using techniques such as case folding, tokenization, and stopword removal. The sentiment labeling process categorizes reviews into positive, negative, and neutral sentiments based on user ratings. The TF-IDF algorithm was used for feature extraction, and the SMOTE technique addressed class imbalance. Results revealed a predominance of negative sentiment (53.5%), followed by neutral (32.1%) and positive (14.4%) sentiment. Model performance comparisons at different data sharing ratios (80/20 and 70/30) demonstrated that Random Forest and SVM consistently outperformed Naive Bayes. At the 80/20 ratio, Random Forest achieved the highest accuracy of 83.73%, highlighting its effectiveness in sentiment classification. The research contributes to the field of sentiment analysis and natural language processing by providing insights into user experiences with the TikTok application in Indonesia. The findings can guide application developers in understanding user perceptions and improving user experience.
Optimizing the LQ45 Stock portfolio using Piecewise Linear Function: A Case Study from an Investor's Point of View Azis, Chusnul Chatimah; Halim, Nurfadhlina Abdul; Suhaimi, Nurnisaa binti Abdullah
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 1 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i1.61

Abstract

In optimization problem solving, both linear and nonlinear approaches can be used, with nonlinear programming considering constraints or not. One effective method of nonlinear programming is the Piecewise Linear approach, which breaks down complex nonlinear functions into straight-line segments to make their solution easier. This method can be applied in the financial sphere, such as in stock investment. This study discusses the application of piecewise linear function in optimizing investment portfolios in Bank Jago Tbk. (ARTO), Barito Pacific Tbk. (BRPT), and Go To Gojek Tokopedia Tbk. (GOTO) stocks. The purpose of this study is to provide insight that Piecewise Linear can provide optimal solutions in managing investment portfolios by calculating the risks and returns of selected stocks. The results showed a risk with a level ???? as big as 0.01, the expected profit from the investment of the three stocks in the calculation period reached IDR 1,803,109. On the other hand, for investors who are more cautious and have a Level ???? as big as 1, the anticipated profit in the same investment is around IDR 1,275,052.
Analysis of Investment Decision Assessment Using the Net Present Value (NVP) Method at PT Bank Mandiri (Persero) Tbk Muqtashida, Amalia Aura; Benedicta, Hellena; Suhaimi, Nurnisaa Binti Abdullah
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 3 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i3.121

Abstract

This paper explores the fundamental elements of a robust business management strategy, essential for sustained success in the dynamic business landscape. It delves into crucial components such as investment decision-making, comprehensive planning, business development, and judicious risk-taking. These strategic decisions not only influence immediate financial performance but also contribute to long-term benefits such as market growth and heightened competitiveness. Focusing on the banking sector, the paper acknowledges the potential for substantial returns juxtaposed with inherent risks. Emphasizing that these risks are manageable, particularly in the stock market, it advocates for a meticulous approach to investment decision analysis. The strategic choices made in this process play a pivotal role in maximizing returns while minimizing the impact of stock market risks. With a preference for the Net Present Value (NPV) method highlighted in the literature review, the paper underlines the significance of comprehensive investment decision analysis.
Optimization of Renewable Energy Company Stock Portfolio for Investment Decision Making using the Markowitz Model Saputra, Renda Sandi; Rahayu, Alpi fauziah; Suhaimi, Nurnisaa Binti Abdullah
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i4.142

Abstract

This study focuses on optimizing the renewable energy company's stock portfolio using the Markowitz model, which aims to balance risk and return for proper investment decision making. With the increasing demand for clean energy, portfolio optimization in the renewable energy sector is important for investors. This research takes into account historical stock performance and applies the Mean-Variance Optimization framework to minimize risk while maximizing return. This portfolio consists of selected renewable energy companies, and the analysis runs from September 2021 to August 2024. This study aims to analyze the allocation of investment portfolios in renewable energy company stocks in Indonesia. Based on the analysis results, the investment portfolio is allocated to five main stocks, namely BUMI.JK with an investment value of IDR 17,075,844 (17.08%), INDY.JK of IDR 5,825,852 (5.83%), KEEN.JK of IDR 33,766,798 (33.77%), RAJA.JK of IDR 43,084,876 (43.08%), and WIKA.JK of IDR 246,630 (0.25%). These results indicate that most of the funds are invested in RAJA.JK and KEEN.JK stocks, which contribute more than 75% of the total investment portfolio
Challenges and Responsibilities of Freedom of Expression in the Industrial Era 4.0: Analysis of Social Interaction on Instagram Social Media Suhaimi, Nurnisaa Binti Abdullah; Haq, Fadiah Hasna Nadiatul; Sidiq, Fahmi
International Journal of Linguistics, Communication, and Broadcasting Vol. 2 No. 2 (2024): International Journal of Linguistics, Communication, and Broadcasting
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijlcb.v2i2.116

Abstract

The industrial era 4.0 has brought significant changes in people's lives, with the rapid development of technology and information, as well as the important role of social media such as Instagram in digitalization changes. Freedom of expression on these platforms is becoming increasingly important, but also increasingly complex. Freedom of expression is a basic right of every individual which is included in Human Rights (HAM). However, this concept is not absolute and is always accompanied by certain responsibilities and obligations. Laws and statutory regulations stipulate that freedom of expression must be exercised by complying with ethical norms, laws, and other individual rights and freedoms. Freedom of expression also plays an important role in the world of the internet and social media. The internet has become a platform that allows individuals to express themselves without physical limitations, with almost limitless potential. Social media such as Instagram allows users to share creative content, in the form of photos, videos and text. However, users must use this freedom wisely and responsibly. They have complete control over their uploads, with a privacy settings feature that allows them to control who can access their content. Social media should not regulate individual ethics and behavior, but rather give individuals the right and obligation to use the platform wisely. Thus, freedom of expression on social media such as Instagram requires awareness of individual responsibility in carrying it out. By obeying the rules, norms and rights of other people, this freedom can be exercised well without harming anyone and still strengthening the social norms that apply in society.
Education Revolution: Leveraging Technology to Improve Learning Quality by 2025 Saputra, Moch Panji Agung; Suhaimi, Nurnisaa binti Abdullah; Wahid, Alim Jaizul
International Journal of Ethno-Sciences and Education Research Vol 5, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v5i1.867

Abstract

The technological transformation in education in 2025 has had a significant impact on the way we teach and learn. The use of artificial intelligence (AI) and learning analytics enables a more personalized, interactive, and adaptive learning experience. AI helps provide rapid feedback and adapts learning materials to students’ needs, while learning analytics enables real-time monitoring of student progress. Despite the many benefits that can be gained, the main challenges faced are the digital divide between urban and rural areas, limited infrastructure, and issues of training for educators and protection of students’ personal data. Therefore, investment in infrastructure, training for educators, and development of data protection policies are crucial to ensure effective implementation of technology in education. Technology can play a major role in creating a more inclusive and adaptive education, provided that the existing challenges can be overcome.
Co-Authors Agung Prabowo Amal, Moh Alfi Azis, Chusnul Chatimah Benedicta, Hellena Halim, Nurfadhlina Abdul Haq, Fadiah Hasna Nadiatul Lianingsih, Nestia Mugi Lestari, Mugi Muqtashida, Amalia Aura Rahayu, Alpi fauziah Rini Cahyandari Salih, Yasir Saputra, Renda Sandi Sidiq, Fahmi Wahid, Alim Jaizul Yasmin, Arla Aglia