bluuebunny/crossref_metadata_2025 huggingface dataset:
The Linear Regression Analysis in Minitab and Fuzzy Logic in Matlab as Tools for Calculating Oyster Mushroom Yields at Thara Farm, Ciawi District, Bogor Regency.
Authors: Sidik Djabar Sidik , Elan Nurul Paozan  , Naufal Syifa Abdul Karim  , Fisrawati
Published: January 2025

Indonesia is a tropical country rich in biodiversity, with a predominance of flora and fauna compared to other countries with similar climates, one example being mushrooms. Mushrooms are a type of fungi that thrive in temperatures ranging from 22-28°C, humidity levels of 70-90%, and lighting between 85-540 lux. In mushroom cultivation, farmers face various challenges, such as unstable yields at certain times. Therefore, this study aims to identify the primary factors affecting the stability of mushroom yields at PT Tharam. According to expert data, during the period from July to December, harvests can reach up to 600 kg per day, while in January to June, yields can drop to as low as 200 kg. Through correlation and regression analysis, it has been determined that the factors influencing the increase and decrease of mushroom yields at PT Tharam include irrigation intensity, nutrient application, temperature, humidity, rainfall, and pest attacks on mushrooms.Keywords:  Oyster Mushroom; Temperature; Lighting; Watering; Humidity
Clustering Analysis Approach to Enhance Inventory Management and Product Recommendations in the Ornamental Plant Industry
Authors: Faturohman Muhammad Iqbal , Naziha Thalia
Published: January 2025

The ornamental plant industry has grown significantly as consumers seek to enhance living spaces with diverse plant species. This study aims to optimize inventory management and marketing strategies by applying K-Means clustering to categorize plants based on price, pot size, light requirements, care levels, and popularity. The method used is K-Means clustering, which groups plants into three clusters based on key characteristics. By analyzing these attributes, K-Means clustering identifies patterns and similarities among different plant species, allowing businesses to understand consumer preferences and inventory management better. The results identified three main clusters: Cluster 1 (moderate care, light, popularity) plants like Aglaonema require balanced stock and targeted promotion for medium-light environments. Cluster 2 (low care, light, popularity) plants such as Aglaonema Chiangmai need high stock levels and budget-friendly marketing. Cluster 3 (high care, light, popularity) plants like Alocasia demand elevated stock, premium quality, and care-focused promotion.
Towards Predictive Fatigue Management: A Blockchain-Enabled IoT Framework for Driver Safety in Logistics
Authors: Miftahol Arifin  , Noor Qisthani Nabila , Titan Syifa Fikra , Ananda Raharja Pradana , Fanny Dimas , Faizah Faizah
Published: January 2025

Driver fatigue is a critical issue in the logistics industry, contributing significantly to accidents and operational inefficiencies. The system utilizes IoT devices, including physiological and vehicular sensors, to monitor real-time data, such as Heart Rate Variability (HRV), Galvanic Skin Response (GSR), and Acceleration Variance (AV). Blockchain integration ensures secure, immutable data storage and transparency, with smart contracts automating fatigue alerts and management actions. The research results show that HRV increased from 50 ms to 70 ms, reflecting better stress recovery, while AV decreased from 0.85 m/s² to 0.45 m/s², indicating more stable driving behavior. Fatigue alerts dropped by 60%, from 25 to 10 alerts per observation period, demonstrating the system’s effectiveness in early fatigue detection and prevention. The study concludes that the IoT-blockchain integration provides a robust, scalable solution for mitigating fatigue-related risks, enhancing driver safety, and fostering operational efficiency in the logistics sector.
The Welding Defect Analysis on ASTM A106 Grade B with Inconel 82 Using Metallography Test and Microhardness Test
Authors: Muliawan Arief , Ilmianih Rizki
Published: January 2025

Inspeksi pengelasan merupakan praktik penting untuk menilai integrasi struktur dan komponennya dalam banyak aplikasi insdustri. Kualitas pipa industri dipastikan harus dapat menahan pada tekanan dan suhu yang tinggi, seperti pada riser tube primary reformer. Pada penelitian ini melakukan inspeksi hasil pengelasan pada pipa ASTM A106 grade B dengan inconel 82 menggunakan metalografi dan microhardness. Berdasarkan Hasil visual test dan penetrant test menunjukkan adanya crack pada area pertemuan antara lasan Inconel 82 dengan ASTM A106 grade B. Hasil metallography test pada area pertemuan antara Inconel 82 dengan ASTM A106 grade B terdapat continuous microcrack dan continuous macrocrack. Hasil pengujian microhardness pada daerah sekitar crack memiliki nilai kekerasan lebih rendah dari daerah yang jauh dengan crack. Sambungan pengelasan ASTM A106 grade B dengan Inconel 82 tidak mampu digunakan secara optimal pada temperatur 748oC karena Inconel 82  memiliki unsur silicon sebesar 0.5% yang menyebabkan perbedaan  solidifikasi antara ASTM A106 grade B dengan Inconel 82
Implementation of Random Forest Algorithm for Classification of Eligibility For Social Assistance Recipients In Information Systems
Authors: Mita Trianda  , Triase Triase
Published: January 2025

This study aims to develop a web-based information system for classifying the eligibility of social assistance (BANSOS) recipients using the Random Forest algorithm in the Bagan Batu Kota Subdistrict. The system is designed to assist local authorities in identifying BANSOS recipients more accurately and efficiently, minimize errors, and enhance distribution fairness. A quantitative research method was employed, with data collection techniques including observation, interviews, literature review, and document analysis. The dataset consists of 1,100 samples with features such as income, family size, and housing conditions. The Random Forest algorithm was implemented by building a classification model based on training and testing data. The evaluation showed a system accuracy rate of 97%, with a classification error of only 3%. The system provides features for recipient data management, field validation, and automated reporting, supporting more precise decision-making. The results of this study are expected to offer a solution for more effective and transparent social assistance distribution.
Geographic Information System in Web-Based Disease Spread Mapping in Public Hospitals
Authors: Febriansah Siregar Bayu , Ikhwan Ali
Published: January 2025

The application of web-based Geographic Information Systems (GIS) in mapping the spread of diseases at Kotapinang General Hospital aims to improve the effectiveness of health data management and response to disease outbreaks. With a large population and significant health challenges, Indonesia needs a real-time system to monitor and analyze disease spread. This research develops a GIS system that utilizes Google Maps API to visualize epidemiological data, identify high-risk areas, and provide relevant information to health workers. The research methodology includes disease data analysis, database design, and system testing. The study results show that this system not only increases hospitals' capacity to manage health data, but also accelerates decision-making in disease control. Despite data quality and user skills challenges, this web-based GIS offers a significant solution for health management in South Labuhanbatu Regency. This study recommends further development to improve the features and accessibility of the system.
Case Based Reasoning System for Tourette Syndrome Disease Detection
Authors: Abdurrasyid  , Indrianto Indrianto , Meilia Nur Indah Susanti  , Rima Rizqi Wijayanti
Published: January 2025

Tourette Syndrome (TS) is a neurological disorder affecting children under 18, with an estimated prevalence of over 150,000 cases annually in Indonesia and 1% globally. Misdiagnosis rates of 20-30% complicate effective management. TS involves involuntary, repetitive tics, ranging from sudden movements or sounds to aggressive behaviors, posing significant challenges for diagnosis and treatment. This study utilizes an expert system with a case-based reasoning (CBR) approach to improve TS diagnosis. Interviews with TS patients and specialists provided data on symptoms and diagnostic structures. A weighting mechanism and an accumulation formula were implemented to deliver accurate diagnostic outcomes and first aid suggestions, optimized for minimal computing resources without reliance on extensive datasets. Testing on 10 patients, under expert supervision, demonstrated the system's ability to accurately diagnose and classify TS. The system effectively simulates expert-level TS detection, offering precise diagnosis and recommendations, potentially enhancing early intervention and reducing diagnostic errors.
Strategic Approaches to Digital Transformation in Tanzania
Authors: Oreku George S.
Published: January 2025

Tanzania has achieved impressive political, economic, and social progress in recent years. However, the country continues to face considerable development challenges, such as economic inequality, population growth, and corruption. At the same time, new opportunities, such as digital transformation, have the potential to drive necessary changes and reforms. This paper explores digital transformation in Tanzania, considering its geopolitical realities and the immense opportunities it creates. A combined survey data approach was used to gather comprehensive information. The findings reveal that digital transformation, in conjunction with Tanzania’s geopolitical realities, can generate significant opportunities for the country. Tanzania’s strategic location is a significant advantage for fostering digital transformation. The study recommends that the country capitalize on ongoing digital transformation initiatives and geopolitical factors to overcome economic stagnation.
Indonesia in the Face of Great Power Competition
Authors: Alfachridzi Emir
Published: January 2025

The escalating great power competition between the United States and China in the South China Sea has triggered tensions and potential conflicts in the region. This situation presents significant challenges for inferior power countries, such as Indonesia, in protecting their national interests. Although Indonesia is not officially a claimant in the disputes, the overlapping claims between Indonesia's Exclusive Economic Zone around the Natuna Islands and China's "nine-dash line" have placed Indonesia in a precarious position. This paper refutes Richard Betts' argument that strategy is merely an illusion by demonstrating the importance of a clear and adaptive strategy for inferior states in navigating the complex regional geopolitical dynamics. By employing Yarger's Theory, this paper analyzes Indonesia's national security objectives in maintaining regional stability and peace, as well as the balance between ends, ways, and means in formulating an effective strategy. Furthermore, the concept of combination defense by Callard and Faber is utilized to illustrate a comprehensive approach that integrates military, non-military, and supra-military elements. Through qualitative analysis and literature review, this paper aims to highlight the significance of Indonesia's national maritime strategy in aligning security, economic, and diplomatic aspects to optimize resources for safeguarding its national interests in the South China Sea.
Resilience and Risks to Radiological Events in Times of War
Authors: Stýblová Eva , Kavan Štěpán
Published: January 2025

In the context of nuclear and radiological accidents, strengthening preparedness and response capabilities is essential, especially under the complex and unstable conditions of armed conflicts. While existing nuclear safety research generally assumes peaceful environments, it fails to account for the unique challenges posed by wartime scenarios, where access to affected sites, infrastructure stability, and responder safety are compromised. Armed conflicts increase risks not only for civilian populations but also for emergency response teams who may face logistical and safety barriers. This study seeks to address these gaps by developing tailored methodological and technological approaches to enhance resilience in nuclear emergency preparedness, response, and recovery systems. Using scenario-based planning, it emphasizes resilience assessments and ethical considerations to adapt existing frameworks to the specific risks of conflict zones. The outcome will be actionable guidelines, tools, and educational resources designed to improve nuclear safety protocols, ensuring better protection for both responders and affected populations in future conflict-related radiological incidents.
Learning to Plan for the Future Through the Tree of Hope Activity: Literacy Movement at Tanzil KG Lindungan Selangor, Malaysia
Authors: Lasmiatun Lasmiatun , Layla Regita
Published: January 2025

The Tree of Hope activity is an innovative program implemented in Malaysia to help children of Indonesian migrant workers plan for their future. This case study was conducted at At Tanzil Learning Center, Lindungan Village involving 45 students in grades 1-4 aged 5-12 years old. Using a mixed method of lectures and practical exercises, the activity aimed to help the children express their aspirations visually and verbally. The activity process included showing educational videos about various professions, making a wish tree, and sharing stories about aspirations. The results showed that the most popular professions were TNI (20%), Police (17.8%), Doctor (15.6%), Teacher (13.3%), and Firefighter and Pilot (11.1% each). This activity not only succeeded in increasing the children's motivation and confidence, but also created a fun and interactive learning environment. The program has proven to be effective in providing psychological and social support for immigrant children, as well as building a community that supports each other in achieving common goals. Through this creative approach, Tree of Hope contributes positively to the development and future of Indonesian migrant worker children in Malaysia.
Analisis Nikah Misyar Perspektif Yusuf Al Qaradhawi
Authors: Ishak Andi Muh.
Published: January 2025

This study aims to find out the law of Misyar marriage according to the view of Yusuf Al Qaradhawi and to find out the validity of Misyar's marriage from the perspective of Maslahah. This research uses qualitative methods. The data collection process is carried out with literature studies. In analyzing data, researchers use qualitative analysis techniques with steps of data exposure, data reduction, and drawing conclusions. The results of the author's research found that: (1) Misyar's marriage law according to Yusuf Al Qaradhawi is valid if it is carried out as befits an ordinary marriage, that is, it meets all its pillars and conditions, it is done consensually, there is a guardian, there are witnesses, and there is a dowry. (2) Misyar marriage is a marriage in which a wife is allowed to give up some of her rights as a wife and the husband gives up some of her obligations as the head of the household. Misyar marriage is viewed from the point of view of maslahah, namely the istislah bi al-'urf method, namely choosing the benefit that best suits the needs of the community, especially Indonesia, then Misyar marriage should be prohibited in Indonesia, on the basis of the consideration that its hypocrisy is far greater than the benefits, and although it is legal according to the syar'i view, but there is no legal power in the context of the Indonesian state and also injures the point of the purpose of marriage including creating sakinah family, mawaddah warahmah.
Influence of Teachers’ Pedagogical Competencies on Junior Secondary School Students’ Performance in Social Studies in Kontagora, Niger State, Nigeria
Authors: Eno Victoria I , Zainab Z. O , Utsu E. A , Akpanudi G. A
Published: January 2025

This empirical paper emphasizes on pedagogical competence of teachers which means teacher’s understanding of learning materials, design and implementation of learning, evaluation of learning outcomes, and the development of learners to actualize different potentials and in turn enhance their students’ performance in social studies. Descriptive survey research designed was used. The population of this study consists of 771 teachers in public junior secondary schools in Kontagora LGA, Niger state, Nigeria. The simple random sampling technique was adopted. The sample size stood at 263. A questionnaire: Influence of Teachers’ Pedagogical Competencies on Junior Secondary School Students’ Performance in Social Studies (ITPCJSSSPSS) was used for data collection. Two research questions were answered and two hypotheses tested at 0.05 level of significance. Data were analyzed using descriptive statistics while hypothesis was tested using chi-square. The finding reveals that teachers’ pedagogical competencies in lesson plan and classroom competence; including students’ performance are very closely related and important concepts for teachers to improve their performance. However, several factors can limit teachers’ pedagogical competencies such as teacher factor, societal factor and poor school resource utilization. This paper provide recommendation for training and retraining of teachers, this will enable them develop their lesson plan competence and classroom assessment competence and in turn enhance students’ performance in subjects matters especially in social studies
Analysis of Errors in Graph Writing Committed by Vietnamese Learners of IELTS – A Case Study in Vietnam
Authors: Oanh Ho Thi Kieu
Published: January 2025

This article analysed the errors made in the IELTS (International English Language Testing System) graph writing by 60 Vietnamese learners of Advanced IELTS at an English centre in Ho Chi Minh city, Viet Nam. The analysis was based on the theoretical framework developed by the Cambridge IELTS Consultant – Dane (2023) and Châu (2024). 60 IELTS graph writings done by these learners at the beginning of an advanced IELTS course were collected and assessed after they had learned the first lesson on graph description. The study was qualitative-oriented. Various kinds of errors were found and described in detail to find out their causes as the basis for the solutions to be put forward. The research results showed that the errors of word repetition, wrong information, missing words, wrong words were the most common among other errors made in each writing due to a variety of reasons. The implications withdrawn from these error causes could help learners of Advanced IELTS in general and the Vietnamese ones in particular have a good insight into the requirements of the graph task, the way to manage the task time allocation, the steps to develop a full graph writing to minimize and even avoid errors in their IELTS graph writing to describe graphs effectively and successfully.
Reciprocal Peer Evaluation of Teaching and Classroom Practices: attitude, impediments, and solutions: A case study of Sudanese faculty members at University of Shendi, Sudan
Authors: Balla Babikir Abdelmaroof Ahmed
Published: January 2025

This study seeks information on Sudanese faculty members’ attitude to reciprocal peer evaluation of teaching. In addition, the study endeavors to investigate which impediments matter most and which matter less to Sudanese faculty members regarding their engagement in reciprocal peer review of teaching and to suggest solutions to them. In view of these ends, a questionnaire was designed and administered to fifty faculty members at Shendi University. The study found out that Sudanese faculty members, in principle, embrace reciprocal peer evaluation of teaching, and the impediment that matters most to them and hinders their engagement in reciprocal peer evaluation of teaching is that reciprocal peer evaluation of teaching has not been nurtured and established as a practice and culture among their peers, while the impediment that matters less is time constraints and busy workloads of the staff members. The study suggests that in-service pedagogical training should be a must for all staff members and initiatives to promote reciprocal peer evaluation should be taken by the institution, the staff members, and determined by the institution leadership to remove the impediments.
Exploring the Impact of ChatGPT on EFL Reading Practices: Opportunities and Challenges
Authors: El Hassan Fatma Ahmed Mohamed , Alsalwah Alhanouf Fahad
Published: January 2025

This study investigates the integration of ChatGPT into reading classes for EFL students, focusing on the challenges faced by teachers and the impact on student engagement. Key barriers identified include a lack of technological familiarity, concerns about academic integrity, and fears of student dependence on AI tools. The findings reveal that using ChatGPT significantly enhances reading comprehension, vocabulary acquisition, and overall engagement among EFL undergraduates. However, cultural and contextual factors in Saudi Arabia influence its effectiveness. Recommendations include targeted training programs for teachers, clear guidelines for ethical AI usage, and strategies for seamlessly incorporating ChatGPT into existing curricula. Additionally, fostering a culture of innovation among educators and conducting regular assessments of student outcomes are essential for optimizing the use of AI tools in language education. This study contributes valuable insights for effectively leveraging ChatGPT to improve EFL reading skills and enhance overall language learning experiences.
AI-Driven Cost Optimization in Oil and Gas Projects
Authors: Monigha Adogioye
Published: January 2025

The oil and gas sector, a cornerstone of the global energy supply, is poised at the brink of a technological renaissance as it embraces Artificial Intelligence (AI). This paradigm shift is driven by the industry's imperative to enhance efficiency, bolster safety, and notably, optimize costs amidst volatile market conditions and escalating operational complexities. This paper presents an in-depth exploration of the multifaceted applications of AI technologies in streamlining cost management across various phases of oil and gas projects—from exploration to distribution. At the heart of this exploration is the elucidation of AI's transformative role in predictive analytics, automation, and decision support systems. By harnessing the power of machine learning algorithms, the industry can predict equipment failures, optimize maintenance schedules, and ensure uninterrupted production, thereby significantly reducing downtime costs. Furthermore, AI-driven data analytics enable the identification of patterns and insights from vast datasets, leading to more informed and cost-effective decision-making. The paper also delves into the integration of AI in operational domains such as drilling optimization, where AI algorithms analyze geological data to determine optimal drilling locations and parameters, thus minimizing the risk of costly non-productive time. Similarly, in the realm of supply chain management, AI facilitates dynamic routing and inventory control, curtailing logistical expenses. Highlighting case studies and empirical data, the paper underscores the tangible benefits realized by early adopters of AI in the industry, showcasing a potential reduction in operational costs and an increase in efficiency that often surpasses traditional methodologies. This detailed examination not only charts a course for future AI-driven endeavors in the oil and gas sector but also serves as a clarion call for stakeholders to navigate the intricacies of digital transformation strategically. In conclusion, the paper posits that the integration of AI stands as a beacon of innovation, promising not only cost optimization but also a sustainable and resilient future for the oil and gas industry. The findings herein aim to galvanize industry leaders, policymakers, and technologists to foster a collaborative ecosystem where AI can flourish, driving the industry towards a new horizon of operational excellence.
La Curcumi na Restablece los Niveles de p53 en Células Derivadas de Cáncer Cervicouterino en un Modelo In Vitro e In Vivo
Authors: Rodríguez Donat Vianey Berenice , Patiño Morales Carlos César , Jaime Cruz Ricardo , Villavicencio Guzmán Laura , Salzar García Marcela
Published: January 2025

La curcumina es un fitoquímico natural con propiedades antineoplásicas, incluida la modulación de p53. Se ha sugerido que apuntar a la actividad de p53 es una estrategia importante en la terapia contra el cáncer. El propósito de este estudio fue describir el efecto de curcumina sobre p53 en líneas celulares derivadas de cáncer cervicouterino y en tumores inducidos in ovo. Se expusieron células HeLa y SiHa a curcumina. Se realizó evaluación de la viabilidad celular por MTT y TUNEL y se cuantificó la expresión de p53 mediante western blot, los resultados indican un efecto importante en la disminución de la viabilidad de las células que recibieron tratamiento y que hay un incremento de los niveles de p53, además aquí demostramos mediante ensayos de pulso y casa que la curcumina aumenta la vida media de p53. En muestras obtenidas de tumores inducidos in ovo también se observó un aumento en los niveles de p53 por inmunohistoquímica.   El efecto citotóxico de la curcumina en las células de cáncer de cuello uterino se relacionó también con la activación de la vía Keap1/Nrf2. Nuestros hallazgos sugieren que el uso de curcumina puede reactivar la vía p53 en células cancerosas con p53 de tipo silvestre.
Framing Analysis of the Mcdonald's Corporate Boycott in Indonesia in kompas.com and kumparan.com Media
Authors: Heningtyas Asshifa , Muhammad Thoyib Amali
Published: January 2025

This study analyzes the framing of news about the McDonald's boycott in Indonesia published by two online media, Kompas.com and Kumparan.com. Using the framing analysis method, this study aims to understand how the two media outlets structure narratives related to the boycott triggered by McDonald's support for the conflicts that occur in Israel and Palestine. In this analysis, the author uses Robert Entman's framing model which includes four main elements: define problems, diagnose causes, make moral judgments, and suggest remedies. The results of the analysis show that Kompas.com tend to emphasize the economic and social aspects of the boycott, with an emphasis on market stability and consumer perspectives in Indonesia. On the other hand, Kumparan.com highlighted the political aspects and solidarity movements, by presenting the background of the conflict that triggered the boycott and opinions from various community groups. This difference in framing reflects the editorial approach of each media in shaping public opinion regarding the issue of the McDonald's boycott in Indonesia. This study contributes to an understanding of how media framing can affect public perception of controversial issues in economic, social, and political contexts.
PERBANDINGAN METODE NAÏVE BAYES DAN K-NEAREST NEIGHBOR DALAM MENGKLASIFIKASI STATUS PERTUMBUHAN ANAK STUNTING (STUDI KASUS : POSYANDU CEMARA)
Authors: Miftahul Jannah  , Hasan Mhd Arief , Al Fajar Muhammad
Published: January 2025

Klasifikasi merupakan metode untuk mengelompokkan teks sehingga teks dengan isi yang serupa akan dikelompokkan dalam jenis yang sama. Dalam konteks pertumbuhan anak stunting di Posyandu Cemara, metode data mining untuk klasifikasi menjadi relevan dalam mengidentifikasi kategori pertumbuhan anak sebagai normal atau tidak normal. Stunting, sebagai masalah gizi kronis, disebabkan oleh kurangnya asupan gizi dalam jangka waktu panjang, mengakibatkan gangguan pertumbuhan pada anak dan tinggi badan yang lebih rendah dibandingkan dengan anak-anak seusianya.Dalam penelitian ini, kami menggunakan metode klasifikasi Naïve Bayes dan K-Nearest Neighbor. Naïve Bayes menggunakan perhitungan probabilitas dan statistik, sementara K-Nearest Neighbor adalah metode klasifikasi yang menentukan kategori objek berdasarkan data pembelajaran dengan jarak paling dekat. Hasil eksperimen menunjukkan bahwa Naïve Bayes menghasilkan akurasi sebesar 71.25%, presisi sebesar 66%, dan recall sebesar 11%. Sementara itu, K-Nearest Neighbor memberikan akurasi sebesar 66.67%, presisi sebesar 82%, dan recall sebesar 75%.Temuan ini memberikan wawasan tentang performa dua metode klasifikasi dalam konteks klasifikasi pertumbuhan anak stunting. Diskusi selanjutnya melibatkan implikasi praktis dari hasil penelitian ini dan saran untuk pengembangan penelitian selanjutnya di bidang ini..
Rancangan UI (User Interface) dan UX (User Experience) Sistem Imunisasi Anak Menggunakan Metode Design Thinking
Authors: Fu'adah Amran Hasanatul , Farianti Amran Husna , Martilova Dona , Anugrah Bayu
Published: January 2025

Berkembangnya teknologi informasi dan komunikasi yang semakin pesat termasuk bidang kesehatan yang menerapkan penggunaan komputer dalam kegiatannya atau yang biasa dikenal dengan istilah E-Health. E-Health dapat diartikan sebagai ilmu pengetahuan baru yang memiliki inovasi dalam pertukaran informasi medis, kesehatan masyarakat dan hal-hal yang berkaitan dengan jasa pelayanan dan informasi kesehatan yang ditingkatkan melalui saluran internet dan teknologi, salah satu nya adalah imunisasi. Penelitian ini akan berfokus pada rancangan UI dan UX dengan menggunakan metode design thinking. Penggunaan metode design thinking akan mengadaptasi metode yang biasa diterapkan oleh desainer menggunakan prosedur iteratif dalam pemikiran desain dari pernyataan masalah hingga solusi masalah. Tujuannya adalah untuk menghasilkan ide sebanyak mungkin sehingga ditemukan permasalahan dan solusi terbaik untuk masalah tersebut. Metode ini akan dimulai dengan tahap Empathize, Define, Ideate, Prototype, dan Test. Prototipe yang telah dirancang menggunakan Figma kemudian diuji kepada 5 penguji dengan menggunakan metode pengujian System Usability Scale (SUS). Berdasarkan pengujian yang telah dilakukan diperoleh hasil uji dengan total nilai 86 dan disimpulkan acceptable, grade scale B dan adjective rating adalah excellent.
Sistem Pakar Diagnosa Penyakit Mata Dengan Metode Certainty Factor
Authors: Bagaskara Mochammad Naufal , Dwi Hartanti  , Vihi Atina
Published: January 2025

Perkembangan teknologi informasi telah mengubah cara layanan kesehatan disediakan dengan maraknya layanan kesehatan online yang semakin diminati. Akan tetapi, mengidentifikasi penyakit mata secara online menjadi sebuah tantangan karena kompleksitas gejala yang ada dan kendala dalam pemeriksaan fisik yang terbatas. Pembuatan sistem pakar berbasis website dengan menggunakan metode Certainty Factor (CF) adalah langkah penting dalam mendukung layanan kesehatan mata secara online. Penelitian ini menyoroti pentingnya diagnosis awal yang cepat dan akurat untuk penyakit mata seperti konjungtivitis, glaukoma, atau degenerasi makula. Sistem pakar berbasis CF di Klinik Netra Husada Wonogiri bertujuan untuk memberikan solusi yang efektif terutama ketika akses langsung ke dokter mata terbatas. Pemilihan metode CF karena kemampuannya dalam mengatasi ketidakpastian dalam proses diagnosis dan memberikan estimasi kepercayaan terhadap hasil diagnosis. Selain menyediakan kemudahan akses, sistem ini diharapkan dapat meningkatkan kesadaran masyarakat akan pentingnya perawatan mata. Dengan akses yang lebih mudah, diharapkan masyarakat akan lebih proaktif dalam memantau kesehatan mata mereka sendiri dan mencari bantuan medis jika diperlukan, guna mencegah terjadinya komplikasi serius. Pengembangan sistem pakar berbasis website dengan metode Certainty Factor untuk diagnosis awal penyakit mata memiliki potensi besar dalam meningkatkan aksesibilitas dan kualitas layanan kesehatan mata secara online. Penelitian dilakukan melalui beberapa tahap, dari mulai pengumpulan data hingga pengembangan sistem dengan metode waterfall. Harapannya sistem ini mampu memberikan diagnosis awal dengan cepat, akurat, dan dapat dipercaya, sehingga meningkatkan tingkat kesejahteraan dan kualitas hidup masyarakat.
Penerapan Metode Resilient Backpropagation (RPROP) Untuk Prediksi Aktivitas Gempa Bumi Berdasarkan Skala Magnitudo
Authors: Widyaningrum Bajeng Nurul , Kurnia Ramadhani Lingga
Published: January 2025

Indonesia merupakan salah satu negara dengan tingkat gempa bumi yang cukup tinggi karena memiliki beberapa lempeng utama.  Oleh karena itu, prediksi aktivitas gempa bumi menjadi hal yang penting untuk dilakukan guna mengurangi risiko dan kerugian yang ditimbulkan. Telah banyak penelitian terkait dengan prediksi gempa bumi dengan menggunkan beberapa metode. Salah satu metode yang digunakan adalah Metode Backpropagation. Melihat dari penelitian-penelitian sebelumnya, peneliti mengusulkan penerapan Jaringan Saraf Tiruan dengan Algoritma Resilient Backpropagatio untuk prediksi aktivitas gempa bumi berdasarkan nilai magnitudo di Indonesia. Data yang digunakan yaitu data aktivitas gempa bumi bulanan skala magnitudo 4,5 keatas dari periode waktu tahun 1992 hingga 2023 untuk memastikan keberagaman pola aktivitas gempa bumi yang terjadi di berbagai wilayah di Indonesia. Selain parameter skala magnitudo, informasi penting seperti lokasi episenter, dan waktu kejadian juga dimasukkan sebagai fitur input untuk jaringan saraf. Hasil penelitian menunjukkan bahwa prediksi gempa bumi menggunakan metode Jaringan Saraf Tiruan Resilient Backpropagation dengan model arsitektur 6-10-1 dan learning rate 0,6 menunjukkan tingkat akurasi RMSE 0,04778 dan MAE 0,03509. Hasil prediksi menunjukkan pada bulan Februari dengan 67 kejadian dan tertinggi pada bulan Desember dengan 185 kejadian dengan melihat aktifitas gempa bumi di wilayah Indonesia dengan skala magnitudo diatas 4,5. Penelitian ini menunjukkan bahwa model jaringan saraf tiruan dengan algoritma Backpropagation dengan optimasi Resilient mampu memberikan prediksi aktivitas gempa bumi dengan tingkat akurasi yang memuaskan
IMPLEMENTASI DETEKSI DRONE MENGGUNAKAN YOLO (You Only Look Once)
Authors: Wijanarko Restu Gilang , Pradana Afu Ichsan , Hartanti Dwi
Published: January 2025

Penelitian ini berfokus pada pengembangan sistem deteksi drone yang akurat dan efektif berbasis teknologi kamera. Penggunaan drone yang semakin meningkat di berbagai sektor, seperti fotografi udara, pemantauan lingkungan, pemetaan topografi, pengiriman barang, inspeksi infrastruktur, dan pertanian presisi, telah membawa banyak manfaat. Namun, penggunaan drone yang tidak bertanggung jawab juga dapat menimbulkan masalah serius, seperti pelanggaran privasi, risiko keamanan, dan gangguan pada operasi penerbangan. Untuk mengatasi tantangan ini, penelitian ini mengusulkan pendekatan deteksi drone menggunakan kamera sebagai perangkat utama, memanfaatkan algoritma pengolahan citra digital dan teknik pembelajaran mesin. Sistem ini diharapkan mampu mendeteksi keberadaan drone dalam berbagai kondisi lingkungan dan pencahayaan, serta memberikan informasi yang lebih rinci tentang lokasi dan aktivitas drone. Dengan menggunakan teknologi pembelajaran mesin, sistem ini dapat dilatih untuk mengenali berbagai jenis drone dan membedakannya dari objek lain yang mungkin muncul di latar belakang, serta dapat terus ditingkatkan kinerjanya seiring dengan bertambahnya data pelatihan yang digunakan. Penelitian ini menggunakan metode Research and Development (R&D) dengan fokus pada implementasi sistem deteksi drone menggunakan kamera web dan perpustakaan perangkat lunak OpenCV. Hasil penelitian ini diharapkan dapat memberikan kontribusi signifikan dalam meningkatkan keamanan dan keselamatan di berbagai sektor, serta mencegah penyalahgunaan teknologi drone untuk tujuan yang merugikan, dan temuan dari penelitian ini dapat menjadi dasar bagi pengembangan sistem deteksi drone yang lebih canggih di masa depan.
Evaluasi Faktor-Faktor Penerimaan Aplikasi SeaBank Menggunakan Model UTAUT2
Authors: Nur Tsalitsna Imamah  , Arista Pratama  , Asif Faroqi
Published: January 2025

Sistem pembayaran non tunai semakin populer sebagai infrastruktur keuangan yang mendukung pertumbuhan teknologi keuangan. Salah satu metode yang diminati adalah bank digital seperti SeaBank, yang menawarkan kemudahan, efisiensi, dan keamanan transaksi. SeaBank memberikan layanan rekening tabungan dengan bunga tinggi, promo menarik, dan transfer gratis, menjadi solusi finansial komprehensif bagi pengguna. Namun, SeaBank tidak memiliki ATM dan kantor cabang pada kota besar saja yang dapat membatasi penerimaan aplikasi, serta permasalahan seperti kegagalan transaksi dan pengaduan yang tidak segera ditindaklanjuti menunjukkan perlunya analisis faktor penerimaan teknologi terhadap minat dan perilaku penggunaan aplikasi SeaBank. Research ini bermaksud untuk mengerti aspek yang memengaruhi minat dan perilaku pengguna dalam menerima aplikasi SeaBank menggunakan model UTAUT2. Sampel sebanyak 401 responden diambil dari pengguna aplikasi SeaBank, kemudian dianalisis dengan SEM-PLS menggunakan SPSS dan SmartPLS. Hasil penelitian menunjukkan faktor yang memengaruhi niat penggunaan adalah performance expectancy, social influence, price value, dan habit, sedangkan perilaku penggunaan dipengaruhi oleh behavioral intention.
Implementasi Sistem Penghitungan Volume Kendaraan Menggunakan YOLOv8
Authors: Putra Wihan Perkasa Nugraha , Pradana Afu Ichsan , Nurchim Nurchim
Published: January 2025

Dengan banyaknya kendaraan di jalan, penting untuk memantau lalu lintas agar keamanan dan manajemen lalu lintas dapat terjaga dengan baik. Pengumpulan data jumlah kendaraan secara manual memerlukan banyak sumber daya dan biaya. YOLOv8 (You Only Look Once) adalah teknologi visi komputer yang memungkinkan deteksi objek secara otomatis dengan akurasi dan kecepatan tinggi. Penelitian ini bertujuan untuk mengotomatisasi perhitungan jumlah kendaraan yang melintas dengan YOLOv8, yang dapat mendeteksi berbagai jenis kendaraan dalam berbagai kondisi cuaca. Studi ini terdiri dari beberapa tahap, yaitu pengumpulan data, preprocessing, pemodelan, dan evaluasi. Dataset diperoleh dari dataset Kaggle dan rekaman video lalu lintas di Indonesia. Dataset dibagi menjadi data latih dan validasi dan diproses dengan bounding box. Pemodelan menggunakan YOLOv8 Nano dengan 50 epoch, dan evaluasi dilakukan menggunakan confusion matrix. Implementasi dilakukan menggunakan OpenCV untuk menghitung jumlah kendaraan dari rekaman video. Sistem ini berhasil menghitung jumlah kendaraan berdasarkan klasifikasi yang berbeda dengan baik, meski ada kendala saat frame drop. Penelitian ini berhasil mengembangkan sebuah sistem yang akurat dan diuji dengan rekaman CCTV lalu lintas di Surakarta, meskipun klasifikasi jenis kendaraan belum sesuai dengan standar dinas perhubungan dan kualitas frame rate video masih memengaruhi akurasi sistem. Sebaiknya dilakukan pengujian waktu nyata dan penambahan identitas unik pada kendaraan yang dideteksi.
Deteksi Tingkat Depresi Kerja Pada Guru Sekolah Dasar Menggunakan Metode Fuzzy Mamdani
Authors: Berutu Nurhalimah , Sriani
Published: January 2025

Deteksi tingkat depresi pada guru sekolah dasar sangat penting untuk menjaga kesejahteraan mental dan kualitas pengajaran. Depresi pada tenaga pengajar dapat mempengaruhi efektivitas pengajaran serta kesejahteraan siswa. Penelitian ini bertujuan untuk mengembangkan sistem deteksi depresi kerja menggunakan metode Fuzzy Mamdani. Data yang digunakan diperoleh melalui kuesioner PHQ-9, alat pengukur standar untuk menilai tingkat depresi. Sistem fuzzy yang dirancang mengolah dua input utama, yaitu Indeks Massa Tubuh (IMT) dan skor PHQ-9, untuk menghasilkan prediksi tingkat depresi. Evaluasi sistem menunjukkan kemampuannya dalam mengklasifikasikan tingkat depresi ke dalam kategori tidakdepresi, depresi ringan, depresi sedang, dan depresi berat dengan akurasi yang baik. Dari pengujian terhadap 100 guru sekolah dasar, 98% responden terdeteksi mengalami depresi ringan dan 2% mengalami depresi sedang. Hasil ini menekankan pentingnya pemantauan dan intervensi lebih lanjut untuk menjaga kesejahteraan mental guru. Implementasi sistem ini diharapkan dapat meningkatkan efektivitas dan efisiensi pemantauan kesehatan mental guru serta berkontribusi pada peningkatan kualitas pendidikan.
Ekstraksi Aspek Aksesibilitas untuk Peningkatan Pengalaman Pengguna Menggunakan NER dengan CNN dan LSTM
Authors: Dwijayanti Irmma , Alfirna Rizqi Lahitani  , Kartikadyota Kusumaningtyas  , Muhammad Habibi
Published: January 2025

Transportasi online memberikan dampak positif bagi sebagian besar masyarakat, namun penggunaan aplikasi oleh penyandang disabilitas masih menghadapi sejumlah tantangan. Belum adanya fasilitas yang memadai dan pengalaman pengguna yang baik menjadi kendala utama. Realitas ini menunjukkan bahwa perlunya perhatian khusus terhadap prinsip aksesibilitas untuk meningkatkan pengalaman pengguna dan kenyamanan bagi penyandang disabilitas. Melalui ulasan pengguna dapat diidentifikasi aspek-aspek aksesibilitas untuk mendukung peningkatan pengalaman pengguna. Penelitian ini bertujuan mengekstraksi informasi dari ulasan pengguna terkait aksesibilitas menggunakan metode NER dengan pendekatan CNN dan LSTM. Data yang dikumpulkan melalui web scraping terdiri dari 6.255 ulasan aplikasi Gojek, Grab, Maxim, dan Indriver. Hasil evaluasi menunjukkan bahwa kedua model memiliki akurasi tinggi yaitu CNN 99,84%, dan LSTM 99,48%. Namun memerlukan perbaikan dalam mendeteksi entitas yang jarang muncul atau berkonteks kompleks. Hasil analisis menunjukkan bahwa ulasan lebih banyak membahas fitur aplikasi dan keluhan yang berkaitan dengan aksesibilitas. CNN lebih efektif dalam menangkap pola spesifik, sedangkan LSTM lebih kuat dalam menangkap variasi kata.
Optimalisasi Sistem Dompet Kurban Terintegrasi Peternakan Modern Berbasis AI-IoT dengan Teknologi YOLO
Authors: Apriliyanto Erwin , Dimas Fajar Nugroho  , Kurniawan Wakhid , Iriandi Putra Romi , Yusuf Ariyadi Muhammadi
Published: January 2025

Sebagai negara dengan jumlah umat Islam terbesar di dunia, Indonesia menghadapi tantangan untuk memenuhi kebutuhan hewan kurban yang terus bertambah setiap tahunnya. Penelitian ini fokus pada pengembangan Dompet Kurban Terintegrasi Peternakan Modern yang memanfaatkan teknologi AI-IoT dengan algoritma YOLO untuk meningkatkan efisiensi serta mempermudah pengelolaan kurban. Proses penelitian meliputi tahapan seperti pengumpulan data, analisis kebutuhan, desain sistem, simulasi, implementasi, hingga evaluasi kinerja. Sistem yang dihasilkan menawarkan fitur pelacakan secara real-time, estimasi berat hewan melalui teknologi citra, serta integrasi pembayaran digital. Berdasarkan hasil uji coba, waktu yang diperlukan untuk mengukur berat sapi dapat dipersingkat dari 60 detik menjadi rata-rata 2,1 detik dengan akurasi yang hampir setara dengan metode tradisional. Selain itu, penerapan IoT juga menurunkan biaya operasional peternakan hingga 30%. Teknologi ini tidak hanya mendukung peningkatan efisiensi peternakan, tetapi juga mempermudah masyarakat dalam menabung dan menjalankan kurban. Penelitian ini menyimpulkan bahwa penerapan teknologi IoT dan AI dapat menjadi solusi inovatif untuk mengatasi tantangan dalam pengelolaan kurban di Indonesia
OSN, Olimpiade Sains Nasional Optimalisasi Analisis Data Peserta Olimpiade Sains Nasional Indonesia Menggunakan Algoritma K-Means Clustering
Authors: Purwatiningsih Agustina
Published: January 2025

Petunjuk Salah satu program utama yang diselenggarakan oleh Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi (Kemendikbudristek) melalui Pusat Prestasi Nasional (Puspresnas) adalah Olimpiade Sains Nasional (OSN). OSN diselenggarakan secara bertingkat, mulai dari tingkat kabupaten/kota hingga nasional, dengan tujuan meningkatkan kualitas pendidikan di Indonesia. Namun, pembinaan dan seleksi peserta OSN seringkali menghadapi masalah seperti data yang tidak terstruktur dan kurangnya pendekatan pengambilan keputusan strategis berbasis data. Algoritma K-Means clustering sangat cocok untuk menemukan pola dalam data pendidikan seperti performa siswa, efektivitas pembinaan, atau wilayah dengan tingkat pencapaian tertentu.Tujuan dari penelitian ini adalah untuk mengisi celah tersebut dan menghasilkan informasi strategis untuk pembinaan dan pengambilan keputusan yang lebih baik dengan menggunakan K-Means dalam analisis data OSN. Hasil dari penelitian ini, terdapat 3 klaster untuk provinsi pemenang lomba OSN dan 6 klaster kota dan kabupaten menurut perolehan hasil medali. Semoga informasi yang disajikan dalam penelitian ini bisa sebagai acuan untuk pemerataan pendidikan di Indonesia.
Analisis Pengukuran Indeks Produktifitas Produk Tahu pada Industri Tahu di Kota Batam
Authors: Arsyad Sumantika  , Bahariandi Aji Prasetyo
Published: January 2025

All businesses must aim to sustain consistent success in the current industry. Increasing productivity is one approach to boost the performance of the industry. Productivity describes the efficiency and effectiveness of the company. Tofu is the main food of the Batam people, but the company's production target does not meet expectations. From August to October 2024, production output will be 1,200,000 pcs, 1,140,000 pcs, and 1,110,000 pcs, respectively, while the company's target is 1,400,000/month. This research aims to find out how productive tofu companies are in Batam City. The method used is Objective Matrix (OMAX). This method is carried out by calculating the productivity criteria ratio, determining the initial standard value and achievement target, determining the value in the body of the matrix, and calculating the productivity index. Then, the criteria were determined using 6 productivity ratios. The data was collected on the tofu machine production floor for three months, from August to October 2024. The data collection and processing results show that the total productivity index of Batam City tofu XYZ companies was at its highest point in August with an index value of 375, while in October, it was at its lowest point with an index value of 310. This shows a linear decrease in productivity. Then, the recommended solution is choosing a good supplier, regular machine maintenance, and establishing good SOPs
Labor competencies and their impact on the performance of the personnel of the parochial GADS of the province of Santa Elena
Authors: Malavé Yagual Diana Carolina , Benavides Rodríguez Arturo Gustavo
Published: January 2025

The objective of this article is to evaluate the incidence of labor competencies play a fundamental role in the performance of personnel in the parish Autonomous Decentralized Governments (GAD) of the province of Santa Elena. Several techniques and tools were used to analyze how technical, social and personal skills influence the quality and efficiency of the services offered by these institutions. The study used descriptive research through the desegregation of variables, which also allowed for a situational diagnosis, and correlational research through the analysis of indicators to analyze the variables of interest. Data collection was carried out through a survey of parish government officials to identify gaps in competencies and their relationship with the fulfillment of organizational objectives. Significant deficiencies were identified in the design of training programs and in the periodic evaluation of performance, which limits the integral development of personnel and negatively affects productivity levels. Consequently, it is proposed to implement a management model based on competencies, including continuous training processes and evaluation mechanisms.