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RTOS-BASED SYSTEM FOR TODDLER NUTRITIONAL STATUS DETECTION
Get PDFDetermining the nutritional status of toddlers is essential for monitoring growth and preventing long-term health problems. Manual assessment requires significant time and is prone to human error; therefore, an automatic detection system based on height and weight parameters is needed. This study aims to develop a Real-Time Operating System (RTOS)–based system to detect the nutritional status of children aged 24–60 months, capable of managing task priorities, ensuring timely execution, and preventing race conditions using semaphores. The system employs an ultrasonic sensor to measure height, load cell sensors to measure body weight, and a web-based interface to input gender and age. Nutritional classification is determined through Z-score calculations using WHO reference data. Tests conducted on 200 children in various locations showed that the ultrasonic sensor achieved an average absolute error of 0.39 cm, a relative error of 0.409%, and an accuracy of 99.59%, while the load cell sensor achieved an average absolute error of 0.22 kg, a relative error of 1.587%, and an accuracy of 98.41%. The average execution times for the measurement and Z-score computation tasks were 4014.4 ms and 11.31 ms, respectively. The nutritional status classification results showed accuracy levels of 99.5% for Weight-for-Age (W/A), 99.5% for Height-for-Age (H/A), and 97.5% for Body Mass Index-for-Age (BMI/A) compared with manual assessments. The developed system demonstrated reliable performance in measurement and classification, with results consistent with conventional methods, indicating its potential as an efficient and accurate tool to assist healthcare workers in monitoring toddler nutrition statu
MEMBANGUN SEKOLAH BERKELANJUTAN: IMPLEMENTASI OPTIMALISASI SARANA PRASARANA DALAM SEKOLAH INKLUSI DAN ADIWIYATA
Get PDFEarly childhood education in Kotawaringin Timur Regency faces several challenges, particularly in managing facilities and infrastructure. Many kindergartens and playgroups lack adequate resources, such as interactive classrooms and outdoor play areas, which limits children’s creativity and exploration. This condition requires teachers to be innovative in utilizing limited resources to create meaningful learning experiences. To address these issues, a community service program was conducted to enhance teachers’ knowledge and skills in optimizing school facilities to support sustainable learning. The program emphasized strategies for maximizing limited resources, fostering collaboration with parents, using social media, and integrating horticulture into the learning environment. Interactive training methods were employed, including presentations, discussions, and hands-on practice. A total of 94 participants from 47 educational institutions joined the program, recruited through collaboration with Himpaudi Kotim, IGRA, and PKG Markisa. The results showed that teachers gained new insights into maximizing existing facilities, strengthening parent communication via Instagram and WhatsApp, and applying horticulture as an engaging learning medium. The discussions also highlighted the relevance of these strategies to school quality improvement, including accreditation. In conclusion, this program provided practical solutions for optimizing educational facilities, supporting inclusive and Adiwiyata-oriented schools, and fostering stronger collaboration between schools, parents, and technology to achieve sustainable education
PELATIHAN DIGITALISASI LAYANAN POSYANDU DENGAN SEHATLINK UNTUK PEMANTAUAN KESEHATAN KELUARGA KELURAHAN RAGUNAN
Get PDFPosyandu plays a crucial role in promotive and preventive health efforts, particularly in stunting prevention and early detection of chronic diseases, yet challenges remain in data recording and information dissemination. This community service activity aimed to enhance cadre capacity and community participation through digitalizing services using the SehatLink website. The program involved 24 cadres from Posyandu RW 01 Ragunan Village, employing training, technical assistance, and pre-test and post-test evaluations. Results showed significant improvements in cadre management aspects: digital training needs increased by 74%, perceived effectiveness of the application in stunting prevention reached 83%, trust in digital data rose to 80%, and support for data-based decision making reached 81%. Among the community, understanding of healthy eating patterns increased by 73%, effectiveness of digital education by 85%, ease of access to health information by 78%, and family involvement in health monitoring by 73%. These findings confirm that SehatLink effectively strengthens cadre capacity and enhances community engagement in digital health services, especially for stunting prevention and early detection of chronic diseases. Program sustainability requires ongoing training, development of contextual educational content, and integration into regional health information systems
PERAN INFLUENCER MARKETING DAN TESTIMONI TERHADAP KEPUTUSAN PEMBELIAN PRODUK KOSMETIK DI E-COMMERCE SHOPEE PADA GENERASI Z DI KOTA DEPOK
No full textThis research investigates how influencer marketing and consumer testimonials on the purchase decisions of Generation Z in Depok City, focusing on cosmetic products sold on Shopee. The rapid growth of the digital cosmetic industry has made these marketing strategies crucial for engaging the largest and digitally active consumer group in Indonesia. Primary data were collected via Likert-scale questionnaires from 100 purposively sampled respondents between July and September 2025. Multiple linear regression analysis using SPSS showed that both influencer marketing (β positive, p < 0.05) and testimonials (β positive, p < 0.05) significantly influence consumer choices assessed secara terpisah maupun bersama-sama. Nilai determinasi (R² = 0.784) indicates that 78.4% of the variation in purchase decisions is explained by these two variables. These findings highlight the importance for cosmetic marketers on Shopee to leverage influencer marketing and testimonials to effectively increase Generation Z's purchasing behavior.Pertumbuhan industri kosmetik di era digital mendorong perusahaan untuk menggunakan strategi pemasaran inovatif, khususnya melalui influencer marketing dan testimoni konsumen. Fenomena ini sangat relevan bagi Generasi Z, kelompok konsumen terbesar di Indonesia, yang aktif berbelanja produk kecantikan melalui e-commerce seperti Shopee. Penelitian ini bertujuan untuk menganalisis pengaruh influencer marketing dan testimoni terhadap keputusan pembelian produk kosmetik pada Generasi Z di Kota Depok, baik secara parsial maupun simultan. Metode penelitian menggunakan pendekatan kuantitatif dengan teknik purposive sampling terhadap 100 responden. Data dikumpulkan melalui kuesioner dengan skala Likert 1–5 dan dianalisis menggunakan regresi linier berganda, uji asumsi klasik, uji t, uji F, serta koefisien determinasi melalui bantuan SPSS. Hasil penelitian menunjukkan bahwa influencer marketing dan testimoni berpengaruh positif dan signifikan terhadap keputusan pembelian. Nilai R² sebesar 0,784 menandakan bahwa 78,4% variasi keputusan pembelian dijelaskan oleh kedua variabel independen, sedangkan sisanya dipengaruhi faktor lain di luar penelitian
ANALYSIS OF THE NEED FOR AN INFORMATION SYSTEM ON PRICES AND AVAILABILITY OF BASIC MATERIALS
Get PDFThe development of information technology has driven digital transformation in various sectors, including the economic sector. Managing data on the prices and availability of basic commodities is crucial for maintaining community economic resilience. This study applies a design thinking approach to analyze the need for an information system on the prices and availability of basic commodities in Yogyakarta City, with a testing plan prepared using black box, white box, and security methods. The analysis produced three main findings: the need for Single Sign-On (SSO) with role-based access, real-time monitoring of commodity prices, and cross-agency integration in agenda and program management. The proposed system design consists of four main modules: administration, agenda, services, and programs/activities. Since this study is limited to the needs analysis and prototype design stage, empirical test results are not yet available. Nevertheless, the study provides an initial framework and foundation for cross-agency integration in the Yogyakarta City Government to support transparency, coordination, and control of basic commodity prices
OPTIMIZING PHARMACEUTICAL DISTRIBUTION IN PUBLIC HEALTH CENTERS USING FUZZY C-MEANS CLUSTERING
Get PDFEfficient drug distribution is fundamental to ensuring the quality of public healthcare services. However, health departments often face challenges with imbalances between drug demand and available supply. This study addresses this issue by applying the Fuzzy C-Means (FCM) clustering algorithm to categorize drug demand levels across 16 public health centers (puskesmas) in Langkat Regency, Indonesia, from 2021 to 2023. Using historical data from 2,400 drug records, the analysis identified five distinct demand clusters: Very Low, Low, Medium, High, and Very High. The results revealed a significant disparity in drug needs, with the "Very High" demand cluster dominating (51.29% of data) in centers like Besitang and Tanjung Selamat, driven by high morbidity rates. In contrast, other clusters were less prevalent, such as the "Low" demand cluster, which was primarily concentrated in the Gebang health center. These findings, visualized using t-SNE plots, highlight significant regional variations in pharmaceutical needs. This data-driven clustering provides a robust framework for the Langkat District Health Office to develop more targeted, efficient, and equitable drug distribution strategies, ultimately improving healthcare service delivery
COMPARATIVE ANALYSIS OF CNN ARCHITECTURES FOR TOMATO LEAF DISEASE CLASSIFICATION USING TRANSFER LEARNING
Get PDFTomato is one of the widely available horticultural products and holds significant economic value in Indonesia. However, its productivity is often disrupted by various leaf diseases. This study aims to compare the performance of three CNN architectures—DenseNet121, Xception, and MobileNetV2—in classifying tomato leaf diseases. The dataset used consists of 10,000 balanced images across ten classes: Bacterial Spot, Septoria Leaf Spot, Early Blight, Late Blight, Mosaic Virus, Yellow Leaf Curl Virus, Leaf Mold, Target Spot, Spider Mites Two-Spotted Spider Mite, and Healthy. All images were resized to 224x224 pixels and divided into 80% training data and 20% test data. Augmentation techniques were applied to balance the data across classes. Experimental results show that the Xception architecture outperforms the other models, achieving an accuracy of 98.79%, with a precision of 98.80%, recall of 98.79%, and an F1-Score of 98.78%. These findings indicate that the Xception model is highly effective for plant disease classification and is suitable for implementation in environments with limited resources
REKOMENDASI PEKERJAAN BIDANG EKONOMI : SISTEM REKOMENDASI MENGGUNAKAN CONTENT BASED
Get PDFThe recommendation system was developed to assist students of the Institut Teknologi dan Bisnis Widya Gama Lumajang, particularly those from the Faculty of Economics and Business, in determining their preferred career options. This system helps students by providing various job references that match their individual criteria. The data was collected from a tracer study, which includes information such as academic grades, non-academic achievements, job positions, company names, salaries received. From the total dataset, 1,120 records were deemed valid and used in the research process. The aim of this research is to assist students by providing job recommendations based on similar criteria between current students and alumni. The method applied in this study is quantitative experimental research based on data mining, with the main approach being Content-Based filtering and the MLP (Multi-Layer Perceptron) Classifier algorithm. The data was split into two parts: 65% for training and 35% for testing. This division aims to allow the model to learn from most of the data while also being tested for accuracy using unfamiliar data. The recommendation model was developed using the MLP Classifier algorithm with a hidden_layer_size configuration of 100 neurons and a max_iter of 200 iterations. For the initial test, 10 sample data points were used to evaluate the model’s performance. During training, the loss value was monitored to assess how well the model understood the data and adjusted its internal weights. With this configuration, the system is expected to provide accurate job recommendations based on the user’s profile and academic history
DEVELOPMENT OF A FUNDRAISING WEBSITE WITH PAYMENT GATEWAY TO SUPPORT DIGITAL ECONOMY AT LAZISMU
Get PDFThis study discusses digital-based fundraising and financial services in the management of zakat, infaq, and shadaqah (ZIS). In this process, strategies and data related to distribution, calculation, management, and disbursement of funds often pose challenges. This issue is particularly evident in LAZISMU Bangka Belitung, which has yet to establish a website for large-scale online fundraising and for providing information about its available programs. Currently, the process of fundraising and ZIS management is still carried out conventionally. Therefore, this study proposes a digital system for LAZISMU that can provide information, manage ZIS, and facilitate digital payments through an integrated payment gateway. This innovation aims to make it easier for the public to fulfill their zakat obligations and access information about the fund distribution programs available at LAZISMU Bangka Belitung. The method used in developing this system is a prototype. The results of the study indicate that the developed system can simplify the process of fundraising and managing ZIS digitally. The implementation of this system is expected to enhance the efficiency of zakat management and have a broader positive impact in supporting communities in need
PENGEMBANGAN SISTEM AUDIT TERINTEGRASI PADA SIAKAD MENGGUNAKAN FRAMEWORK COBIT 5
Get PDFThe Academic Information System (SIAKAD) plays a crucial role in supporting academic activities within the university environment. Evaluating the system's maturity is necessary to identify weaknesses and potential improvements. Therefore, periodic audits of SIAKAD are essential to obtain constructive feedback from stakeholders. Conducting regular audits of SIAKAD is more effective when supported by an application integrated with the system. This study aims to develop an audit system integrated with SIAKAD. The COBIT 5 framework is used for auditing SIAKAD, while the audit system is developed using PHP programming language and a MySQL database. The focus of this research is the development of an audit system within the Evaluate, Direct, and Monitor (EDM) domain. This study proposes a new approach to developing an effective SIAKAD audit system by integrating SIAKAD with a COBIT 5-based audit system. The developed audit system has been tested on a limited scale with 20 respondents from the Bantaeng Manufacturing Industry Community Academy. At this stage, the audit system development has only reached the process of summarizing questionnaire results. The calculation of SIAKAD maturity levels has not yet been integrated and is still performed manually. Gap analysis results indicate that SIAKAD’s maturity level remains low, with the following scores:EDM1: 30, EDM2: 20, EDM3: 33.6, EDM4: 16.7, and EDM5: 23.3. Based on these maturity scores, improvements in governance are required, particularly in the EDM2 and EDM4 subdomains