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Efektivitas Metode Sentra Bahan Alam dalam Meningkatkan Perkembangan Sensorymotor Skill pada Anak Usia Dini
Full text linkPenelitian ini bertujuan untuk menguji upaya meningkatkan perkembangan sensorimotor pada anak usia dini dengan metode sentra bahan alam di Sekolah Cerdas Ummat Madani, Bekasi. Pendekatan yang digunakan adalah deskriptif kualitatif dengan teknik observasi, wawancara, dan dokumentasi dengan proses analisis data kualitatif melalui beberapa aktifitas yaitu reduksi data, penyajian data, dan penarikan kesimpulan. Subjek penelitian ini adalah unsur lembaga yang meliputi kepala sekolah, tenaga pendidik/guru, dan orang tua. Hasil penelitian menunjukkan bahwa pertumbuhan dan perkembangan anak usia dini kenyataannya banyak yang mengalami keterbatasan dalam perkembangan sensorimotor pada anak. Dalam konteks ini metode sentra bahan alam yang inovatif dan efektif sangat diperlukan untuk mendukung perkembangan sensorimotor pada anak usia dini
Penggunaan Technology Acceptance Model (TAM) 3 Untuk Mengukur Tingkat Penerimaan Aplikasi Threads Pada Kalangan Remaja
Full text linkPerkembangan teknologi informasi yang pesat telah mendorong lahirnya berbagai aplikasi media sosial baru, salah satunya adalah Threads yang dikembangkan oleh Meta. Threads menarik perhatian kalangan remaja, namun menghadapi kendala teknis seperti bug, error, crash, algoritma tidak relevan, notifikasi spam, dan batasan karakter, yang dapat mempengaruhi penerimaan pengguna. Tujuan dari penelitian ini untuk menganalisis tingkat penerimaan aplikasi Threads di kalangan remaja di kota Palembang dengan menggunakan pendekatan TAM 3. Data dikumpulkan melalui kuesioner online terhadap 100 responden yang ditentukan dengan teknik purposive sampling, dan dianalisis menggunakan metode Partial Least Square - Structural Equation Modeling (PLS-SEM) dengan bantuan software SmartPLS 4. Hasil penelitian menunjukkan bahwa dari total 19 hipotesis yang diuji, sebanyak 12 hipotesis dinyatakan berpengaruh signifikan (p-value < 0,05) dan 7 hipotesis tidak signifikan (p-value ≥ 0,05). Faktor yang terbukti berpengaruh signifikan dalam penerimaan aplikasi Threads adalah Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Behavioral Intention (BI), Subjective Norm (SN), Computer Self-Efficacy (CSE), Computer Playfulness (CP), Output Quality (OQ), dan Voluntariness (VOL). Temuan ini diharapkan dapat memberikan pemahaman lebih mendalam penerimaan aplikasi Threads pada kalangan remaja
ImplementasiAnalisis Kesulitan Belajar Matematika Materi Bangun Datar Siswa Kelas 4 MI Ma’arif NU 5 Sekampung
No full textPenelitian ini bertujuan untuk menganalisis kesulitan belajar matematika pada materi bangun datar yang dialami oleh siswa kelas 4 MI Ma’arif NU 5 Sekampung. Materi bangun datar merupakan salah satu topik penting dalam pembelajaran matematika yang membutuhkan pemahaman konsep dan kemampuan visualisasi ruang. Namun, banyak siswa yang menghadapi kendala dalam memahami dan mengerjakan soal terkait materi ini. Metode penelitian yang digunakan adalah deskriptif dengan pendekatan kuantitatif, melibatkan 30 siswa sebagai sampel. Data dikumpulkan melalui tes tertulis dan wawancara mendalam untuk mengidentifikasi jenis-jenis kesulitan yang dialami siswa. Hasil penelitian menunjukkan bahwa kesulitan utama siswa meliputi pemahaman konsep sifat-sifat bangun datar, kesulitan dalam menggambar bangun datar dengan tepat, serta kesalahan dalam menghitung keliling dan luas. Faktor penyebab kesulitan tersebut antara lain kurangnya media pembelajaran yang menarik, metode pengajaran yang kurang variatif, dan rendahnya minat belajar siswa. Berdasarkan temuan ini, disarankan agar guru menggunakan metode pembelajaran yang lebih interaktif dan media visual yang dapat membantu siswa memahami materi bangun datar secara lebih efektif
Application of the DeLone and McLean Success Model to the SEMAIK Website: A Case Study in Central Lombok
No full text In In the digital age, the use of information technology in public services, including population administration, is crucial. To facilitate access to online population services, the Population and Civil Registration Office of Central Lombok Regency provides the SEMAIK website. Nonetheless, several issues persist, particularly in system quality and service quality. System performance often becomes unstable, with the website slowing down when many users submit service requests simultaneously, while service responsiveness is also frequently delayed. These issues highlight the need for a more comprehensive evaluation of the platform. This study aims to quantitatively assess the effectiveness of the SEMAIK website using the DeLone and McLean Information System Success Model. Data were collected through questionnaires distributed to 126 respondents and analyzed using the SEM-PLS approach. The findings indicate that information quality positively influences system use but does not significantly affect user satisfaction. Meanwhile, service quality, system quality, and system use all show positive effects on user satisfaction. Additionally, although system use does not significantly contribute to net benefits, user satisfaction demonstrates a strong positive effect on net benefits. The model also meets the criteria for good model fit based on the goodness-of-fit assessment. However, the results suggest that aspects related to information quality and system use require improvement, as their effects on user satisfaction and net benefits are not yet optimal. These findings provide concrete recommendations for enhancing the SEMAIK website to ensure more effective and reliable digital public services
1D-CNN-Based Childhood Stunting Prediction through Socio-Economic Data Integration and Community Participation
No full textStunting remains a significant global public health challenge, affecting approximately 148 million children under the age of five. This condition leads to long-term cognitive and physical deficits, particularly in low- and middle-income countries. Many existing prediction models fail to capture the complex interdependencies between nutritional, socio-economic, and environmental factors. To address this gap, our study introduces a 1D-Convolutional Neural Network (1D-CNN) model designed to predict childhood stunting using structured datasets collected from community health centers (Puskesmas) and validated by the Cirebon City Health Department (Dinas Kesehatan Kota Cirebon), Indonesia. The dataset includes anonymized records of children under five years old, comprising anthropometric measurements, socio-economic profiles, nutritional intake, and environmental indicators, gathered through household surveys and routine public health reporting. The proposed 1D-CNN architecture is optimized for structured data by integrating convolutional and pooling layers, dropout regularization, and dense classification layers. To enhance interpretability, we employ explainable AI (XAI) methods—SHAP and LIME—to reveal the relative influence of each feature in the model’s decision-making process. Additionally, the study applies a participatory validation approach through focus group discussions (FGDs) with community health workers, ensuring contextual relevance and ethical integrity. Experimental results demonstrate the superior performance of the proposed model, achieving 93.12% accuracy, with a precision of 97% and a recall of 89%, resulting in an F1-score of 93% across both stunted and non-stunted classes. These findings outperform traditional machine learning approaches and highlight the potential of AI-driven predictive frameworks for early stunting detection and policy-oriented health interventions. This research contributes to the advancement of data-driven public health strategies by integrating predictive analytics, community participation, and transparent AI methodologie
Design and Construction of an System for Diagnosis of Online Game Addiction Using The Forward Chaining and Certainty Factor Methods Based on a Website (Case Study: RSU South Tangerang)
No full text Online games are a type of game that provides a unique pleasure for players, as they can be played not only alone (singleplayer) but also with two or more people (multiplayer) from various locations and countries. Online games are a kind of game that gives players something special because they can be played either singleplayer or with two or more people from different places and countries. According to the APJII 2025 poll, 34.91% of participants spend one to two hours a day playing online games. This suggests that playing online games has ingrained itself into people's daily lives. Because of this, many people can become addicted to online games without realizing it. It might result in adverse bodily effects like exhaustion, weakened immunity, visual issues, anxiety, restlessness when not playing, diminished focus, and emotional shifts (irritability or sensitivity). Therefore, an expert system is needed to diagnose online game addiction as a means of determining the level of addiction. This website aims to determine the level of online game addiction, using the data and the forward chaining method, which aims to generate a conclusion from existing facts. With this method, a conclusion will be obtained, which is then further processed to determine the certainty value. And this expert system requires the certainty factor method to find this certainty value. Given the problems and needs at RSU Tangerang Selatan, this research has produced an expert system for diagnosing online game addiction, which provides ease of use because it is published on a website. This expert system generates output that includes conclusions based on existing facts, the level of online game addiction determined by the certainty factor method, a certainty value ranging from 0% to 100%, and solutions provided by experts
Deep Learning-Based Consumer Preference Analysis for Batik Packaging Design Using Convolutional Neural Networks
No full textPackaging design plays an essential role in shaping consumers’ first impressions of a product, particularly in the batik industry, where cultural meaning and visual identity are deeply intertwined. This study aims to explore how a Convolutional Neural Network (CNN) can help identify consumer preferences toward various batik packaging designs. The dataset consists of real packaging from local SMEs as well as prototype designs created specifically for this research, incorporating variations in motifs, colors, and structural formats. All images were standardized and normalized to ensure consistency before being processed by the CNN model. The architecture consists of several convolutional layers, pooling layers, and fully connected layers, with dropout applied to reduce overfitting. Model training was conducted using the Adam optimizer and the sparse categorical cross-entropy loss function. The results demonstrate that the model achieved a testing accuracy of 92.51%. Stable performance across precision, recall, and F1-score indicates that the CNN effectively captures visual patterns associated with consumer appeal. These findings highlight the potential for batik SMEs to utilize deep learning as a decision-support tool, enabling them to design packaging that is more appealing, relevant, and aligned with contemporary consumer preferences
Penerapan Pendekatan Resiprokal untuk Mengurangi Perilaku Verbal Berulang Pada Anak Usia 5-6
No full textPenelitian ini bertujuan untuk menganalisis penerapan pendekatan resiprokal dalam mengurangi perilaku verbal berulang pada anak usia 5–6 tahun di TK Islam Bakti 4 YPBWI Gresik. Perilaku verbal berulang, seperti pengulangan kata atau frasa tanpa konteks yang tepat, dapat menghambat perkembangan bahasa dan interaksi sosial anak. Penelitian ini menggunakan metode kualitatif deskriptif dengan subjek seorang anak laki-laki berusia 5 tahun yang menunjukkan perilaku verbal berulang. Teknik pengumpulan data meliputi observasi partisipan, wawancara dengan guru dan orang tua, serta dokumentasi selama sepuluh hari pembelajaran. Pendekatan resiprokal diterapkan melalui interaksi dialogis yang menekankan pertukaran peran antara guru dan anak secara timbal balik. Hasil penelitian menunjukkan adanya penurunan signifikan perilaku verbal berulang, disertai peningkatan kemampuan anak dalam merespons instruksi, menyampaikan pendapat, serta terlibat dalam percakapan bergantian. Temuan ini menunjukkan bahwa pendekatan resiprokal efektif dalam mendorong komunikasi fungsional dan memperkuat perkembangan bahasa serta sosial anak usia dini. Penelitian ini memberikan implikasi praktis bagi pendidik PAUD dalam mengembangkan strategi pembelajaran yang inklusif dan berorientasi pada interaksi bermakna
Air Quality Classification Using Naive Bayes Algorithm With SMOTE Technique Based on ISPU Data
No full textAir pollution in DKI Jakarta is an important issue and has a negative impact on public health. This study applies the naive Bayes algorithm to classify air quality, Utilizing the SMOTE technique effectively addresses the issue of data imbalance. The data analyzed came from air pollution index data from 2022 to 2024, taken from five air monitoring stations in Jakarta. The analysis process was carried out following the CRISP-DM stages, starting from understanding the problem to evaluating the model. The results showed that SMOTE succeeded in increasing prediction accuracy in fewer classes. Without SMOTE, the model accuracy reached 90% but appeared biased towards fewer classes, with a recall value of only 0.75 and a precision of 0.62. While SMOTE, the model accuracy became 88%, with a precision value of 0.86, recall 0.87, and f1-score 0.87, which showed more balanced results across classes
Penerapan Model Project Based Learning terhadap Kecerdasan Berfikir Logis Anak Usia 4-5 Tahun di TK Muslimat NU 21 Pakis
Full text linkPenelitian ini dilatarbelakangi oleh kurang optimalnya kemampuan kognitif anak, khususnya kecerdasan berfikir logis pada anak usia 4-5 tahun di kelompok A TK Muslimat NU 21 Pakis. Penelitian ini bertujuan untuk mengetahui peningkatan kecerdasan berfikir logis anak melalui penerapan model Project Based Learning (PJBL). Pendekatan penelitian yang digunakan adalah Penelitian Tindakan Kelas (PTK), dengan model Kemmis dan Mc Tanggart (2014) yang meliputi tahap perencanaan, tindakan, observasi, dan refleksi. Subjek penelitian adalah 20 anak kelompok A usia 4-5 tahun yang terlibat dalam kegiatan pembelajaran berbasis proyek. Data dikumpulkan melalui lembar observasi, dokumentasi, dan penilaian unjuk kerja berdasarkan indikator perkembangan berfikir logis yang mengacu pada Permendikbud Nomor 137 Tahun 2014, sesuai dengan karakteristik perkembangan anak usia dini. Hasil penelitian menunjukkan adanya peningkatan kemampuan berfikir logis anak pada setiap siklus tindakan setelah diterapkannya model Project Base Learning, efektif dalam meningkatkan kecerdasan berfikir logis anak usia dini. Temuan penelitian ini diharap dapat menjadi acuan bagi pendidik dalam mengembangkan strategi pembelajaran yang mampu mengoptimalkan kemampuan kognitif anak