This paper details the development and empirical evaluation of an adaptive learning system aimed at enhancing digital science literacy among junior high school students in Indonesia. The primary challenge addressed is the limitation of one-size-fits-all educational models. Our research proposes a user-centric solution, the Sistem Rekomendasi Cerdas (SRC), developed through a co-design methodology. The system’s core is a User-based Collaborative Filtering (UBCF) algorithm. Its effectiveness was evaluated through a pre-test/post-test experimental study involving 60 students, divided into an experimental and a control group. Quantitative results show that the experimental group achieved a significantly higher increase in science literacy scores (p < 0.001) compared to the control group. Qualitative findings from interviews with the experimental group reveal that the platform enhanced learning motivation, content relevance, and helped overcome learning barriers. This study concludes that the SRC, developed via a co-design model, is a highly effective tool for improving digital science literacy, demonstrating that a user-centered approach is fundamental to creating impactful educational technology.
 
Keywords - Adaptive Learning, Co-Design, Recommender System, Digital Literacy, Usability.

Research was conducted on the detection of batik wastewater in the batik industry of Pekalongan, which generates liquid waste containing synthetic dyes, heavy metals, and hazardous compounds that can potentially pollute the environment if not properly treated. This study aims to develop a simple detection method based on digital image analysis to identify the color characteristics of batik wastewater. Data were obtained by sampling liquid waste from several affected rivers, which were then analyzed using a digital camera and image processing software to determine the intensity values of the red, green, and blue (RGB) channels. The results show that variations in waste concentration significantly influence the distribution of RGB values, enabling faster, cheaper, and more practical identification of pollution patterns compared to conventional laboratory methods. These findings are expected to serve as the foundation for developing a digital technology-based batik wastewater quality monitoring system as part of efforts to mitigate environmental pollution in Pekalongan.
 
Keywords - Batik wastewater, Digital image analysis, RGB intensity, Environmental pollution, Image processing

Peningkatan kebutuhan terhadap energi terbarukan mendorong upaya identifikasi wilayah dengan potensi radiasi surya tinggi, terutama di kawasan tropis seperti Pulau Sumatera. Penelitian ini bertujuan untuk mengklasifikasikan potensi radiasi surya di 154 kabupaten/kota di Sumatera menggunakan metode K-Means Clustering. Data diperoleh dari Global Solar Atlas (GSA) berupa nilai rata-rata harian Global Horizontal Irradiance (GHI) dalam satuan kWh/m²/hari. Hasil klasterisasi menghasilkan tiga kelompok utama, yaitu rendah, sedang, dan tinggi. Cluster rendah (22 wilayah, rata-rata 4,240 kWh/m²/d) kurang sesuai untuk pengembangan PLTS karena tingkat tutupan awan yang tinggi. Cluster sedang (75 wilayah, rata-rata 4,535 kWh/m²/d) menunjukkan potensi yang stabil dan seimbang, sehingga cocok untuk PLTS skala menengah. Cluster tinggi (57 wilayah, rata-rata 4,793 kWh/m²/d) — didominasi oleh Sumatera Utara, Sumatera Selatan, Aceh, dan Bengkulu — merupakan wilayah paling potensial untuk PLTS skala besar. Secara keseluruhan, sebagian besar wilayah di Sumatera termasuk kategori potensi sedang hingga tinggi, menunjukkan prospek besar pengembangan energi surya dalam mendukung transisi energi bersih dan berkelanjutan di Indonesia.
 
Kata Kunci - Radiasi surya, K-Means Clustering, Energi terbarukan, PLTS

Perkembangan teknologi Internet of Things (IoT) telah memberikan peluang besar dalam peningkatan produktivitas pertanian melalui pemantauan kondisi lingkungan secara real time. Tanaman stroberi merupakan komoditas hortikultura yang membutuhkan perhatian khusus terhadap faktor lingkungan, terutama pada kondisi suhu lingkungan, kelembaban tanah, dan pH tanah. Ketiga parameter tersebut sangat berpengaruh terhadap pertumbuhan dan kualitas produksi buah stroberi. Penelitian ini mengembangkan sistem monitoring berbasis IoT yang dirancang untuk mengukur parameter suhu, kelembaban tanah, dan pH tanah pada lahan budidaya tanaman stroberi. Sistem ini memanfaatkan beberapa sensor diantaranya DS18B20 sebagai deteksi suhu lingkungan, YL-69 sebagai deteksi kelembaban tanah, dan sensor soil pH sebagai deteksi pH tanah yang diintegrasikan dengan modul Raspberry Pi sebagai pengolah78 data dari sensor dan mengirimkan data ke platform melalui aplikasi ThingSpeak secara real time. Untuk memperoleh hasil pengujian yang akurat dilakukan pengambilan data dengan membandingkan hasil pembacaan ke tiga sensor dengan alat ukur yang ada dijual dipasaran. Hasil pengujian menunjukkan bahwa sistem mampu bekerja dengan baik dalam memantau kondisi lingkungan tanaman stroberi dan memberikan informasi dengan rata-rata tingkat akurasi untuk kelembaban tanah sebesar 99,985%, pH tanah sebesar 99,907% dan suhu lingkungan sebesar 99,991%. Sistem ini memungkinkan petani dapat melakukan tindakan pengelolaan lahan yang lebih tepat dan sesuai kondisi yang terdeteksi.
 
Kata Kunci - internet of things, raspberry pi, sensor, stroberi, thingspeak.

Variational Quantum Circuits (VQCs) have emerged as a cornerstone of hybrid quantum–classical algorithms designed to harness the computational potential of near-term quantum devices. By combining parameterized quantum gates with classical optimization, VQCs provide a flexible framework for tackling machine learning, chemistry, and optimization problems intractable for classical methods. This review comprehensively overviews VQC design principles, ansatz structures, optimization strategies, and real-world applications. Furthermore, we discuss fundamental challenges such as barren plateaus, the expressibility–trainability trade-off, and current noisy intermediate-scale quantum (NISQ) hardware limitations. Finally, we highlight emerging directions that could enable scalable, noise-resilient, and physically interpretable variational quantum models for future quantum computing applications

Kubis merupakan salah satu komoditas pangan yang memiliki nilai ekonomi tinggi dan banyak dikonsumsi oleh masyarakat. Namun, hama dan penyakit lainnya adalah risiko terbesar dalam budidaya tanaman kubis. Salah satu faktor penting dalam keberhasilan produksi kubis adalah periode pertumbuhan, tetapi sering gagal karena banyak serangan hama. Penelitian ini bertujuan untuk mengklasifikasikan penyakit pada daun kubis menggunakan metode Support Vector Machine (SVM) berdasarkan fitur tekstur, yaitu Gray Level Coccurrence Matrix (GLCM) dan fitur warna Hue, Saturation, and Value (HSV) untuk memudahkan petani mengetahui jenis penyakitnya, sehingga dapat melakukan tindakan yang tepat untuk mencegah kerusakan lebih lanjut. Kumpulan data yang digunakan adalah 606 gambar daun kubis yang terbagi menjadi dua bagian, yaitu data latih dan data uji dengan rasio 80:20. Kumpulan data tersebut diklasifikasikan ke dalam lima kategori penyakit, yaitu: Bercak Cincin, Bercak Daun, Busuk Hitam, Jamur Berbulu Halus, dan Kutu Daun. Uji fitur GLCM dilakukan dengan membandingkan hasil percobaan sudut yaitu 0°, 45°, 90°, 135° dengan akurasi terbaik pada sudut 0°. Selain itu, parameter diuji pada metode SVM dengan kernel RBF, yaitu nilai C (1,5,10) dan gamma (10-1 – 10-5). Hasil akurasi terbaik menggunakan fitur GLCM dan HSV diperoleh dari nilai C = 10 dan gamma = 10-1 dengan akurasi 94,21%. Hal ini menunjukkan bahwa pengujian sudut fitur GLCM dan kernel RBF mempengaruhi hasil akurasi sehingga dalam penelitian ini penggunaan fitur GLCM dan HSV memberikan hasil yang lebih optimal. Proses klasifikasi juga memiliki waktu perhitungan yang relatif cepat, yaitu 1,90 detik.
Kata kunci: Penyakit Daun Kubis, Gray Level Co-occurrence Matrix, Hue Saturation Value, Support Vector Machine, Kernel RBF

Kepuasan pelanggan menjadi indikator utama dalam meningkatan mutu pelayanan, salah satunya pada sektor pendidikan non-formal seperti lembaga bimbingan belajar (bimbel). Penelitian ini bertujuan untuk membangun sistem yang pengukur tingkat kepuasan siswa terhadap layanan bimbel dengan menggunakan metode Customer Satisfaction Index (CSI). Terdapat lima variabel utama yang dianalisis, yaitu harga, fasilitas, kualitas tentor, materi dan hasil belajar. Teknik pengumpulan data pada penelitian ini dilakukan dengan kuisioner kepada 20 responden, yang mencakup dua atribut penilaian, yaitu kepentingan (importance) dan kepuasan (satisfaction). Hasil pengolahan data menunjukkan nilai CSI berada pada kriteria “sangat puas” dengan indeks 88.16%. Penelitian ini juga menghasilkan sistem review dan rating siswa yang diintegrasikan dengan portal bimbel berbasis web yang telah ada. Sistem ini memungkinkan siswa memberikan penilaian dan ulasan langsung terhadap layanan bimbel serta menjadi sarana umpan balik yang objektif. Dengan adanya integrasi ini, pengelola bimbel dapat memantau kepuasan pelanggan serta melakukan evaluasi dan peningkatan layanan bimbel. Penelitian ini menunjukkan bahwa metode CSI yang dikombinasikan dengan sistem informasi mampu mendorong kualitas layanan pendidikan non-formal kearah yang lebih adaptif dan responsif.
 
Kata Kunci - Customer Satisfaction Index, Bimbingan Belajar, Review dan Rating, Sistem Informasi, Kepuasan Pelanggan

This community service program is designed to address the need for digitalization in administrative management and improve digital literacy in schools. The main focus of the activity is training on the use of Google Workspace as an integrated knowledge management system to improve work efficiency and collaboration among staff. Problems faced by schools include the continued use of manual administrative systems and a low understanding of how to use digital platforms. The training was conducted as a workshop with a learning-by-doing approach, allowing participants to learn directly and contextually. The training material covered the operation of various Google Workspace features, such as Google Forms, Sheets, Calendar, Docs, Drive, and Meet. This activity was designed so that participants not only understand the function of each application but also are able to integrate them into daily administrative activities. The training evaluation was conducted through pre- and post-tests, which showed a significant increase in participants' technical understanding. In addition to improving digital competency, this training also encouraged a shift in work culture towards a more collaborative, efficient, and data-driven one. The program's success demonstrates that digital transformation in educational environments can be achieved through an educational, participatory approach tailored to local needs. With positive results, this activity has the potential to be replicated in other educational institutions as a sustainable strategy for cloud-based administrative management. This training is proof that adopting digital technology in schools can strengthen administrative governance comprehensively and sustainably.

Fatigue is a critical issue in labour-intensive small industries, especially in traditional food production such as tofu manufacturing. This study aims to develop a fatigue classification model using a decision tree algorithm by integrating subjective assessments of the work system through the Macroergonomic Organizational Questionnaire Survey (MOQS) and objective physiological indicators, specifically Cardiovascular Load (CVL). The research was conducted in a tofu home industry located in Kalisari Village, Banyumas, Indonesia. Primary data were collected from 10 workers through MOQS questionnaires and heart rate measurements taken at rest and during work. CVL values were calculated and used as labels for classification into three categories: low, moderate, and high fatigue. Meanwhile, MOQS dimension scores (organization, job, personal, environment, and technology) were transformed into interval data and used as classification features. A decision tree model was built using the CART algorithm and visualized for interpretability. The results show that all workers experienced at least moderate fatigue, with 20% categorized as high fatigue. The decision tree revealed that the dimensions of organizational and personal factors were the most influential in predicting fatigue levels. The model provides a practical and interpretable tool to support decision-making in scheduling, workload balancing, and ergonomic interventions. This study demonstrates a novel approach to combining macroergonomic assessments and physiological data with machine learning for practical fatigue risk management in small-scale food production environments.

The Faculty of Mathematics and Natural Sciences (FMIPA) of the University of East Kalimantan (Unikaltar) consistently conducts satisfaction surveys to improve the quality of services provided to students. This survey aims to evaluate the performance of each work unit, including lecturers, with the hope that the results obtained can identify aspects that are still hampering or suboptimal. The survey results serve as the basis for formulating steps to improve and enhance the quality of educational services within the faculty. This study specifically highlights the level of student satisfaction with the performance of lecturers in the Islamic Religious Education course. The survey implementation process includes several stages, starting from data collection using a survey instrument, the data input process, and testing the validity and reliability of the instrument to ensure data reliability. Next, the collected data is processed and analyzed to obtain an objective picture of student perceptions. Based on the analysis, the student satisfaction index value obtained is 3.16. This figure is in the "Good" or "Satisfied" category, indicating that students are generally satisfied with the service and learning process carried out by lecturers in the course. These findings provide important input for the institution in maintaining and improving the quality of learning, particularly in the field of religious studies. In the future, it is hoped that similar surveys can continue to be carried out periodically so that the service improvement process can run continuously.