Evaluasi Kinerja Sensor Proximity Induktif sebagai Alternatif Pengganti RFID pada Prototipe Rail Guided Vehicle Berbasis Arduino

Teknologi Rail Guided Vehicle (RGV) merupakan salah satu solusi otomasi transportasi material dalam lingkungan industri yang membutuhkan sistem navigasi dan identifikasi jalur secara presisi. Umumnya, sistem ini memanfaatkan Radio Frequency Identification (RFID) sebagai media deteksi posisi. Namun, penggunaan RFID memiliki beberapa kendala antara lain interferensi sinyal pada area dekat dengan logam serta kompleksitas saat diaplikasikan pada dunia industri yang beragam. Penelitian ini bertujuan untuk mengevaluasi kinerja sensor proximity induktif sebagai alternatif pengganti RFID dalam mendeteksi posisi pada prototipe RGV berbasis mikrokontroler Arduino. Pengujian dilakukan melalui serangkaian skenario pergerakan RGV pada lintasan dengan beberapa titik deteksi. Hasil penelitian menunjukkan bahwa sensor proximity induktif memberikan performa yang stabil dan akurat dengan mencapai rata-rata error sebesar 0,22 cm, yang lebih rendah dibandingkan dengan sensor RFID yang memiliki rata-rata error sebesar 0,56 cm serta tingkat akurasi deteksi terhadap objek logam di sepanjang rel RGV mencapai 98%

MONITORING KUALITAS UDARA UNTUK MENGUKUR KONSENTRASI PARTIKEL UDARA BERBASIS INTERNET OF THINGS

Increasing air pollution has become one of the most pressing environmental issues of the modern era, with significant impacts on human health and ecosystems. This research presents an Internet of Things (IoT)-based air quality monitoring system designed to measure concentrations of PM2.5 particles, carbon monoxide (CO), and nitrogen dioxide (NO2). This system uses sophisticated sensors connected via an IoT network to collect real-time air quality data from various locations. The data obtained is then sent to a cloud platform for analysis and visualization using a web-based application. This methodology enables continuous monitoring and widespread mapping of air quality with high accuracy. The results of the tests show that this system can provide accurate and timely information on air pollution levels, which can be used to increase public awareness, optimize environmental policies, and minimize health risks. It is hoped that this research can contribute to the development of more effective and responsive air monitoring technology in the future.  Peningkatan polusi udara telah menjadi salah satu isu lingkungan paling mendesak di era modern, dengan dampak signifikan terhadap kesehatan manusia dan ekosistem. Penelitian ini menyajikan sistem pemantauan kualitas udara berbasis Internet of Things (IoT) yang dirancang untuk mengukur konsentrasi partikel PM2.5, karbon monoksida (CO), dan nitrogen dioksida (NO2). Sistem ini menggunakan yang terhubung melalui jaringan IoT untuk secara real time mengumpulkan data kualitas udara dari berbagai lokasi. Data yang diperoleh kemudian dikirimkan ke platform cloud untuk analisis dan visualisasi menggunakan Blynk. Metodologi ini memungkinkan pemantauan yang terus menerus dan pemetaan kualitas udara secara luas dengan akurasi tinggi. Hasil dari pengujian menunjukkan bahwa sistem ini dapat memberikan informasi yang akurat dan tepat waktu mengenai tingkat polusi udara, yang dapat digunakan untuk meningkatkan kesadaran publik, mengoptimalkan kebijakan lingkungan, dan meminimalkan risiko kesehatan. Penelitian ini diharapkan dapat berkontribusi pada pengembangan teknologi pemantauan udara yang lebih efektif dan responsif di masa depan

Komparasi Penerapan Adaboost Pada K-NN Dan Decision Tree Untuk Prediksi Penyakit Hati

The liver is a vital human organ that plays a crucial role in detoxification, cholesterol regulation, and various metabolic activities within the body. Impairment of liver function can lead to several diseases such as hepatitis, liver cancer, cirrhosis, and other liver-related conditions. In Indonesia, approximately 0.6% of the population is identified as having hepatitis, despite the implementation of the HB 0–4 immunization program by the Ministry of Health. Liver disease is a common public health issue, with WHO data reporting an annual death toll of 1.2 million people due to liver-related illnesses in Southeast Asia and Africa. The importance of early detection of liver disease symptoms highlights the need for a predictive system capable of accurately identifying individuals at risk. This study employs a machine learning approach using K-Nearest Neighbor (K-NN) and Decision Tree classification algorithms, enhanced by the application of the Adaboost ensemble learning technique to optimize their performance. Evaluation results show that Adaboost improves the accuracy of the K-NN algorithm to 95.77% and the accuracy of the Decision Tree to 100%. Although the improvement in K-NN is quite significant, Adaboost does not have a substantial impact on the accuracy of the Decision Tree. This research indicates that the Adaboost method is effective in enhancing the classification performance for liver disease, particularly when applied to the K-NN algorithm

SISTEM OPTIMALISASI ENERGI LISTRIK DENGAN INTERNET OF THINGS ASSISTED ARTIFICIAL INTELLEGANCE

In the current digital era, the increasing awareness of energy efficiency, coupled with high operational costs and environmental impacts, has become a primary concern. Internet of Things (IoT) and Artificial Intelligence (AI) technologies offer solutions to optimize electricity consumption through real-time data collection and advanced analytics. This study aims to explore the integration of IoT and AI in smart energy management systems to reduce costs and environmental impact. By employing machine learning algorithms, the research will predict electricity consumption and provide energy efficiency recommendations. It is anticipated that this system will enhance energy efficiency, lower operational costs, and contribute to environmental sustainability. This study is expected to make a significant contribution to the development of innovative solutions for electricity optimization based on IoT and AI.Penggunaan energi listrik yang tidak efisien dapat menyebabkan pemborosan daya dan peningkatan biaya operasional, terutama dalam skala industri dan perumahan. Untuk mengatasi permasalahan ini, dikembangkan sistem optimalisasi energi listrik berbasis Internet of Things (IoT) yang didukung oleh kecerdasan buatan (AI). Sistem ini bertujuan untuk meningkatkan efisiensi penggunaan listrik dengan cara memonitor, menganalisis, dan mengoptimalkan konsumsi daya secara real-time. IoT digunakan untuk menghubungkan perangkat listrik dengan sensor yang dapat mengukur parameter seperti tegangan, arus, daya, serta pola penggunaan energi. Data yang dikumpulkan dari sensor kemudian dikirim ke sistem berbasis cloud untuk diproses oleh algoritma AI. Dengan menggunakan teknik pembelajaran mesin (machine learning), AI dapat mengenali pola konsumsi listrik, memprediksi kebutuhan daya, serta memberikan rekomendasi atau tindakan otomatis untuk mengurangi pemborosan energi.Sistem ini juga dilengkapi dengan fitur otomatisasi, seperti pengaturan jadwal operasional perangkat listrik dan pengendalian beban berdasarkan permintaan daya aktual. Selain itu, pengguna dapat mengakses dan mengontrol sistem ini melalui aplikasi berbasis web atau seluler, sehingga memudahkan pemantauan serta pengambilan keputusan yang lebih efisien. Hasil implementasi menunjukkan bahwa penggunaan sistem ini mampu mengurangi konsumsi listrik secara signifikan tanpa mengurangi kenyamanan atau produktivitas pengguna. Dengan demikian, sistem optimalisasi energi listrik berbasis IoT assisted AI ini tidak hanya memberikan manfaat ekonomi dalam bentuk penghematan biaya listrik, tetapi juga berkontribusi terhadap keberlanjutan energi dan pengurangan jejak karbon

INFLUENCE OF AUDIT OPINION, FIRM SIZE, COMPANY GROWTH ON AUDITOR SWITCHING

This study examines non-cyclical consumer sector companies listed on the Indonesia Stock Exchange (IDX) during the period 2020–2024 to investigate the influence of audit opinions, firm size, and corporate growth on auditor switching. The independent variables consist of audit opinion, firm size, and company growth, while auditor switching serves as the dependent variable. The research relies on secondary data collected through purposive sampling, resulting in 80 companies with a total of 400 firm-year observations. Logistic regression analysis was performed using SPSS 25 to process the data. According to this study, that firm size has a negative effect on auditor switching, whereas audit opinion and company growth show no affect on auditor switching. Keywords: Audit Opinion, Firm Size and Company Growt

Rancang Bangun Alat Rewinding Motor Otomatis Berbasis Mikrokontroler

Rewinding motor adalah proses penggulungan ulang kumparan motor listrik pada stator maupun rotor untuk memperbaiki belitan yang telah rusak atau mengalami kerusakan. Proses ini penting agar motor dapat berfungsi kembali secara efisien. Penelitian ini bertujuan merancang alat rewinding otomatis berbasis mikrokontroler untuk meningkatkan efisiensi dan akurasi proses yang selama ini dilakukan secara manual dan kurang stabil. Alat ini menggunakan Arduino Uno, Sensor Proximity, dan komponen pendukung lainya. Hasil pengujian menunjukkan bahwa alat rewinding otomatis mampu menggulung kawat email ukuran 0,25 mm dan 0,40 mm dengan waktu yang jauh lebih cepat dibandingkan metode semi otomatis dan manual, seta untuk menjaga objektivitas ilmiah, tingkat kesalahan pengukuran diperkirakan berada dalam batas toleransi teknis ≤ 1%. Sistem ini juga terbukti mampu menghentikan motor secara otomatis sesuai jumlah lilitan yang diinputkan melalui keypad. Dengan demikian, alat ini mampu meningkatkan efisiensi proses produksi, menghasilkan gulungan yang lebih konsisten, dan sangat layak diterapkan dalam industri perbaikan motor listrik maupun institusi pendidikan. Penggunaan mikrokontroler dan sensor pada alat ini memberikan kontribusi nyata dalam peningkatan produktivitas dan kualitas hasil rewinding

The RANCANG BANGUN SASIS JENIS TANGGA PADA KENDARAAN LISTRIK RODA 3

Several factors that need to be considered in the manufacture of 3-wheeled electric vehicles include vehicle weight, motor selection and control system. These three aspects affect the energy consumption of electric cars. The heavier the vehicle, the greater the energy needed to move it, so that in making a car, the vehicle weight is expected to be not too heavy but also strong and sturdy. This study focuses on discussing the design and construction of the frame on a 3-wheeled electric car. The type of chassis used in 3-wheeled electric vehicles is a ladder chassis type. The research method used is simulation and experimentation of the design and tools that have been made. The material used is 25x25 mm hollow aluminum 6061 with a more efficient design that has a ground clearance of 128 mm. The final result of this study is the total weight of the chassis reaches 20 kg, while the chassis resistance is able to withstand a maximum load of 70 kg.Beberapa faktor yang perlu diperhatikan dama pembuatan kendaraan listrik roda 3 antara lain berat kendaraan, pemilihan motor, dan sistem kendali. Ketiga aspek tersebut mempengaruhi konsumsi energi mobil listrik. Semakin berat kendaraan maka semakin besar pula energi yang dibutuhkan untuk menggerakkannya, sehingga dalam pembuatan mobil diharapkan bobot kendaraan tersebut seringan mungkin namun juga kuat dan kokoh. Penelitian ini akan fokus membahas mengenai perancangan dan konstruksi kerangka pada mobil listrik roda 3 menggunakan jenis tangga.  Material yang digunakan yaitu aluminium 6061 hollow ukuran 25x25 mm dengan desain yang lebih efisien yang memiliki ground clearance 128 mm. Hasil akhir pada penelitian ini adalah berat total sasis mencapai 20 kg, sedangkan untuk ketahanan sasis yaitu mampu menahan beban maksimal sebesar 70 kg

Pengaruh Motivasi, Loyalitas dan Disiplin Kerja terhadap Kinerja Karyawan PT. Kara Santan

This study aims to analyse the effect of motivation, loyalty, and work discipline on employee performance of PT Kara Santan Pertama. This research uses a quantitative approach with data collection methods through questionnaires filled out by 53 respondents from a total of 65 permanent employees. The data analysis technique was carried out using multiple linear regression with the hypothesis of f test, t test and coefficient of determination. The results showed that motivation, loyalty, and work discipline simultaneously had a significant effect on employee performance. Partially, each independent variable also shows a significant positive effect on performance. Work discipline has the most dominant influence compared to other variables. This study concludes that increasing motivation, loyalty, and work discipline can significantly improve the performance of PT Kara Santan Pertama employees.

The Traces of Religious Education in the Poem "Sebelum Nyawa Terlepas Raga" by Hartono "John Witir"

This article examines the poem “Sebelum Nyawa Terlepas Raga” by Hartono “John Witir” as a literary work that reflects spiritual and religious values, particularly in the context of awareness of the afterlife. This poem explicitly serves as an invitation for self-reflection on worldly arrogance that has the potential to distance individuals from God, as well as a warning about the dangers of pride that can cloud one’s conscience. This study aims to elucidate the religious educational ideology contained in the poem. Using a qualitative descriptive approach, the object of study is the poem ‘“Sebelum Nyawa Terlepas Raga” itself. The analysis was conducted by applying hermeneutic theory, utilising quotations from the poem that directly represent religious educational values. The data collection process involved three stages: collection, reduction, and presentation of data. Subsequently, the data were analysed descriptively to produce an accurate and comprehensive picture of the characteristics and interconnections of the elements under study. The findings of this study indicate that the poem “Sebelum Nyawa Terlepas Raga” by Hartono “John Witir” contains dimensions of religious relationships that include interactions between humans and God, humans and their fellow humans, and humans and themselves. Of these three forms of religious relationships, the relationship between humans and God is the most dominant aspect in this poem. Keywords: Poetry “Sebelum Nyawa Terlepas Raga”, Religious Education, Hermeneutic

MOTIVATION AND SELF-CONFIDENCE AS PREDICTORS OF SPEAKING FLUENCY AND ACCURACY IN EFL CONTEXTS

Effective communication is vital for humans as social beings, especially in EFL contexts. Speaking skills such as fluency and accuracy are essential, and emotional factors like motivation and self-confidence significantly influence learners’ performance. Although these predictors are widely recognized, their relationships with speaking proficiency are interpreted differently across studies, indicating a need for further research to develop an effective instructional model. This study adopted a quantitative correlational approach to investigate the associations between motivation and self-confidence as predictor variables, and speaking fluency and accuracy as outcome variables, both individually and collectively. Data were collected from 60 respondents through questionnaires and analyzed using descriptive statistics, Pearson correlation, and linear regression. Results indicated a moderate correlation between motivation and speaking fluency (r = 0.406), and between self-confidence and fluency (r = 0.559). For speaking accuracy, motivation showed a low correlation (r = 0.324), while self-confidence had a moderate correlation (r = 0.491). Simultaneously, the predictors showed moderate correlations with fluency (R = 0.559) and accuracy (R = 0.493). The influence values were 0.313 for fluency and 0.243 for accuracy, indicating that motivation and self-confidence contributed 31.3% and 24.3% to students’ speaking fluency and accuracy, respectively