Abstract:The purpose of this quantitative research is to analyze the extent to which motivation and discipline influence the performance of PT. Jayatama Selaras Extrusion Blow employees. The data collection method applies a questionnaire…
ionnaire distributed to respondents. Researchers in this research use quantitative analysis such as validity and reliability tests, classical assumption tests, multiple linear regression analysis, hypothesis testing, and determination coefficient tests. All of these analyses were conducted using SPSS version 25. This study involved all PT. Jayatama Selaras Extrusion Blow employees, totaling 50 respondents. The saturated sample method was used to determine the sample. The results showed that with a regression coefficient of 2.145 ≥ 1.677, motivation partially has a significant effect on employee performance. With a regression coefficient of 12.914 ≥ 1.677 discipline partially has a significant effect on employee performance. It is shown that simultaneously motivation and discipline have a significant effect on employee performance, F count 256.961 ≥ F table 3.195, and the significance value of each variable ≤ 0.05. The coefficient of determination test proves that motivation and discipline influence employee performance by 95.7%, while 4.3% are factors that are not involved in this research.
Abstract:This research aims to examine both partially and simultaneously the influence of Organizational Climate and Job Stress on Turnover Intention at CV. HD Citarasa of South Tangerang. The research method used is descriptive…
quantitative which is verification in nature. The respondents used were all employees CV. HD Citarasa South Tangerang has 56 employees. The data analysis techniques used include validity instrument analysis, reliability instrument analysis, and hypothesis testing both partially and simultaneously using the Statistical Package for Social Science (SPSS) for Windows version 26 program. The partial research results show that Organizational Climate has a positive influence on Turnover Intention obtained tcount (3.288) > ttable (1.674). Then, Job Stress has a positive influence on Turnover Intention, the value obtained is tcount (5.070) > ttable (1.674). As for the simultaneous results, it shows that Organizational Climate and Work Stress have a positive influence on Turnover Intention with the hypothesis results (simultaneously) obtaining a value of fcount (16.512) > ftable (3.172).
Abstract:This research aims to analyze and evaluate the criminal liability imposed on tourists who damage the Uma Lengge Maria cultural heritage in Maria Village, Wawo District, Bima Regency. Bima is an area that has cultural and…
tourism diversity. One of the cultural and tourism diversity is the Uma Lengge Maria Cultural Reserve which is located in Maria Village, Wawo District, Bima Regency. Uma Lengge is a traditional house of the Bima people which has existed for a long time and must be maintained in its existence and beauty so that it remains intact and its beauty can be enjoyed for the future. This research use desciptive qualitative approach. A descriptive approach is an approach that aims to systematically describe the facts and characteristics of a particular population or in a particular field factually and carefully. Data collection methods were carried out by observation, interviews and documentation. The data analysis method is carried out in the stages of data collection, data reduction, data presentation, and drawing conclusions. The results of the research show that legal action is taken against criminal liability for tourists who damage the cultural heritage at Uma Lengge Maria. Uma Lengge in the Maria Village Tourist Area, there are 13 uma lengge and 103 jompa. The existence of uma lengge must be maintained so that its existence remains well into the future. there are sanctions and criminal liability for tourists who damage the Uma Lengge Maria cultural heritage in Wawo District, Bima Regency, West Nusa Tenggara.
Abstract:This study aims to determine the effect of intrapreneurship and organization on the financial performance of MSMEs (Micro, Small And Medium) in Denpasar City. This study uses a qualitative method. The MSME population in…
Denpasar City reached 32,476 MSMEs and the sample used was 100 MSMEs in Denpasar city. This study uses data collection techniques by distributing questionnaires. Validity and reliability tests were carried out on respondents who owned MSMEs in Denpasar City. The results of the t test can be obtained t-count of the Intrapreneurship variable of 1.231 with a significance value of 0.221. This significance value is greater than the significance limit value, which is equal to 0.05. Means that Intrapreneurship has a positive and insignificant effect on Financial Performance. The results of the t test can be obtained by the t-count value of the Organizational variable of 5.052 with a significance value of 0.000. This significance value is smaller than the significance limit value, which is equal to 0.05. Means the organization has a positive and significant effect on financial performance. Based on the results of the F test, the F value is 20.324 with a significance level of 0.000, so simultaneously the Intrapreneurship and Organization variables have a significant effect on the Financial Performance variable. As well as from the test results of the coefficient of determination, the R Square value shows a value of 0.295 or 29.5% indicating that the ability of the independent variable to explain the effect on the dependent variable and the remaining 70.5% can be explained by other variables outside of the research variable.
Abstract:In the era now, the rapid development of technology makes people use the internet. E-commerce players use the internet as a digital marketing medium. One of the e-commerce that developed at that time was Bukalapak. This…
study aims to determine the effect of trust and ease of use of applications on purchasing decisions on the Bukalapak site in East Lombok. The method used in this research is associative method and the type of data used is quantitative data. The population of this study were all people who used the Bukalapak application in East Lombok. Determination of the sample using Non-Probability Sampling with a total of 75 respondents. The data analysis method uses validity test, reliability test, classical assumption test, hypothesis testing and multiple linear regression. The results of this study indicate that the trust variable has a positive and significant influence on purchasing decisions The Ease-of-Use variable has a positive and significant influence on purchasing decisions.
Abstract:This article discusses issues related to the existence of artificial intelligence as a legal subject, and criminal liability when artificial intelligence commits criminal acts. The purpose of this study is to find out the…
e categorization of artificial intelligence as a legal object or legal subject, and to find out to whom criminal responsibility is assigned when artificial intelligence commits a crime. The research method used in writing this article is normative legal research, with a conceptual approach. The results of this study are that artificial intelligence is not a legal subject, because the actions carried out by artificial intelligence are only orders from its users, and for criminal acts committed by artificial intelligence, those who must be responsible are the creators of artificial intelligence or users of artificial intelligence
Abstract:Abstract : Service quality reflects how well visitors' expectations are fulfilled based on their actual experiences. The Dinas Perpustakaan dan Kearsipan Kabupaten Asahan has made efforts to provide good services, but observations…
servations reveal some dissatisfaction. Visitors expressed concerns over the incomplete book collection, inadequate handling of complaints, and inaccurate services. To address these issues, the Service Quality approach was employed to evaluate the gap between visitors’ perceptions of the services they received and their expectations. The SERVQUAL method was used to analyze five service dimensions: Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The results showed negative gaps in Empathy (-0.4), Reliability (-0.3), and Assurance (-0.2), which indicate areas for improvement. Conversely, Tangibles and Responsiveness had positive gaps, showing visitor satisfaction with these aspects. These findings provide valuable insights for the library to identify areas that require improvement in order to enhance service quality in the future.
Keywords: mysql; php; service quality; service satisfaction level
Abstrak : Kualitas layanan mencerminkan seberapa baik harapan pengunjung terpenuhi berdasarkan pengalaman nyata mereka. Dinas Perpustakaan dan Kearsipan Kabupaten Asahan telah berusaha memberikan layanan yang baik, namun observasi menunjukkan adanya beberapa keluhan. Pengunjung merasa tidak puas dengan koleksi buku yang tidak lengkap, penanganan keluhan yang kurang optimal, dan pelayanan yang kurang tepat. Untuk mengatasi masalah ini, digunakan pendekatan Service Quality yang mengevaluasi gap antara persepsi pengunjung terhadap layanan yang diterima dengan harapan mereka. Metode SERVQUAL digunakan untuk menganalisis lima dimensi layanan: Bukti Fisik, Kehandalan, Daya Tanggap, Jaminan, dan Empati. Hasil pengujian menunjukkan adanya gap negatif pada dimensi Empati (-0,4), Kehandalan (-0,3), dan Jaminan (-0,2), yang memerlukan peningkatan. Sebaliknya, dimensi Bukti Fisik dan Daya Tanggap menunjukkan gap positif, menandakan pengunjung merasa puas dengan aspek-aspek ini. Hasil ini memberikan wawasan penting bagi pihak perpustakaan dalam mengidentifikasi area yang perlu diperbaiki untuk meningkatkan kualitas layanan ke depan.
Kata Kunci : mysql; php; service quality; tingkat kepuasan layanan
Abstract:Abstract: Existing IoT anomaly detection studies have achieved high classification performance, but most focus on accuracy and F1-score without explicitly controlling the false positive rate (FPR). In addition, many approaches…
oaches rely on a single detection perspective, limiting their operational reliability. To address this gap, this study proposes a hybrid anomaly detection framework integrating Long Short-Term Memory (LSTM), Shannon entropy, and autoencoder reconstruction error. Shannon entropy is incorporated as an additional feature, while LSTM and the autoencoder capture temporal and reconstruction characteristics. The resulting hybrid representation is processed by a constraint-based threshold selection mechanism that enforces FPR . Experiments on the TON-IoT and Edge-IIoTset datasets achieved average F1-scores of 0.9250 and 0.9934, while maintaining average FPR values of 0.0091 and 0.0714, respectively. Analysis of entropy distributions showed consistent differences between normal and anomalous traffic across both datasets, indicating that Shannon entropy provides discriminative information for anomaly detection. These results demonstrate strong detection performance with controlled false alarms, while ablation studies confirm the significant contribution of Shannon entropy to overall model performance.
Keywords: false positive rate; hybrid deep learning; Internet of Things; network anomaly detection; Shannon entropy
Abstrak: Penelitian deteksi anomali Internet of Things (IoT) telah menunjukkan performa klasifikasi yang tinggi, namun sebagian besar masih berfokus pada accuracy dan F1-score tanpa mengendalikan false positive rate (FPR) secara eksplisit. Selain itu, banyak pendekatan hanya memanfaatkan satu perspektif deteksi sehingga reliabilitas operasionalnya masih terbatas. Untuk mengatasi kesenjangan tersebut, penelitian ini mengusulkan kerangka deteksi anomali hybrid yang mengintegrasikan Long Short-Term Memory (LSTM), Shannon entropy, dan autoencoder reconstruction error. Shannon entropy digunakan sebagai fitur tambahan, sedangkan LSTM dan autoencoder menangkap karakteristik temporal dan deviasi rekonstruksi. Representasi hybrid yang dihasilkan kemudian diproses melalui mekanisme constraint-based threshold selection dengan batas FPR . Hasil pengujian pada dataset TON-IoT dan Edge-IIoTset menghasilkan F1-score rata-rata sebesar 0,9250 dan 0,9934, dengan FPR rata-rata sebesar 0,0091 dan 0,0714. Perbedaan nilai entropy yang konsisten antara trafik normal dan anomali pada kedua dataset menunjukkan bahwa Shannon entropy menyediakan informasi diskriminatif untuk deteksi anomali. Hasil tersebut menunjukkan performa deteksi yang kuat dengan false alarm yang terkendali, sementara studi ablasi mengonfirmasi kontribusi signifikan Shannon entropy terhadap performa model.
Kata kunci: deteksi anomali jaringan; false positive rate; hybrid deep learning; Internet of Things; Shannon entropy
Abstract:Abstract: Anomalous sound detection is essential for industrial predictive maintenance, as machine failures often originate from subtle acoustic changes during operation. However, high background noise and limitations of…
conventional Convolutional Neural Networks (CNN) reduce detection reliability. This study proposes a 1D-CNN-based anomaly detection framework with multi-view feature fusion and temporal segmentation to enhance detection performance. The approach combines MFCC, Log-Mel Spectrogram, and Chroma STFT features, while temporal segmentation divides audio signals into 5-second segments to better capture transient anomalies. Experiments on the MIMII dataset under varying Signal-to-Noise Ratio (SNR) conditions show that MFCC and Log-Mel fusion achieves the best performance, with 97.90% accuracy and ROC-AUC of 0.9789. The model maintains accuracy above 90% at −6 dB, demonstrating strong robustness in noisy industrial environments.
Keywords: industrial anomaly detection; 1D-CNN; multi-view feature fusion; temporal segmentation; MIMII dataset.
Abstrak: Deteksi anomali suara merupakan komponen penting dalam sistem pemeliharaan prediktif industri, karena kegagalan mesin sering diawali oleh perubahan akustik yang bersifat halus selama proses operasi. Namun, tingkat kebisingan yang tinggi serta keterbatasan arsitektur Convolutional Neural Network (CNN) konvensional dapat menurunkan keandalan deteksi. Penelitian ini bertujuan mengusulkan kerangka deteksi anomali berbasis 1D-CNN yang mengintegrasikan strategi fusi fitur multi-view dan segmentasi temporal untuk meningkatkan kinerja deteksi. Pendekatan yang digunakan menggabungkan fitur MFCC, Log-Mel Spectrogram dan Chroma STFT, sementara teknik temporal splitting membagi sinyal audio menjadi segmen berdurasi 5 detik untuk menangkap anomali yang bersifat sementara. Eksperimen menggunakan dataset MIMII pada berbagai kondisi Signal-to-Noise Ratio (SNR) menunjukkan bahwa kombinasi MFCC dan Log-Mel Spectrogram menghasilkan kinerja terbaik dengan akurasi 97,90% dan ROC-AUC sebesar 0,9789. Model juga mempertahankan akurasi di atas 90% pada kondisi kebisingan ekstrem (−6 dB) yang menunjukkan ketahanan yang baik dalam lingkungan industri yang bising.
Kata kunci: deteksi anomali industri; 1D-CNN; fusi fitur multi-view; segmentasi temporal; dataset MIMII
Abstract:Abstract: Human metapneumovirus (HMPV) poses a global health threat, but its detection remains challenging due to limited environmental monitoring. This study aims to develop a portable diagnostic tool for rapid HMPV detection…
ection by integrating cutting-edge biotechnology (CRISPR-Cas system and immunoassay) with air quality sensors on an Internet of Things (IoT)-based microfluidic platform controlled by an ESP32 microcontroller. The system is supported by a companion application and data analysis using Vertex AI, and is capable of providing results in less than fifteen minutes. The development results demonstrate the potential for improving detection accuracy and reliability, particularly with further development of virus-specific biosensors, sensor optimization, and algorithms. This technology is effective as a complementary tool for early screening and environment-based risk management in areas with limited laboratory facilities, although it does not completely replace molecular diagnostic methods such as PCR. A rapid diagnostic approach based on environmental sensors, IoT, and artificial intelligence is a promising strategy to improve early HMPV detection, accelerate public health responses, and strengthen respiratory infection prevention through integrated environmental monitoring and education functions.
Keywords: air quality; CRISPR-Cas; Human Metapneumovirus (HMPV); Internet of Things, portable diagnostic; public health; rapid detection; sensors.
Abstrak: Human metapneumovirus (HMPV) merupakan ancaman bagi kesehatan global, namun pendeteksiannya masih sulit akibat keterbatasan pemantauan lingkungan. Studi ini bertujuan mengembangkan alat diagnostik portabel untuk deteksi cepat HMPV melalui integrasi bioteknologi mutakhir (sistem CRISPR-Cas dan immunoassay) dengan sensor kualitas udara pada platform mikrofluida berbasis Internet of Things (IoT) yang dikendalikan mikrokontroler ESP32. Sistem ini didukung aplikasi pendamping dan analisis data menggunakan Vertex AI, serta mampu memberikan hasil dalam waktu kurang dari lima belas menit. Hasil pengembangan menunjukkan potensi peningkatan akurasi dan keandalan deteksi, terutama dengan pengembangan lanjutan berupa biosensor spesifik virus, optimalisasi sensor, dan algoritma. Teknologi ini efektif sebagai alat pelengkap untuk skrining awal dan manajemen risiko berbasis lingkungan di wilayah dengan keterbatasan fasilitas laboratorium, meskipun tidak sepenuhnya menggantikan metode diagnostik molekuler seperti PCR. Pendekatan diagnostik cepat berbasis sensor lingkungan, IoT, dan kecerdasan buatan menjadi strategi menjanjikan untuk meningkatkan deteksi dini HMPV, mempercepat respons kesehatan masyarakat, serta memperkuat pencegahan infeksi saluran pernapasan melalui fungsi pemantauan dan edukasi lingkungan yang terintegrasi.
Kata kunci: CRISPR-Cas; diagnostik portabel; deteksi cepat; Human Metapneumovirus (HMPV); kesehatan masyarakat; IoT (Internet of Things); sensor kualitas udara.