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SISTEM INFORMASI MANAJEMEN PENGKLASIFIKASIAN HADIST SHAHIH BUKHARI DAN MUSLIM MENGGUNAKAN ALGORITMA NEURAL NETWORK Rasenda, Rasenda; Rini, Nova; Supriatiningsih, Supriatiningsih
Proceeding National Conference Business, Management, and Accounting (NCBMA) 7th National Conference Business, Management, and Accounting
Publisher : Faculty of Economics and Business Universitas Pelita Harapan

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In the book of Bukhari and Muslim hadith there are 7008 hadith sentences, of the 7008 sentences the Hadith is not yet known a hadith included in the category of prohibitions or orders. By doing the classification, it will be easier for readers to understand the hadith. The classification of hadiths is done in several stages, including: pre-processing text, the use of word vector features, and modeling of neural network architecture with multilayer perceptron. The use of layers in neural networks and feature extraction with word vectors has proven to provide good results for the classification of hadiths. The results showed a fairly high degree of accuracy that is equal to 97.72% by using two layers and 256 neurons, this research can be used to classify hadiths which have the impact of making it easier for people to understand hadiths very well.

OPTIMIZING HADITH CLASSIFICATION WITH NEURAL NETWORKS: A STUDY ON BUKHARI AND MUSLIM TEXTS Rasenda, Rasenda; Fabrianto, Luky; Faizah, Novianti Madhona
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8732

The Bukhari and Muslim hadith collections encompass a total of 7008 hadith sentences, but it is not immediately clear which of these hadiths fall into the categories of prohibitions or orders. To enhance understanding and accessibility for readers, this study focuses on classifying these hadiths through a systematic process. The classification involves several key stages: Text Pre-processing, pre-processing the raw text data to clean and normalize (Stemming, Stopword Removal and Tokenization), Word vector features are extracted to capture the semantic relationships and contextual meanings of the words, then processed into a neural network model based on a multilayer perceptron (MLP) architecture (Model Architecture, Training and Optimization). The approach leverages the strength of neural networks, particularly through the use of multiple layers and feature extraction via word vectors, which significantly contributes to the accuracy of the classification process. The results of the study is very good, with a high accuracy rate of 97.72% achieved by employing a model with two layers and 256 neurons

Pengaruh Kompensasi Dan Lingkungan Kerja Terhadap Kinerja Karyawan Dengan Kepuasan Kerja Sebagai Variabel Intervening Di Kantor Pusat Radio Republik Indonesia (RRI Jakarta Putera, Adhitya Ibanda; Rasenda, Rasenda; Wiyana, Hari; Asih, Afifah Tri
Jurnal Ekonomi, Manajemen dan Akuntansi (JEKMA) Vol. 3 No. 1 (2024): Jurnal JEKMA, April 2024
Publisher : Yayasan Bina Internusa Mabarindo

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In the era of globalization and rapid technological advancement, human resources (HR) have become a key factor in a company's success. This study focuses on the impact of compensation and work environment on employee performance, with job satisfaction as an intervening variable at Radio Republik Indonesia (RRI) Jakarta, a public broadcasting institution that must adapt quickly to remain relevant and competitive. The study employs Structural Equation Modeling (SEM) with Partial Least Squares (PLS) to analyze data from 150 respondents. The findings reveal that: (1) Compensation has a positive and significant effect on employee performance. (2) Work environment does not have a significant impact on employee performance. (3) Compensation has a positive and significant effect on job satisfaction. (4) Work environment also has a positive and significant effect on job satisfaction. (5) Job satisfaction has a positive and significant effect on employee performance. (6) Job satisfaction acts as a mediator between compensation and employee performance. (7) Job satisfaction also mediates the relationship between work environment and employee performance. These findings emphasize that while both compensation and work environment positively influence job satisfaction, only compensation has a direct and significant impact on employee performance. Job satisfaction plays a crucial mediating role in this relationship. The study suggests evaluating and adjusting compensation schemes and improving the work environment to optimize employee performance at RRI Jakarta.

SISTEM INFORMASI MANAJEMEN PENGKLASIFIKASIAN HADIST SHAHIH BUKHARI DAN MUSLIM MENGGUNAKAN ALGORITMA NEURAL NETWORK Rasenda, Rasenda; Rini, Nova; Supriatiningsih, Supriatiningsih
Proceeding National Conference Business, Management, and Accounting (NCBMA) 7th National Conference Business, Management, and Accounting
Publisher : Faculty of Economics and Business Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar

In the book of Bukhari and Muslim hadith there are 7008 hadith sentences, of the 7008 sentences the Hadith is not yet known a hadith included in the category of prohibitions or orders. By doing the classification, it will be easier for readers to understand the hadith. The classification of hadiths is done in several stages, including: pre-processing text, the use of word vector features, and modeling of neural network architecture with multilayer perceptron. The use of layers in neural networks and feature extraction with word vectors has proven to provide good results for the classification of hadiths. The results showed a fairly high degree of accuracy that is equal to 97.72% by using two layers and 256 neurons, this research can be used to classify hadiths which have the impact of making it easier for people to understand hadiths very well.

Meningkatkan Kesadaran Peduli Lingkungan Melalui Kegiatan Daur Ulang Sampah Anorganik di Rumah Literasi Ranggi Diba, Adinda Farah; Hani, Nadia; Darmayana, Zahra; Hairani, Zahra; Rasenda, Rasenda; Sarina, Desi; Suryani, Ruthpani; Yusnadi, Yusnadi; Subaedah, Sitti
Indo-MathEdu Intellectuals Journal Vol. 6 No. 2 (2025): Indo-MathEdu Intellectuals Journal (In-Press)
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v6i2.2932

This study aims to increase environmental awareness through education on cleanliness and recycling at the Ranggi Literacy House located in the PWI Housing Complex Block A59, Jalan PWI, Sampali Village, Percut Sei Tuan District, Deli Serdang Regency, North Sumatra 20371. The method used in this research is action research with a qualitative approach. The research subjects were 15 children at Ranggi Literacy House, ranging in age from 6 to 12 years old. The research was conducted in several stages, namely planning, action implementation, observation and reflection. Data were collected through direct observation, interviews, documentation of activities, and a simple questionnaire regarding participants' understanding before and after the activity. Furthermore, the data was analysed descriptively qualitatively to see the extent to which this activity can increase environmental awareness among participants. The results of the study showed that after participating in the education, there was an increase in children's understanding of the importance of disposing of waste in its place and skills in recycling waste into more useful items. With the sustainability of this program, it is hoped that environmental awareness can increase and create a culture of caring for the environment among children and the surrounding community.

Meningkatkan Kesadaran Peduli Lingkungan Melalui Kegiatan Daur Ulang Sampah Anorganik di Rumah Literasi Ranggi Diba, Adinda Farah; Hani, Nadia; Darmayana, Zahra; Hairani, Zahra; Rasenda, Rasenda; Sarina, Desi; Suryani, Ruthpani; Yusnadi, Yusnadi; Subaedah, Sitti
Indo-MathEdu Intellectuals Journal Vol. 6 No. 2 (2025): Indo-MathEdu Intellectuals Journal
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/imeij.v6i2.2932

This study aims to increase environmental awareness through education on cleanliness and recycling at the Ranggi Literacy House located in the PWI Housing Complex Block A59, Jalan PWI, Sampali Village, Percut Sei Tuan District, Deli Serdang Regency, North Sumatra 20371. The method used in this research is action research with a qualitative approach. The research subjects were 15 children at Ranggi Literacy House, ranging in age from 6 to 12 years old. The research was conducted in several stages, namely planning, action implementation, observation and reflection. Data were collected through direct observation, interviews, documentation of activities, and a simple questionnaire regarding participants' understanding before and after the activity. Furthermore, the data was analysed descriptively qualitatively to see the extent to which this activity can increase environmental awareness among participants. The results of the study showed that after participating in the education, there was an increase in children's understanding of the importance of disposing of waste in its place and skills in recycling waste into more useful items. With the sustainability of this program, it is hoped that environmental awareness can increase and create a culture of caring for the environment among children and the surrounding community.

Attention-based convolutional neural networks for interpretable classification of maritime equipment fabrianto, luky; Prihandayani, Tiwuk Wahyuli; Rasenda, Rasenda; Faizah, Novianti Madhona
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.426

This study introduces a Convolutional Neural Network with an Attention Mechanism (CNN+AM), utilizing the Squeeze-and-Excitation (SE) block, to classify critical ship components: generators, engines, and oil-water separators (OWS). The SE block enhances the model's ability to focus on discriminative features, thereby improving classification performance. To overcome the limitation of the original dataset, which contained only 199 images, extensive data augmentation techniques were applied, expanding the dataset to 2,648 images. The augmented dataset was divided into training (70%), validation (15%), and testing (15%) sets to ensure reliable evaluation. Experimental results show that the CNN-AM achieved an accuracy of 72.39%, surpassing the baseline CNN model with 68.16%. These findings confirm that the attention mechanism significantly improves generalization and the ability to differentiate visually similar classes. Furthermore, the integration of interpretability tools, such as Gradient-weighted Class Activation Mapping (Grad-CAM), provides visual explanations of model predictions, increasing trust and reliability for safety-critical maritime applications. The proposed approach demonstrates strong potential for real-time ship component monitoring, offering meaningful contributions to predictive maintenance and operational safety within the maritime industry.

Reconfigurable Metasurface Panels for Active Electromagnetic Shielding of Protective Domes Sihotang, Hengki Tamando; Dermawan, Budi Arif; Rasenda, Rasenda; Rizky A, Galih Prakoso
Cebong Journal Vol. 4 No. 3 (2025): July: Green dan Blue Economy
Publisher : IHSA Institute

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The increasing complexity of electromagnetic (EM) environments in defense and communication systems necessitates shielding solutions that are both adaptive and efficient. Conventional static shielding domes, while effective in blocking electromagnetic interference (EMI), are inherently limited by their fixed frequency response, high structural weight, and lack of real-time adaptability. This research investigates the design and performance of reconfigurable metasurface panels for active electromagnetic shielding of protective domes, with the aim of enhancing shielding effectiveness, tunability, and structural efficiency. The study explores the integration of reconfigurable metasurfaces into dome architectures, enabling dynamic control of electromagnetic wave propagation through electronically tunable elements. Performance metrics including shielding effectiveness (in dB), tunable frequency ranges, angular stability, and real-time adaptability were evaluated and benchmarked against conventional static shielding designs. Results indicate that reconfigurable metasurface domes achieve superior shielding performance across wide frequency bands while offering significant weight reduction and improved adaptability. These characteristics make them well-suited for critical applications such as military radomes, satellite communication shelters, aerospace systems, and secure civilian infrastructures. However, challenges remain regarding large-scale fabrication, integration complexity, power requirements for active tuning, and environmental durability. Despite these limitations, the findings highlight the transformative potential of reconfigurable metasurfaces as the foundation of next-generation adaptive shielding technologies. This research demonstrates that reconfigurable shielding domes not only address the shortcomings of static designs but also pave the way for resilient, flexible, and future-proof electromagnetic protection systems.

A bayesian dynamic latent state model for predicting infant sleep-wake patterns under daily massage intervention A , Galih Prakoso Rizky; Rasenda, Rasenda; Dermawan, Budi Arif; Arifuddin, Nurul Afifah; Alrasyid , Wildan
International Journal of Basic and Applied Science Vol. 14 No. 1 (2025): Computer Science, Engineering, Basic and Applied mathematics Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i1.699

Sleep disturbances in infants present a persistent challenge for caregivers and healthcare providers. This study proposes a Bayesian Dynamic Latent State Model to predict infant sleep-wake patterns in response to daily massage, a non-pharmacological intervention. The model captures latent sleep propensity as a dynamic hidden process influenced by current and previous massages, individual random effects, and autoregressive components. Observed outcomes include nocturnal sleep duration and nighttime awakenings, modeled using Gaussian and Poisson distributions respectively. Through numerical simulations and a real-world case study, the model demonstrates clear benefits: average nocturnal sleep duration increased by approximately 1.2–1.5 hours, while nighttime awakenings decreased by about 35–40% on intervention days, with residual improvements on subsequent days. Compared to traditional static and time-series models, the proposed Bayesian approach provides greater flexibility in handling uncertainty, explicitly models carry-over effects, and integrates individual heterogeneity in sleep responses contributions that have not been fully addressed in prior infant sleep studies. This research thus advances the scientific understanding of dynamic, intervention-driven sleep processes, while also offering practical implications for evidence-based pediatric nursing and personalized infant care strategies. While promising, validation is currently limited to a small dataset and simplified assumptions. Future work will involve larger-scale testing, incorporation of additional external factors, and benchmarking against alternative machine learning models.

Analisis Muatan Life Skill Dalam Program Komunitas CreSHome (Creative, Smart, and Homey Community) Jubaidah, Jubaidah; Diba, Adinda Farah; Saputri, Arum Dwi; Amenobelia, Amenobelia; Anysa, Ega; Almarind, Marisa; Syahputri, Nurlaily; Rasenda, Rasenda; Yolanda, Yolanda; Thomas, Thomas
ETHNOGRAPHY: Journal of Design, Social Sciences and Humanistic Studies Vol. 2 No. 1 (2025): ETHNOGRAPHY: Journal of Design, Social Sciences and Humanistic Studies
Publisher : Lembaga Intelektual Muda Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/ethno.v2i1.116

CreSHome is a youth community that actively develops the capacity of its members through various activities such as Legislative School, Political School, Leadership Program, visits to the North Sumatra Library, the 3rd Anniversary celebration, and Town Hall Meetings. This research focuses on four aspects of life skills, namely personal skills, social skills, academic skills, and vocational skills. The aim of this research is to analyze what life skills are contained within the CreSHome community through the programs implemented by the CreSHome community. This research employs a descriptive qualitative approach. The research subjects were selected using purposive sampling techniques with a total of 25 participants. Data collection was conducted through direct observation and in-depth interviews. Data analysis was performed descriptively on all research data. The analysis results indicate that CreSHome programs significantly contain and develop these skills. These findings provide important insights for the development of non-formal education-based communities to foster the life skills of the younger generation in a holistic manner

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