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All Journal Jurnal Simetris EKUITAS (Jurnal Ekonomi dan Keuangan) Jurnal ICT : Information Communication & Technology Journal of Applied Data Sciences Kresna: Jurnal Riset dan Pengabdian Masyarakat Journal Of World Science Jurnal Indonesia Sosial Teknologi Indonesia Auditing Research Journal Journal of Business Management and Economic Development Prosiding Amal Insani Foundation (Indonesian of Interdisciplinary Journal) Horizon: Indonesian Journal of Multidisciplinary Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi INOVTEK Polbeng - Seri Informatika Green Engineering: Journal of Engineering and Applied Science
Asro Asro
Universitas Primagraha
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Influence of Job Training and Work-Life Balance on Employee Performance with Job Satisfaction as an Intervening Variable: Case Study at the Civil Service and Human Resource Development Agency of Tangerang Regency Alfarizy, Muhamad Akbar; Prahiawan, Wawan; Imron, Ali; Bin Harun, Asro
Journal of Business Management and Economic Development Том 3 № 03 (2025): Journal of Business Management and Economic Development
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jbmed.v3i03.1955

Abstract

The aim of this research is to examine the impact of job training on employees’ performance as well as the significance of work-life balance in improving performance. In addition, it examines the association between job training plus in job satisfaction, along with how work-life balance influences satisfaction levels. The study research aims to evaluate the effect of staff contentment on work outcomes and its mediating role in integrating skills development and work-life balance with employee performance. The study employed a quantitative, descriptive methodology. This approach allows for a systematic measurement of variables and identification of patterns within the employee population. Data collection methods included observation, interviews, reviewing literature, and distributing questionnaires. The study population consisted of all employees at the BKPSDM Office in Tangerang Regency, based on data collected from 71 individuals selected using saturated sampling. Instrument validation and assessments of reliability were carried out on 30 employees outside the sample using IBM SPSS Statistics with Spearman rank correlation. Structural Equation Modelling (SEM) in SmartPLS 4.0 was utilized for data analysis. The analysis reveals that both job training and work-life balance contribute positively and meaningfully to employee performance. They additionally have a beneficial effect on job satisfaction, which subsequently enhances performance and mediates the influence of training Along with professional-personal equilibrium affecting employee results.
Analisis Literatur Review Perencanaan Strategi Sistem Informasi Menggunakan Metode Metode Five Competitive Force Pada CV. Bio Chitosan Indonesia Susan Juli Safitri; Gelar Alam Ramdhaniawan; Asro Asro; Novi Rukhviyanti
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 4 (2024): November: Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i4.263

Abstract

The rapid development of science and technology, in line with the progress of time, has led to the increased use of personal computers, playing a crucial role in assisting human tasks. Additionally, the use of technology in work processes helps to improve speed and accuracy compared to not using technology. Today, Systems Information and Technology (SI/IT) are not only needed as tools to support an organization's operational activities but also as an essential aspect of business strategy to achieve organizational goals. Computer-based information systems have now become a primary necessity for fulfilling information needs. Many sectors have utilized computer information systems as a means to simplify tasks. Therefore, this journal will discuss "Information System Strategy Planning using the Five Competitive Forces."
Comparative Evaluation of Preprocessing Techniques in Twitter Sentiment Analysis for Indonesia’s 2024 Regional Elections Asro; Solihin
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/tt65bb54

Abstract

The rapid expansion of social media has positioned Twitter as a critical platform for capturing public opinion during political events, including Indonesia’s 2024 Regional Elections. This study investigates the impact of preprocessing strategies and class balancing on the performance of sentiment analysis models applied to election-related tweets. An initial dataset of 9,096 tweets was collected and refined into 6,202 relevant entries from 2024–2025 through text cleaning, normalization, tokenization, and duplicate removal. Sentiment distribution analysis reveals a dominance of positive sentiment (58.4%), followed by negative (33.6%) and neutral (8.0%) expressions. Two classical machine learning classifiers—Naïve Bayes and Logistic Regression—were implemented using TF–IDF feature representation. To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied exclusively to the training data, and hyperparameter optimization was conducted using GridSearchCV. Model evaluation employed an 80/20 train–test split with accuracy, precision, recall, F1-score, and confusion matrices as performance metrics. Experimental results indicate that logistic regression combined with SMOTE and hyperparameter tuning achieved the highest accuracy of 93.08%, outperforming Naive Bayes. The findings confirm that carefully designed preprocessing pipelines and class balancing significantly enhance the reliability of sentiment classification in political social media analysis.
Analisis Sentimen tentang Transformasi Program Makan Siang menjadi Makan Bergizi Gratis menggunakan Logistik Regression pada laman Youtube Asro, Asro; Sudaryono, Sudaryono
Jurnal ICT: Information Communication & Technology Vol. 24 No. 1 (2024): JICT-IKMI, Juli, 2024
Publisher : LPPM STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v24i1.257

Abstract

Abstract- This study delves into sentiment analysis concerning the transformation from a simple free lunch program to a nutritious free lunch initiative, based on user comments on YouTube. Employing logistic regression analysis with varied test sizes of 10%, 20%, and 30%, the data was rigorously examined to discern public opinion. Initial data collection through crawling from May to July 2024 yielded 5,390 comments, reflecting a significant engagement primarily in June. Post-processing categorized the sentiments as 1,682 negative, 634 neutral, and 958 positives. The classification accuracy varied: 85.32% (10% test size), 82.90% (20% test size), and 81.41% (30% test size), indicating the logistic regression model's effectiveness despite increasing data volume. This research underscores the utility of sentiment analysis in evaluating public reception and potential areas for improvement in governmental nutrition programs.
Public Sentiment Analysis on the 2024 Presidential Election Using Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) On Social Media Data Asro, Asro; Azizah, Nur; Sudaryono
Prosiding Amal Insani Foundation Vol. 1 (2024): PROSIDING INTERNASIONAL
Publisher : Amal Insani Foundation

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

Abstract

This study aims to evaluate the effectiveness of the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) in analyzing public sentiment from YouTube comments related to the 2024 Indonesian Presidential Election. A total of 1,800 comments, collected from November 2023 to March 2024, were analyzed to test these models. The results show that SVM, with the highest accuracy of 76.33% and precision and F1-Score of 75.29% and 72.67% on the 10% test data, outperformed NBC, which recorded a highest accuracy of 72.19% under similar conditions. These findings highlight the importance of using more sophisticated methods in sentiment analysis to understand the complex and diverse dynamics of public opinion. This study provides valuable insights for stakeholders in developing effective communication strategies and offers a foundation for advancing sentiment analysis methodologies in political contexts.
Strategi Pengembangan Bisnis Laundry Berbasis Online Asro; Istiharoh, Iis
Prosiding Amal Insani Foundation Vol. 2 (2023): PROSIDING NASIONAL
Publisher : Amal Insani Foundation

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

Abstract

In the modern digital era, technology and social media are crucial in supporting businesses, including the laundry business. This business falls under the category of Micro, Small, and Medium Enterprises (MSMEs) that operate in the service sector. Xilaundry, located in Serang Regency, Banten Province, exemplifies how MSMEs utilize technology in their operations. Xilaundry uses social media platforms such as WhatsApp, Instagram, and Facebook for marketing and promotional strategies. Two payment methods are available for customers: conventional (pay on the spot) and digital (ATM, mobile banking, OVO, and Gopay). Xilaundry implements a SWOT analysis for its business strategy development. The results show that Xilaundry's business is feasible to run. Xilaundry's finances record a monthly turnover of IDR 6,570,800 and a cash expenditure of IDR 2,890,000. This generates a net profit of around IDR 2,743,800 per month. Thus, Xilaundry can generate a net income of approximately IDR 34,680,000 in a year. In the SWOT and social media context, Xilaundry can leverage its strength in using social media for marketing and promotion (strength). However, they must maintain service quality to avoid weaknesses in service (weakness). The opportunity that Xilaundry can take is the increase in social media and digital payment users (opportunity), while threats can come from competitors who also use social media in their marketing strategies (threat).
Klasifikasi Kemancetan Lalu Lintas di Indonesia Menggunakan Metode Naive Bayes Classification Padri, Abdul Robi; Asro, Asro; Chairuddin, Chairuddin
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 14 No. 2 (2023): JURNAL SIMETRIS VOLUME 14 NO 2 TAHUN 2023
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v14i2.10102

Abstract

Tujuan dari penelitian ini untuk data menganalisis akurasi kemancetan menggunakan google colab  dalam mendeteksi kemacetan berdasarkan provinsi di indonesia, penulis mencoba menguji strategi dalam menangani Kemacetan wilayah indonesia, dengan memanfaatkan metode naive bayes. Pada jurnal ini menerapkan dengan google colab. Penelitian ini memakai data yang bersumber dari crawling data di twiter. Penggunaan metode naive bayes dalam mencari Rute terpendek efesien dan tidak mancet. Penerapan Angkot Sekolah online menggunakan Metode naive bayes dalam Minimalisir Biaya Perjalanan menjemput Siswa dapat mengurangi macet, mengurangi kecelakaan, mengurangi waktu keterlambatan siswa, minimalisir ongkos perjalanan. Saran yang diberikan yaitu menjadi bahan evaluasi bagi pemerintah dalam menangani Kemacetan di indonesia, secara efisien, aman dan transparan.
THE EFFECT OF WORK-LIFE BALANCE AND ORGANIZATIONAL CITIZENSHIP BEHAVIOR ON EMPLOYEE PERFORMANCE AT THE LEBAK REGENCY PERSONNEL AND HUMAN RESOURCE DEVELOPMENT AGENCY Rozi, Achmad; Nabillah Wondu, Tiara; Harun, Asro
Prosiding Amal Insani Foundation Vol. 3 (2026): PROSIDING INTERNASIONAL
Publisher : Amal Insani Foundation

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

Abstract

This study aims to analyze the influence of work-life balance and organizational citizenship behavior on employee performance at the Lebak Regency Personnel and Human Resources Development Agency (BKPSDM). The study used a quantitative approach with a population of 30 employees and saturated sampling techniques. Data were collected through questionnaires and analyzed by multiple linear regression. The results of the study show that work-life balance and organizational citizenship behavior have a positive and significant effect both partially and simultaneously on employee performance. The value of the determination coefficient (R²) of 0.610 or 61.0% indicates that the two variables are able to explain employee performance by 61.0%, while the remaining 39.0% is influenced by other factors outside of this study. Partially, organizational citizenship behavior has a more dominant influence than work-life balance in improving employee performance.
Building A Chat App Using Website-Based Cryptography Abdul Robi Padri; Asro Asro
Jurnal Indonesia Sosial Teknologi Vol. 7 No. 1 (2026): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v7i1.9169

Abstract

One of the social media that is popular today among the general public is the short message application. This research aims to develop a secure web-based chat application by applying cryptographic algorithms, especially Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA), to maintain the confidentiality of messages. The increasing use of instant messaging apps raises serious concerns regarding data privacy and information security. This research uses a system development approach that includes the design, implementation, and testing stages. AES is used for symmetric encryption of the message body, while RSA is used for secure key exchange. System testing is conducted in a local network environment that involves multiple users to evaluate the system's functionality and performance. The results show that the application is able to encrypt and decrypt messages with high accuracy, supports multi-user communication, and maintains the confidentiality of messages during transmission. In addition, performance testing shows that the encryption and decryption processes run efficiently within acceptable time limits. The conclusion of this study shows that the integration of AES and RSA algorithms in web-based chat applications is effective in improving the security of digital communications. The implication of this study is that the hybrid cryptographic approach can be practically implemented on web-based communication systems to improve user data protection, as well as potentially applied to a variety of other digital communication platforms that require a high level of security.
Development of a Digital Twin Based Smart Green Building Energy Management Model Integrating IoT Sensors and Predictive Sustainability Analytics Asro Asro; Solihin Solihin; John Chaidir; Febri Adi Prasetya; Tuti Susilawati; Muhamad Furqon; Bentar Priyopradono
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 2 (2025): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i2.287

Abstract

Introduction: The integration of Digital Twin (DT) technology and the Internet of Things (IoT) into Building Energy Management Systems (BEMS) offers a transformative approach to optimizing energy consumption in buildings. This study explores the development of a Digital Twin based BEMS prototype, which leverages real time data collection, predictive analytics, and machine learning to enhance energy efficiency, reduce costs, and support sustainability goals in modern buildings. The research also addresses key gaps in current energy management systems, including real time adaptive control and integration with smart grid platforms. Literature Review: Previous research highlights the limitations of traditional BEMS, which often rely on static control strategies and lack real time adaptability. Recent advancements, including predictive maintenance and machine learning integration, have improved energy optimization. However, challenges such as data interoperability, scalability, and cybersecurity remain. This review consolidates current approaches and identifies opportunities for enhancing BEMS through the integration of DT technology, IoT, and machine learning. Materials and Method: The methodology employed involves the design of a Digital Twin based BEMS prototype, incorporating IoT sensors for real time data collection on variables such as HVAC load, occupancy, and environmental factors. The system uses time series forecasting and adaptive control strategies to optimize energy consumption. A case study building is used for validation, with performance metrics such as energy savings, CO₂ footprint reduction, and peak load reduction assessed to evaluate the system's effectiveness. Results and Discussion: The results demonstrate a significant reduction in energy consumption (up to 50%) compared to traditional BEMS, along with improved forecasting accuracy and sustainability performance. The prototype achieved a high R² score in predicting energy usage, validated through real world application in the case study building. The economic feasibility analysis showed substantial cost savings and a strong return on investment, making the system a financially viable solution for energy efficient building management.
Co-Authors Abda Abda Abdul Robi Padri Abdul Robi Padri Agung Wicaksono Alfarizy, Muhamad Akbar Ali Imron Alwin Hartono Limaran Amir Akbar Wicaksono Amiruddin Amiruddin Bahiroh, Eloh Bentar Priyopradono Chairuddin Chairuddin Dewi Kania Dewi, Deshinta Arrova Dickson P. Aritonang Dikri Gifari Febri Adi Prasetya Gelar Alam Ramdhaniawan Henderi . Ida Ayu Putu Sri Widnyani Iis Istiharoh Indra Indra Istiharoh, Iis John Chaidir Kambara, Roni Kurniawan, Tri Basuki M Yusron M. Yusron M. Yusron, M. Mashal Alqudah Meisa Monica Muhamad Furqon Mujiburohman Mukhsin, Moh Nabillah Wondu, Tiara Nur Azizah Padri, Abdul Robi Patah Herwanto Rivaldi Arif Rozi, Achmad Salsanabila Mariestiara Putri Setiawati, Firda Solihin Solihin Solihin Sudaryono Sudaryono Sudaryono Sudaryono Sudaryono Sulaiman, Agus Susan Juli Safitri Tb. Ade Rahmatullah Thalia, Shelma Najwa TUTI SUSILAWATI Wawan Prahiawan