Publication Search

This study aims to analyze public sentiment toward the hashtag #KaburAjaDulu, which has circulated widely on the social media platform X (formerly Twitter). The hashtag reflects the growing anxiety among the public, especially younger generations, regarding socio-political issues in Indonesia. The data were collected using web scraping techniques, focusing on user-generated tweets that contain the hashtag. A comprehensive text preprocessing phase was conducted to clean the raw data by removing irrelevant elements such as URLs, emojis, numbers, and punctuation. The research applies a hybrid classification approach using a combination of Support Vector Machine (SVM) and Random Forest algorithms to categorize sentiment into three classes: positive, negative, and neutral. The performance of the model was evaluated using metrics such as accuracy, precision, recall, and F1-score to determine the effectiveness of the classification. The study aims to demonstrate that combining algorithms can improve classification performance compared to using a single algorithm. This research contributes to the field of sentiment analysis and provides valuable insights for researchers, policymakers, and social observers in understanding public opinion trends in digital media.

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.

SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 byToni Firmansyah, S. Farm., Apt. and Asrianty Salam, Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and support decision-making in business strategy and product development.

This research is motivated by the problems in manual attendance systems at schools, which remain vulnerable to fraud, time-consuming, and inefficient. The expected solution is to develop an automated attendance system based on face recognition that can operate in realtime with high accuracy. The research object is vocational high school students, with the applied method implementing the YOLO v10 algorithm for face detection, followed by the face_recognition library for identification. The instruments used include an Imou CCTV camera as the input device, a mid-range laptop as the hardware platform, and Python with SQLite as the software environment for data processing and attendance storage. The results show that the developed system achieved an average face detection accuracy of 96% under normal lighting and 91% under low lighting, with an average processing speed of 27 FPS. The implementation of an anti-duplication feature also ensured data validity by allowing each student to be recorded only once per day. In conclusion, the use of YOLO v10 in face-based attendance proved to be effective, efficient, and capable of reducing fraud. The implication of this study is that the system can be applied in both Islamic boarding schools and general schools as a modernization of attendance systems, with a recommendation for further development through web-based application and cloud database integration.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.

Public service institutions currently utilize digital technology to improve information accessibility for society. Satres PPA and PPO Polresta Banyumas has an important role in providing services, protection, and education related to violence cases against women and children. However, information regarding services, reporting procedures, and educational materials is still not fully accessible to the public. This study aims to design and develop a service and educational website for Satres PPA and PPO Polresta Banyumas using the Laravel framework. The research method used in this study is the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The website was developed using Laravel, MySQL, and Bootstrap to support responsive interface design. The results show that the developed website is able to provide service information, educational articles, reporting procedures, and contact information effectively. System testing results indicate that all website features function properly according to user requirements. The website is expected to improve public access to information and increase awareness regarding the protection of women and children.

This study aims to analyze the implementation of information technology in improving the quality of public services. The research method used is library research by collecting and analyzing various scientific sources, such as journals, books, research articles, and government documents related to information technology and public services. The results show that the implementation of information technology through online service systems, official websites, and administrative information systems is able to improve the effectiveness, efficiency, transparency, and accessibility of public services. Information technology also helps accelerate administrative processes, reduce data management errors, increase employee productivity, and strengthen communication between the government and the community. In addition, the implementation of information technology supports the realization of e-government and good governance through increased accountability and information transparency. However, the implementation of information technology still faces several challenges, such as limited human resources, inadequate technological infrastructure, unstable internet connections, and the low ability of some communities to use digital services. Therefore, it is necessary to improve employee competencies, develop technological infrastructure, and conduct public socialization to optimize the implementation of information technology in public services. Overall, information technology has proven to be a strategic solution in creating modern, effective, efficient, transparent, and community-oriented public services.

This study aims to analyze the effect of profitability, company size, and type of public accounting firm on Key Audit Matters (KAM), with audit fees as a moderating variable in manufacturing sector companies listed on the Indonesia Stock Exchange for the 2022–2024 period. This study used a quantitative approach with a purposive sampling method. Data were obtained from audited financial statements and annual reports published on the official Indonesia Stock Exchange website. The study sample consisted of 67 companies, with a total of 201 observations. Data analysis techniques used included descriptive statistical analysis, classical assumption tests, multiple linear regression, and Moderated Regression Analysis (MRA). The results showed that profitability had a significant negative effect on KAM disclosure, while company size had a significant positive effect on KAM disclosure. The type of public accounting firm showed a significant negative effect on KAM disclosure. Furthermore, audit fees did not moderate the relationship between profitability and KAM, but they did moderate the relationship between company size and type of public accounting firm on KAM disclosure. This study demonstrates that company and auditor characteristics play a significant role in determining the disclosure of Key Audit Matters in the independent auditor's report.

This study conducts a systematic review of literature concerning the role of Management Information Systems (MIS) in managing Umrah pilgrim data across Indonesia. Employing a Systematic Literature Review (SLR) guided by the PRISMA protocol, the study examined and synthesized 24 peer-reviewed articles published between 2019 and 2026, drawn from Google Scholar, SINTA, and nationally accredited journal portals. Findings indicate that MIS adoption has yielded notable improvements in operational efficiency, data reliability, service transparency, and the overall quality of managerial decision-making within Umrah travel organizations. Web-based MIS remains the predominant technological approach, offering integrated modules for pilgrim registration, document handling, financial tracking, and departure scheduling. At the national level, government-initiated platforms such as SISKOHAT and SISKOPATUH have demonstrated tangible contributions to the administration of Hajj and Umrah services. Nevertheless, persistent obstacles continue to hinder full-scale adoption, including inadequate digital infrastructure in certain regions, inconsistent internet connectivity, and gaps in human resource competencies for operating digital systems. The study argues that embracing MIS is no longer optional for Umrah travel operators; rather, it constitutes a strategic necessity. Future research is encouraged to investigate long-term implementation outcomes, cross-system comparisons, and data security considerations within the broader digital landscape of pilgrimage service management.

The selection process for accepting new employees is one of the important stages in a company to ensure that the candidates accepted have qualifications that suit the company's needs. At WINMART, the selection process is still carried out manually, so it is less efficient and prone to errors. Therefore, a system is needed that can assist in more objective and efficient decision making. This Decision Support System (DSS) is designed to assist the selection process for recruiting new employees using the Simple Additive Weighting (SAW) method, which can assess several relevant criteria, such as work experience, education, skills and competency tests. This system was built on a web basis, so it can be easily accessed by parties involved in the selection process, such as HRD and managers. The SAW method was chosen because of its ability to convert various subjective criteria into more objective numerical scores, so that selection results can be more transparent and accountable. By using this system, it is hoped that it can increase efficiency, accuracy and transparency in the new employee selection process at WINMART, as well as facilitate decision making in selecting candidates who best suit the desired criteria.

Breast tumors are classified into two types, namely benign and malignant tumors, the latter commonly referred to as breast cancer. Breast cancer is one of the major health problems affecting women worldwide, including in Indonesia. According to WHO data in 2022, there were 2.3 million breast cancer cases with 685,000 deaths globally, while in Indonesia, 396,914 cases and 234,511 deaths were reported. The high incidence rate is exacerbated by low public awareness in recognizing early symptoms and performing early detection, resulting in 60–70% of cases being diagnosed at an advanced stage, supported by findings that 65.6% of female students still have a low level of knowledge. Female students were selected as research subjects because they are in a vulnerable reproductive age group and have an important role in increasing awareness of early detection, yet they still have limited knowledge. Based on this, this study aims to design a web-based early detection system for breast tumor risk using the Forward Chaining method, which functions as a tool to identify early symptoms, assess risk levels, and provide information on prevention and initial management. This study employed the method with the Expert System Development Life Cycle (ESDLC) model, consisting of the stages of assessment, knowledge acquisition, design, testing, and documentation, along with the Forward Chaining inference method.

This study aims to analyze the effect of Good Corporate Governance (GCG), Firm Size, and Sales Growth on Financial Performance at PT Ace Hardware Indonesia Tbk listed on the Indonesia Stock Exchange (IDX) during the 2015–2024 period. Good Corporate Governance (GCG) in this study is proxied by institutional ownership, financial performance is measured using Return on Assets (ROA), firm size is measured by the natural logarithm of total assets, and sales growth is measured using the sales growth ratio. This study employed a quantitative method with a descriptive approach. The data used were secondary data in the form of annual financial statements obtained from the official websites of the IDX and the company. Data analysis techniques included descriptive statistics, classical assumption tests, multiple and simple linear regression analysis, and hypothesis testing consisting of t-test, F-test, and coefficient of determination with the assistance of SPSS version 27 software. The results of the study indicate that partially, the Good Corporate Governance (GCG) variable has a t-value of -1.526 < t-table 2.447, meaning that it has no significant effect on financial performance. The firm size variable has a t-value of -2.857 > t-table 2.447, indicating a significant negative effect on the company’s financial performance. The sales growth variable has a t-value of 1.593 < t-table 2.447, meaning that it has no significant effect on financial performance. Simultaneously, Good Corporate Governance (GCG), firm size, and sales growth have a significant effect on financial performance, with an F-value of 13.023 > F-table 4.76 and a significance value of 0.005 < 0.05. This study is expected to provide consideration for management and investors in decision-making and serve as a reference for future research in related fields.

This study aims to design and develop a web-based sales information system for a goat farming business at Herman Farm using the Rapid Application Development (RAD) method. The identified problems include manual transaction recording, stock management, and sales reporting processes, which are inefficient, prone to errors, and unable to provide real-time data access. The RAD method is selected due to its ability to accelerate system development through an iterative approach and active user involvement in each stage, including requirements planning, system design, construction, and implementation. Data collection techniques include observation, interviews, and literature studies. The developed system provides features for managing goat data, sales transactions, customer management, and integrated sales reporting within a web-based platform. The results show that the system improves efficiency in data management and transaction processes, while producing more accurate, structured, and accessible reports. Therefore, this system can assist Herman Farm in optimizing its sales operations and expanding its online marketing reach.

This activity aims to provide children at the Al-Riyadhoh Tenggumung Wetan Surabaya Islamic Boarding School (TPQ) on how to manage their time and energy during Ramadan to ensure a balance between learning and worship. The method used was descriptive with a qualitative approach and an Asset-Based Community Development (ABCD) approach. Data collection techniques were carried out through observation, interviews, and documentation. The results of the activity showed that the webinar and mentoring provided were able to increase the children's understanding and enthusiasm in managing their time between learning, worship, and rest during Ramadan. This activity also had a positive impact on increasing children's motivation to learn and discipline in carrying out daily activities. Therefore, good time and energy management is crucial to help children carry out learning and worship activities more effectively during Ramadan. In addition, this activity encourages the formation of positive habits, personal responsibility, and children's awareness to use their time productively and beneficially every day.

The search and booking of boarding houses (kost) remain a significant challenge for newcomers in campus areas, particularly in Kelurahan Samata, home to UIN Alauddin Makassar, which admits approximately 15,000 new students annually. Many of these students come from outside the region and require temporary accommodation near the campus. This issue is primarily caused by limited access to information and the lack of an optimal system to support the search and booking process. Therefore, it is necessary to evaluate the level of user acceptance of the developed system. This study aims to analyze user acceptance of a boarding house search and booking information system in the case of Kelurahan Samata using the User Acceptance Testing (UAT) method. UAT is a testing approach used to determine whether a system meets user requirements, is accepted according to expected standards, and to identify the need for further improvements to ensure its feasibility for use. The UAT was conducted by end users, namely boarding house seekers and property owners/managers, by responding to 10 evaluation indicators: (1) ease of search, (2) time efficiency, (3) booking process, (4) geospatial search features, (5) completeness of information, (6) availability of suitable boarding houses, (7) accuracy of information, (8) ease of payment process, (9) check-in scheduling, and (10) navigation features for directions. The results of the User Acceptance Testing (UAT) indicate that the system achieved an average score of 87.77, suggesting that the system is highly acceptable and significantly facilitates users. These findings demonstrate that the system is well received by users, confirming that it functions effectively and is capable of accommodating all required functionalities.

The implementation of smoking prohibition policies in Islamic boarding schools continues to depend largely on manual monitoring methods, which often face challenges related to consistency and supervision range. This study aims to design an Internet of Things (IoT)-based cigarette smoke detection system as an alternative monitoring approach that is more effective, measurable, and sustainable. The system design combines an MQ-2 gas sensor with a NodeMCU ESP8266 microcontroller programmed through the Arduino IDE platform. When smoke levels detected by the sensor exceed the predetermined limit, the system automatically triggers a buzzer and LED as warning indicators while simultaneously sending monitoring data to cloud-based platforms such as Firebase or ThingSpeak for real-time observation through web interfaces. The research outputs include a comprehensive system design consisting of system architecture, electronic circuit schematics, flowcharts, and pseudocode that are systematically arranged to support future prototype development and implementation. Through this design, the proposed system is expected to provide an initial technological solution that can enhance the effectiveness of monitoring and enforcing smoke-free regulations within Islamic boarding school environments.

This study aims to design and develop an Augmented Reality (AR)-based application for real-time data monitoring of an automatic weather station at PT. XYZ. The system was developed using a prototyping method, involving five key stages: sensor data acquisition via CBOX devices and the Modbus RTU protocol, data transmission through a Flask-based Web API, storage in a MySQL database, QR code-based target image creation using the Vuforia Engine, and a 3D visualization interface developed with Unity integrated with the Vuforia SDK on Android devices. The system successfully received and stored weather data—such as temperature, humidity, and wind speed—into the MySQL database. The AR application also displayed a stable 3D interface panel over QR code markers, providing real-time data updates through an HTTP-based mechanism. This research demonstrates the successful integration of SCADA, Flask, MySQL, and Unity, enhancing both the functionality and commercial appeal of PT. XYZ’s weather station products. Future research should focus on field testing, cloud network integration, and device compatibility.