Publication Search

This study addressed the lack of visual communication media within PT Mensa BinaSukses, which resulted in a lack of togetherness. The visual media at the previous event failed to effectively convey the main message to the employees. To solve this problem, the researchers redesigned the visual communication tools, specifically banners and digital posters, using a User-Centered Design approach. The redesign process applied visual communication principles, focusing on color psychology, typography, and structured layouts to enhance message readability. The evaluation revealed a significant increase in the level of employee attendance. The survey results indicated that the redesigned visual media successfully captured employee attention, clarified event information, and fostered a strong sense of togetherness and collaboration with the company.

Background: Low immunization coverage and exclusive breastfeeding coverage are problems in various regions. This program is caused by a lack of maternal knowledge and family support. This problem increases the risk of infection, growth disorders, and impacts the health status of infants. Therefore, the IMASI MOVEMENT (Immunization and Exclusive Breastfeeding Movement) is needed to increase community knowledge and participation regarding infant and toddler health. Method: The methods used include interactive counseling, demonstrations of breastfeeding techniques according to the pink book (KIA), distribution of leaflets, and evaluation through pre-tests and post-tests. Evaluation was carried out on aspects of structure, process, results, and impact of the activity. Results: The results of the activity showed an increase in participants' knowledge scores by ?50–60% after education. Participant attendance reached ?85% of the target, and there was an increase in participation in integrated health post activities compared to the previous month. Discussion: The increase in knowledge scores in the post-test results compared to the pre-test indicates that the educational intervention is effective in increasing mothers' understanding of the benefits of exclusive breastfeeding and the importance of immunization. These findings indicate that community-based health education is an effective strategy to improve maternal health literacy and has the potential to increase the coverage of exclusive breastfeeding and complete basic immunization. Conclusion: This program has proven effective in increasing awareness and health behavior of mothers and toddlers as an effort to prevent stunting and infectious diseases.

The Free Nutritious Meal Program (MBG) is a free school lunch initiative in Indonesia introduced during the administration of Prabowo Subianto. This study aims to examine the effectiveness of the government's MBG (Free Nutritious Meal) program on kindergarten students' learning interest through a literature review approach. The background of this study is based on the issue of low student learning interest, which is influenced not only by pedagogical factors but also by physical conditions, particularly nutritional intake. This research employed a qualitative approach using a literature review method. The data sources consisted of scientific articles published within the last five years and accessed through Google Scholar. Data were collected through documentation studies, while thematic synthesis was used for data analysis. The findings indicate that the MBG program has a significant positive impact on improving students' learning interest, particularly in terms of attention, motivation, participation, and attendance. The results also reveal that meeting students' physiological needs contributes to their cognitive and emotional readiness to learn. However, the effectiveness of the program is influenced by the quality of its implementation and management in the field. Therefore, more optimal program management and continuous evaluation are needed to maximize its impact on improving the quality of learning.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

 Education in vocational high schools (SMKs) requires effective data management to improve students’ academic achievement and discipline. At SMK Islam Secang, students’ academic scores and attendance data have so far functioned merely as administrative archives, making it difficult to identify patterns of student performance. This study aims to classify students based on academic achievement and discipline by applying the K-Means Clustering algorithm using RapidMiner. The data used in this study consist of scores from six subjects and attendance records of 35 students from the Light Vehicle Engineering (TKR) department over two semesters. The data were obtained from original school records, compiled using Microsoft Excel, and processed in RapidMiner. The clustering process employed four clusters for academic achievement and two clusters for discipline, with Euclidean Distance used as the similarity measure. The results show that in the first semester, students were grouped into four academic achievement clusters: high achievement (6 students), moderate achievement (7 students), potentially problematic (14 students), and problematic (8 students). In the second semester, the distribution changed to high achievement (19 students), moderate achievement (14 students), potentially problematic (4 students), and problematic (1 student). Meanwhile, student discipline was divided into two clusters: disciplined (31 students) and undisciplined (4 students). These results demonstrate that K-Means Clustering is effective in mapping student conditions, revealing patterns in academic performance and attendance, and supporting educational evaluation, learning planning, and early detection of students who require academic or disciplinary intervention. Keywords: Data Mining, K-Means Clustering, Academic Achievement, Discipline, RapidMiner, Vocational High School (SMK)

Social crimes at the village level require participatory and sustainable prevention approaches. This study aims to analyze the synergy between the Sidoarjo Police Resort through its BINMAS unit and the residents of Waruberong Village in implementing the “4D” anticipation framework (Corruption, Narcotics, Bullying, and Sexual Harassment). A descriptive qualitative method was employed, utilizing data collection through observation, semi-structured interviews, and documentation analysis of socialization activities and police-community forums. The results indicate that this partnership successfully shifts the security paradigm from a reactive enforcement model toward proactive collaboration grounded in education and early reporting. BINMAS functions effectively as an administrative liaison, coordinating Senkom Mitra Polri, village officials, and residents, thereby standardizing and streamlining report handling processes. The implementation of the 4D framework significantly enhances public legal literacy, strengthens trust in the DUMAS Presisi system, and encourages active community participation in security patrols and awareness campaigns. Although minor administrative challenges, such as limited reporting literacy and fluctuating attendance, were identified, they can be mitigated through structured mentoring. Overall, the 4D-based partnership model proves highly relevant for strengthening participatory security ecosystems at the village level. This study recommends standardizing educational modules, providing continuous administrative training for Senkom members, and integrating digital reporting platforms to ensure the program's long-term sustainability.

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.

This study aims to analyze the implementation of the Bravo PUPR Online attendance system in improving the work discipline of Civil Servants (ASN) at the National Road Implementation Center of East Nusa Tenggara. The research focuses on punctuality of attendance, consistency in fulfilling working hours, task completion, compliance with attendance procedures, alignment between recorded data and actual conditions, and acceptance of consequences for violations. The study employs a qualitative approach with data collection techniques including observation, documentation, and interviews with leaders, system operators, and ASN as direct users. The results indicate that the implementation of the Bravo PUPR Online attendance system has improved administrative order in attendance and increased ASN awareness of time discipline. However, work discipline has not been fully optimal, as several issues remain, such as inconsistent attendance, suboptimal fulfillment of working hours, and discrepancies between attendance data and actual field conditions. In addition, technical constraints such as internet connectivity and GPS accuracy, as well as behavioral factors like negligence and lack of supervision, also affect system effectiveness. In terms of compliance, the Bravo system integrated with e-HRM is considered effective in detecting violations and enforcing strict consequences, ranging from warnings to administrative sanctions. This demonstrates that the attendance system functions not only as a recording tool but also as an instrument for monitoring discipline.

Kedisiplinan kehadiran siswa merupakan aspek penting dalam proses pembelajaran karena mencerminkan partisipasi, tanggung jawab, dan kepatuhan terhadap aturan sekolah. Namun, data absensi sering kali hanya diperlakukan sebagai catatan administratif dan jarang dianalisis untuk mengidentifikasi pola keterlambatan yang berulang. Penelitian ini bertujuan untuk mengelompokkan pola keterlambatan siswa berdasarkan data absensi harian menggunakan algoritma K-Means guna memberikan gambaran yang lebih terstruktur dan objektif tentang disiplin kehadiran. Penelitian ini menggunakan pendekatan data mining yang meliputi pengumpulan data, preprocessing, transformasi data, normalisasi, dan clustering. Dataset yang digunakan terdiri atas 678 catatan absensi harian selama 47 minggu. Setelah direkapitulasi, data menghasilkan 54 kategori durasi keterlambatan dengan total 1.738 kejadian keterlambatan. Variabel utama yang dianalisis adalah frekuensi kejadian keterlambatan pada setiap kategori, dan StandardScaler digunakan sebelum proses clustering. Data kemudian dikelompokkan ke dalam tiga cluster, yaitu High, Medium, dan Low. Hasil penelitian menunjukkan bahwa keterlambatan singkat berdurasi 1-7 menit membentuk cluster High dengan total 1.007 kejadian, yang menunjukkan bahwa keterlambatan ringan yang berulang merupakan pola paling dominan. Cluster Medium mencakup keterlambatan 8-13 menit dengan 425 kejadian, sedangkan cluster Low mencakup keterlambatan 14-63 menit dengan 306 kejadian. Penelitian ini memberikan kontribusi berupa sudut pandang berbasis clustering dalam menafsirkan data absensi dan berimplikasi bahwa sekolah perlu memberi perhatian tidak hanya pada keterlambatan berat, tetapi juga pada keterlambatan singkat yang sering berulang melalui pemantauan lebih dini dan intervensi disiplin yang lebih tepat sasaran.

Penelitian ini dilatarbelakangi oleh proses absensi karyawan pada Stand Bento dan Stand Es Teh Luwes Ungaran yang masih dilakukan secara manual menggunakan buku absensi. Kondisi tersebut menimbulkan beberapa kendala, seperti kesalahan pencatatan jam masuk dan pulang, risiko kehilangan atau kerusakan data, serta lambatnya proses rekapitulasi laporan kehadiran. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem absensi karyawan berbasis web menggunakan teknologi QR Code guna mengoptimalkan pengelolaan kehadiran pada usaha kuliner skala kecil. Metode pengembangan sistem yang digunakan adalah model Waterfall, yang meliputi tahapan analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Sistem dikembangkan menggunakan PHP, MySQL, XAMPP, dan Visual Studio Code, serta dilengkapi fitur login, pengelolaan data karyawan, generate QR Code, scan QR Code, histori absensi, dan rekapitulasi laporan kehadiran. Pengujian dilakukan menggunakan Black Box Testing dan User Acceptance Testing (UAT). Hasil pengujian menunjukkan bahwa seluruh fungsi utama sistem berjalan valid sesuai kebutuhan pengguna. Sistem ini mampu mendukung pencatatan kehadiran secara lebih cepat, terstruktur, dan terintegrasi dengan basis data, serta membantu pengelola usaha dalam memantau dan merekap data kehadiran karyawan secara lebih efisien.

Absensi karyawan merupakan aspek penting dalam manajemen sumber daya manusia yang memengaruhi disiplin kerja serta akurasi administrasi dalam suatu organisasi. PT. Bahtera Komunikasi Kreatif saat ini masih menggunakan sistem absensi berbasis sidik jari yang belum terintegrasi dengan pengelolaan cuti seperti izin, cuti sakit, dan work from home (WFH), sehingga proses pencatatan dan pelaporan masih dilakukan secara manual dan berpotensi menimbulkan keterlambatan serta kesalahan administrasi. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem manajemen absensi dan cuti karyawan berbasis web yang lebih fleksibel, terintegrasi, dan mudah diakses. Metode penelitian yang digunakan meliputi observasi, wawancara, tinjauan pustaka, dan kuesioner, dengan pendekatan pengembangan sistem menggunakan model Software Development Life Cycle (SDLC) metode Waterfall. Sistem diimplementasikan menggunakan PHP Native, MySQL, serta teknologi web seperti HTML, CSS, JavaScript, dan Bootstrap, dengan dukungan HTML5 Geolocation API dan fitur kamera untuk validasi kehadiran. Pengujian sistem dilakukan menggunakan Black Box Testing dan User Acceptance Testing (UAT) untuk memastikan fungsi sistem berjalan dengan baik serta dapat diterima oleh pengguna. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan efisiensi, akurasi data, serta mempermudah monitoring dan pelaporan secara real-time dengan nilai UAT sebesar 4,45 yang termasuk kategori sangat baik. Selain itu, sistem yang dikembangkan juga mampu mengurangi ketergantungan pada proses manual serta meningkatkan transparansi dalam pengelolaan data kehadiran karyawan, sehingga dapat mendukung peningkatan kinerja operasional perusahaan secara keseluruhan.

This study analyzes the role of supporter fanaticism and loyalty in influencing the purchase decisions of official PSMS Medan merchandise. A qualitative descriptive method was employed through in-depth interviews, observation, and documentation, supported by secondary data from literature studies. The results show that fanaticism is reflected in emotional attachment, active involvement, long-term support, and social environmental influences. Supporter loyalty appears in consistent attendance at matches, following games, discussing the club, and repeated purchases of official merchandise. Purchase decisions are influenced by product type, design/form, and quantity, while also considering financial capability. Overall, fanaticism shapes emotional bonding, whereas loyalty drives repeated purchasing behavior; both contribute significantly to merchandise purchasing. These findings highlight the importance of design innovation, product quality improvement, and marketing strategies based on emotional and historical attachment to the club. Keywords: Consumer Behavior; Fanaticism; Merchandise; Purchase Decision; Supporter Loyalty.

Employee attendance is an important indicator to demonstrate the discipline and performance of village employees. The process of recording employee attendance previously at the Lumban Dolok Village Office was still done manually. This can cause problems such as incorrect data, slow report collection, and absenteeism. Therefore, the purpose of this study is to develop a web-based presence-monitoring information system that uses the Location-Based Service (LBS) method. The purpose of the LBS method is to ensure that the attendance process can be carried out only when employees are within a specified radius of the Lumban Dolok Village Office. This system uses latitude and longitude data from the user's device to calculate the geographic distance to the location's center point. The developed system uses the user's device's latitude and longitude to calculate the distance between the employee's location and the attendance center. Within a radius of 25 meters, the attendance process can only be carried out if the employee is within that radius; if they are outside the radius, then the attendance will be automatically rejected by the system. In this study, the waterfall system development method was employed, with PHP and UML. The results of the study show that this system can help the village office monitor employee attendance directly, speed up the collection of attendance reports, and reduce the risk of data manipulation. In addition, attendance reports are easily accessible by admins and village heads to assess employee performance. Thus, the web-based attendance information system using the LBS method is expected to improve compliance, transparency, and effectiveness of attendance management at the Lumban Dolok Village Office.

Health program planning is an essential process in improving public health status through a systematic and data-driven approach. This study aimed to analyze health program planning based on situational analysis and the problem solving cycle (PSC), as well as to identify the root causes of problems using the fishbone approach. The research employed a descriptive qualitative method supported by simple quantitative data. Data were collected through in-depth interviews, observations, and documentation involving purposively selected informants. The results of the situational analysis identified several major health problems, including stunting, low posyandu attendance, and limited maternal knowledge regarding nutrition. Priority setting using the USG method determined stunting as the main health issue. Furthermore, root cause analysis using a fishbone diagram revealed that stunting was influenced by various factors related to man, machine, method, material, environment, money, and management. The application of the problem solving cycle facilitated systematic intervention planning, including nutrition education, community empowerment, and child growth monitoring. Program implementation demonstrated improvements in maternal knowledge and posyandu attendance. In conclusion, health program planning based on situational analysis, fishbone analysis, and the problem solving cycle proved effective in producing targeted and sustainable interventions.

Health program planning is an essential process in improving public health status through a systematic and data-driven approach. This study aimed to analyze health program planning based on situational analysis and the problem solving cycle (PSC), as well as to identify the root causes of problems using the fishbone approach. The research employed a descriptive qualitative method supported by simple quantitative data. Data were collected through in-depth interviews, observations, and documentation involving purposively selected informants. The results of the situational analysis identified several major health problems, including stunting, low posyandu attendance, and limited maternal knowledge regarding nutrition. Priority setting using the USG method determined stunting as the main health issue. Furthermore, root cause analysis using a fishbone diagram revealed that stunting was influenced by various factors related to man, machine, method, material, environment, money, and management. The application of the problem solving cycle facilitated systematic intervention planning, including nutrition education, community empowerment, and child growth monitoring. Program implementation demonstrated improvements in maternal knowledge and posyandu attendance. In conclusion, health program planning based on situational analysis, fishbone analysis, and the problem solving cycle proved effective in producing targeted and sustainable interventions.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

This study examines the role of the Karawang Cerdas Scholarship in fostering students’ responsibility and learning motivation in Islamic Religious Education (PAI) among 11th-grade students at MAN 2 Karawang. The study was motivated by the importance of developing responsibility and learning motivation as essential objectives of Islamic education while exploring the scholarship’s contribution beyond financial assistance. A qualitative case study approach was employed, with data collected through interviews, observations, and documentation involving scholarship recipients, PAI teachers, and program administrators. Data were analyzed using the Miles and Huberman model through data reduction, data display, and conclusion drawing. The findings indicate that the Karawang Cerdas Scholarship strengthens students’ academic responsibility, discipline, compliance with school regulations, awareness of maintaining the school’s reputation, and accountability in utilizing scholarship funds through the Statement of Absolute Responsibility (SPTJM). The program also enhances learning motivation, reflected in increased enthusiasm, active classroom participation, sustained academic achievement, and clearer educational goals. These improvements contribute to higher attendance, better PAI learning outcomes, fewer disciplinary violations, and the development of positive character traits. The study concludes that the Karawang Cerdas Scholarship functions not only as financial assistance but also as an effective instrument for character development and learning motivation.

This research is motivated by the issue of employee productivity at Estetiderma Clinic Bekasi, as indicated by the unmet distribution target data during the 2021–2024 period. In addition, there are indications that improvements are needed in the effectiveness of recruitment methods and employee work discipline, as reflected in the attendance data. The purpose of this study is to determine whether recruitment (X1) and work discipline (X2) have an effect on employee productivity (Y), either partially or simultaneously, at Estetiderma Clinic Bekasi. The research method used is associative quantitative research. The population and sample consist of all 130 employees of Estetiderma Clinic Bekasi. The data analysis techniques employed include multiple linear regression analysis, correlation coefficient analysis, coefficient of determination, and hypothesis testing (t-test and F-test). The results of the study show that: (1) the recruitment variable (X1) has a t-value of 9,503 > t-table 1.978 and a significance value of 0.000 < 0.05, indicating a positive and significant effect of recruitment on employee productivity; (2) the work discipline variable (X2) has a t-value of 13,154 > t-table 1.978 and a significance value of 0.000 < 0.05, indicating that work discipline has a positive and significant effect on employee productivity; and (3) the simultaneous F-test result shows an F-value of 114.347 > F-table 3.067 with a significance value of 0.000 < 0.05, which means that recruitment and work discipline simultaneously have a significant effect on employee productivity. These two variables contribute 64.3% to employee productivity, while the remaining 35.7% is influenced by other factors not included in this study.

A faith-based marriage strengthening program is essential for building family resilience in urban congregations facing high divorce rates and declining marital quality. This community service activity aimed to revitalize the marital bonds of 22 couples in the Pria Sejati Bandung community and GPPS Agape Bandung congregation through the "Reborn Marriage" program. Using a participatory action research approach, a team of 12 facilitators implemented three main stages: initial coordination to identify needs and plan together with the community; an intensive one-day intervention consisting of teachings on grace, agape love, and divine purpose of marriage, along with testimony sharing, footwashing ritual, and gift giving; and a marriage commitment renewal ceremony. The results showed 100% attendance rate of all registered couples, active participation in every coaching session, and qualitative findings from focus group discussions including renewed spiritual intimacy, mutual forgiveness between spouses, and alignment of marital visions based on divine values. A total of 86% of couples expressed willingness to participate in regular follow-up mentoring, and local leaders emerged among participants who are ready to facilitate small groups after the program. Discussions confirmed that combining biblical teachings on agape love with experiential symbolic rituals can holistically transform marital relationships. This community-based intervention proves replicable in other local communities and churches in urban settings, especially those seeking to strengthen family resilience through integrated pastoral care and participatory action.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.