Portal Jurnal Ilmiah
Goretan Pena

The rapid advancement of digital technology has placed the government in the position of a large-scale personal data controller through various E-Government platforms and public service applications. However, the government's capacity to protect this data has proven inadequate, as demonstrated by several major data breach incidents involving national platforms such as the Temporary National Data Center (PDNS) in 2024, Satu Sehat, and DPMPTSP Online. This research aims to analyze the civil liability of government agencies as personal data controllers in cases of personal data breaches, viewed through the framework of Law Number 27 of 2022 on Personal Data Protection (UU PDP) and Law Number 30 of 2014 on Government Administration (UU AP). The research method employed is normative juridical (doctrinal legal research) through a statutory approach and a conceptual approach, with primary legal materials drawn from the aforementioned laws and secondary materials from scientific articles and relevant legal textbooks. The findings indicate that the government, as a public body and personal data controller under UU PDP, can be held civilly liable when a data breach occurs due to negligence or unlawful acts in data management. Civil liability may arise through two mechanisms: the unlawful act (onrechtmatige overheidsdaad) mechanism under Article 1365 of the Civil Code, and the administrative court (PTUN) mechanism under UU AP. However, implementation faces significant obstacles, including the absence of government implementing regulations for UU PDP, fragmentation of supervisory authority, the absence of standardized compensation mechanisms, and limited institutional capacity. This research concludes that comprehensive regulatory harmonization, the establishment of a strong Personal Data Protection Authority, and the development of fast, accessible compensation procedures are urgently needed to realize effective legal protection for citizens' personal data.

This study aims to analyze the role of work engagement in mediating the effect of digital transformation of human resource management (HRM) on employee performance in SMEs in Medan City. This research employs a quantitative approach with an explanatory design. Data were collected through questionnaires distributed to 100 SME employees using purposive sampling technique. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. The results indicate that digital transformation of HRM has a positive and significant effect on work engagement and employee performance. Work engagement also has a positive and significant effect on employee performance. Furthermore, work engagement significantly mediates the relationship between digital transformation of HRM and employee performance with partial mediation. These findings suggest that the success of digital transformation in improving employee performance depends not only on the implementation of technology but also on the level of employee work engagement. This study contributes theoretically to the development of digital HRM literature and provides practical implications for SMEs in managing human resources more effectively in the digital era.

This study aims to analyze the effect of digital marketing capability on SME performance with market agility as a mediating variable. The research employs a quantitative approach with an explanatory design. The population consists of SME actors in Kecamatan Medan Kota, with a sample of 100 respondents selected using purposive sampling. Data were collected through questionnaires using a Likert scale and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that digital marketing capability has a positive and significant effect on both SME performance and market agility. Market agility also has a significant positive effect on SME performance. Furthermore, market agility mediates the relationship between digital marketing capability and SME performance with partial mediation. These findings suggest that digital marketing capability will be more effective in improving SME performance when supported by the ability to adapt to market changes. This study contributes to the business management literature and provides practical implications for SME actors in optimizing adaptive digital marketing strategies to enhance business performance.

Intercepting a highly maneuvering moving target remains a difficult planning problem because the target may change heading, accelerate, halt, or reverse without warning, while the pursuer only receives noisy position observations. This study proposes the Adaptive Pursuit Route Algorithm (APRA), an interception path-planning method that combines short-horizon target-state estimation, time-to-go aim-point projection, dynamically weighted cost terms, and a bounded residual that is learned online from past prediction errors. APRA is evaluated against three classical pursuit laws-Pure Pursuit, Proportional Navigation (PN), and Augmented PN (APN)-on a physics-based synthetic dataset of 3,200 trajectories spanning eight motion regimes, yielding 12,800 engagements. APRA attains the best result on every metric: an interception rate of 90.91% (95% CI 0.899-0.919), the shortest mean interception time (9.65 s), the lowest mean prediction error (8.73 units), the highest path efficiency (0.798), and the lowest control energy (48,022). One-way ANOVA confirms that the differences in time, energy, and prediction error are statistically significant (p < 0.001), and a Welch t-test shows APRA is significantly faster than APN (t = -14.48, p < 0.001). The results indicate that disciplined filtering combined with bounded online adaptation is more robust against deceptive and abrupt maneuvers than raw lead-based guidance.

This study was designed to improve student learning engagement using the Make a Match cooperative learning model for students at Tanjungbalai Polytechnic. The learning engagement in this study focused on physical and mental engagement. This study employed Classroom Action Research (CAR), where the lecturer acted as the learning implementer while the researcher acted as the observer. The design of the study employed the Kemmis and Mc. Taggart model. This study was conducted in the even semester. The subjects were students at Tanjungbalai Polytechnic. The object of the study was the participants' learning engagement, and data collection techniques used observation and interviews. The data were analyzed descriptively and presented in tables and graphs. The results showed an increase in student learning engagement in siklus I, reaching 80.10% (good category), and then in siklus II, increasing to 90.10% (very good category). This represents a 9.54% increase. Therefore, the use of the Make a Match cooperative learning model in courses at Tanjungbalai Polytechnic is

The mental health of final year students is an important aspect in the world of higher education, especially in facing the demands of completing a thesis at the Faculty of Engineering, Asahan University. However, until now there is no system that can help assess students' mental health levels in a structured and automatic manner. Therefore, this research aims to design and build an expert system application using the Sugeno Fuzzy Inference System (FIS) method based on PHP and MySQL to assess the mental health level of final year students. The data used in this research was obtained through distributing questionnaires to final year students at the Faculty of Engineering, Asahan University. The variables used include stress intensity, sleep quality, academic load, and social interaction. The data obtained was 99 final year student respondents. The data processing was carried out using the FIS Sugeno method by forming fuzzy sets, membership functions, and 81 fuzzy rules to produce students' mental health levels. Based on the results of system testing, the FIS Sugeno method was successfully applied to automatically assess students' mental health levels. The system is capable of carrying out data input processes, fuzzification, fuzzy inference, and producing assessment output quickly and in a structured manner. The benefit of this research is that it helps provide an initial picture of the mental health conditions of final year students so that it can be taken into consideration in efforts to treat and assist students.

The assessment of student visit satisfaction at the Asahan University library is currently influenced by various uncertainty factors from each individual, making it difficult to measure objectively using the existing system. This study aims to build a more measurable classification system using the Fuzzy Sugeno logic method. The system is evaluated using four input parameters with a value range of 0 to 100, namely service quality, facilities, environmental comfort, and ease of information access, to generate an output variable divided into dissatisfied, satisfied, and very satisfied categories. Based on the test results, inputting a service quality value of 85, facilities 85, environmental comfort 55, and ease of information access 55 produced a recommendation value of 54.285, which was successfully classified linguistically into the "Satisfied" category. The application of the Fuzzy Sugeno method is proven to provide an accurate assessment, which is expected to assist library management in evaluating services and making strategic decisions for future quality improvements.

The study aims to analyze the effect of the Discovery Learning model assisted by the interactive media Quizizz on students' critical thinking skills in mathematics at SMK Swasta Al-Ma'shum Sidodadi. The main background of this study is the low level of students' critical thinking skills in solving complex problems. The research method used was a quasi-experimental design with a nonequivalent control group design. The research sample consisted of the experimental class (Xth-2) implementing the Discovery Learning model assisted by Quizizz and the control class (Xth-1) using direct learning. Data were collected through a critical thinking skills test in the form of essay questions measuring indicators of interpretation, analysis, evaluation, and inference. The results of the data analysis showed a significant increase in the average critical thinking skills in the experimental class (80.65) compared to the control class (66.41). Hypothesis testing using an Independent Samples T-Test in SPSS 20 yielded a significance value of 0.000 < 0.05. These findings confirm that the integration of the discovery learning model with the Quizizz gamification media has a significant positive impact on improving students' critical thinking skills.

The rapid development of information technology has encouraged the healthcare sector to utilize data as a basis for faster, more precise, and effective decision-making. One of the largest data sources in the healthcare sector is BPJS (Social Security Administration for Health) patient data, which includes medical history, examination results, previous medical procedures, and medication use. This data is a critical asset that, when properly managed and analyzed, can assist hospitals and healthcare facilities in determining appropriate medical interventions for patients. The purpose of this study was to design and develop an application for prioritizing medical procedures for BPJS patients in, using the KNN method, the PHP programming language, and a MySQL database. The data used in this study were BPJS patient visit data. Based on test results at various levels of K=3, K=5, and K=7, the data demonstrated very high consistency. Even though the K value (number of nearest neighbors) was increased from 3 to 7, the final classification results still showed a predominance of the Medium Priority category. With a KNN-based classification system, medical personnel no longer need to manually assess each patient.

The assessment of student satisfaction regarding educational facilities at the Faculty of Engineering, Universitas Asahan, has been subjective and limited to manual recapitulation. This study aims to implement a web-based Fuzzy C-Means (FCM) algorithm (using PHP and MySQL) to group student satisfaction levels more objectively. This study uses primary data obtained from questionnaires given to 200 respondents. Based on the computational testing results, the FCM algorithm successfully reached convergence and grouped the data into three clusters. From a total of 200 data, 89 respondents were in the Dissatisfied cluster (C1), 64 respondents in the Moderately Satisfied cluster (C2), and 47 respondents in the Satisfied cluster (C3). This system is also capable of grouping qualitative data in the form of student suggestions according to their clusters. This implementation is proven effective in generating accurate information as a comprehensive evaluation report for faculty leaders to prioritize eduacational facility improvements.

Gender change is a legal phenomenon that has generated debate in the Indonesian legal system, particularly regarding the recognition of legal identity for applicants after gender transition. The main problem in this study lies in the absence of legal regulations that specifically and comprehensively regulate the procedures, requirements, and legal consequences of gender change, resulting in disparities in court decisions. This study aims to analyze the legal vacuum related to gender change in Indonesia, the legal consequences of determining gender change on population administration, and to comparatively analyze the judges' considerations in Decision Number: 195/Pdt.P/2021/PN.Jkt.Utr and Decision Number 30/Pdt.P/2022/PN.Pwt. The research method used is normative legal research with a statutory approach, a conceptual approach, and a case approach. The research results show that the regulation of gender reassignment in Indonesia is still limited to aspects of population administration, as stipulated in Article 56 paragraph (1) of Law Number 23 of 2006 concerning Population Administration in conjunction with Law Number 24 of 2013. The absence of substantive regulations causes judges to rely on legal findings in deciding gender reassignment requests. The legal consequences of gender reassignment include changes in population identity, civil legal status, and implications for marriage and inheritance. In Decision Number 195/Pdt.P/2021/PN.Jkt.Utr, the judge used a progressive, human rights-based approach, resulting in the granting of the request. Whereas in Decision Number 30/Pdt.P/2022/PN.Pwt, the judge used a normative, moral, and religious approach, resulting in the rejection of the request. This disparity demonstrates the lack of legal certainty regarding gender reassignment in Indonesia.

Abstract: This study aims to determine the effect of customer experience on customer loyalty at PT. KAI Divre I North Sumatra. This study uses a quantitative approach with a simple linear regression method. The research sample consisted of 209 customers who had used the services of PT. KAI Divre I North Sumatra at least twice, with the sampling technique using the accidental sampling method. The results of the analysis indicate that there is a significant influence between customer experience and customer loyalty. Based on the hypothesis test using simple linear regression, a significance value of p<0.001 (p<0.05) wasa obtained, so the hypothesis in this study was accepted. The regression equation is known as Y=12.051+0.627X, which means that every 1 point increase in the customer experience variable will increase customer loyalty by 0.627. the coefficient of determination (R2) value of 0.753 indicates that customer experience contributes 75.3% to customer loyalty, while 24.7% is influenced by other factors outside the study. The results of the descriptive analysis show that the empirical average of customer loyalty (65.21) is higher than the hypothetical average (47.5), while the empirical average of customer experience (84.72) is also higher than the hypothetical average (62.5). this indicates that customer loyalty is in the medium category, while customer experience is in the high category. Based on these results, it can be concluded that customer experience is a crucial factor in increasing customer loyalty at PT. KAI Divre I North Sumatra.   Keywords: Customer Experience, Customer Loyalty, PT. KAI. Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh customer experience terhadap loyalitas pelanggan pada PT. KAI Divre I Sumatera Utara. Penelitian ini menggunakan pendekatan kuantitatif dengan metode regresi linear sederhana. Sampel penelitian berjumlah 209 pelanggan yang telah menggunakan layanan PT. KAI Divre I Sumatera Utara minimal dua kali, dengan teknik pengambilan sampel menggunakan metode accidental sampling. Hasil analisis menunjukkan bahwa terdapat pengaruh signifikan antara customer experience terhadap loyalitas pelanggan. Berdasarkan uji hipotesis menggunakan regresi linear sederhana, diperoleh nilai signifikansi p < 0,001 (p < 0,05), sehingga hipotesis dalam penelitian ini diterima. Diketahui persamaan regresi Y = 12,051+0,627X, yang berarti setiap kenaikan 1 poin pada variabel customer experience akan meningkatkan loyalitas pelanggan sebesar 0,627. Nilai koefisien determinasi (R²) sebesar 0,753 menunjukkan bahwa customer experience memberikan kontribusi sebesar 75,3% terhadap loyalitas pelanggan, sedangkan 24,7% dipengaruhi oleh faktor lain di luar penelitian. Hasil analisis deskriptif menunjukkan bahwa rata-rata empiris loyalitas pelanggan (65,21) lebih tinggi dibandingkan rata-rata hipotetik (47,5), sedangkan rata-rata empiris customer experience (84,72) juga lebih tinggi dibandingkan rata rata hipotetik (62,5). Hal ini menunjukkan bahwa loyalitas pelanggan berada pada kategori sedang, sementara customer experience berada pada kategori tinggi. Berdasarkan hasil tersebut, dapat disimpulkan bahwa customer experience merupakan faktor penting dalam meningkatkan loyalitas pelanggan pada PT. KAI Divre I Sumatera Utara.   Kata Kunci: Customer Experience, Loyalitas Pelanggan, PT. KAI

  Higher education institutions are required to produce graduates who are competitive in the job market, yet tracer study data is often analyzed only descriptively, leaving deeper patterns unexplored. This study proposes an integrated approach combining Random Forest, SHAP (SHapley Additive exPlanations), and fairness evaluation to analyze alumni career outcomes. Data were sourced from the 2024 tracer study of Universitas Royal, comprising 466 alumni records with a binary target variable indicating employment status. Preprocessing included missing value handling, one-hot encoding, and stratified train-test splitting with an 80:20 ratio. Class imbalance was addressed using the class_weight='balanced' parameter. The Random Forest model achieved an accuracy of 95.7%, F1-score of 0.946, and AUC-ROC of 0.938, significantly outperforming the dummy baseline of 58.5%. Cross-validation across five folds yielded a mean accuracy of 96.4%, confirming model stability. SHAP analysis revealed that features related to educational level appropriateness and relevance of study field to current occupation were the most dominant predictors. Fairness evaluation per study program showed minimal performance disparity between Sistem Informasi (94.7%) and Sistem Komputer (100%), indicating no significant predictive bias. This framework demonstrates that explainable and fair machine learning can serve as a reliable foundation for evidence-based academic policy making

The low learning outcomes of students in Economics at SMA Negeri 2 Singaparna, evidenced by Grade XI Final Semester Assessment (PAS) scores falling below the Minimum Mastery Criteria (KKM), motivated this study. This research aimed to examine the effect of the cooperative learning model type Team Assisted Individualization (TAI) assisted by question cards on improving student learning outcomes in monetary and fiscal policy material. A quasi-experimental method with a pretest-posttest control group design was employed. The research population is students in grade XI of SMA Negeri 2 Singaparna for the 2025/2026 school year. Using purposive sampling, class XI 7 (n = 39) served as the experimental group and class XI 8 (n = 39) as the control group. Data were analyzed using an independent sample t-test. Results showed a Sig. (2-tailed) value of 0.000 < 0.05, confirming the hypothesis. The experimental class mean score (85.41) significantly exceeded the control class mean (78.05). Therefore, the TAI cooperative learning model assisted by question cards is proven effective in improving student learning outcomes.

Abstract: The advancement of generative artificial intelligence (AI) opens new opportunities in precision agriculture, particularly in plant health monitoring and diagnosis. This study aims to systematically review studies discussing the use of Generative AI in plant health monitoring from 2019 to 2024. The method used is a Systematic Literature Review (SLR) following the PRISMA protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Searches were conducted on Google Scholar, Scopus, Science Direct, and Portal Garuda databases using defined keywords. Of the 247 identified articles, 38 articles met the inclusion criteria and were analyzed in depth. The results show that Generative AI technologies, especially Generative Adversarial Networks (GAN), Diffusion Models, and vision-based Large Language Models (LLMs), have significantly contributed to plant disease detection, image data augmentation, and agronomic recommendation systems. Disease detection accuracy using GAN-based approaches averaged 94.7%, while visual transformer-based models recorded accuracy up to 96.3%. Key barriers include limited labeled datasets, technology gaps in rural areas, and lack of model adaptation to local Indonesian plant varieties. This study concludes that integrating Generative AI in plant health monitoring systems has great potential but requires multidisciplinary collaboration, local dataset development, and appropriate technology adoption policies. Keywords: Generative AI, GAN, Plant Health, Monitoring, Systematic Literature Review, Precision Agriculture   Abstrak: Perkembangan kecerdasan buatan (AI) generatif membuka peluang baru dalam bidang pertanian presisi, khususnya dalam monitoring dan diagnosis kesehatan tanaman. Penelitian ini bertujuan untuk mengkaji secara sistematis berbagai studi yang membahas pemanfaatan Generative AI dalam monitoring kesehatan tanaman dari tahun 2019 hingga 2024. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan mengikuti protokol PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Pencarian dilakukan pada basis data Google Scholar, Scopus, Science Direct, dan Portal Garuda menggunakan kata kunci yang telah ditetapkan. Dari 247 artikel yang teridentifikasi, sebanyak 38 artikel memenuhi kriteria inklusi dan dianalisis secara mendalam. Hasil kajian menunjukkan bahwa teknologi Generative AI, terutama Generative Adversarial Networks (GAN), Diffusion Model, dan Large Language Model (LLM) berbasis visi, telah memberikan kontribusi signifikan dalam deteksi penyakit tanaman, augmentasi data citra, dan sistem rekomendasi agronomis. Tingkat akurasi deteksi penyakit menggunakan pendekatan berbasis GAN mencapai rata-rata 94,7%, sedangkan model berbasis transformer visual mencatat akurasi hingga 96,3%. Hambatan utama yang ditemukan meliputi keterbatasan dataset berlabel, kesenjangan teknologi di wilayah pedesaan, serta kurangnya adaptasi model terhadap varietas tanaman lokal Indonesia. Penelitian ini menyimpulkan bahwa integrasi Generative AI dalam sistem monitoring kesehatan tanaman memiliki potensi besar namun memerlukan kolaborasi multidisiplin, pengembangan dataset lokal, dan kebijakan adopsi teknologi yang tepat. Kata Kunci: Generative AI, GAN, Kesehatan Tanaman, Monitoring, Systematic

Abstract: This study aims to determine the effect of the Game Based Learning model on students' learning outcomes in Economics subjects for Grade X students at SMA Negeri 1 Percut Sei Tuan in the 2025/2026 academic year. This research employed a quasi-experimental method using a pretest-posttest control group design. The population consisted of 356 Grade X students from 10 classes, while the sample included class X-1 as the experimental class and class X-2 as the control class, each consisting of 36 students. Data were collected through observation, interviews, documentation, and tests. Data analysis was conducted using normality tests, homogeneity tests, and hypothesis testing through the Independent Sample T-Test. The results showed that the average posttest score of the experimental class was 86.11, which was higher than that of the control class at 72.56. The hypothesis test yielded a significance value of 0.000 < 0.05, indicating that Ha was accepted and H0 was rejected. These findings demonstrate that the Game Based Learning model has a significant effect on students' learning outcomes. Therefore, the implementation of the Game Based Learning model can be considered an effective alternative for improving students' learning outcomes in Economics subjects. Keywords: Game Based Learning; Learning Outcomes; Economics Education; Quasi Experiment; Innovative Learning.   Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran Game Based Learning terhadap hasil belajar siswa pada mata pelajaran Ekonomi kelas X di SMA Negeri 1 Percut Sei Tuan Tahun Ajaran 2025/2026. Penelitian ini menggunakan metode quasi experiment dengan desain pretest-posttest control group design. Populasi penelitian berjumlah 356 siswa kelas X yang terdiri dari 10 kelas, sedangkan sampel penelitian adalah kelas X-1 sebagai kelas eksperimen dan kelas X-2 sebagai kelas kontrol yang masing-masing berjumlah 36 siswa. Teknik pengumpulan data dilakukan melalui observasi, wawancara, dokumentasi, dan tes. Analisis data menggunakan uji normalitas, uji homogenitas, dan uji hipotesis (Independent Sample T-Test). Hasil penelitian menunjukkan bahwa rata-rata nilai posttest kelas eksperimen sebesar 86,11 lebih tinggi dibandingkan kelas kontrol sebesar 72,56. Hasil uji hipotesis memperoleh nilai signifikansi sebesar 0,000 < 0,05, sehingga Ha diterima dan H0 ditolak. Temuan ini menunjukkan bahwa model pembelajaran Game Based Learning berpengaruh signifikan terhadap hasil belajar siswa. Dengan demikian, penerapan model pembelajaran Game Based Learning dapat menjadi alternatif yang efektif dalam meningkatkan hasil belajar siswa pada mata pelajaran Ekonomi. Kata Kunci: Game Based Learning; Hasil Belajar; Ekonomi; Quasi Experiment; Pembelajaran Inovatif.

The research aims to develop a valid, practical, and effective Think Talk Write (TTW)-based e-LKPD assisted by the Liveworksheets application to improve students' mathematical communication skills in trigonometry. The research is motivated by students' low mathematical communication skills in conveying mathematical ideas, using symbols and notation appropriately, and presenting mathematical representations in problem solving. This study uses the Research and Development (R&D) method with a 4D development model consisting of the Define, Design, Develop, and Disseminate stages. The research subjects are 33 students at Xth-2 class of SMK SMK Swasta Al-Ma'shum Sidodadi. The research instruments consisted of a validation sheet, a teacher and student response questionnaire, and a mathematical communication skills test. The results showed that the developed e-LKPD met the criteria for validity based on the validator's assessment, practicality based on teacher and student responses, and effectiveness with a classical completion rate of 82%. Thus, the TTW-based e-LKPD assisted by Liveworksheets is suitable for use in mathematics learning to help improve students' mathematical communication skills.

Abstract: Unpredictable weather changes often become a problem in the process of drying clothes, especially when it rains suddenly. This condition can cause clothes to get wet again by reducing the efficiency of time and energy. Therefore, this study aims to design and implement a prototype of an automatic clothesline based on the Internet of Things with an ESP32 microcontroller and an LDR sensor as a weather condition detector based on light intensity. The research methods used in this study include hardware and software design, system assembly, and testing the device's performance in various environmental conditions. The LDR sensor is used to read changes in light intensity, then the data is processed by the ESP32 to control the stepper motor as a driver for the automatic opening and closing mechanism of the clothesline. The results of the study show that all system components, including the LDR sensor, ESP32 microcontroller, stepper motor, buzzer, and power supply can work in an integrated and stable manner. This system has a 100% success rate with an average response time of around ±1 second, so it is able to respond to changes in environmental conditions quickly and effectively. Keywords: Prototype, Automatic clothesline, ESP32, LDR Abstrak: Perubahan cuaca yang tidak menentu sering menjadi permasalahan dalam   proses penjemuran pakaian, khususnya ketika hujan turun secara tiba-tiba. Kondisi tersebut dapat menyebabkan pakaian kembali basah dengan menurunkan efisiensi waktu serta tenaga. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan prototype jemuran pakaian otomatis berbasis Internet Of Things dengan mikrokontroller ESP32 serta sensor LDR sebagai pendeteksi kondisi cuaca berdasarkan intensitas cahaya. Metode penelitian yang digunakan dalam penelitian ini meliputi perancangan perangkat keras dan perangkat lunak, perakitan sistem, serta pengujian kinerja alat di berbagai kondisi lingkungan. Sensor LDR digunakan untuk membaca perubahan intensitas cahaya, kemudian data di proses oleh ESP32 untuk mengendalikan motor stepper sebagai penggerak mekanisme buka dan tutup jemuran secara otomatis. Hasil penelitian menunjukkan bahwa seluruh komponen sistem, meliputi sensor LDR, mikrokontroller ESP32, motor stepper, buzzer, dan catu daya dapat bekerja secara integrasi dan juga secara stabil. Sistem ini memiliki tingkat keberhasilan 100% dengan rata-rata waktu respon sekitar ±1 detik, sehingga mampu merespon perubahan kondisi lingkungan dengan cepat dan efektif. Kata kunci: Prototype, Automatic clothesline, ESP32, LDR

Abstract: This study aimed to develop, validate, and evaluate the effectiveness of a Project Based Learning (PjBL) based Human Anatomy and Physiology module in improving the Higher Order Thinking Skills (HOTS) of Biology Education students. The study employed a Research and Development (R&D) approach consisting of needs analysis, product design, development, expert validation, revision, and limited implementation stages. The validation process involved two instructional material experts and two subject matter experts using a five-point Likert scale assessment instrument. The effectiveness of the module was tested on 38 Biology Education students using a one-group pretest–posttest design. Data were analyzed using descriptive statistics, N-Gain analysis, and paired-sample t-test. The results indicated that the developed module demonstrated a very high level of feasibility. The instructional material experts awarded an average score of 4.80, while the subject matter experts assigned an average score of 4.74, both categorized as highly feasible. The implementation of the module resulted in an increase in students’ mean scores from 59.55 in the pretest to 79.74 in the posttest. The N-Gain value of 0.45 indicated a moderate improvement, with 68.42% of students achieving moderate to high levels of learning gains. Furthermore, the paired-sample t-test revealed a statistically significant difference between pretest and posttest scores (t = 8.651; p < 0.001). These findings suggest that the developed PjBL-based module is valid, feasible, and effective in enhancing students’ higher-order thinking skills. This study contributes to the development of innovative instructional materials that integrate project-based learning with Human Anatomy and Physiology content to support active learning and the development of 21st-century competencies among pre-service biology teachers. Keywords: Project Based Learning, Instructional Module, Human Anatomy And Physiology, Higher Order Thinking Skills, Biology Education.   Abstrak: Penelitian ini bertujuan untuk mengembangkan, menguji validitas, dan menganalisis efektivitas modul Anatomi Fisiologi Tubuh Manusia berbasis Project Based Learning (PjBL) dalam meningkatkan keterampilan berpikir tingkat tinggi (Higher Order Thinking Skills/HOTS) mahasiswa Pendidikan Biologi. Penelitian menggunakan metode Research and Development (R&D) yang meliputi tahap analisis kebutuhan, perancangan produk, pengembangan, validasi ahli, revisi, dan implementasi terbatas. Validasi dilakukan oleh dua ahli bahan ajar dan dua ahli materi menggunakan instrumen penilaian skala Likert 1–5. Uji efektivitas dilakukan pada 38 mahasiswa Program Studi Pendidikan Biologi melalui desain one-group pretest-posttest. Data dianalisis menggunakan statistik deskriptif, N-Gain, serta uji t berpasangan. Hasil penelitian menunjukkan bahwa modul yang dikembangkan memiliki tingkat kelayakan yang sangat tinggi. Hasil validasi ahli bahan ajar memperoleh skor rata-rata 4,80 dan validasi ahli materi memperoleh skor rata-rata 4,74, yang keduanya termasuk kategori sangat layak. Implementasi modul menunjukkan peningkatan rata-rata skor mahasiswa dari 59,55 pada pretest menjadi 79,74 pada posttest. Hasil analisis N-Gain sebesar 0,45 menunjukkan peningkatan pada kategori sedang, dengan 68,42% mahasiswa mencapai peningkatan pada kategori sedang hingga tinggi. Hasil uji t berpasangan menunjukkan perbedaan yang signifikan antara skor pretest dan posttest (t = 8,651; p < 0,001). Temuan ini mengindikasikan bahwa modul berbasis PjBL yang dikembangkan valid, layak, dan efektif dalam meningkatkan HOTS mahasiswa. Penelitian ini berkontribusi dalam penyediaan bahan ajar inovatif yang mengintegrasikan pembelajaran berbasis proyek dengan materi Anatomi Fisiologi Tubuh Manusia untuk mendukung pembelajaran aktif dan pengembangan kompetensi abad ke-21 pada calon guru biologi. Kata Kunci: Project Based Learning, Modul Pembelajaran, Anatomi Fisiologi Tubuh Manusia, Higher Order Thinking Skills, Pendidikan Biologi.

Abstract: This study examines the influence of digital competence, work motivation, and organizational culture on employee performance at PT Yuri Cakra Brothers. A quantitative descriptive approach was applied using multiple linear regression analysis. The population comprised all permanent employees of the company (approximately 120 individuals), with 92 respondents selected through the Slovin formula at a 5% margin of error. Data were collected using a structured Likert-scale questionnaire (1–5) and analyzed with SPSS 26. Prior to hypothesis testing, classical assumption tests, including normality, multicollinearity, and heteroscedasticity tests, were conducted to ensure model validity. The findings indicate that digital competence has a positive and significant effect on employee performance (t = 4.312; p = 0.000). Work motivation also positively and significantly affects employee performance (t = 3.875; p = 0.000). Likewise, organizational culture demonstrates a positive and significant effect (t = 5.127; p = 0.000). Simultaneously, the three independent variables significantly influence employee performance (F = 47.839; p = 0.000). The model yields an Adjusted R² of 0.607, suggesting that 60.7% of the variance in employee performance is explained by digital competence, work motivation, and organizational culture, while the remaining 39.3% is attributable to other factors beyond the scope of this study. Keywords: Digital Competence; Work Motivation; Organizational Culture; Employee Performance   Abstrak: Penelitian ini bertujuan menganalisis pengaruh kompetensi digital, motivasi kerja, dan budaya organisasi terhadap kinerja karyawan di PT Yuri Cakra Brothers. Penelitian menggunakan pendekatan deskriptif kuantitatif dengan analisis regresi linear berganda. Populasi penelitian mencakup seluruh karyawan tetap perusahaan yang berjumlah sekitar 120 orang, dengan sampel sebanyak 92 responden yang ditentukan menggunakan rumus Slovin pada tingkat kesalahan 5%. Data dikumpulkan melalui kuesioner terstruktur menggunakan skala Likert 1–5 dan dianalisis menggunakan SPSS 26. Sebelum pengujian hipotesis, dilakukan uji asumsi klasik yang meliputi uji normalitas, multikolinearitas, dan heteroskedastisitas untuk memastikan kelayakan model. Hasil penelitian menunjukkan bahwa kompetensi digital berpengaruh positif dan signifikan terhadap kinerja karyawan (t = 4,312; p = 0,000). Motivasi kerja juga berpengaruh positif dan signifikan terhadap kinerja karyawan (t = 3,875; p = 0,000). Demikian pula, budaya organisasi menunjukkan pengaruh positif dan signifikan terhadap kinerja karyawan (t = 5,127; p = 0,000). Secara simultan, ketiga variabel independen berpengaruh signifikan terhadap kinerja karyawan (F = 47,839; p = 0,000). Nilai Adjusted R² sebesar 0,607 menunjukkan bahwa 60,7% variasi kinerja karyawan dapat dijelaskan oleh kompetensi digital, motivasi kerja, dan budaya organisasi, sedangkan 39,3% sisanya dipengaruhi oleh faktor lain di luar penelitian ini. Kata kunci: Kompetensi Digital; Motivasi Kerja; Budaya Organisasi; Kinerja Karyawan