Culture and social life are one particle that becomes a binding unity, culture faithfully escorts the development of human civilization from pre-Islamic times to the perfect Islamic era as a teaching from ancient Greece to modern times like today. From this long process, culture basically has values that can traditionally be passed on to the next generations. Indonesia is a country that has a lot of culture, which consists of a collection of cultures that exist throughout the Indonesian homeland in the form of local culture. Foreign cultures continue to enter unstoppably into Indonesia which can erode or dilute the local culture owned by the Indonesian people. This problem lies in the need for the government's role in protecting Indonesian culture in the era of globalisation, such as in preserving local culture, the government must facilitate all forms of artistic activities held by the community, besides that the government also has a role to provide support in activities related to culture and open as much as possible the participation of young people or adolescents in maintaining its preservation. The research method used is descriptive method, the foundation of the research method is the philosophy of postpositivism. It aims to be able to determine whether the social and cultural life movement will succeed in having a broad impact and provide changes in living standards as expected.

With a focus on legal certainty and investor protection, as well as the balance between tax obligations and corporate social responsibility (CSR), this study looks at the strategic role of FDI in Indonesia's economic growth after the Job Creation Law was put into effect. The case study of Apple's investment strategy, which includes the Apple Developer Academy, is used to highlight an innovative investment model. The problem formulation includes changes in the level of PMA after the Job Creation Law, the role of legal regulations in protecting foreign investors, the impact of Law No. 6 of 2023 on strategic sectors, and the balance between tax obligations and CSR. Utilising the Apple case study, regulatory analysis, and literature review, the normative juridical technique with a case study methodology was applied. To comprehend the legal and economic ramifications of the Job Creation Law's implementation on foreign investment in Indonesia, a qualitative data analysis was carried out.
 
Abstrak
Penelitian ini mengkaji peran strategis Penanaman Modal Asing (PMA) dalam pertumbuhan ekonomi Indonesia pasca implementasi Undang-Undang Cipta Kerja. Tujuannya adalah menganalisis dampak undang-undang ini terhadap daya tarik investasi asing, khususnya terkait kepastian hukum dan perlindungan investor, serta keseimbangan antara kewajiban pajak dan Tanggung Jawab Sosial Perusahaan (CSR). Studi kasus strategi investasi Apple, termasuk Apple Developer Academy, digunakan untuk menyoroti model investasi inovatif. Rumusan masalah mencakup perubahan tingkat PMA setelah UU Cipta Kerja, peran regulasi hukum dalam melindungi investor asing, dampak UU No. 6 Tahun 2023 terhadap sektor strategis, dan keseimbangan kewajiban pajak dan CSR. Metode yuridis normatif dengan pendekatan studi kasus digunakan, memanfaatkan studi pustaka, analisis peraturan perundang-undangan, dan studi kasus Apple. Analisis data dilakukan secara kualitatif untuk memahami implikasi hukum dan ekonomi dari implementasi UU Cipta Kerja terhadap investasi asing di Indonesia.

The Indonesian government has decided that the Corona virus desease 2019 (covid 19) as a pandemic disaster. This decision is followed by applying effort to cut off the spreading of the virus through the implementation of social distancing, restricted traveling, isolation, preventing public ocation, closured public services and limiting the using of public facilities. This condition has serious impact on the implementation of public service such as integrated healthcare center (Posyandu), public health center (Puskesmas) and the using of public health facilities as well. Most parents worried and hesitated about to visit Posyandu to do general health check up of their children. And also there are only view employess and administration staffs coming to the office. Some officer and medical staffs also are less. Nevertheless, the goverment (the minister of health) has provided a technical guide to the Puskesmas and Posyandu to run the health activity services during the pandemic, so that the health services that can be done to the children and mother, still can be done by the program of “mobile posyandu”. The study aim to discuss the implementation of posyandu services in the time of pandemic through the operation of mobile posyandu. This study focuses on the services of mobile posyandu and held in 8 different places at Lemah Mulya Village District Majalaya Karawang West Java. The study is using a qualitative method and the data collections is held by holding interviews, observation, focus group discussion (FGD) and litelature study. The result showed that the implementation of mobile Posyandu during the covid 19 pandemic is quite positive and has been done by rescheduling and delivering tasks and duties into each group and each Posyandu volunteer. So that the services of good health for children and mother can stil be done and going on with the strict imposement of health protocol within the pandemic.
 
 

Penelitian ini yang menjadi objek adalah perusahan sub sektor konsumsi pada perusahaan manufaktur yang terdaftar pada Bursa Efek Indonesia (BEI) tahun 2020-2023. Di Indonesia sendiri perusahaan manufaktur sub sektor konsumsi sangat berkembang dengan pesat, hal ini dapat dilihat dari perusahaan yang terdaftar di Bursa Efek Indonesia dari tahun ke tahun semakin banyak. Sehingga peneliti ingin mengetahui pengaruh dari ROA (Return on Aset), ROE (Return On Equity), DER (Debt To Equity Ratio), dan CR (Current Ratio) terhadap harga saham pada perusahaan manufaktur sektor konsumsi yang terdaftar di Bursa Efek Indonesia selama periode 2020-2023. Populasi penelitian mencakup seluruh perusahaan manufaktur pada sektor konsumsi yang sudah terdaftar di BEI dengan tahun data yang di ambil 2020 sampai dengan 2023 berjumlah 180, kemudian untuk analisis data dilakukan menggunakan aplikasi SPSS versi 23. Untuk teknik pengambilan sampel penelitian ini ialah menggunakan teknik non-probabilitas dengan metode purposive sampling, selanjutnya terkumpul 60 sampel penelitian berdasarkan data dari 15 perusahaan manufaktur dengan periode waktu selama 4 tahun.  Hasil penelitian ini menunjukkan bahwa variabel pada ROA, ROE, DER, dan CR memiliki pengaruh yang positif serta signifikan terhadap harga saham. Temuan ini tentu relevan untuk perusahaan sektor makanan dan minuman yang terdaftar di BEI selama periode tahun 2020 sampai dengan tahun 2023.

Hypertension is a problem throughout the world and is one of the main risk factors for cardiovascular disease. Hypertension or high blood pressure can be caused by several factors, both factors that can be changed and cannot be changed. This study aims to find out the percentage of the population with hypertension who receive health services in each region in West Nusa Tenggara province based on age and gender. This research method uses a descriptive research type with samples, namely data on residents suffering from hypertension in 10 districts in West Nusa Tenggara (NTB) Province in 2019-2021 with a sampling technique, namely a non-probability technique of purposive sampling type. The research results showed that of the 119,500 participants consisting of men and women, the majority of participants were over 18 years old. male participants numbered 135,453 while the number of women was 142,889. The results of the research obtained a distribution of respondents based on gender between men (62,09%) and women (74,79%). Hypertension in teenagers needs to be watched out for. Suggestions, it is necessary to carry out early prevention efforts related to diet and lifestyle in adolescents, including: changing diet, limiting the use of salt to 4-6 grams per day, foods containing baking soda, seasonings and food preservatives, reducing food intake. which contains high cholesterol, stop smoking, drinking alcohol, and exercise regularly.

Diagnostic codification must fulfill 10 characteristics of quality data, namely one of which is accurate, namely the truth and validity of data values. External Causes are external causes of fracture cases which classify based on the place and activity of the incident. It is very important that external causes codes are documented in medical record files for financing analysis, health services and reporting. The purpose of this study was to determine the accuracy of the fracture diagnosis code and external causes at Mardi Waluyo Hospital, Blitar City in 2021. The research method used a retrospective descriptive. The sampling technique is simple random sampling, with 52 samples. The implementation of coding at Mardi Waluyo Hospital, Blitar City, was carried out by coder officers and was in accordance with the policies and standard operating procedures at the hospital. The level of accuracy of the fracture diagnosis code with a percentage of 85% is included in the category that needs improvement and external causes with a percentage of 6% is included in the unsatisfactory category. The inaccuracy of the external causes code is caused by the use of the 5th character or the activity code that has not yet been coded. The inaccuracy of the officers in coding caused the resulting code to be inaccurate, so it was suggested that filling out medical record documents must be filled in completely and clearly to support proper and accurate coding of fractures and external causes so as to produce a better percentage of accuracy.

Breast cancer is cancer that forms in the cells of the breast. It is the most common cancer in women and the leading cause of cancer deaths in women worldwide. Breast cancer is usually divided into two types: benign, or usually called benign and malignant, or usually called malignant. Benign cancers are usually characterized by small, round, tender lumps. In the fields of medicine, finance, marketing, and social science, data mining is a popular tool for performing proven analysis. This study will compare K-Nearest Neighbor (KNN), Naive Bayes, and Decision Tree C4.5 approaches for classifying breast cancer. The problem of this research is which algorithm has a high level of accuracy that can be used with breast cancer datasets and can provide information about patterns or models for early detection of breast cancer. The results of the research conducted using CRISP-DM show that K-Nearest Neighbor (KNN) has the highest accuracy value with 97.14% and its AUC value is 0.976. The AUC value also showed excellent classification, with an AUC value between 0.90 and 1.00.

Smart waste management and recycling have become critical issues in urban planning and environmental sustainability due to the increasing volume of waste generated by modern societies. In this study, we investigated the performance of Support Vector Machine (SVM) and Neural Network (NN) methods in an Arduino-based waste sorting system. Our testing phase revealed exceptional performance, with SVM achieving an accuracy of 92% and NN achieving 96%, alongside perfect precision, recall, and F1-score metrics. The consistent True Positive (TP) results across all waste categories underscored the system's capability to accurately direct waste into correspondingcolored bins. These findings highlight the significance of automated waste management systems in promoting effective waste sorting practices and facilitating sustainable recycling efforts. Moreover, advancements in technology and machine learning algorithms offer promising prospects for further enhancing the efficiency and scalability of such systems, thereby contributing to a cleaner and healthier environment for future generations. Future research in smart waste management could focus on exploring additional machine learning algorithms, advanced sensor technologies, and Internet of Things integration. Investigating alternative algorithms beyond SVM and NN, adopting advanced sensors like hyperspectral imaging or lidar, and incorporating IoT devices for real-time monitoring could enhance waste sorting accuracy and scalability.

SMK Nahdlatul ‘Ulama (NU) 01 Kendal adalah Sekolah Kejuruan kelompok Bisnis – Manajemen dan Pariwisata dibawah naungan Lembaga Pendidikan Ma’arif NU Kabupaten Kendal. SMK NU 01 Kendal memiliki 7 (tujuh) kompetensi keahlian salah satunya yakni Rekayasa Perangkat Lunak. Jurusan Rekayasa perangkat lunak atau biasa disebut RPL menawarkan beberapa keahlian dibidang teknologi informasi berupa pemrograman, selain itu juga diajarkan mengenai desain dengan menggunakan Photoshop, Corel Draw, dan lainnya. Desain animasi tiga dimensi (3D) belum menjadi muatan yang diajarkan oleh SMK NU 01 Kendal dalam jurusan RPL. Di era ini, desain animasi 3D menjadi fokus bidang yang menarik dalam industri multimedia. Maka pada PkM ini akan memberikan pelatihan membuat animasi 3D menggunakan aplikasi Blender. Aplikasi Blender merupakan salah satu program animasi 3D yang sifatnya open source. Aplikasi Blender digunakan untuk membuat model 3D, animasi, efek visual, model cetak 3D, dan permainan video. Hasil dari kegiatan yang di ikuti oleh 12 siswa RPL ini menunjukan bahwa ada peningkatan kemampuan mengetahui aplikasi blender dan memahami membangun desain 3D dari sebelum kegiatan hanya 9,7% yang merespon denga jawaban Ya, namun setelah pelatihan dalam hasil post-test menunjukkan adanya peningkatan dari 12 responden yang menjawab Ya menjadi sebesar 92,7%. Hal ini memberikan arti bahwa pengabdian yang kami lakukan berhasil.

Vehicle detection is the artificial intelligence that can help us in transportation highway systems like counter vehicles passing through the road on Eid Mubarak day etc. The object in this case is divided into six classifications there are car, motorbike, van, truck, and three-wheel. On the dataset vehicle is mostly an image of a car that we get from Kaggle. To solve vehicle detection problems such as poor vehicle detection and reduced detection accuracy, we provide a new vehicle detection with a dataset at kaggle. The clustering process consists of steps in which input images are transformed into morphometrics. The next step is to classify the image data using the K-Means algorithm. The images grouped by this detection are vehicles. The first step is to determine the randomly drawn mean or center point of two image data values ??in the database. If there is no data transfer, the group is considered stable and group creation is completed. Seven vehicle image data are used to test this application. And the result of our experiment on vehicle detection is about 85.7 % accurate