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Constitutional Relations Between The President, The House Of Representatives, And The Regional Representative Boards In Lawmaking After The Amendment Of The 1945 Constitution
Get PDFAmendments to the 1945 Constitution shifted legislation authority from the President to the House of Representatives. However, the strengthening of the House of Representatives into a \u27super parliament\u27 does not necessarily give it absolute power in lawmaking. Every draft bill, whether originating from the House of Representatives or the President, must be discussed and approved together to be enacted. From the outset, the 1945 Constitution did not apply the pure doctrine of Montesquieu\u27s trias politica. The separation of powers is understood in the sense of \u27distribution of power\u27, making the House of Representatives and the President both have legislation authority. The bicameral parliament system allows the Regional Representative Boards to be able to submit draft bills relating to autonomous authority and participate in joint discussions. The participation of the executive in the discussion of the draft bill with the legislative is because the executive holds the function of implementing the law. Thus, the draft bill must be discussed together to obtain the approval of both institutions. Once approved, each draft bill will then be approved by the President
Upaya Meningkatkan Partisipasi Pemilih Pemula Pemilu 2024 Melalui Sosialisasi Surat Suara di SMA PGRI 2 Denpasar
Get PDFThe 2024 elections to elect the President and Vice President, Members of the DPR RI, Members of the DPD RI, Members of the Provincial DPRD, and Members of the Regency/City DPRD will be held simultaneously throughout Indonesia on February 14th, 2024. According to data from the General Election Commission (KPU), the Millennial and Z generations dominate the vote in this election with 114 million voters or approximately with a total of 56% of all voters, so it can be ensured that for the success of the election, the participation of these two generations is very important. The service method was carried out by providing election outreach to 100 students at SMA PGRI 2 Denpasar on Tuesday, January 30 2024 at 10.30 - 11.00 WITA with the stages of providing material and a question and answer session. The results obtained were that many students already knew that the 2024 elections would take place and the location of each voting place. However, most students do not know details such as the types of ballot papers and the administrative procedures for transferring votes. After the socialization activities were completed, the students understood the message that their voting rights were important and that they should not abstain.Pemilu 2024 untuk memilih Presiden dan Wakil Presiden, Anggota DPR RI, Anggota DPD RI, Anggota DPRD Provinsi, dan Anggota DPRD Kabupaten/Kota akan dilaksanakan secara serentak di seluruh wilayah Indonesia pada tanggal 14 Februari 2024. Menurut data dari Komisi Pemilihan Umum (KPU), generasi Milenial dan Z mendominasi suara dalam Pemilu ini sebanyak 114 juta pemilih atau sekitar dengan total 56% dari keseluruhan pemilih, sehingga dapat dipastikan untuk menyukseskan pemilihan, keikutsertaan kedua generasi ini sangatlah penting. Metode pengabdian dilakukan dengan cara sosialisasi kepemiluan kepada 100 siswa-siswi ke SMA PGRI 2 Denpasar pada hari Selasa, 30 Januari 2024 pada pukul 10.30 - 11.00 WITA dengan tahapan pemberian materi dan sesi tanya jawab. Hasil yang diperoleh adalah banyak siswa-siswi yang telah mengetahui bahwa Pemilu 2024 akan berlangsung dan lokasi tempat pemilihan masing-masing. Namun, sebagian besar siswa-siswi tidak mengetahui secara detail seperti jenis-jenis surat suara dan tata cara administratif untuk melakukan pindah memilih. Setelah kegiatan sosialisasi selesai, siswa-siswi memahami pesan bahwa hak suara mereka penting dan jangan sampai melakukan golput
Peran Komunikasi Pemasaran Untuk Meningkatkan Loyalitas Pelanggan Di Red Studio
Get PDFIn today\u27s digital era, everything is digitalized in all aspects. The company can achieve success not only determined by the quality of products, services and services offered but also determined by the company\u27s ability to ensure customer loyalty to remain loyal to use the services and products marketed. This service aims to understand how the role of marketing communication in increasing customer loyalty at Red Studio. The methods used in this service are, 1. observation 2. active participation 3. guidance and mentorinf 4. practical projects. The results obtained show that by implementing a more effective marketing strategy in the future, the company can strengthen long-term relationships with consumers.Di era serba digital saat ini,semua serba digitalisasi dalam segala aspek. Perusahaan bisa meraih kesuksesan tidak hanya ditentukan oleh kualitas produk,layanan maupun jasa yang ditawarkan akan tetapi juga ditentukan oleh kemampuan perusahaan dalam menjamin loyalitas pelanggan untuk tetep setia memakai jasa dan produk yang dipasarkan. Pengabdian ini bertujuan untuk memahami bagaimana peran komunikasi pemasaran dalam meningkatkan loyalitas pelanggan di Red Studio. Metode yang digunakan dalam pengabdian ini yaitu, 1. observasi 2.partisipasi aktif 3. bimbingan dan mentorinf 4. proyek praktis. Hasil yang diperoleh menunjukkan dengan perusahaan menerapkan strategi pemasaran yang lebih efektif kedepannya bisa memperkuat hubungan jangka panjang dengan konsume
Penerapan Good Governance Pada Pengelolaan Dana Desa Di Desa Matagara Kecamatan Tigaraksa Kabupaten Tangerang
Get PDFThe aim of this research is to determine the application of good governance in managing village funds in Matagara Village, Tigaraksa District, Tangerang Regency. This study used qualitative research methods. Data collection uses observation, interviews and documentation methods. The results of this research show that the implementation of good governance in the management of village funds in Matagara Village has gone well based on the principle of accountability, makes an accountability report in the form of LPJ and uses the siskeudes application as a form of accountability for the village head. On the principle of effectiveness and efficiency, various projects or activities are in accordance with the needs of village communities. However, in principle, transparency is not yet optimal because the transparency provided by the government is only through billboards or banners in villages and information regarding budgets and activities in villages is not communicated through other information media such as village websites. In principle, village community participation is always involved by the government in every village meeting to convey input regarding their respective areas. In principle, village government rules and laws apply to activities or projects from the planning stage to accountability in accordance with applicable rules and laws
AUTOMATED EDIBILITY CLASSIFICATION OF MUSHROOMS USING MORPHOLOGY-BASED RANDOM FOREST ALGORITHM.
No full textJamur merupakan organisme yang memiliki keragaman morfologi yang tinggi, namun beberapa jenis di antaranya bersifat beracun dan membahayakan jika dikonsumsi. Kesamaan ciri fisik antara jamur yang dapat dimakan dan yang beracun sering kali menyulitkan proses identifikasi secara manual. Penelitian ini bertujuan mengembangkan sistem klasifikasi otomatis berbasis algoritma Random Forest untuk membedakan jamur edible dan poisonous, memanfaatkan seluruh 21 atribut (18 kategorikal, 3 numerik) dari dataset komprehensif Kaggle (61.069 entri). Metodologi penelitian mengikuti alur CRISP-DM yang dimodifikasi, dimulai dari pengumpulan data hingga implementasi. Tahap pra-pemrosesan data krusial dilakukan secara ekstensif, meliputi penanganan duplikasi data dan imputasi missing value (menggunakan median dan modus). Selanjutnya, transformasi label kelas (edible=0, poisonous=1) dan One-Hot Encoding diterapkan pada fitur kategorikal untuk representasi numerik yang tepat. Fitur numerik seperti cap-diameter dan stem-height dinormalisasi menggunakan Standard Scaling untuk menyeimbangkan kontribusi. Data kemudian dibagi 80:20 untuk pelatihan dan pengujian. Model Random Forest dikembangkan dengan parameter optimal (n_estimators=200, max_depth=15, class_weight="balanced") untuk efisiensi dan robustabilitas terhadap ketidakseimbangan kelas. Hasil evaluasi menunjukkan performa sangat baik dengan akurasi keseluruhan 99,34%, serta nilai precision, recall, dan f1-score yang seimbang pada 0.99 untuk kedua kelas. Analisis feature importance mengidentifikasi stem-width, stem-height, dan cap-diameter sebagai atribut paling berpengaruh. Learning curve menunjukkan stabilitas model tanpa overfitting. Implementasi pada sampel jamur baru juga mengkonfirmasi kemampuan prediksi yang konsisten, menjadikan model ini layak sebagai sistem pendukung keputusan otomatis dalam deteksi jamur beracun.Mushrooms exhibit high morphological diversity; however, some species are poisonous and harmful if consumed. The physical similarities between edible and poisonous mushrooms often complicate manual identification. This research aims to develop an automated mushroom classification system based on the Random Forest algorithm to distinguish between edible and poisonous mushrooms. It leverages all 21 attributes (18 categorical, 3 numerical) from a compr[1]ehensive Kaggle dataset comprising 61,069 entries. The research methodology follows a modified CRISP-DM workflow, from data collection through to implementation. Crucial data preprocessing steps were extensively performed, including handling data duplicates and imputing missing values (using median and mode). Subsequently, class labels were transformed (edible=0, poisonous=1), and One-Hot Encoding was applied to categorical features for appropriate numerical representation. Numerical features such as cap-diameter and stem-height were normalized using Standard Scaling to balance their contributions. The data was then split 80:20 for training and testing. The Random Forest model was developed with optimal parameters (n_estimators=200, max_depth=15, class_weight="balanced") for efficiency and robustness against class imbalance. Evaluation results demonstrated excellent performance with an overall accuracy of 99.34%, along with balanced precision, recall, and F1-score values of 0.99 for both classes. Feature importance analysis identified stem-width, stem-height, and cap-diameter as the most influential attributes. The learning curve indicated model stability without significant overfitting. Implementation on new mushroom samples also confirmed consistent predictive capability, making this model suitable as an automated decision support system for detecting poisonous mushrooms.
Keywords: Musrom, Clasification, Random Forest, Morphology, Machine Learnin
Kolaborasi Aktor Dalam Formulasi Kebijakan Pengentasan Kemiskinan Ekstrem Di Kota Serang
Get PDFPoverty is generally defined as the lack of financial resources necessary to meet basic needs, such as food, shelter, and health care. However, poverty is not only limited to financial deprivation, but also includes limited access to essential services such as education, health, and nutrition, which exacerbates the impact of income poverty. Extreme poverty is a condition in which individuals or groups live below the international poverty line, with an income of less than 1.90 per day based on purchasing power parity. Therefore, this research examines the equalization and collaboration of actors and the formulation of poverty alleviation policies in Serang City. The method employed is a qualitative approach that utilizes both primary and secondary data, along with the Hierarchical Analysis Process (AHP) power analysis technique, to inform a policy strategy. The results showed that the actors involved in poverty alleviation in Serang City are the Central Government, Banten Provincial Government, Serang City Government, Private Sector, Educational Institutions, and Non-Governmental Institutions/Community Organizations. Then, the strategy of providing access to education and economic opportunities is a priority to be formulated and implemented in order to reduce sustainable povert
Green Mussel Shells as Liquid Organic Fertilizer (CARAJA): Efforts to Utilize Local Potential in Banyu Urip Village Gresik
Get PDFBanyu Urip Village is one of the villages located in the coastal area of Ujung Pangkah District, Gresik Regency. The local potential of Banyu Urip Village is green mussels, which are a result of the sea catch of fishermen in the local village. This potential is also a problem due to the accumulation of wasted green mussel shell waste that has not been managed optimally. With this problem, the community service team carried out community service activities aimed at providing alternative solutions as well as community empowerment. The method used in the community service activity of making green shell liquid organic fertilizer "CARAJA" is Participatory Action Research (PAR) with subjects of ± 25 people. The community service activities include 4 stages, namely 1) observation with partners, 2) socialization related to the management of green mussel shells, 3) training in making "CARAJA" liquid organic fertilizer and 4) experiments/trials on the use of liquid organic fertilizer on the growth of mustard seedlings. The results of the community service analysis have shown changes in mustard green plant height when using liquid organic fertilizer, and local communities become knowledgeable and skilled in participating in various stages starting from observation, socialization, and training to experiments on the use of liquid organic fertilizer made from green mussel shell powder (CARAJA). In the final stage, with the existence of experiments/trials, additional findings were added to strengthen the fact that the liquid organic fertilizer "CARAJA" can be managed into a product that has a selling value and shows a significant influence in increasing the growth of mustard greens (Brassica Juncea) and optimizing the management of local potential in the village
PENDAMPINGAN PEMBUATAN NOMOR INDUK BERUSAHA (NIB) SEBAGAI LEGALITAS USAHA DALAM UPAYA PENINGKATAN VOLUME PENJUALAN BAGI UMKM DI DESA KRAMATWATU KECAMATAN KRAMATWATU KABUPATEN SERANG
No full textUMKM merupakan tulang punggung perekonomian nasional, namun masih banyak yang belum memiliki legalitas usaha yang memadai. Salah satu bentuk legalitas tersebut adalah Nomor Induk Berusaha (NIB) yang diterbitkan melalui sistem Online Single Submission (OSS). Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan pendampingan dalam pembuatan NIB bagi pelaku UMKM di Desa Kramatwatu, Kecamatan Kramatwatu, Kabupaten Serang, sebagai upaya meningkatkan legalitas usaha sekaligus mendorong peningkatan penjualan. Metode pelaksanaan meliputi sosialisasi regulasi, pelatihan teknis penggunaan OSS, dan pendampingan individu dalam proses pembuatan akun dan penerbitan NIB. Hasil kegiatan menunjukkan bahwa sebagian besar peserta berhasil memperoleh NIB dan menyatakan adanya peningkatan kepercayaan konsumen serta peluang kerja sama dengan pihak lain setelah usaha mereka memiliki legalitas formal. Kegiatan ini membuktikan bahwa pendampingan pembuatan NIB tidak hanya memperkuat posisi hukum pelaku usaha, tetapi juga berdampak pada akses pasar dan peningkatan omzet penjualan
PENINGKATAN KAPASITAS UMKM LEVEL UP JAKARTA MELALUI PELATIHAN PEMBUATAN HARGA POKOK PRODUKSI (HPP)
Get PDFUMKM Level Up adalah program yang diselenggarakan oleh kementrian komunikasi dan informatika dalam rangka mendorong sisi digitalisasi guna memperluas akses pemasaran dan meningkatkan daya saing. Kegiatan ini di ikuti oleh 50 peserta dari berbagai jenis usaha, fokus kegiatan yang di lakukan adalah pelatihan dan webinar penyusunan harga pokok produksi (HPP). Penyusunan harga pokok produksi (HPP) sangat berguna untuk menenrukan harga jual dan memprediksi berapa besar keuntungan yang akan di dapat. Kegiatan ini dilakukan dalam 2 sesi, sesi 1 berisikan penyampaian materi dan sesi ke-2 di isi dengan tanya jawab dan diskusi seputar permasalahan keuangan pelaku umk
APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS (CNN) FOR HEPATITIS C VIRUS (HCV) DISEASE DETECTION
No full textHepatitis C is a disease that attacks the liver and can progress to more serious conditions, such as cirrhosis or liver cancer, if not diagnosed and treated properly. Conventional diagnostic methods for Hepatitis C often face challenges in terms of efficiency and accuracy, so an innovative AI-based approach is needed to improve early detection. In this study, we apply a 1D Convolutional Neural Network (CNN) to classify Hepatitis C patients, using a dataset from Kaggle consisting of 615 samples with various medical parameters. The dataset goes through a series of preprocessing stages, including data cleaning, normalization, and feature transformation, before being applied to a 1D CNN model. The model is trained using the Adam optimizer, with ReLU activation functions in the convolution layer and sigmoid in the output layer. Model performance is evaluated through accuracy, precision, recall, and F1-score metrics. The results show that the developed 1D CNN model achieves an accuracy of 75% in detecting Hepatitis C. Although these results show promising potential, there is still room for improvement through exploration of more complex architectures or the use of larger datasets. Thus, this research is expected to make artificial intelligence an effective tool in the diagnosis of Hepatitis C, increasing accuracy and efficiency in the process.
Keywords: Hepatitis C, 1D CNN, Deep Learning, Disease Classification, Medical DiagnosisHepatitis C (HCV) is a serious liver infection that can progress to cirrhosis or cancer, especially if early diagnosis is neglected. While conventional diagnostic methods such as ELISA are accurate, they are often limited in terms of efficiency and accessibility. This study introduces an innovative approach using a one-dimensional convolutional neural network (1D-CNN) for HCV disease classification, utilizing a Kaggle dataset consisting of 615 patient samples. The methodology includes data preprocessing such as handling missing values and transforming categorical variables to numeric values to ensure data readiness. The 1D-CNN model was trained using the Adam optimizer with ReLU activation functions in the convolution layer and sigmoid in the output layer. Model performance was comprehensively evaluated through accuracy, precision, recall, and F1-score metrics. The results showed that the 1D-CNN model achieved an accuracy of 83.74% on the training data and 81.30% on the testing data after hyperparameter tuning. This improvement is significant compared to the initial accuracy of only around 52%. However, the model exhibits a strong bias towards the majority class (Blood Donor), with very poor performance on minority classes such as Hepatitis, Fibrosis, and Cirrhosis. Nonetheless, this study contributes to the exploration of 1D-CNN for non-image medical data, which is still rarely studied. We conclude that despite the model\u27s potential, further developments such as data balancing are needed to improve the model\u27s overall generalization and accuracy.
Keywords: Deep Learning, Disease Classification, Hepatitis C, 1D CNN, Medical Diagnosi