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Malnutrition has always been a global problem and is the main cause of child mortality in developing countries. Nutritional status is a measure of success in meeting the nutritional needs of toddlers which can be seen from the achievement of toddler's weight. The short-term effects of malnutrition on toddlers are physical growth disorders in children, metabolic disorders, brain development disorders, and intelligence disorders. In the long term, malnutrition will cause a decrease in learning outcomes and cognitive abilities, decreased immunity, the risk of developing diabetes, heart and blood vessel disease, obesity, stroke, cancer, and disability in old age. To find out about the growth and development of early childhood, especially in relation to the development of early childhood nutritional values, regular measurements of the height and weight of toddlers from an early age are carried out through Posyandu activities. Toddler height and weight data will be grouped according to the nutritional characteristics of each toddler. In this study, infants will be clustered based on their nutritional characteristics using the K-Means algorithm clustering method. Based on the evaluation results, the number of clusters 3 is more optimal than the number of clusters 5 in the toddler dataset used in the study. It is hoped that the research results obtained can serve as a basis or recommendation material for posyandu throughout Indonesia to determine the nutritional status of the under-five age group, so that the handling is more appropriate and can help prevent malnutrition in under-fives.

Basically, the ingredients for forming concrete consist of cement, water, and aggregate, namely fine aggregate and coarse aggregate. The aggregates commonly used are natural aggregates, namely sand as fine aggregate and gravel or crushed stone as coarse aggregate. Sand as fine aggregate is obtained from mining processes in nature, especially in Indragiri Hulu district, sand mining occurs almost along the Indragiri river. Rock ash is generally dark in color (blackish gray), and consists of fairly coarse grains. When compared to sand, rock ash has a cheaper price. The method used in this study is the experimental method, namely research that aims to investigate causal relationships between one another and compare the results so as to make an innovation. The results of the tests that have been carried out by the author on variations in the addition of stone ash to the concrete mixture for fine aggregate with variations of 25%, 50% and 75%. The results of laboratory tests in this study found that the optimum percentage of rock ash as a substitute for sand was a variation of 50% rock ash with a compressive strength of 28 days of 19.60 Mpa. Rock ash on 50% test specimen can be used as a substitute for sand because in terms of compressive strength with the quality provisions K-225 meets the requirements with a value of 19.60 MPa.    

As an organization engaged in the mining sales sector and in line with the rapid economic development in Indonesia, the sales sector is also growing rapidly over time. In an effort to regulate the quality of mining in Indonesia, the government has issued policies in the form of provisions and legislation. Law regarding mineral and coal mining No.4 of 2009 along with government regulation No.23 of 2010.  

There is demand for transportation services from other sectors (such as agriculture, industry, trade, mining, fisheries and others) causing the provision of transportation services (Adisasmita: 2011). This is like what happened in the Pandaan area, East Java. Due to the large number of factories producing goods needed by the community, especially bottled drinking water, the demand for transportation services is also increasing. So transportation capacity must be provided in balance with demand, in order to be able to serve the development of activities in other sectors.  

The purpose of this study was to determine the effect of capital structure, liquidity, profit growth, and company size on earnings quality in mining sector companies listed on the Indonesia Stock Exchange for the 2019-2021 period. Earnings Quality Variables using Quality of Income. The sample method used was purposive sampling. From the population in the Mining Sector Companies during the 2019- 2021 period, 13 companies that met the sample criteria were taken. The analytical tool used is multiple linear regression analysis. Data processing in this study used the SPSS (Statistic Package for the Social Sciens) software program 25.00 for Windows. The results showed that capital structure, profit growth, and company size had no negative and insignificant effects on earnings quality. Liquidity has a positive and significant effect on earnings quality. The influence of Capital Structure, Liquidity, Profit Growth, and Company Size together has a positive and significant effect on earnings quality in mining sector companies listed on the IDX.

This study aims to determine the role of information technology in public sector accounting in preventing fraud that occurs in public sector organizations. The research conducted was a literature review research based on articles appropriate to the research topic for further analysis. The result of this research is that there are fraud prevention methods which include technical strategies and preventive strategies. The technical strategy includes efforts to prevent fraud through the use of privacy officer services, IoT access, managing data access, establishing timely reporting, and controlling data in real time. The preventive strategy is in the form of developing a fraud detection system that is run using machine algorithms, data mining, and meta learning methods.

Toko ellia umami berupaya meningkatkan produksi produknya agar lebih banyak orang mengetahuinya, mirip dengan berapa banyak orang yang membeli dan menjual produk yang sama secara bersamaan. Toko Ellia Umami menjual berbagai macam barang, yang menimbulkan kemungkinan data tidak konsisten dan tidak dapat disamakan. Beberapa produk mungkin lebih populer dari yang lain, oleh karena itu toko ellia umami harus mengetahui aturan yang mengatur penjualan dan transaksi serta produk itu sendiri. Algoritma FP-Growth adalah satu-satunya algoritma penambangan data yang digunakan untuk memeriksa persyaratan transaksi data. Di toko ellia umami, FP-Growth dapat digunakan untuk menganalisis data transaksi pembelian produk dan mengidentifikasi transaksi yang tertunda.Tujuan dari tugas akhir ini adalah mengimplementasikan algoritma FP-Growth untuk menginformasikan kepada toko ellia umami tentang rekomendasi produk dan layanan berdasarkan data dari transaksi yang melibatkan penjualan toko ellia umami. Berdasarkan hasil akhir, pola hubungan data dari toko ellia umami dengan tingkat minimum (support 0,1) dan (confiden 0,1) menunjukkan bahwa jika pelanggan membeli Libby M, pelanggan juga akan membeli Celpen dan anak.

This research leads to the Effect of the Ratio of Roa, Roe on Profit Building in Mining Companies Listed in the Jakarta Islamic Index for 2018-2022. The benefit of this research is to find out whether there is an effect of the Roa, Roe Ratio on Profit Growth in Mining Companies Registered in the Jakarta Islamic Index for 2018-2022. The analytical method used in this study is panel data regression. and processed data used in this study by utilizing Eviews 12 and Microsoft Excel 2010 software. The sampling method used was purposive sampling, namely by considering several criteria specified in this research. The research results show that Roa has an effect on profit growth and Roe has no effect on profit growth, while together (simultaneously) Roa and Roe have an effect on profit growth in mining sector companies in JII 2018-2022Keywords: net income, total assets and share price

Akomodasi merupakan orientasi sosial yang bermakna keutuhan sosial demi menjauhi serta mendamaikan kegentingan, pertikaian yang saling berkaitan. Seumpama bentuk kegiatan akomodasi yang bermanfaat mempersiapkan perlengkapan guna melengkapi keperluan. provinsi jawa barat terdapat tempat wisata yang ramai dikunjungi oleh wisatawan nusantara dan mancanegara oleh sebab itu pengunjung menggunakan fasilitas akomodasi yang tersedia di setiap daerah, wisatawan nusantara ramai menginap di villa sedangkan wisatawan mancanegara lebih memilih hotel berbintang. Penelitian ini memfokuskan bagaimana pengelompokan wisatawan daerah wisata akomodasi dan jenis wisatawan terbanyak yang ramai berkunjung menggunakan algoritma k-means, analisis ini memakai metode Knowledge Discovery in Database (KDD). Teknik pengumpulan data atau pengumpulan data bersumber dari Dinas Pariwisata dan Kebudayaan Provinsi Jawa Barat. Dengan tujuan kiranya menjadi pengetahuan untuk wisatawan serta mampu mempublikasikan wisata di media sosial dan diharapkan akan lebih meningkat jumlah wisatawan yang berkunjung dan meningkatnya pembangunan sarana dan prasarana di setiap daerah akomodas.Hasil dari penelitian ini bahwa daerah akomodasi yang ramai dikunjungi adalah Kota Bandung dengan jenis wisatawan yang datang yaitu pengunjung  dalam negeri (Nusantara).

The rapid growth of e-commerce in Indonesia has generated a massive and continuous volume of product reviews. This user-generated content is vital for business intelligence, yet its sheer scale makes manual analysis inefficient, subjective, and practically impossible. Automated sentiment analysis is therefore crucial for businesses to efficiently understand customer feedback and market perception. This research addresses this gap by implementing the Naïve Bayes Classifier (NBC) algorithm to automatically classify the sentiment of Indonesian-language e-commerce product reviews. This study utilized a dataset of 2,000 reviews collected from a major e-commerce platform's "Electronics" category. The data underwent critical text preprocessing stages (case folding, tokenizing, stopword removal, and stemming using the Sastrawi library) to handle the complexities of informal Indonesian text. The dataset was split using an 80/20 ratio, resulting in 1,600 training reviews and 400 testing reviews. Model performance was then evaluated using a Confusion Matrix, focusing on the key metrics of Accuracy, Precision, and Recall. The test results showed excellent performance, achieving an Accuracy of 90.00%, Precision of 91.93%, and Recall of 95.00%. These results demonstrate that the Naïve Bayes algorithm, when supported by robust preprocessing, is a highly effective, reliable, and computationally efficient method for this task, providing a valuable tool for e-commerce stakeholders.

Criminal provisions in a statutory regulation are certain doses or remedies as a means of achieving the formulated goals. The purpose of this article is to examine and analyze the inconsistency of the material content of the criminal provisions against the formulation of the objectives of legal certainty in the Law of the Republic of Indonesia No. 3 of 2020 concerning Mineral and Coal Mining. The research method uses a normative juridical method. Secondary data in the form of primary legal data on laws and regulations related to the criminal provisions of the Minerba Law is elaborated so that the adequacy of the content of the criminal provisions is able to test the clarity of the objectives of legal certainty. The results found that there were inconsistencies in criminal provisions as a means of achieving goals in the formulation of guaranteeing legal certainty. The application of Article 162 of the Mineral and Coal Law is subjective and tends to criminalize members of the community around mineral and coal mining. This fact proves that the objective of legal certainty is objective, ambiguous with subjective criminal means. The main article of criminal provisions in the Minerba Law is Article 158 which is systematically constructed with Article 35. Basically, the criminal provisions are used as the legal regime for licensing in the strategies and techniques of government control and control in the mineral and coal sector.

Indonesia merupakan negara dengan beberapa kota di setiap provinsinya, namun tentunya setiap kota mempunyai tingkat inflasi yang berbeda setiap tahunnya. Dengan banyaknya data inflasi di Indonesia, sulit bagi pemerintah untuk mengkategorikan angka inflasi. Penulis berinisiatif melakukan penelitian tentang mengelompokkan nilai inflasi pengeluaran di jawa barat. Tujuan membuat laporan ini merupakan untuk memperoleh informasi dengan kualitas terbaik dari data yang diproses. Proses ini di harapkan dapat membantu pemerintah dalam mengetahui nilai inflasi berdasarkan kelompok pengeluaran tertinggi dan terendah di Jawa Barat. Metode yang digunakan adalah metode k-means clustering. Penelitian ini juga di dukung menggunakan salah satu perangkat lunak atau tools untuk mengolah data mining yaitu RapidMiner. Didapat hasil cluster terbaik yaitu 5 cluster berdasarkan nilai DBi 0,063. Dimana yang termasuk ke dalam cluster tersebut adalah cluster 0, cluster 2, dan cluster 4 dengan tingkat inflasi rendah berjumlah 5 Kabupaten/Kota. Dan yang termasuk ke dalam tingkat inflasi tinggi adalah cluster 1 dan cluster 3 berjumlah 2 Kabupaten/Kota. Hasil dari data ini juga menunjukkan nilai akurasi sebesar 100%, sehingga bisa disimpulkan jika algoritma k-means mempunyai nilai akurasi tinggi.

Berdasarkan data yang dipublikasikan oleh Badan Penanggulangan Bencana Daerah (BPBD), Jawa Barat merupakan provinsi dengan jumlah kejadian bencana alam tertingggi di Indonesia sebanyak 3006 kejadian untuk periode 2015-2021. Kondisi ini mengharuskan BPBD (Badan Penanggulangan Bencana Daerah) dan Pemda Provinsi Jawa Barat untuk memperhatikan penanggulangan bencana serta penanganan dampak bencana. Bencana-bencana yang terjadi dapat mengakibatkan dampak yang merusak berbagai bidang. Salah satu dampak yang sangat berpengaruh adalah dampak kerusakan rumah. Kerusakan rumah akibat bencana merupakan dampak yang menyangkut kerusakan pada bidang ekonomi, sosial dan lingkungan. Karena itu, penanganan dampak kerusakan rumah harus dilakukan secara matang, tepat serta cara penanganannya harus berkembang setiap saat. Agar kedepannya bisa melakukan penanganan seperti yang diinginkan, maka perlu diketahui klaster/kelompok bencana berdasarkan dampak jumlah kerusakan rumah berdasarkan kondisi akibat bencana yang telah terjadi di Jawa Barat, dengan cara melakukan pengimplementasian algoritma K-Means clustering untuk mengklasterisasikan data jumlah kerusakan rumah berdasarkan kondisi yang diambil dari portal resmi data terbuka milik Pemda Provinsi Jawa Barat yaitu Open Data Jabar. Dalam kaitannya dengan data dampak bencana, teknik pengelompokan pada data mining sangat berguna dalam mengelompokkan data dampak bencana berupa keruskan rumah berdasarkan kemiripannya. Proyek tugas akhir ini mengimplementasikan algoritma k-means untuk mengklasterisasi data jumlah kerusakan rumah akibat bencana berdasarkan kondisinya yang terjadi di Jawa Barat dan menghasilkan 2 klaster/kelompok dengan nilai dbi teroptimal sebesar 0,118 dimana klaster 0 berisi data yang berasal dari 16 Kabupaten di Jawa Barat dan klaster 1 yang berisi data yang berasal dari 9 Kota di Jawa Barat.

With the development of increasingly modern and rapid economic growth, it is the reason that everyone can make transactions anywhere and anytime, including investment activities carried out in the capital market. Investors must have a lot of careful consideration to invest. This study aims to determine the effect of Earning Per Share, Price Earning Ratio, Inflation, Interest Rates, Exchange Rates on mining companies listed on the Indonesia Stock Exchange in 2017-2022. The method used in this research is a quantitative method. This study used 15 samples of mining sector companies listed on the Indonesia Stock Exchange based on certain criteria. The results of the study found that partially Price earning ratio, inflation, interest rates and exchange rates did not have a significant effect on stock prices, while Earning per share had a positive and significant effect on stock prices.

Mercury (Hg) is a metal that is commonly found in water and has toxic properties, so it is very dangerous for human health and the environment. Mercury in the environment can come from gold mining activities such as in Pesanggaran Village, Banyuwangi. Based on information from the surrounding community, the waste disposal flowed into the river and it was feared to affect the quality of river water in this area. This study aimed to analyze the mercury level in the river water using the UV-Visible Spectrophotometer method, where river water samples were taken from the upstream, middle, and downstream parts. Determination of mercury levels was carried out at the STIKES Banyuwangi Laboratory. The results showed that the Hg content in the river water around the gold mining area of Pesanggaran Village, Banyuwangi ranged from 0.031 to 0.033 mg/L. The Hg level of river water in this area was above the threshold and it was not recommended to use as drinking, bathing, cooking or washing. However, it is necessary to analyze Hg levels using other methods, such as the AAS (Atomic Absorption Spectroscopy) method which is more expensive but more accurate results will be obtained.

Pada periode tahun 2018 sampai dengan tahun 2021 saham PT. BSI tbk (BRIS) cenderung mengalami fluktuasi harga setiap hari, sehingga dari kumpulan data time-series saham BRIS dibutuhkan penggalian data untuk menemukan pola model prediksi yang dapat menemukan informasi yang bermanfaat. Metode Data mining atau disebut juga dengan knowledge discovery merupakan penggalian informasi yang tersimpan dalam basis data yang besar melalui studi mengumpulkan, membersihkan, memproses, dan menganalisis, sehingga mendapatkan hal yang berguna dari data saham BRIS. Adapun model yang digunakan adalah metode regresi linier berganda, dan metode ARIMA dimana kedua metode tersebut memiliki keunggulan dalam analisis data numerik yang cukup akurat. Tujuan penelitian ini adalah untuk menerapkan dan menghasilkan model persamaan yang akurat antra kedua metode tersebut dalam memprediksi harga saham PT. BSI tbk.  Hasil yang didapat adalah  model regresi linier berganda dengan hasil nilai MAPE 1,1% yaitu 98,9% lebih akurat dibandingkan dengan model ARIMA yaitu dengan hasil nilai MAPE 2,36% dan akurasinya 98,9%.

This study aims to examine the effect of audit committee characteristics on CSRD in manufacturing and mining sector companies listed on the Indonesia Stock Exchange (IDX) in 2019. In addition, this study also examines whether there is an effect of risk management as a mediating variable in the relationship between audit committee characteristics and CSR disclosure. This research using purposive sampling method, which result in 178 samples. The analytical tool in this research using structural equation modeling (SEM)-PLS (Partial Least Square). The results show that the characteristics of the independent audit committee, number of member meetings, financial expertise and gender diversity have a positive effect on CSRD, while the size of the audit committee has no effect on CSRD. Indirect testing shows that risk management only affects the relationship between the number of member meetings and CSRD. Meanwhile, risk management failed to become a mediator for other variables with CSRD.

Discount is a sales strategy that lowers the price offered to buyers in the hope of increasing sales profits. However, when offering these discounts, stores often don't think about how discounted products can attract customers, so a support system is needed that can respond to the right and appropriate discounts. This support system with data mining techniques using apriori algorithm. This apriori method can search for several products that are often purchased simultaneously, therefore when juxtaposed with this study the effectiveness of the recommendations will be very good. Not only that, if it is added with a combination of recommendations with discounts, it will make customers interested to buying the product. The expected result of this research is to obtain a new sales strategy by making recommendations on items that will be used as discount packages.

ABSTRACT The rapid development of technology has a very large effect in various fields. One of them is in the field of buying and selling business, which is getting higher and higher competition between business actors. One of the strategies to increase sales is to implement a recommendation for goods, but from the various categories of goods in the store, there are products that are not in demand by customers, so that if left alone, the products that are not in demand will not sell well and will make the accumulation of goods in the store, in addition to that with the many categories, it makes some customers confused to choose products that suit their wishes buyer. Therefore, the author conducts an assessment first by conducting a literature study, which finally the purpose of this study is to make it easier for users and business owners to recommend goods in the store and determine the desired product by implementing a recommendation system on the Rameiki Mart Store website which is taken from the amount of data, this is also beneficial for store owners because the existence of this recommendation system can help as a means of product promotion , as well as in recommendations for the purchase of goods. In this study, the researcher created a recommendation system using the a priori algorithm method.

Karyawan pada dasarnya adalah manusia yang menggunakan tenaga dan kemampuannya untuk mendapatkan balasan berupa pendapatan, baik itu dalam bentuk uang maupun lainnya dari pemberi kerja atau pengusaha atau majikan. Tidak dapat dipungkiri pula bahwa sebuah perusahaan bisa berjalan dan berkembang jika terdapat karyawan yang bekerja didalamnya. Keberadaannya di sebuah perusahaan begitu penting, sehingga segala informasi yang berkaitan dengan karyawan sangat diperlukan. Data Mining merupakan suatu proses penggalian data atau penyaringan data dengan memanfaatkan kumpulan data yang memiliki ukuran cukup besar melalui serangkaian proses untuk mendapatkan informasi yang berharga dari data tersebut. Data Mining bisa digunakan oleh perusahaan besar untuk menggali data dan mendapatkan informasi yang dapat menunjang serta meningkatkan proses bisnis perusahaan tersebut. Setiap perusahaan pasti mempunyai data transaksi yang tersimpan dalam basis datanya. Data transaksi tersebut semakin hari semakin banyak dan bertambah. Terkadang data transaksi tersebut hanya dibiarkan menumpuk tanpa ada tindakan lebih lanjut. Dengan bertambahnya jumlah data pada perusahaan tersebut, maka peran analis untuk menganalisis data secara manual perlu digantikan dengan aplikasi yang berbasis komputer. Sehingga proses penganalisisan dapat dilakukan secara otomatis dan lebih mudah