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Business is an economic activity carried out by individuals or organizations to produce and sell goods or services with the aim of making a profit. The NSH Group Store is a business that sells carpets, pillows, bolsters, and dolls located in the Sei Dadap I/II Plantation, Sei Dadap District, Asahan Regency, North Sumatra 21225. The NSH Group Store was established in 2016 and is owned by Mrs. Siti Komariah Siregar. Among the challenges faced by the NSH Group Store owner are irregular stock procurement. Sales transaction processes still use conventional methods, reducing efficiency and time effectiveness, and potentially leading to data errors. Supply Chain Management is a series of approaches used to efficiently integrate suppliers so that goods can be distributed in the right quantities, locations, and at the right time, with the aim of minimizing overall system costs. A bolster pillow is a pillow that can function as both a pillow and a bolster. Bolster pillows are oval and long, so they can be hugged while sleeping. The benefits of a bolster pillow include maintaining a proper sleeping position, reducing pressure on joints, helping reduce aches, improving sleep quality, and improving overall health. Therefore, by implementing Supply Chain Management (SCM), data processing will be faster and more accurate.

Business ventures are activities carried out by individuals or organizations involving the production, sale, purchase, or exchange of goods and services, with the aim of generating profit. A basic necessities store (commonly known as a “sembako” store in Indonesia) sells daily staple needs, especially the nine essential commodities (sembako), which include items such as rice, sugar, cooking oil, eggs, salt, and other key food ingredients. UD. Putri 2, located in Dusun 1A, Sumber Harapan Village (21261), Tinggi Raja Subdistrict, Asahan Regency, was established in 2018 and has since become an essential part of the local community. This has required UD. Putri 2 to constantly monitor their stock inventory. However, the company still faces inefficiencies in managing sales data processing, which often leads to inventory shortages. When the supply of goods is insufficient to meet customer demand, customers may turn to other stores. If this occurs repeatedly, the store risks losing profit due to the unavailability of goods. Supply Chain Management (SCM) refers to the integrated processes and production activities starting from the acquisition of raw materials from suppliers, the value-adding processes that turn raw materials into finished products, the inventory storage process, and the distribution of finished goods to retailers and consumers. The implementation of SCM can optimize inventory management of staple goods, minimize inventory costs, and improve supply chain efficiency at UD. Putri 2.

Behind the success of the Free Nutritious Meal Program (MBG), there are several problems related to the health factors of the program targets, namely, there are several cases of allergies that occur in schools, inadequate understanding of allergen management owned by food processing vendors, and the high cost of laboratory tests and the process that takes a long time. So, to overcome these problems, an application is proposed that can help detect allergens in food products using data mining and machine learning approaches. SVM and AdaBoost algorithms each have advantages that can be used to help build an optimal allergen detection model. This research uses a cross-validation model validation method with a value of K = 10 to help improve the performance of the model built. In this study, from the entire fold, an average accuracy value of 98.74% was obtained. To evaluate the model built, this research has also conducted several new data inputs, and in each new data input, the accuracy value is obtained above 99%. This indicates that the model built, namely the combination of SVM and AdaBoost algorithms with the cross-validation model validation method, produces high accuracy, so this model can greatly assist the allergen detection process in food products.

This study evaluates the efficiency of two artificial intelligence models, DeepSeek and OpenAI, in generating code for algorithmic systems. Efficiency is assessed through execution speed, code accuracy, and the number of code characters produced. Data were collected from 100 tests covering search, sorting, graph, dynamic programming, optimization, data processing, text, and machine learning algorithms. The objective is to compare the performance of both models to support the development of efficient information retrieval systems. The method involves algorithm testing with statistical analysis of execution time, accuracy, and code length. Results indicate that DeepSeek has an average execution time of 28.74 seconds, slightly slower than OpenAI’s 28.49 seconds. However, DeepSeek’s accuracy (85.88%) surpasses OpenAI’s (85.03%). The average number of code characters is identical at 96.35 characters. The study concludes that DeepSeek excels in accuracy, while OpenAI is faster in certain cases, providing valuable insights for developers in selecting AI models for information retrieval applications.

Communication is a fundamental aspect of human life. However, individuals with hearing and speech impairments often face barriers in communicating with the general public. The Indonesian Sign System (SIBI) serves as a communication solution for the deaf and speech-impaired community in Indonesia, yet public understanding of SIBI remains limited. To address this issue, this study aims to develop an automatic translation model from SIBI sign language into Indonesian text by utilizing Deep Learning technology, specifically the Convolutional Neural Network (CNN) algorithm. CNN was chosen for its ability to effectively recognize visual patterns, making it suitable for processing hand gesture images in sign language. This research involved collecting and classifying a dataset of hand images based on the alphabet or words in SIBI, which were then used to train the CNN model. The designed CNN model was built to accurately classify hand signs and translate them into Indonesian text. The results of this study have the potential to serve as a supportive solution for inclusive communication between the deaf community and the wider public, and can be further developed for contextual sentence translation. Keywords: Indonesian Sign System (SIBI), CNN, Deep Learning, Automatic Translation, Inclusive Communication

The bodywork industry in Indonesia is under high competitive pressure, requiring companies to be more adaptive in understanding customer behavior in order to maintain business continuity. PT. Bengawan Karya Sakti as one of the national bodywork companies, has not optimally utilized historical transaction data to assess customer loyalty. This study aims to identify customer loyalty segmentation through the application of the RFM (Recency, Frequency, Monetary) method, which is used to analyze sales transaction data in 2022 and 2023. The study uses the CRISP-DM approach which includes the stages of business understanding, data exploration, data cleaning and processing, modeling, evaluation, and implementation of results. The transaction data analyzed includes attributes of transaction date, customer, number of transactions, and transaction value, which are then processed into RFM scores based on the transaction year and classified into categories such as Very Loyal, Loyal, At Risk, and others. The segmentation results show an increase in the number of very loyal customers from 2022 to 2023, as well as a significant decrease in inactive and at-risk customers. The chi-square statistical test shows that the difference in customer distribution between years is statistically significant (p-value <0.05), indicating a real influence from the company's strategy or external factors. The main conclusion of this study is that the RFM method is effective in the bodywork industry to support data-based marketing decision making and more targeted customer retention strategies.

Adapun penelitian pendahuluan yang pernah dilakukan diantaranya adalah penelitian yang berkaitan dengan pendeteksian warna, klasifikasi berdasarkan warna tersebut dan penentuan pemilahan berdasarkan kriteria tertentu, mulai dari proses morfologi hingga metode center plotting. Target pada penelitian berikutnya adalah penggabungan analisis dari kedua hasil penelitian sebelumnya dan saat ini, yaitu klasifikasi warna objek dengan metode center plotting dan metode pencacahan objek pada suatu file citra, yang dihasilkan dari perangkat akuisisi data berupa kamera digital dan web camera. Konsep pencacahan objek ini merupakan sekelompok urutan sub proses yang cocok untuk objek yang di-capture dari webcamera dan terbukti dalam implementasinya mampu dilakukan dengan baik. Hasil pengamatan dalam penelitian ini mampu mencacahkan citra berwarna terhadap berbagai bentuk objek yang telah di-capture dengan baik melalui web camera, yang dibuktikan dengan perolehan hasil hingga 100 % dari 31 citra uji, namun hasil sebaliknya saat objek hasil capture dari kamera digital hanya 10 % dari 10 citra uji.   Kata kunci: pencacahan, counter, image processing

Dalam sistem informasi akademik, operator sistem adalah pengguna yang tidak mempunyai latar belakang pengetahuan query yang cukup. Sehingga kebutuhan pengguna adalah kemudahan memperoleh informasi akademik dengan menggunakan bahasa alami yaitu bahasa Indonesia. Program aplikasi pengolah bahasa alami untuk query basisdata akademik dengan format data XML adalah program aplikasi berbasis NLP (Natural Language Processing). Digunakan oleh staf administrasi akademik untuk membantu pekerjaan pencarian data dalam format XML yang berkaitan dengan data akademik mahasiswa dalam basisdata akademik tanpa harus menggunakan bahasa SQL, tetapi menggunakan bahasa Indonesia. Masukan program aplikasi ini berupa sebuah kalimat tanya atau kalimat perintah dalam bahasa Indonesia yang sesuai dengan aturan produksi. Kalimat yang dimasukkan, akan dipilah kata yang bermakna (token) dan kata yang tidak bermakna. Token akan dibandingkan dengan aturan produksi, daftar atribut dan kondisi, untuk mendapatkan field yang dimaksudkan dalam kalimat. Dari kumpulan token akan dikonstruksikan sesuai dengan aturan produksi pembentuk kalimat untuk diterjemahkan dalam XQuery pengakses basisdata XML, sehingga menghasilkan keluaran tabel yang sesuai dengan pertanyaan atau perintah. Dari sistem yang dihasilkan dapat disimpulkan bahwa implementasi dengan berbasis Natural Language Processing dapat digunakan sebagai alternatif dalam merancang sebuah sistem pengakses basisdata, tetapi tidak dengan menggunakan bahasa SQL. Keunggulan dari aplikasi pengolah bahasa alami ini adalah mampu menjawab query bahasa Indonesia dari implementasi 7 aturan produksi yang telah ditetapkan dengan tampilan berbentuk tabel.   Kata kunci : natural language processing, query bahasa Indonesia, token, XML, XQuery, aturan produksi

Teknologi informasi dewasa ini sudah menjadi kebutuhan pokok bagi organisasi perusahaan untuk membantu aktivitas-aktivitas yang ada di dalam perusahaan. Banyak cara yang bisa dilakukanperusahaan untuk menerapkan teknologi informasi yaitu, membeli, membangun sendiri, atau menyerahkan ke pihak lain untuk pengembangannya. Penerapan teknologi informasi melalui pengolahan data secara elektronis (Electronic Data Processing/EDP) mau tidak mau akan memberikan dampak terhadap prosesauditing dan sekaligus proses pengendalian intern perusahaan. Untuk memastikan bahwa pengendalian intern dalam proses pengolahan data secara elektronik (electronic data processing/EDP) telah dilakukan dengan baik dan benar maka perusahaan harus menjalankan fungsi audit terhadat sistem tersebut. Fungsiaudit dilakukan oleh seorang Auditor, baik itu Auditor internal maupun Auditor eksternal. Di dalam melakukan kegiatan audit, seorang auditor sudah memiliki standard kerja sendiri, dengan harapan seorang auditor mampu bertindak secara independent dan dapat dipercaya. Hasil audit dari auditor dapat dimanfaatkan perusahaan sebagai bahan untuk melakukan perbaikan sistem dan efektifitas terhadap pengendalian internal.

Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigations Remote sensing data is of such nature and volume as to require it to be compatible with processing and outputing by computers. They are the easiest, fastest, and most efficient way to produce images, extract data sets, and assist in decision making. One special function is to assist in manipulating other kinds of data about the spatial or locational aspects of areas in the world that are the subjects of interpretation and decision making. The bulk of the data in such systems have in common a geographical significance, that is, they are tied to definite locations on the Earth. In this sense, they are similar to or actually make up what has become a powerful tool in decision making and management. The Image-Based Information System (IBIS) was developed in 1975 at the Jet Propulsion Laboratory, and is designed to be a comprehensive geographic information system that performs operations on raster image, tabular, and graphics format data, using the Video Image Communication And Retrieval (VICAR) image processing system. This was accomplished by the creation of a new VICAR-based file format for tabulating raster format geographic information over multiple data planes.