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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.

Stunting occurs due to malnutrition which inhibits growth in toddlers. Stunting can also be caused by problems during pregnancy. This study aims to identify the risk of stunting during pregnancy and determine pregnant women who are at risk of this condition. By identifying and prioritizing critical factors that contribute to stunting in children under five, this research is expected to assist policy makers in developing effective solutions to reduce stunting rates. Handling the problem of stunting is important for the Government because it relates to the future generation of Golden Indonesia 2045. This study evaluates appropriate actions or therapies to reduce the risk of having children born with the potential to experience stunting. In the process of selecting pregnant women who are at risk of giving birth to children with the risk of stunting, a selection procedure is carried out that considers several factors such as the mother's age, mother's nutritional intake, arm circumference, hemoglobin level, parity, birth spacing, height, and mother's body mass index (BMI). The analytic network process (ANP) approach is used to determine the outcome of the selection process. The ranking is determined based on the calculation of the weighting of the criteria and sub-criteria in the ANP method. Based on the results of calculations using the ANP approach, PM 1 pregnant women get the highest score and are ranked first. These pregnant women are considered to have the highest risk of giving birth to babies with stunting risk.

Monitoring realizes efforts to improve the quality of health services. To obtain information on patient condition data during treatment. The monitoring process is done manually. So that it has an impact on the service and condition of the patient during treatment. The design of monitoring the patient's body temperature and heart during treatment with IoT can be controlled through the NodeMCU sensor ESP8266, MLX9014, MAX30100 sensor and Arduino IDE software program. Furthermore, it can detect the patient's temperature and the patient's heart rate during treatment. And processed by the NodeMCU ESP8266, the data from the two sensors is displayed on the SSD1306 OLED LCD and also to the smartphone of the medical officer on duty via Blynk. In order for the tool to work properly and optimally, it is necessary to adjust the pin placement so that it can work optimally. The problem of internet connection interference causes delays, resulting in a mismatch between the measurement of the test equipment and the standard tool. Data values are taken with an accuracy of 70%-93% for the MAX30100 sensor, for the temperature sensor it is close to optimal with a value that is read on a standard tool with an accuracy of 97%-99%.

Iridology provided special perspective to the concept of health and medical practices. Only by observation from outside the body, namely check for signs of an iris iridology idiomatic condition would be revealed by the organ and tissue in the body system, long before clinical symptoms of an illness experienced by a person may feel or diagnosed by conventional methods Required analytical methods for measuring and determining cholesterol in the human body, by testing the Sobel edge detection, Prewitt and Robert Canny edge detection realized in a software help to define or classify normal cholesterol levels, moderate to high cholesterol levels in the human body. Introduction of the iris database features Matching method by distance classifier based on the results of segmentation, edge detection, semi-polarization and the quantization able to detect the level of cholesterol in the human body ranges up to 80% of the 90 samples. Keywords: Iridology, edge detection, distance classifier, semi-polarization, quantization