Abstract:In recent years, the housing market has faced significant challenges, including fluctuating prices and declining sales. To solve this issue, there was an increasing need for more sophisticated methods to predict housing…
prices accurately. This study aimed to provide real estate marketers with a tool to enhance their pricing tactics and mitigate the decline in home sales by predicting house prices using machine learning techniques. Several parameters were considered in this study, such as location, number of bedrooms, number of bathrooms, land area, building area, and number of carports. Linear regression and neural network methods were used to develop predictive models. The findings showed that the neural network method was more accurate than linear regression, which made it a better tool for real estate pricing strategies, with land area and number of carports being the most influential aspects in house price prediction.
Abstract:This study aims to test whether the variables Liquidity (CR), Solvency (DAR), and Profitability (ROA) have an influence on Profit Changes at PT. Indofood Sukses Makmur Tbk. The population in this study is all financial report…
eport data of PT. Indofood Sukses Makmur Tbk for the 2014-2021 period in each quarter, while the samples in this study are statements of financial position and profit/loss reports. The documentation technique is the data collection technique used. The collected data were analyzed using financial ratios which were then entered into the multiple linear regression equation. Based on the results of this analysis, it can be seen that partially the current ratio and debt to assets ratio do not have a significant effect on changes in earnings. These results are inconsistent with (H1) and (H2) which say the current ratio and debt to asset ratio partially have an influence on changes in earnings. It is also known that partially the return on assets has a significant effect on changes in earnings. These results are in accordance with (H3) which says return on assets has an influence on changes in earnings. From the results of this analysis it can also be seen that simultaneously the current ratio, debt to assets ratio, and return on assets do not have a significant effect on changes in earnings. This result is inconsistent with (H4) which states that the current ratio, debt to asset ratio, and return on assets simultaneously have an influence on changes in earnings.
Abstract:This study discusses the implementation of the Naïve Bayes method to predict catering sales at PT.Negara Rasa Indonesia. The background of this study is based on the problem of suboptimal sales due to the absence of a structured…
tructured sales prediction system. The Naïve Bayes method was chosen because of its simplicity, speed, and ability to classify data with a high degree of accuracy. The data used in this study is historical sales data from the last two years, which has undergone cleaning, labeling, and transformation into four sales categories, namely very popular, popular, fairly popular, and less popular. The testing process was carried out using RapidMiner software by dividing the dataset into training data and test data at various ratios of 80:20. The test results showed a very high level of accuracy, with the highest value reaching 91.41%. These findings prove that the Naïve Bayes method is reliable for predicting catering sales, thereby assisting decision-making in more efficient sales management and planning at PT. Negara Rasa Indonesia.
Abstract:Abstract This study is motivated by the financial literacy of generation Z and also the quality of life insurance products in Indonesia which are moderated by gender in influencing a person's interest in buying life insurance…
surance in Indonesia. This study uses a quantitative method with a descriptive relationship approach. Determination of the sample in this study was carried out by calculating using the Bernoulli formula, with a total of 384 respondents. The data analysis technique used is the Structural Equation Model - Partial Least Square (SEM-PLS). The results of the study show that financial literacy (X1) and product quality (X2) do not have a significant effect on buying interest (Y) where the p-values of both variables are <0.05. Other findings also state that Gender (Z) does not significantly moderate financial literacy and product quality. The conclusion of this study is that the factors that make generation Z interested in buying insurance products are influenced by their perceptions of financial literacy and product quality. More specifically, the perception of product quality factors has a significant and positive influence on generation Z's interest in buying life insurance products in Indonesia. The findings show that of the two variables, product quality can be the strongest predictor in predicting generation Z's interest in purchasing life insurance products. Financial literacy cannot significantly predict generation Z's interest in purchasing insurance products.
Keywords : financial literacy, product quality, gender, purchasing intention
Abstract:The rapid growth of the hotel industry requires hotels to improve operational planning, one of which is by forecasting room reservations. Inaccurate forecasting may cause an imbalance between room availability and customer…
er demand. This study aims to compare the Weighted Moving Average and Single Exponential Smoothing algorithms in forecasting room reservations at Raz Hotel and Convention Medan using historical data from January 2025 to May 2026. The research method consisted of data collection, forecasting using both algorithms, and accuracy evaluation through Mean Absolute Deviation, Mean Squared Error, and Mean Absolute Percentage Error. The results indicate that the Single Exponential Smoothing algorithm achieved a Mean Absolute Percentage Error of 15.24%, which is lower than the 15.63% obtained by the Weighted Moving Average algorithm. Furthermore, the Single Exponential Smoothing algorithm predicted 835.90 room reservations for June 2026. Therefore, it can be concluded that the Single Exponential Smoothing algorithm provides better forecasting accuracy and is more suitable for predicting room reservations at Raz Hotel and Convention Medan.
Abstract:Sales forecasting is a crucial component of operational strategy and inventory management in the culinary industry, particularly for businesses dealing with raw materials that have short shelf lives. The Sate Padang Hapis…
s business faces the challenge of unpredictable monthly fluctuations in consumer demand, which often lead to supply imbalances, overproduction, or lost profit opportunities due to stockouts. This study aims to implement and analyze the accuracy of the Single Moving Average (SMA) quantitative forecasting method in predicting Sate Padang Hapis sales volumes for June 2026. Model performance was evaluated by assessing mathematical accuracy across two time-interval variations: 3-month and 5-month moving averages. Projection error rates were rigorously measured using Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) parameters. The analysis reveals that the Single Moving Average model with a 5-month interval yields projections closest to actual data, achieving the lowest error rates (MAD: 28.00; MSE: 1,304.00; MAPE: 2.28%). Implementing this forecasting model provides management with an objective basis for decision-making, enabling the effective and efficient optimization of raw material logistics and supply management.
Abstract:Graduation marks the completion of a certain level of schooling. This study aims to predict the graduation of students at SDN 016528 BP Mandoge based on their abilities. The goal of this research is to reduce the rate of…
student failure to graduate by making predictions based on examination scores collected by the institution. The method used in this study is Naive Bayes, a technique in Data Mining that utilizes probability and statistics to predict future outcomes based on previous data. This method was chosen due to its advantage in predicting graduation rates from concrete data, ensuring the results are reliable and applicable for future predictions. The dataset used in this study includes graduation data for SDN 016528 BP Mandoge students for the 2019/2020 academic year, comprising 171 students, with 120 students used for training data and 51 students for testing data, achieving a model accuracy of 98%.
Abstract:Abstract: Fitri Keramik Shop sells various types of ceramics. In this research, the researcher created a system that can make it easier to predict demand for ceramics in the following month based on the categories in Fitri…
ri Keramik by explaining the correct method for forecasting, one of the methods that can be used is Double Exponential Smoothing (DES) which is a forecasting method using uses a number of new actual demand data to generate forecast values for future demand by finding the average value as a forecast for the future period. The results of predicting demand for ceramics using an alpha value of 0.3 and having the lowest error rate are May 2023, Terraso: 176; Mosaic : 169; Standard Ceramic Floor: 163; Squared : 117.
Keywords: Analysis, Double Exponential Smoothing, Predicting Demand.
Abstrak: Toko Fitri Keramik melakukan penjualan berbagai jenis keramik. Pada penelitian ini, peneliti membuat sistem yang dapat memudahkan dalam meramalkan permintaan keramik pada bulan berikutnya berdasarkan kategori yang ada pada Fitri Keramik dengan memaparkan metode yang tepat dalam peramalan, salah satu metode yang dapat digunakan yaitu Double Exponential Smoothing (DES) yang merupakan metode peramalan dengan menggunakan sejumlah data aktual permintaan yang baru untuk membangkitkan nilai ramalan untuk permintaan dimasa yang akan datang dengan mencari nilai rata-rata tersebut sebagai ramalan untuk periode yang akan datang. Hasilnya dari memprediksi permintaan keramik dengan menggunakan nilai alpa 0,3 dan memiliki nilai tingkat error terendah yaitu Mei 2023, Teraso : 176; Mozaik : 169; Keramik Lantai Standart: 163; Kuadrat : 117.
Kata kunci: Analisis, Double Exponential Smoothing, Memprediksi Permintaan.
Abstract:Abstract: PT. Alam Jaya Wirasentosa which is located in Hessa Air Genting, Air Batu District, Asahan Regency, North Sumatra. This company is engaged in sales and distribution which has a fairly wide coverage on the island…
d of Sumatra. PT. Alam Jaya Wirasentosa sells Indofood's main products, one of which is bimoli cooking oil. Constraints experienced by PT. Alam Jaya Wirasentosa often has problems with stock availability due to the large number of product requests from consumers. In addition, there are times when there is too much inventory (over stock) that results in too high a cost burden to store and maintain materials during storage in the warehouse even though the goods still have opportunity costs (funds that can be invested / invested in more profitable things). In this study, the SMA method is used to solve the problem of predicting the demand for cooking oil in the next period. In addition, the purpose of this study is to determine the forecasting system used by PT. Alam Jaya Wirasentosa in forecasting the demand for Cooking Oil each month and implementing the Single Moving Average Method in forecasting the Demand for Cooking Oil, especially Bimoli cooking oil. At PT. Alam Jaya Wirasentosa.
Keywords: Forecasting; Single Moving Average; Bimoli Cooking Oil; PT. Alam Jaya Wirasentosa
Abstrak: PT. Alam Jaya Wirasentosa yang berlokasi di Hessa Air Genting, Kecamatan Air Batu, Kabupaten Asahan, Sumatera Utara.Perusahaan ini bergerak dalam bidang penjualan dan distribusi yang memiliki cakupan cukup luas di pulau Sumatera. PT. Alam Jaya Wirasentosa menjual produk utama Indofood salah satunya minyak goreng bimoli. Kendala yang dialami oleh PT. Alam Jaya Wirasentosa sering mengalami masalah ketersediaan stock barang dikarenakan banyaknya permintaan produk dari konsumen. Selain itu ada masa dimana terlalu banyaknya persediaan (over stock) yang ada sehingga mengakibatkan terlalu tingginya beban biaya guna menyimpan dan memelihara bahan selama penyimpanan di gudang padahal barang tersebut masih mempunyai opportunity cost (dana yang bisa ditanamankan / diinvestasikan pada hal yang lebih menguntungkan). Pada penelitian ini menggunakan metode SMA dalam memecahkan masalah prediksi permintaan minyak goreng pada periode selanjutnya. Selain itu tujuan penelitian ini adalah untuk mengetahui sistem peramalan yang digunakan oleh PT. Alam Jaya Wirasentosa dalam meramalkan permintaan Minyak Goreng tiap bulannya dan mengimplementasikan Metode Single Moving Average dalam meramalkan Permintaan Minyak Goreng khusunya minyak goreng Bimoli Pada PT. Alam Jaya Wirasentosa.
Kata Kunci: Peramalan, Single Moving Average, Minyak Goreng Bimoli, PT. Alam Jaya Wirasentosa,
Abstract:Abstract: Sembako is an abbreviation of Nine Basic Ingredients which consists of various food and beverage ingredients that are generally needed by the people of Indonesia. Without basic necessities, the lives of the Indonesian…
onesian people can be disrupted because basic necessities are daily necessities that are freely sold in the market. Toko Suryono is one of the basic food distributors that sells various kinds of basic necessities. The problem is that the number of food sales every month is erratic so it is difficult to predict, so we need a sales system and strategy, one of which is by predicting or forecasting sales for the future process so that this store knows how much food supplies must be provided in the following month so that there is no shortage or excess stock. The result of this research is that forecasting using themethod Least Square can make it easier for the store to provide basic food supplies in the coming month. From the overall calculation of basic needs, the lowest MAD is 16.51 and MAPE is 1.73%.
Keywords: Forecasting; Total Food Sales; Least Square;
Abstrak: Sembako adalah singkatan dari Sembilan Bahan Pokok yang terdiri dari berbagai bahan makanan dan minuman yang umumnya dibutuhkan oleh masyarakat Indonesia. Tanpa sembako, kehidupan rakyat Indonesia bisa terganggu karena sembako merupakan kebutuhan pokok sehari-hari yang dijual bebas di pasaran. Toko Suryono adalah salah satu distributor sembako yang menjual berbagai macam sembako. Masalah jumlah penjualan sembako setiap bulannya yang tidak menentu sehingga sulit diprediksi, maka diperlukannya sebuah sistem dan startegi penjualan salah satunya dengan cara melakukan prediksi atau peramalan penjualan untuk proses kedepannya sehingga toko ini mengetahui berapa persediaan sembako yang harus disediakan dibulan berikutnya agar tidak terjadi kekurangan maupun kelebihan persediaan. Hasil dari penelitian ini adalah peramalan dengan perhitungan metode Least Square dapat memudahkan pihak toko dalam menyediakan persediaan sembako di bulan yang akan datang. Dari keseluruhan perhitungan sembako menghasilkan MAD paling rendah 16,51 dan menghasilkan MAPE sebesar 1,73%.
Kata kunci: Peramalan; Jumlah Penjualan Sembako; Least Square;