Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika

PEMBUATAN TABEL MORTALIA MELALUI MODEL LEE CARTER

2024-01-15T00:37:26+07:00

The Lee-Carter model, proposed in 1992, is one of the most well-known methodologies for modeling mortality rates. This model is known for its simplicity and has been used successfully in America, Japan, and Australia. Basically, the Lee-Carter model is a regression model. However, the independent variables are not given explicitly so an approximation is made. They proposed a singular value decomposition. As a case study, secondary data was taken from the final project in the Department of Mathematics ITB

IMPLEMENTASI MATEMATIS SISTEM PENDAFTARAN PASIEN ONLINE DAN PEMERIKSAAN DOKTER MENGGUNAKAN METODE UEDP PADA RUMAH SAKIT ISLAM MALAHAYATI

2024-03-18T23:36:09+07:00

Malahayati Islamic Hospital, a private healthcare institution in Medan, North Sumatra, established in 1963 by the Malahayati Islamic Education Foundation, has a capacity of 100 beds and is committed to providing quality and affordable healthcare services. However, problems arose with the hospital's website, which did not provide online booking services and doctor's practice schedules. This makes it difficult for patients, especially those coming from out of town, and can result in long queues at registration. To overcome this problem, the author wants to build and implement a web-based Online Patient Registration System and Doctor Practice Schedule at Malahayati Hospital. It is hoped that this system will not only provide easy access for patients to view and register online but also help hospital admins in effective management of doctor schedules. The results of the study are expected to have a positive impact on the efficiency and quality of health services at Malahayati Islamic Hospital

MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA MELALUI MODEL ACCELERATED LEARNING BERBANTUAN MEDIA INTERAKTIF

2023-10-31T20:03:15+07:00

This research aims to improve students’ mathematical problem solving abilities in quadratic equation material through an accelerated learning model assisted by interactive media. This classroom action research was conducted at SMP Negeri 8 Gorontalo City for the 2023/2024 academic year. The research subjects were 25 students in class IX-4. The data collection techniques used are observations and tests. This research lasted for 2 cycles. From the results of observations, teacher activities increased, from 67,31% in cycle I of 87,5% in cycle II with an increase 0f 20,19%. Furthermore, the results of observations of student activities increased, from 66,27% in cycle I to 85,41% in cycle II with an increase of 19,14%. Students’ mathematical problem solving abilities also increased from 56% in cycle I to 84% in cycle II with an increase of 28%. From the research above, it can be conclued that the accelerated learning model asissted by interactive media can improve students’s mathematical problem solving abilities in quadratic equation

PEMODELAN AUTOREGRESSIVE FRACTIONALLY INTEGRATED MOVING AVERAGE (ARFIMA) UNTUK AKTIVITAS CURAH HUJAN DI KOTA MEDAN

2024-01-31T00:49:24+07:00

The Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is a development of the ARIMA model with the differencing values being fractional numbers. This study aims to model ARFIMA on rainfall activity data in the city of Medan which consists of three variables including air temperature, humidity and previous rainfall. In this study, a stationary test of the three data was carried out, after conducting several tests, it can be concluded that the air temperature and rainfall transformation data are stationary with respect to the mean, but the air humidity transformation data shows that the data is not stationary in the mean shown from the slow decreasing ACF plot value. and p-value is more than =0.05. After the data of air temperature, rainfall and humidity are stationary, the estimation of model parameters, diasgonic test of the model, and determination of the best model will be carried out using ARIMA. The ARIMA model equation (1,0,0)(1,0,0).The temperature is asfollows: ARIMA model equation (2,0,3)(1,0,0),Rainfall ARIMA model equation (1,1,1)(1,1,0)¹² HumidityAfter the three variables get the equation from ARIMA, what is done is the data on air humidity is tested again using ARFIMA, in order to compare the suitability of the air humidity data, whether the data is more suitable for ARIMA or ARFIMA. After doing some testing and then getting the ARFIMA results(0,d,[1,2])with isRMSE 19,83846907, MAE 3,786387874, dan MAPE 3,786387874, So it can be concluded that the ARIMA method is better used on air humidity data

PERSAMAAN LOGISTIK MENGGUNAKAN METODE ADAM-BASHFORTH-MOULTON DALAM MEMPREDIKSI JUMLAH PENDUDUK DI INDONESIA

2024-01-11T22:58:13+07:00

This study discusses Logistic Equations using the Adam Bashforth Moulton method to predict population growth, which is then solved first with the Runge Kutta method of order-4 to obtain the initial solution then using Adam Bashforth as a predictor and Adam Moulton as a corrector. The logistical equation for population growth with a carrying capacity in Indonesia is K=1,000,000,000 with a step size of h=1, with a growth rate of 1%. Logistics numerical numerical solution with population growth at t=2027 with a step size of h=1 is 274,250,443 people

PENERAPAN POISSON INVERSE GAUSSIAN REGRESSION UNTUK MEMODELKAN LAMA RAWAT INAP PASIEN DEMAM BERDARAH DENGUE (DBD) UPTDK. RSU. HAJI MEDAN PEMERINTAHAN PROVINSI SUMATERA UTARA

2024-03-18T12:26:57+07:00

Dengue fever is one of the dangerous diseases that can threaten human life if not treated seriously. Dengue hemorrhagic fever is one of the health problems that exist in the community where the number of sufferers tends to increase and the spread is very wide. Dengue hemorrhagic fever (DHF) is a disease caused by infection with the DEN-1, DEN-2, DEN-3 or DEN-4 viruses transmitted to the bite of Aedes aegypti and Aedes Albopictus mosquitoes before it was infected by the dengue virus by dengue sufferers. Aedes aegypti mosquitoes become more infective for 8-12 days after sucking blood from dengue patients before. However, for now only researchers take only a few factors that make the length of stay of dengue patients in UPTDK. RSU. Hajj Medan Government of North Sumtera Province. In this study, the independent variables used were Patient Age Value (), Platelet value (), Leukocyte value (), and Hemoglobin value () in UPTDK. RSU. Haji Medan Government of North Sumtera Province using Poisson Inverse Gaussian Regression (PIGR). Poisson Inverse Gaussian Regression (PIGR) is a form of regression from mixed poisson designed on enumeration data with overdispersion cases. Therefore, research using the Poisson Inverse Gaussian Regression method can be carried out. The Poisson Inverse Gaussian Regression model formed is with a very significant influential variable is the Leukocyte value

PEMODELAN DEA AGGRESSIVE - BOOTSTRAP REGRESSION PADA FAKTOR YANG MEMPENGARUHI EFISIENSI PERBANKAN SYARIAH INDONESIA

2023-10-23T10:21:16+07:00

Data Envelopment Analysis is a non-parametric method developed based on linear programs with objective functions and weight functions. DEA is an analytical technique used to measure the efficiency of a process which the decision making units (DMUs) are homogeneous. The application of the DEA method in various fields yields in steps in determining policies in a process. This study aims to measure the efficiency of Indonesian Islamic banking by applying DEA method with aggressive weighting. The efficiency result of the method is then combined with bootstrap regression method to find out the variables that significantly influence the efficiency value. The data in the research process was taken from the monthly financial reports of Indonesian Islamic banking from 2018 to 2022 with a quantitative research approach and associative research type. The input variables used to measure efficiency include total assets, total labor, labor operating costs, total deposits, and fixed assets.While the output variables include total financing funds, net operating margin, and other operating income. Meanwhile, the independent variables to estimate the factors that influence the efficiency value of DEA include capital adequacy ratio, return on assets, company size, and financing to deposit ratio.The result of the analysis shows the goodness of the model which is the coefficient of determination worth 40.95%. Independent variables that significantly affect the efficiency of DEA aggressive are capital adequacy ratio, return on assets, and financing to deposit ratio

PENERAPAN ANALISIS REGRESI LOGISTIK BINER PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN MAHASISWA BERBELANJA ONLINE DI TIKTOK

2024-01-31T00:40:58+07:00

TikTok is a widely popular application among people of all age groups, from the young to the elderly. Students frequently utilize TikTok as a platform for online shopping, and there are numerous factors influencing their decisions. The research aims to construct a binary logistic regression equation model to determine the significant factors. The study population consists of all students from the Department of Mathematics who enrolled in 2022. The research sample comprises 71 respondents. The dependent variable (Y) in this study is the decision to shop on TikTok, and the independent variables (X) are trust (X1), service quality (X2), product diversity (X3), promotions (X4), security (X5), and price (X6). The research results indicate a binary logistic regression model as follows: π(x)=e^((13.012-1.679X_(2.1)-1.663X_(5.4)))/(1+e^((13.012-1.679X_(2.1)-1.663X_(5.4))) ) , where the service quality variable (X2) and security (X5) significantly influences the decision to shop online on TikTok

PENDEKATAN REGRESI LOGISTIK BINER DAN REGRESI LOGISTIK BERSTRUKTUR POHON DALAM ANALISIS DIAGNOSIS KANKER PAYUDARA

2024-03-19T10:43:22+07:00

The purpose of this research is to determine the factors that have a significant effect on the types of malignant and benign breast cancer using the binary logistic regression approach and classify the factors that have a significant effect on the types of malignant and benign breast cancer using the regression method. tree-structured logistics on breast cancer data from H. Adam Malik Hospital Medan 2021. This research is a type of applied research by collecting secondary data from the H Adam Malik General Hospital Medan. The research variables used are the response variable (Y) and the predictor variable (X). In the response variable there are also two categories, namely benign breast cancer patients and malignant breast cancer patients. While the predictor variables in this study were age, age at menarche, age at menopause, age at parity, use of hormonal contraception, genetics, number of children, breastfeeding period, and mammary fibroadenosis.

This study uses the binary logistic regression method because it is a good method in determining factors. In addition, the tree-structured logistic regression method is also used because it is a good method in determining factor classification with a good level of accuracy for all data. These two methods can make it easier for researchers to calculate and determine the factors that have a significant effect on the type of malignant breast cancer and benign breast cancer using all the available variables.

The results of this study obtained an accuracy value of 94% for the binary logistic regression method and 97.74% for the tree-structured logistic regression method. Because it has an accuracy value of almost 100%, this means that the binary logistic regression method and tree-structured logical regression applied to this research problem are good enough

PENGARUH STRATEGI REACT DENGAN LEMBAR KERJA PESERTA DIDIK (LKPD) DALAM MENINGKAT KEMAMPUAN PEMECAHAN MASALAH MATEMATIKA SISWA

2024-01-08T20:24:26+07:00

The aim of the research is to determine the effect of the REACT strategy with LKPD on students' class XI Mathematics problem solving abilities at SMKN 5 Kepahiang. on the Opportunity material. This research is a quasi-experimental research whose population includes all class XI students at SMK Negeri 5 Kepahiang consisting of eight classes. The data collection technique in this research is an instrument test used to collect data including mathematical problem solving ability test questions. The researcher used a purposive sampling technique for sampling. The number of samples was determined using Taro Yamane's calculation formula so that 70 students were obtained consisting of 35 people in the control class and 35 people in the experimental class. Data collection in this research used documentation studies and tests. The data analysis technique uses the independent sample t-test, but before carrying out the t test, the data analysis requirements are tested, namely the normality test and homogeneity test. The results of the research show that the results of the normality and homogeneity tests show that all data is normally and homogeneously distributed, while the results of the hypothesis test show that the significance value is (0.00 < 0.05), which means that there is a positive and significant influence of the REACT learning strategy with LKPD on ability. Solving mathematics problems for students at SMK Negeri 5 Kepahiang on opportunity material

KEMAMPUAN LITERASI MATEMATIS SISWA SMP DALAM MENYELESAIKAN SOAL ARITMATIKA SOSIAL DITINJAU DARI GAYA BELAJAR DAVID KOLB

2024-03-01T14:24:12+07:00

Researchers in this article describe the mathematical literacy skills of junior high school students in solving social arithmetic problems in terms of David Kolb's learning style. This research method uses descriptive qualitative with 26 students of SMPN 2 Cileles class VIII B as the research subjects. This study used mathematical literacy test instruments, David Kolb learning style questionnaire, and interview guidelines. The results showed that each learning style had varied mathematical literacy skills. Upper divergent students were able to fulfill three mathematical process indicators. Middle divergent students are only able to formulate the context mathematically and use mathematical concepts, facts and procedures. Lower divergent students are only able to formulate the context mathematically. Upper assimilation students were able to fulfill three process indicators Moderate assimilation students were able to fulfill three process indicators in part of the problem. Lower assimilation students were only able to formulate the context mathematically. Upper and medium convergent students were able to fulfill the three mathematical process indicators in part of the problem. Lower convergent students are only able to formulate the context mathematically. Upper and medium accommodation students were able to fulfill three mathematical process indicators in part of the problem. Lower accommodation students were only able to fulfill one process indicator, namely formulating the context mathematically

SPATIAL AUTOCORRELATION ANALYSIS USING THE MORAN AND LISA INDEX ON THE SPREAD OF MALARIA DISEASE IN NORTH SUMATRA PROVINCE

2024-01-23T21:32:53+07:00

Malaria is a disease caused by protozoan infection of the Plasmodium genus, characterized by symptoms of alternating chills and prolonged fever. During the period of 2018-2022, the province of North Sumatra experienced an increase in malaria cases. This research aims to comprehend the spread of malaria cases in North Sumatra Province during that period through univariate analyses. This study uses secondary data obtained from the North Sumatra Provincial Health Office which includes the number of malaria cases. In the univariate analysis, the Moran's Index test revealed positive global spatial autocorrelation in 2021 and 2022, indicating inter-district/city connectivity and clustered patterns of malaria distribution in North Sumatra Province (I>E[I]). LISA analysis identified different clusters each year, but Hot Spots consistently occurred in Asahan Regency (2021-2022) and Batubara Regency (2022), while a Cold Spot persisted in South Tapanuli Regency for 3 years (2020-2022).

PERANCANGAN SISTEM PENDUKUNG KEPUTUSAN SEVERITY INKLUSI BAHAN BAKU BAJA DENGAN MENGGUNAKAN LOGIKA FUZZY MAMDANI

2024-03-18T23:37:42+07:00

Steel is one of the raw materials used by PT. XYZ in the manufacture of its defense products; therefore, quality control (QC) and checking process become the most essential part in the process. To ensure that the steel raw materials used reach the standards, metallurgical properties are examined using several criteria must be carried out well, as microstructure, grain size, decarburization and impurities (inclusions). Inclusions or impurities are unwanted non-metal compounds and are the main factor for the initial appearance of ductile fracture and brittle facture during the production process. The severity of the inclusions in steel raw materials affects the next process so that errors in readings to determine the severity of minor or major inclusions must be minimized. This is because when the inclusion severity level that read is included in the major level then the steel raw material cannot be used and turns to be scrap and causes losses to the company. To minimize the matters, operator accuracy is required in analyzing by a comparison table, because this method analyzes the inclusion compounds one by one and it takes ± 1 minute to determine the severity. The purpose of this research is to build a quality decision-making system based on fuzzy mamdani logic that is used to determine the severity of inclusions and to compare the results of system processing with operators to see the accuracy of the system and time efficiency that has been built. In this study using the Mamdani fuzzy logic method with the variables used are Alumina inclusion length, Silicate inclusion length, Alumina inclusion width and Silicate inclusion width. The system is built using matlab software. The system test results from the 6 samples used to obtain comparisons according to the operator and the system are stated to be minor, making the accuracy obtained quite good and in terms of time, the determination process with the system takes less time, namely ± 2 seconds

PERBANDINGAN METODE BACKWARD DAN FORWARD PADA SELEKSI MIXED-EFFECTS MODEL

2023-12-21T08:45:46+07:00

In the era of globalization, concerns about the stability and vulnerability of nations have become a primary focus in the field of international relations research. One of the indicators measuring a country’s vulnerability is the Fragile State Index. This research discusses the analysis of Fragile State Index in Southeast Asian countries using panel data observed from 2010 to 2021, focusing on economic impacts. The factors involved include Gross Domestic Product, General Government Net Lending/Borrowing, Inflation, and Life Expectancy. A mixed-effects model is employed to examine the influence of economic factors on the Fragile State Index. The selection of the best model is carried out by comparing Backward Elimination and Forward Selection procedures. The research findings indicate that the best model for interpreting the influence of economic factors on the Fragile State Index is the one using the Backward Elimination method. Significant variables in this model include Gross Domestic Product, General Government Net Lending/Borrowing, Life Expectancy, and the interaction between General Government Net Lending/Borrowing and Inflation

ANALISIS FAKTOR YANG MENDORONG TINGKAT PUBLIKASI HASIL PENELITIAN DOSEN

2024-02-19T10:34:29+07:00

The productivity of scientific publications from the research results of Universitas PGRI Adi Buana Surabaya lecturers for the last two years has decreased, marked by rankings on both national and regional assessment scales. One of the obstacles that become a downgrade for lecturer performance assessments in the form of lecturer research outputs is that the output-based performance ecosystem in the field of higher education tridharma in research activities has not been achieved. Therefore, this study aims to determine the factors that encourage and the dominant factors on the level of publication of research results by lecturers at Universitas PGRI Adi Buana Surabaya. This type of research is quantitative research using factor analysis involving 105 research subjects using 10 metric attributes. Factor analysis is able to reduce 10 metric attributes into 3 main components which are the driving factors for the level of publication of lecturer research results

EKSPLORASI ETNOMATEMATIKA ARITMATIKA SOSIAL PADA TAPAI SINGKONG SEBAGAI SUMBER PEMBELAJARAN MATEMATIKA

2024-01-18T12:35:07+07:00

This research aims to overcome a problem in the field of mathematics by utilizing the concept of ethnomathematics, especially in terms of social arithmetic. Apart from that, this research can also be used as a mathematics learning resource that introduces Indonesian culture through the use of traditional food. This research is a type of qualitative descriptive research that uses an ethnographic approach as a research method. This research will use various methods such as interviews, observation, documentation and literature review to collect data. The researchers also collected secondary data, namely taking quotations from several journals as references. In data analysis, it can be concluded that of the two groups of cassava tapai traders studied, the first group experienced an increase in profits of 39.86% every day. If all the goods are sold, the second group will get a profit of 182.68% every day. So it can be concluded that the second group of cassava tapai traders received greater benefits than the first group of cassava tapai traders

SOCIO-ECONOMIC AND ENVIRONMENTAL FACTORS AS DETERMINANTS OF LIFE EXPECTANCY: STATISTICAL APPROACH WITH QUANTILE REGRESSION

2024-03-18T23:36:40+07:00

The use of quantile regression in analyzing determinants of life expectancy provides a deep understanding of the influence of predictor variables across various quantiles of the data distribution. The analysis results reveal significant differences in predictor variables affecting life expectancy at each quantile, with socio-economic, environmental, and health program factors having varying impacts. Model evaluation is conducted considering several goodness-of-fit measures such as MAPE, AIC, and coefficient of determination, selecting the best quantile based on a combination of these values. Based on the analysis, the optimal quantile is chosen based on the lowest MAPE and AIC, and the highest coefficient of determination, considering the efficiency of significant predictor variables. The analysis indicates that the best model is found at the 60th quantile, with two significant predictor variables, namely mean years of schooling and labor force participation. This underscores the significant role of socio-economic factors in determining life expectancy at specific quantiles

ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR SEISMIC ANOMALY DETECTION IN INDONESIA: UNVEILING PATTERNS IN THE PACIFIC RING OF FIRE

2023-12-17T12:18:20+07:00

This study presents an integrated analysis of machine learning algorithms for the detection of seismic anomalies in Indonesia, a region within the volatile Pacific Ring of Fire. Employing Local Outlier Factor, Isolation Forest, and Elliptic Envelope algorithms, we processed a comprehensive dataset of seismic events characterized by latitude, longitude, depth, and magnitude. Our methodology involved standardizing these features and aggregating model predictions to establish a consensus mechanism for outlier detection. The results indicated that the vast majority of seismic events are consistent with the expected geological patterns, with a negligible percentage exhibiting anomalous behavior across the models. Through statistical analysis and visual mapping, we discerned that while anomalies are varied, they may correlate with specific seismic event features such as higher magnitudes or unique geographic locations. The consensus approach revealed a high-confidence subset of outliers, offering a focused direction for further seismological scrutiny. The study's implications extend to enhancing seismic risk assessment and early warning systems, providing a methodological framework for identifying seismic events that deviate from normative patterns. By outlining a scalable approach for anomaly detection, this research contributes to the predictive analytics tools available for disaster risk management and emergency preparedness, aiming to mitigate the impact of seismic hazards in seismically active regions

ANALISIS KEMAMPUAN BERPIKIR REFLEKTIF MATEMATIS SISWA PADA MATERI STATISTIKA DITINJAU DARI SELF-REGULATED LEARNING

2024-02-02T08:27:54+07:00

Students need to have the ability to think in order to solve a problem from the problem at hand. This study aims to describe the reflective thinking ability of seventh grade students of SMP Batik Surakarta when they solve problems involving statistics in terms of Self-Regulated Learning. This research used qualitative research method with descriptive research type. The subjects in this study were students of class VII C SMP Batik Surakarta. Data collection begins with filling out a self-regulated learning questionnaire by students and reflective thinking ability test questions then from the results of the categorisation based on the results of the questionnaire conducted interviews. The results of this study are students who have self-regulated learning with high category have high reflective thinking ability can fulfil the indicators of reflective thinking reacting, comparing, and contemplating. Students who have moderate self-regulated learning have moderate reflective thinking ability can fulfil two indicators of reacting, and comparing. Students who have low self-regulated learning category have less reflective thinking ability that only fulfils one reflective thinking indicator which is reacting

PENGARUH AUDIT INTERNAL DAN KINERJA KARYAWAN TERHADAP PENGENDALIAN INTERNAL SERTA DAMPAKNYA TERHADAP PENCEGAHAN KECURANGAN DI PT. COMMIT TRANS ANGKASA DENGAN MENGGUNAKAN METODE ANALISIS JALUR

2024-01-11T23:01:06+07:00

This study aims to determine the effect of Internal Audit (X₁), Employee Performance (X₂) on Internal Control (Y) with the variable Intervening Fraud Prevention (Z) at PT. TransSpace Committee. This research includes causal associative research using a quantitative approach. The sample used in this study amounted to 50 employees of PT. TransSpace Committee. Data was collected using a questionnaire that had been tested for validity and reliability. The data analysis technique used is path analysis. The results of this study are that the contribution of internal audit (X₁) to Internal Control (Y) is 0.311, this indicates that the contribution or influence of X₁ on Y is 31.1% while the remaining 68.9% is a contribution from the variables other variables not included in the study, and also the contribution of employee performance (X₂) to Internal Control (Y) is 0.173, this indicates that the contribution or influence of X₂ on Y is 17.3% while the remaining 82.7% is the contribution of other variables not included in the study, and also the magnitude of the contribution of internal audit (X₁) to Fraud Prevention (Z) which is equal to 0.307, this indicates that the contribution or influence of X1 on Z is equal to 30.7% while the remaining 69.3% is the contribution of other variables not included in the study, and also the size of the audience's contribution internal t (X₁) and internal control (Y) on fraud prevention (Z) which is equal to 0.539, this shows that the contribution or influence of X₁ & Y on Z is 53.9% while the remaining 46.1% is a contribution from the variable -Other variables not included in the study, and also the contribution of employee performance (X₂) to fraud prevention (Z) is 0.177, this indicates that the contribution or influence of X₂ on Z is 17.7% while the remaining is 72.3 % is the contribution of other variables not included in the study, and also the contribution of employee performance (X₂) and internal control (Y) to fraud prevention (Z) which is equal to 0.522, this shows that the contribution or influence of X₂ & Y to Z is 52.2% while the remaining 47.8% is contributed by other variables not included in the study, and also the amount of k the contribution of internal control (Y) to fraud prevention (Z) is equal to 0.502, this indicates that the contribution or influence of Y on Z is 50.2% while the remaining 49.8% is a contribution from other variables not included in study

OPTIMASI PERENCANAAN PRODUKSI KERAJINAN ROTAN DI ANGGA FURNITURE MENGGUNAKAN LINEAR PROGRAMMING

2024-03-18T23:35:26+07:00

Production planning is an activity to obtain products in accordance with the needs of two parties, namely companies and consumers. Production planning is important in the industry in order to achieve optimal profits. In the rattan handicraft business, furniture faces problems in production planning. The production process is carried out based on the availability of raw materials and the estimated average demand, but it is often difficult to determine the optimal amount and time of production. This results in a shortage or excess of stock which has an impact on profits. By using a linear program, this study aims to determine the optimal results in production planning in the rattan and furniture handicraft business using the simplex method so that optimal profits are obtained. The results showed that the number of products produced was optimal so that the profit obtained was 8.49%.

PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN POLA BILANGAN BERBANTUAN ISPRING SUITE TERHADAP HASIL BELAJAR MATEMATIKA SISWA

2023-10-25T15:27:56+07:00

The purpose of this study was to determine the effect of the use of ispring suite assisted number pattern learning media on the mathematics learning outcomes of class VIII students. This research is a quantitative research using experimental methods and using a pretest-posttest control group design. Sampling used the Random Sampling technique and the selected classes were class VIII-6 as the experimental class and class VIII-4 as the control class. The research instrument uses a learning achievement test in the form of a description/essay. Inferential analysis was performed using the anacova test. The results showed that there was a positive and significant effect on the use of iSpring Suite assisted number pattern learning media on students' mathematics learning outcomes

IMPLEMENTATION OF THE PROBLEM BASED LEARNING (PBL) LEARNING MODEL IN INCREASING MOTIVATION AND LEARNING OUTCOMES OF GRADE VIII STUDENTS OF DAARUL QURAN COLOMADU JUNIOR HIGH SCHOOL ON PYTHAGOREAN THEOREM

2024-01-31T00:48:58+07:00

The low completeness of mathematics learning on the material of the Pythagorean theorem is wavered by the disinteractive interest of students in the process of learning activities. The purpose of this study was to obtain a description of the implementation of the Problem Based Learning model to improve the learning outcomes of grade VIII students of Daarul Quran Colomadu Junior High School on the Pythagorean Theorem material. This type of research is classroom action research that refers to Kemmis and Mc. Taggart's design, namely planning, implementing actions, observation and reflection. The study was conducted in two cycles. The subjects of this study were grade VIII students of Daarul Quran Colomadu totaling 40 students. Data collection techniques are obtained from data from teacher and student observations. This research was conducted in two cycles and each cycle was carried out in two meetings. The results showed that learning using the Problem Based Learning type cooperative learning model can improve student learning outcomes as shown by an increase in the number of students who completed in the first cycle by 31 students (70%) and the number of students incomplete by 9 people (30%). In the second cycle, the number of students who were declared complete increased by 37 students with a percentage of 90% and 3 students declared incomplete with a percentage of 10%.

ANALISIS LAJU PREDIKSI INFLASI DI INDONESIA: PERBANDINGAN MODEL GARCH/ARCH DENGAN LONG SHORT TERM MEMORY

2024-01-11T07:38:25+07:00

Inflation is a condition wherein the general level of prices for goods and services in an economy continually rises. Predicting inflation serves as a crucial link in establishing future inflation values. The dynamic nature of inflation allows for changes over time, forming a nonlinear model capable of providing more accurate inflation predictions. This research aims to examine and compare the effectiveness of GARCH/ARCH and LSTM models in predicting inflation data.The results of the study indicate that the LSTM model proves to be the superior choice for predicting inflation with higher accuracy when compared to the GARCH model. The GARCH model produces more accurate predictions of future inflation periods, as evidenced by the Mean Absolute Percentage Error (MAPE) value of 2.6814%. This value signifies the extent of the comparison between the actual and predicted model values. In contrast, the LSTM model yields a Mean Absolute Error (MAE) value of 0.00895358, demonstrating its superior accuracy.Therefore, the findings of this research can be considered a valuable reference for a country looking to predict inflation more effectively. Utilizing advanced time series models, such as LSTM, can enhance the accuracy of inflation predictions, providing policymakers with valuable insights for informed decision-making

ESTIMASI PARAMETER PADA MODEL SELEKSI SAMPEL HECKMAN DENGAN KOVARIAT ENDOGEN MENGGUNAKAN PENDEKATAN KEMUNGKINAN MAKSIMUM INFORMASI PENUH

2024-03-07T16:39:37+07:00

The linear regression model is a statistical tool used to model the causal relationship of a dependent variable based on one or several independent or explanatory variables. In scenarios where the dependent variable is a censored variable and there is potential to exist sample selection, the sample selection model can be an alternative in analyzing this relationship. In the Heckman sample selection model, independent variables have the possibility of having an endogeneity effect, where they should be treated as endogenous variables in both the outcome equation and the selection equation instead of as exogenous variables. In result, by including endogenous covariates in the Heckman sample selection model, the sample selection model equation will have more than one equation and makes it a simultaneous equation. To estimate simultaneous equations, simple estimation methods such as the maximum likelihood estimator method are no longer appropriate. In this study, we will discuss the estimation of sample selection models with endogenous covariates utilizing the full information maximum estimator (FIML) approach. The sample selection model with endogenous covariates was then applied to the women labor supply data of Tomas Mroz's research and compared with several models. Based on the MSE and SSE values obtained from the linear regression model, Tobit regression model, Heckman sample selection model, and sample selection model with endogenous covariates, it was concluded that the Heckman sample selection model is the best model that fit the dataset since it yields the best results with the smallest MSE and SSE values

PENGARUH MODEL PEMBELAJARAN CORE (Connecting, Organizing, Reflecting, Extending) TERHADAP KEMAMPUAN BERPIKIR KREATIF DAN DISPOSISI MATEMATIS PESERTA DIDIK KELAS VIII DI SMP SWASTA AL- MANAR

2024-01-27T20:02:17+07:00

This research is an experimental study with research objectives: 1) to determine the influence of CORE learning models (connecting, organizing, Reflecting, extending) on the mathematical creative thinking skills of students. 2) to find out the influence of CORE learning models (connecting, organizing, Reflecting, extending) on the mathematical disposition of students. The entire research population of the students of the First High School (SMP) Private Al-Manar in Medan Johor. The research sample is a private junior high school student of Al-Manar Medan Johor class VIII who totaled 126 people. The research method used is experiments with the Pre Test and Post Test research design to determine the initial capabilities and end abilities of the students. Data collection using mathematical ability test instruments, critical thinking skills tests, and mathematical dispositioned cartoon sheets. Hypothesis test analysis technique uses test-t paired. The results of the study are: 1) There is an influence of CORE learning model (Connecting, Organizing, Reflecting, Extending) on students’ creative thinking skills. This is in line with the hypothesis test results where t calculate > t table 3, 84 > 2.01 with Ho test criteria rejected and Ha accepted. 2) There is an influence of CORE learning model (Connecting, Organizing, Reflecting, Extending) on student mathematical disposition. This is in line with the hypothesis test results where t calculate > t table is 3, 95 > 2.01 with Ho test criteria rejected and Ha accepted. From the results of the analysis obtained findings that there are differences in mathematical learning outcomes with students taught through CORE learning models with learners taught through conventional learning models, as well as learning outcomes taught by CORE learning models higher than learners taught by conventional learning models

PENERAPAN CROSS-VALIDATION PADA MODEL EFEK CAMPURAN: DAMPAK FAKTOR EKONOMI DAN KESEHATAN TERHADAP INDEKS KERENTANAN NEGARA-NEGARA DI ASIA TENGGARA

2024-03-18T23:38:00+07:00

This research aims to investigate the impact of economic growth on the stability of countries in Southeast Asia during the period 2010–2021. The research method involves the use of data from the International Monetary Fund (IMF), the World Health Organization (WHO), the World Bank, and the Fragile State Index (FSI). A mixed-effects model was used to analyze the relationship between these variables, and K-fold cross-validation was employed to determine the optimal subset model within the mixed-effects model framework. The research results indicate a model with quadratic nonlinear trend, produces lower root mean squared error (RMSE) and mean absolute error (MAE) values compared to other models, indicating a higher level of accuracy in predicting data. The conclusion of this research is that the mixed-effects model with a quadratic non-linear assumption, particularly the third model, exhibits superior predictive performance with an RMSE of 0.628 and MAE of 0.536. However, it should be highlighted that just a few variables, particularly life expectancy, GDP, and the square of GDP, contribute considerably to the variation in the mean FSI (Fragile States Index The findings provide insights into the model's ability to capture the complexity of relationships among predictor variables and mean FSI, as well as identify the variables influencing a country's vulnerability

SUSTAINABLE SUBCONTRACTOR SELECTION IN IRRIGATION PROJECTS: A WEIGHT PRODUCT MULTI-CRITERIA DECISION ANALYSIS

2023-12-28T12:11:21+07:00

This research aims to reveal the crucial role of subcontractor selection in irrigation projects, which require water resource management to increase agricultural productivity and ensure adequate water availability. The projects are complex, involving designing efficient water distribution systems, constructing structures such as dams, and tight coordination between various stakeholders. The selection of subcontractors significantly impacts the project's success, affecting critical aspects such as time, quality, and cost. This research applies the Weight Product method as a multi-criteria decision-making approach to prioritize these aspects. The advantage of this method lies in its ability to handle multi-criteria decisions systematically. By modeling this method, this research aims to improve the effectiveness and efficiency of subcontractor selection in irrigation projects. The results are expected to provide directional guidance for the dev developing tractor selection applications to improve the quality of project implementation and r quality due to associated risks

SOLUSI MODEL LINEAR NAVIER-STOKES-KORTEWEG DI R_+^3 DENGAN SYARAT BATAS SLIP

2024-02-19T11:53:37+07:00

This article discusses the solution of the linear Navier-Stokes-Korteweg model in considering slip boundary conditions. This model is often used to describe the two-phase flow of fluids, where there is a phase change at the interface known as the capillary effect. To overcome the impact of the capillary effect, Korteweg developed the Navier-Stokes model by incorporating the element of capillary into the Navier-Stokes equations. The results of this article show that the Korteweg-type Navier-Stokes model has a solution for the coefficient case with . The emergence of this coefficient case is related to the condition of the roots of the characteristic equation of the model described in this article.

PENGEMBANGAN PERANGKAT PEMBELAJARAN BERBASIS MODEL DISCOVERY LEARNING UNTUK MENINGKATKAN KEMAMPUAN PEMAHAMAN KONSEP DAN DISPOSISI MATEMATIS SISWA BERBANTUAN GEOBOARD KELAS VII SMP SWASTA AL MANAR MEDAN

2024-01-18T12:40:20+07:00

The purpose of this study is to determine the validity, practicality and effectiveness of learning tools developed based on the discovery lerning model to improve the ability to understand concepts and mathematical dispositions of geoboard-assisted students. Researchers use the development method or R&D (research and development) with a 4-D model (four-D) developed by Thiagarajan, Semmel and Semmel. Which includes the process of define, design, develop, and disseminate stages. The subjects in this study were grade VII students of Al Manar Medan Private Junior High School. From the results of field trials, it can be concluded that: 1) learning devices that meet the validity criteria with a very valid predicate with each RPP average value is 4.61, Module is 4.56, and LAS is 4.58, 2) practical learning tools based on the validation results from the expert team have met the validity with a little revision and the results of interviews with students / users get positive responses, 3) meet the effectiveness criteria based on the results of the concept comprehension ability test meet classical completeness with a value of 86.36%, the results of teacher observations managing learning have been effective because of the increase from the first meeting to the last meeting, the results of achieving the ideal percentage of time interval are at the threshold of time tolerance of predetermined categories, and from the results of the mathematical disposition ability questionnaire it is concluded that all aspects get a positive response

PENERAPAN FUZZY ANALITYCAL HIERARCHY PROCESS UNTUK MENENTUKAN PRIORITAS PEMBANGUNAN IRIGASI DI PROVINSI SUMATERA UTARA

2024-03-18T23:37:24+07:00

In agriculture, irrigation is important, one of the factors that will ensure agriculture runs well is irrigation. Artificial irrigation can be a solution to this problem, but creating artificial irrigation requires quite a large cost. Therefore, Dinas Tanaman Pangan dan Holtikultura is helping farmers to develop a tertiary plot irrigation network covering an area of less than 1000 hectares. With so many applications coming to the Dinas Tanaman Pangan dan Holtikuoltura, the Fuzzy Analytical Hierarchy Process method could be a solution for determining irrigation development priorities. The results of the analysis used the Fuzzy Analytical Hierarchy Process with the criteria: Irrigation Area, Area of Rice Fields Served by Irrigation, Irrigation Development Costs, and Construction Time and alternatives: Sunggal Irrigation Area, Teluk Mengkudu Irrigation Area, Pantai Cermin Irrigation Area, Medang Deras Irrigation Area, Lima Puluh Pesisir Irrigation Area, Gunung Malela Irrigation Area, Nagori Silulu Irrigation Area, Juhar Irrigation Area, Sayur Matinggi Irrigation Area, Panyabungan Irrigation Area and Panyabungan Barat Irrigation Area, namely the Lima Puluh Pesisir area is ranked first in the priority of irrigation development in North Sumatra with a value of 0.852

ADVANCED MACHINE LEARNING TECHNIQUES FOR SEISMIC ANOMALY DETECTION IN INDONESIA: A COMPARATIVE STUDY OF LOF, ISOLATION FOREST, AND ONE-CLASS SVM

2023-12-17T12:19:40+07:00

This study presents a comprehensive comparison of three machine learning algorithms for anomaly detection within seismic data, focusing on the unique geographical and geological context of Indonesia, a region prone to frequent seismic events. Local Outlier Factor (LOF), Isolation Forest, and One-Class SVM were assessed using a meticulously curated dataset from the Indonesian Meteorology, Climatology, and Geophysical Agency, standardized to ensure consistent feature scale. Our analysis encompassed both statistical metrics and visualizations to evaluate the performance of each algorithm. The One-Class SVM emerged as the most effective method, achieving the highest silhouette score, indicative of its superior cluster formation and clear distinction between inliers and outliers. The Isolation Forest also demonstrated strong performance with a favorable silhouette score and Davies-Bouldin index, suggesting effective anomaly isolation capabilities. In contrast, the LOF algorithm showed less precision, as indicated by lower silhouette scores and a higher Davies-Bouldin index, suggesting potential challenges in distinguishing between normal and anomalous seismic patterns. Statistical validation using the Kruskal-Wallis H-test confirmed significant differences in the anomaly score distributions of the three algorithms, with a p-value of 0.0. Visualizations through PCA and t-SNE reinforced the quantitative findings, displaying a clear demarcation of anomalies by the One-Class SVM and Isolation Forest, unlike the LOF.The findings underscore the importance of selecting appropriate anomaly detection methods for seismic data analysis, highlighting the robustness of One-Class SVM and Isolation Forest for such applications. The implications of this research are profound for seismic risk management, providing insights that enhance the accuracy and reliability of earthquake prediction systems, which is vital for regions with high seismic activity such as Indonesia.

PENGARUH PERUBAHAN IKLIM TERHADAP PRODUKSI PERIKANAN TANGKAP DI KOTA BATAM MENGGUNAKAN ANALISIS REGRESI TIME SERIES

2024-02-09T14:04:20+07:00

This research aims to describe the influence of temperature, wind speed and rainfall on caught fish production in the city of Batam. The research method used is quantitative using a time series regression test which was analyzed from January 2019 to December 2022 with the variables analyzed being temperature (X1), wind speed (X2), rainfall (X3) and capture fisheries production (Y) . Partial test results show that the relationship between wind speed (X2) and rainfall (X3) on Y is negative, meaning that the higher the wind speed (X2) and rainfall (X3), the lower the production of caught fish (Y). Meanwhile, partial test results show that temperature (X1), wind speed (X2) and rainfall (X3) together have a significant effect on capture fisheries production (Y) in Batam city. The partial test results show that the significance value for the temperature variable (X1) is 0.25 > 0.05, which means that the temperature variable (X1) has no effect on capture fisheries production (Y) in Batam city. Meanwhile, the partial test results on the variables wind speed (X2) and rainfall (X3) obtained a value of 0.00 < 0.05, which means that the variables wind speed (X2) and rainfall (X3) have an effect on capture fisheries production (Y) in Batam city. Meanwhile, the results of simultaneous tests show that temperature (X1), wind speed (X2) and rainfall (X3) together have a significant effect on capture fisheries production (Y) in the city of Batam with a significance value of 0.00 < 0 .05. The coefficient of determination value in this study was 0.686. This means that weather changes have a proportion of influence on Batam city capture fisheries production of 68.6% while the rest is influenced by other variables outside this model