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All Journal CESS (Journal of Computer Engineering, System and Science) Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Zero : Jurnal Sains, Matematika, dan Terapan G-Tech : Jurnal Teknologi Terapan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Asimetris: Pendidikan Matematika dan Sains Journal of Information Technology (JIfoTech) Jurnal Pengabdian Mitra Masyarakat Advance Sustainable Science, Engineering and Technology (ASSET)

Rina Widyasari

Universitas Islam Negeri Sumatera Utara

Author-ID : 3041683

Religion Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences

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Implementasi Metode Promethee dalam Penentuan Penerima Bantuan Zakat pada Mahasiswa Rima Aprilia; Rina Widyasari
CESS (Journal of Computer Engineering, System and Science) Vol 6, No 2 (2021): Juli 2021
Publisher : Universitas Negeri Medan

During the payment of a single tuition fee (UKT) every semester, students are always faced with the problem of outstanding students but unable to pay tuition fees. Therefore, the university provides a solution to give zakat obtained from lecturers to outstanding and underprivileged students through the selection process. So far, the student selection process is still done manually, not using a system or program. So that the distribution of educational aid recipients (zakat) is considered not on target. This will certainly be a continuous problem of injustice, especially now that we have entered the digital era 4.0, all processes use a digital system. The provision of educational fund assistance in the form of zakat must be based on established rules, in this case the rules are in the form of established criteria, namely student IP, parental income, number of siblings, number of dependents of parents, semester, and others. The purpose of this study is to test whether the Promethee method is a method that can solve these problems. In addition, this research also forms a flow chart for selecting recipients of educational assistance using the Promethee method. The results of this study indicate that the problem of determining recipients of zakat assistance by students can be solved using the PROMETHEE method. Promethee (Preference Ranking Organization for Enrichment Evaluation), This method is appropriate for determining recipients of zakat assistance.

Algorithm Symmetric 2-DLDA for Recognizing Handwritten Capital Letters Ismail Husein; Rina Widyasari
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 2 (2022)
Publisher : LPPM Universitas Bumigora

Statistical pattern recognition is the process of using statistical techniques to obtain information and make informed decisions based on data measurements. It is possible to solve the doubt inherent in the objective function of the 2-Dimension Linear Discriminant Analysis by employing the symmetrical 2-Dimension Linear Discriminant Analysis approach. Symmetrical 2-dimensional linear discriminant analysis has found widespread use as a method of introducing handwritten capital letters. Symmetric 2-DLDA, according to Symmetric 2-DLDA, produces better and more accurate results than Symmetric 2-DLDA. So far, pattern recognition has been based solely on computer knowledge, with no connection to statistical measurements, such as data variation and Euclidean distance, particularly in symmetrical images. As a result, the aim of this research is to create algorithms for recognizing capital letter patterns in a wide range of handwriting. The ADL2-D symmetric method is used in this study as the development of the ADL2-D method. The research results in an algorithm that considers the left and right sides of the image matrix, as opposed to ADL2-D, which does not consider the left and right sides of the image matrix. In pattern recognition, the results with symmetric ADL2-D are more accurate

Utilization of Betel Leaf Extract as a Natural Hand Sanitizer to Prevent The Spread of Covid-19 in MTS. S Al-Hidayah, Silo Baru Village, Asahan Regency Syafitriani; Novianti; Andayani; Rina Widyasari; Ismail Husein
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2022): ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Betel leaf (Piper betle Linn) can be found in Silo Baru Village, Silau Laut District, Asahan Regency. This service activity aims to increase public knowledge about the content of betel leaf extract compounds as natural hand sanitizers, improve community skills in processing traditional betel leaf plants, and produce environmentally friendly hand sanitizer products made from betel leaf. Betel leaf, known as a natural antiseptic, analgesic and anti-inflammatory. Betel leaf extract contains flavonoid compounds, polyphenols, tannins and essential oils that can eradicate disease-causing germs. The content of compounds in betel leaf extract 15% and above is as effective as 70% ethanol which can reduce the number of bacteria and viruses. This activity is carried out using mentoring and training methods. The results of this activity include producing a natural hand sanitizer product that can support government programs in preventing the spread of the covid-19 virus, increasing local community knowledge through students and several teachers at MTs.S Al-Hidayah who participate in mentoring on how to manage and the introduction of the content of betel leaf extract to be used as the main ingredient in making natural hand sanitizers.

Optimasi Pemasangan Jalur Pipa Air Bersih Melalui Minimum Spanning Tree Dengan Algoritma Prim Rina Filia Sari; Rina Widyasari; Fithria Aidra Marpaung
G-Tech: Jurnal Teknologi Terapan Vol 7 No 1 (2023): G-Tech, Vol. 7 No. 1 Januari 2023
Publisher : Universitas Islam Raden Rahmat, Malang

Water is a very important need for human survival, without water there will be no life on earth. Because of the importance of the need for clean water, it’s natural if the clean water sector gets priority main handling because it involves the lives of many people. There are many ways to get clean water, one of which is by installing the pipes of clean water will be done in Kwala Air Hitam Village. The issue of pipe installation this clean water can be overcome through the Minimum Spanning Tree approach pipe installation can be more optimal. Search for the Minimum Spanning Tree using the prim algorithm manually. The research aims to get a minimum cost of installation of clean water pipes through Minimum Spanning Tree uses Prim Algorithm. The Prim Algorithm is a algorithm in the graph theory to find a minimal range tree for a graph which is connected to each other. In the results of research the Minimum Spanning Tree using the Prim Algorithm manually is obtained in total the length of the pipe which will be installed is 9.806 metres with 52 points and 56 sides. And the first graph had 52 points and 59 sides with a length of the pipes are 9.969 metres. So, the minimum fee amount Rp. 1.732.850.000 (one billion seven hundred thirty two million eight hundred fifty thousand rupiahs).

RELATIVE RISK ANALYSIS OF THE SPREAD OF COVID-19 VIRUS IN MEDAN CITY BY SPATIAL AND NON-SPATIAL APPROACHES Yurid Audina; Rina Filia Sari; Rina Widyasari
ZERO: Jurnal Sains, Matematika dan Terapan Vol 6, No 2 (2022): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v6i2.14557

The city of Medan is the city with the highest cases of COVID-19 virus among cities in North Sumatra. This study was conducted to analyze the relative risk level for the spread of the COVID-19 virus. Estimation of relative risk is a statistic in disease mapping that is used to determine the distribution of disease. Relative risk estimation can be estimated using a direct estimator model or Standardized Morbility ratio and a small area estimation model using Bayesian Conditional Autoregressive (CAR) with the Poisson-Gamma model. The Poisson-Gamma model is one of the models in estimating small areas in the form of count data which is suitable for use in disease mapping cases. This study aims to find the relative risk value as the basis for mapping the spread of the COVID-19 virus in the city of Medan using the Standardized Morbility Ratio and Bayesian Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research. Condition Autoregressive models. And look for the value of the Central Error Squared (KTG) / Mean Squared Error (MSE) as a comparison which model is more efficient in estimating this research.

IMPLEMENTATION OF THE GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) MODEL IN THE CASE OF THE SPREAD OF CORONAVIRUS IN THE DISTRICT CITY OF NORTH SUMATRA Alfina Febriani Nasution; Riri Syafitri Lubis; Rina Widyasari
ZERO: Jurnal Sains, Matematika dan Terapan Vol 6, No 2 (2022): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v6i2.14785

Corona Virus Disease 2019 (COVID-19) is a new virus that can be transmitted and the worst impact is death. Covid-19 first appeared in Wuhan, China and eventually spread throughout the world, one of which was North Sumatra Province. The spread of Covid-19 cases was quite rapid, until finally the World Health Organization (WHO) declared the Covid-19 case a pandemic. Based on the conditions that occurred, this final project discusses the prediction of positive cases of Covid-19 in five locations in North Sumatra using the Generalized Space Time Autoregressive (GSTAR) model. Considering that Covid-19 spreads very easily, it does not only depend on time but also the proximity between locations, so the GSTAR model is quite good to use in predicting it, assuming the parameters between locations are heterogeneous. The estimation used is OLS with inverse distance weight. This study aims to determine the best GSTAR model and forecast positive cases of Covid-19 at five locations in North Sumatra. The results show that the best GSTAR model in this study is -OLS with an inverse weight of distance with forecasting results for the next 10 days in May 2022.

ANALYSIS OF FACTORS INFLUENCING THE EVENT STUNTING WITH CHI-SQUARE METHOD APPROACH AUTOMATIC INTERACTION DETECTION IN NORTH SUMATRA Mei Yunina Arianti; Ismail Husein; Rina Widyasari
ZERO: Jurnal Sains, Matematika dan Terapan Vol 6, No 2 (2022): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v6i2.14783

In statistics, one way to group (classify) a data mathematically is called classification. There are several types of classification methods, one of which is Chi-Square Automatic Interaction Detection, which is abbreviated as CHAID. CHAID method will be applied to North Sumatra stunting data. Stunting is a condition in which a person's height is shorter than that of other people of the same age. The dependent variable in the study was stunting, which was measured in infants aged 24-59 months, while the independent variable was a factor that affected stunting. The factors that influence the incidence of stunting in infants aged 24-59 months in North Sumatra based on the results of the analysis (CHAID) are family income, sanitation and water sources. From the results of the CHAID analysis, 5 different groups were obtained, namely: Infants aged 24-59 months who were stunted were infants with an economic income of IDR 1,000,000 - IDR 2,000,000 (98.4%) and inadequate sanitation (100%), Babies aged 24-59 months who are stunted are babies with an economic income of IDR 1,000,000 - IDR 2,000,000 (98.4%) and proper sanitation (93.2%), babies aged 24-59 months who are not stunted are infants with an economic income of Rp. 3,000,000 - Rp. 5,000,000 (95.5%). Infants aged 24-59 months who are not stunted are infants with an economic income of > Rp. 5,000,000 (99.5%) and adequate water sources (100%) and infants aged 24-59 months who are not stunted with an economic income of > IDR 5,000,000 (99.5%) and inadequate water sources (97.1%).

PENERAPAN METODE MARKOV CHAIN ANALYSIS DALAM MEMPREDIKSI TINGKAT ELEKTABILITAS CALON PRESIDEN 2024 MELALUI TAGAR SOSIAL MEDIA DAN GOOGLE TRENDS Mei Sarah Siregar; Rina Widyasari
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.389

To summarize the findings of the research on the prediction of electability for potential presidential candidates in the 2024 election using the Markov chain method, the study found the following results: For social media hashtags: Anies Baswedan: 0.404817, Ganjar Pranowo: 0.218493, Prabowo Subianto: 0.158993, Erick Thohir: 0.217697 For Google Trends: Anies Baswedan: 0.473078, Ganjar Pranowo: 0.328017, Prabowo Subianto: 0.128324, Erick Thohir: 0.070581 These results indicate that Anies Baswedan has the highest predicted electability based on both social media hashtags and Google Trends. Ganjar Pranowo ranks second in both categories. However, in terms of social media hashtags, Erick Thohir has a significantly higher electability than Prabowo Subianto, while in Google Trends, Prabowo Subianto has a slightly higher electability than Erick Thohir. It is important to note that these predictions may change over time as more data becomes available. Therefore, continuous calculations using the Markov chain method are necessary to update the predictions of presidential candidates' electability

PREDIKSI JUMLAH PEMAKAIAN AIR BERSIH MENGGUNAKAN METODE HYBRID SINGULAR SPECTRUM ANALYSIS (SSA) DAN SARIMA DI PDAM TIRTANADI SIBOLANGIT Sophia Salsalina; Rina Widyasari
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.405

Clean water is one of the basic human needs that is needed on an ongoing basis. Water has an important role in human life. As the population increases, the use of clean water also increases, resulting in the need for demand for the availability of clean water to continue to increase, this is explained by data from the Central Statistics Agency (2022) that the population growth rate in Sibolangit District from 2021-2022 is 0.25% and that This is also explained by data on the amount of clean water consumption by PDAM Tirtanadi Sibolangit which has increased by 6.5%. The purpose of this study is to apply the SSA-SARIMA hybrid model to predict the amount of clean water consumption in the coming period at PDAM Tirtandi Sibolangit so that there is no shortage and wastage of clean water. Hybrid SSA-SARIMA is a combination of two data analysis methods that take advantage of the advantages of each method, namely Singular Spectrum Analysis (SSA) and Seasonal Autoregressive Moving Average (SARIMA). SSA is a technique used to separate signals into periodic and non-periodic components while SARIMA is used to model time series data with trend and seasonal patterns and make predictions for future periods. SARIMA cannot separate periodic and non-periodic signals in data like SSA did. The data used in this study is monthly data on clean water usage from January 2018 to December 2022. The prediction results for the amount of clean water consumption in PDAM Tirtanadi Sibolangit in 2024 use the SSA-SARIMA(1,1,0)(1,0,0) hybrid model. )12 experienced a decrease in the use of clean water with a level of forecasting accuracy having a MAPE value of 6.920446%.

PERAMALAN HARGA CRUDE OIL MENGGUNAKAN METODE LONG SHORT-TERM MEMORY (LSTM) DALAM RECURRENT NEURAL NETWORK (RNN) Syahira Rahmadhani Siregar; Rina Widyasari
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.421

Crude oil or petroleum is a very important requirement in meeting world energy consumption. Every country definitely needs a supply of petroleum to fulfill their needs. Fluctuations in oil prices are always considered as a barometer of the economy throughout the world, so any change in oil prices is always an interesting topic to be discussed in the economic environment in every country. Therefore it is necessary to predict the price of petroleum, while the method used to predict oil prices is the Long Short Term Memory method, this study aims to predict future crude oil prices based on historical data using the Long Short Term Memory method, knowing the accuracy Forecasting crude oil prices and increasing market efficiency to be more efficient in allocating resources and in this study resulted in an RMSE accuracy of 2,665 and 2.7% Mape for data starting in 2018-2023, while for data for 2020-2023 it produces an RMSE accuracy of 2,630 and MAPE is 2.9%.

Co-Authors Afnaria Afnaria Alfina Febriani Nasution Andayani Chairina Chairina Chindy Aulia Putri Chindy Aulia Putri Fithria Aidra Marpaung Hendra Cipta Ismail Husein, Ismail Khairul Purqon Mei Sarah Siregar Mei Yunina Arianti Mei Yunina Arianti Muhammad Fathonni Mutiah Nasution Novianti Rahmadita Pratiwi Rakhmawati, Fibri Rima Aprilia Rina Filia Sari Riri Syafitri Lubis Siregar, Machrani Adi Putri Sophia Salsalina Syafitriani Syahira Rahmadhani Siregar Syech Suhaimi Yanna Rezki Fadillah Yurid Audina

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