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All Journal Zero : Jurnal Sains, Matematika, dan Terapan ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Math Educa Journal Mandalika Mathematics and Educations Journal Journal of Computer Networks, Architecture and High Performance Computing Indonesia Bergerak: Jurnal Hasil Kegiatan Pengabdian Masyarakat
Rima Aprilia
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Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Education Mathematics Physics Public Health Other

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IMPLEMENTATION OF PAGERANK ALGORITHM IN MATLAB Rima Aprilia; Rina Filia Sari
ZERO: Jurnal Sains, Matematika dan Terapan Vol 1, No 1 (2017): January - June
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.845 KB) | DOI: 10.30829/zero.v1i1.1458

Abstract

Implementation of the PageRank algorithm to rank web generally only contain static and dynamic pages, with the rapid url users then needed an algorithm for calculating web rankings. In determining the ranking of a web, links incoming and outgoing links are also random surfer model is one decisive factor in determining the ranking of a web. Implementation of PageRank on MATLAB formed on a program in the m-file.
Monte Carlo Simulation Of Estimating Clean Water Supplies Fajari Husnul Walid; Sajaratud Dur; Rima Aprilia
ZERO: Jurnal Sains, Matematika dan Terapan Vol 5, No 1 (2021): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v5i1.11099

Abstract

Estimates are important tools in effective and efficient planning for predicting future events. Identical estimates of the future values of a variable for planning or decision making of a situation to estimate future values. Monte Carlo simulation is a simulation model that involves a series of random and sampling with a probability distribution that can be known and determined, then this simulation can be used. In this study, data is taken from the amount of water usage in PDAM Tirtanadi H.M branch. Yamin, North Sumatra from January 2018 to June 2019. Then, the data is processed and analyzed using Monte Carlo Simulation to determine the forecast results in the years that follow. The result is an estimated amount of water usage in 2019 and 2020 at PDAM Tirtanadi H.M branch. Yamin, North Sumatra is 8,604,556 and 8,592,873. The estimated amount of water use is down from the amount of water use in 2018 which reached 8,685,356. The amount of water usage in 2018, 2019 and 2020 decreases by about .
ALGORITMA MODEL PENENTUAN LOKASI FASILITAS TUNGGAL DENGAN PROGRAM DINAMIK Firmansyah Firmansyah; Rima Aprilia
ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA Vol 2, No 1 (2018): April 2018
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.687 KB) | DOI: 10.30829/algoritma.v2i1.1613

Abstract

Facility plays an important role of the real world, the facility is no longer a secondary requirement but becomes a primary need. Provision of facilities from any company requires a competitive location, so that the facilities provided can be useful for others. Dynamic Programming was once used to determine the best opening schedule of Subset as an "optimal" location and relocation strategy for planning. So in this research done determination of location of facility and its relocation with dynamic programming so hopefully can use optimal budget with optimal time.Keywords: Facility Location, Dynamic Programming
REGRESI PROBIT BINER PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEEFEKTIFAN PEMBELAJARAN PADA MASA COVID-19 Husnul Fadhillah; Fibri Rakhmawati; Rima Aprilia
Math Educa Journal Vol 6, No 1 (2022)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/mej.v%vi%i.3871

Abstract

Online learning or distance learning is learning that utilizes technology whose teaching materials are sent using an online system. This learning system is an implementation of distance education carried out to try to prevent the spread of COVID-19. This study was conducted to find out what factors affect the effectiveness of learning during the COVID-19 pandemic. The data used is primary data by distributing google forms to students who are respondents at the Faculty of Science and Technology UIN North Sumatra Medan with the response variable is the effectiveness of the online learning system where (1) for effective and (0) for less effective using the probit regression method binary. The predictor variables used were the use of learning strategies, accuracy in mastering behavior, learning curriculum, student motivation, technology literacy and learning evaluation. The amount of data collected is 400 respondents with the results of the study at a significance level of 0.05 that the factors that affect the effectiveness of learning during the COVID-19 pandemic are the use of learning strategies and literacy of technology with a classification accuracy of 91.75%.
Optimisasi Perencanaan Produksi Menggunakan Metode De Novo Programming Dan Pendekatan Minimum-Maximum (Min-Max) Goal Programming Nurmalinda Utami Siregar; Rina Filia Sari; Rima Aprilia
SAINTIFIK Vol 10 No 2 (2024): Saintifik: Jurnal Matematika, Sains, dan Pembelajarannya
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/saintifik.v10i2.498

Abstract

Penelitian ini bertujuan untuk menghasilkan jumlah keuntungan dan kapasitas produksi yang maksimal berdasarkan pada 3 jenis produk yaitu paving block segi empat, paving block segi enam, dan paving block segi delapan. Metode yang digunakan yaitu model de novo programming dan pendekatan minimum-maximum (min-max) goal programming. Untuk membentuk model de novo programming dilakukan dengan menentukan jumlah variabel keputusan, fungsi tujuan, dan fungsi kendala, selanjutnya dilakukan pemodelan min-max de novo programming pada keuntungan dan kapasitas produksi agar mendapatkan solusi optimal maksimum dan minimum pada tiap fungsi tujuan dan langkah terakhir dilakukan perhitungan menggunakan model goal programming. Berdasarkan hasil olah data menggunakan software LINGO, diperoleh nilai d = 0 artinya keuntungan dan kapasitas produksi maksimal dengan jumlah poduksi paving block segi empat sebanyak 54.060 pcs, paving block segi enam sebanyak 52.700, dan paving block segi delapan sebanyak 49.620 pcs dengan keuntungan maksimum yang diperoleh sebesar Rp. 86.936.320.
Penerapan Model Arima Untuk Peramalan Jumlah Orang yang Melakukan Pembayaran Pajak Reklame Dispenda Rima Aprilia; Aulia Rahman Siregar; Nurmala Sari Siregar; Irfan Suhendra; Fariz Hakim Fernanda
Indonesia Bergerak : Jurnal Hasil Kegiatan Pengabdian Masyarakat Vol. 3 No. 1 (2025): Januari: Jurnal Hasil Kegiatan Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/inber.v3i1.760

Abstract

The forecasting of advertisement tax payments at the Medan City Revenue Agency aims to support planning and decision-making regarding advertisement tax revenue from 2021 to 2023, covering the period from January to December. In this process, historical data on advertisement tax payments is analyzed to determine the most suitable ARIMA model by considering the Autoregressive (AR), Differencing (I), and Moving Average (MA) parameters. The research indicates that the ARIMA model can provide accurate predictions of advertisement tax payment trends, thereby serving as a tool to enhance the effectiveness of local tax management. For the period from January to October 2024, it is estimated that 1,141 individuals will make advertisement tax payments, with the lowest forecasted number occurring in January 2024 at 1,128 individuals.
Optimasi Vehicle Routing Problem (VRP) Terhadap Rute Pengangkutan Sampah Di Kota Medan Dengan Algoritma Ant Colony Optimization Kinanti, Tri; Rima Aprilia
Mandalika Mathematics and Educations Journal Vol 7 No 3 (2025): Edisi September
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i3.9787

Abstract

The growing population in Medan City has resulted in a significant increase in waste volume, creating the need for an efficient transportation system from Temporary Disposal Sites (TPS) to the Final Disposal Site (TPA). This study aims to apply the Ant Colony Optimization (ACO) algorithm to improve the efficiency of waste collection routes in the Medan Marelan District. ACO is a metaheuristic algorithm inspired by the foraging behavior of ants, where pheromone trails guide route selection. In this research, TPS and TPA locations were divided into six zones. Each zone was analyzed to determine the most efficient route based on the shortest travel distance. The research methodology consists of two main phases: route construction and pheromone updating. Data analysis was conducted manually for the first zone and through computational simulations using Python for the remaining five zones. The results show that ACO effectively produced optimal waste transportation routes in all areas. The shortest routes obtained were: Zone 1 at 17.05 km, Zone 2 at 25.25 km, Zone 3 at 16.995 km, Zone 4 at 8 km, Zone 5 at 14.83 km, and Zone 6 at 11.5 km. These findings confirm that the ACO algorithm is effective in addressing the Vehicle Routing Problem (VRP) in the context of waste transportation and offers a promising approach for enhancing urban waste management systems.
Prediction of Ovarian Cyst Disease Mortality Rate Cases Using Markov Chain Monte Carlo with Gibbs Sampling Algorithm Fazriani, Salsabila Rizky; Rima Aprilia
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6724

Abstract

Ovarian cyst is one of the reproductive disorders that can develop into ovarian cancer and cause death if not treated properly. This study aims to predict the death rate due to ovarian cyst disease using the Markov Chain Monte Carlo (MCMC) method with the Gibbs Sampling algorithm. The data used is secondary data from Malahayati Islamic Hospital Medan City in 2024, which consists of 15 patients, including one deceased patient (fictitious) for the purposes of the classification model. The independent variables used include age, length of hospitalization, and number of diagnoses, while the dependent variable is the patient's death status. The estimation process was conducted with 600 iterations, where the initial 100 iterations were used as burn-in, and the rest were used to obtain the posterior mean of the model parameters. The results show that the model is able to predict death status with 100% accuracy, where all predictions match the actual data. The parameter coefficients show that the higher the age, the longer the hospitalization, and the more the number of diagnoses, the higher the risk of death. The MCMC method with Gibbs Sampling algorithm proved to be effective in generating probabilistic predictions as well as identifying important factors that affect the risk of death of patients with ovarian cysts
Co-Authors Aulia Rahman Siregar Fajari Husnul Walid Fariz Hakim Fernanda Fazriani, Salsabila Rizky Firmansyah Firmansyah Husnul Fadhillah Irfan Suhendra Kinanti, Tri Nurmala Sari Siregar Nurmalinda Utami Siregar Rakhmawati, Fibri Rina Filia Sari Sajaratud Dur