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Analysis of Landing Airplane Queue Systems at Juanda International Airport Surabaya Farida, Yuniar; Akbar, Fadilah; Hafiyusholeh, Moh.; Hartono, Moh.
CAUCHY Vol 7, No 1 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i1.12772

Abstract

Juanda International Airport is currently preparing to realize the construction of terminal 3. This construction project impression that Juanda Airport is experiencing an overload, including in the airplane queue. This study aims to analyze the current queuing system at the Juanda International Airport apron, whether effective, quite effective, or less effective in serving the number of existing flights with two terminals. An analysis of the queuing system was conducted in several scenarios. They are in normal/regular condition, a scenario if there is an increase in flight frequency, and a scenario if there is a reduction in aprons’ number because of certain exceptional situations. To analyze the airplane’s landing queue at Juanda airport apron, the queuing model (M/M/51) : (FCFS/∞/∞) is used. From this model, the results show that in normal conditions, the estimated waiting time for each airplane in the system is 0.18 hours with a queue of 2 up to 3 planes/hour, categorized as effective. In one apron reduction scenario, each airplane’s estimated waiting time in the system is 0.7 hours, with a queue of 6 up to 7 planes categorized as less effective. In the scenario of additional flights, only 9 other flights are allowed every day to keep the service performance still quite effective. By obtaining this results analysis, the decision of PT. Angkasa Pura 1 (Persero) to build terminal 3 is suitable to reduce queuing time and improve Juanda International Airport services to be more effective.
Spline Nonparametric Regression to Analyze Factors Affecting Gender Empowerment Measure (GEM) in East Java Mahfiroh, Luluk; Farida, Yuniar
CAUCHY Vol 7, No 1 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i1.12993

Abstract

Gender is a multidimensional issue that's not limited to gender discrimination, but alsoincludes the economic, educational, and health aspects, which then become the focus of almost all the Sustainable Development Goals (SDGs). Evaluation of the development devoted to the perspective of the gender using several indicators, Gender Development Index (GDI) and Gender Empowerment Measure (GEM). GEM describes the role of women in the economic sphere and is measured by equality in political participation. GEM of East Java for 5 consecutive years (2014 – 2018) is lower than the average national GEM. This study aims to identify factors affecting GEM in East Java using nonparametric regression spline quadratic. The result ofthe regression model shows the factors affecting GEM East Java is the Labor Force Participation Rate(LFPR) population of women (), School Participation Rate(SPR) high school population of women (), Percentage of Population Female thatWorking in the formal sector (), sex ratio (), Percentage of Population Female that Working as members of People’s Representative Council (), Percentage of Population Female that working as Civil Servants (), and rate of women's income donations (). The model generates value of 93.74% and MAPE of 3.22%.This research contributes to the implementation of non-parametric spline regression in identifying various factors that influence social phenomena.
Analisis Performa Mata Uang Virtual (Cryptocurrency) Menggunakan Preference Ranking Organization Method For Enrichment Evaluation (Promethee) Farida, Yuniar; Khasanah, Zhara Shafira Uswatun
Rekayasa Vol 14, No 1: April 2021
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v14i1.8793

Abstract

Cryptocurrencies are among the inventions that have caused a stir in the economy of late. Because in its use there are still pros and cons of various countries. Some countries reject the use of cryptocurrencies and others support the use of cryptocurrencies because it is considered a modernization of payment tools. Besides being used for payment instruments, cryptocurrencies can also be one of the options to invest. The number of cryptocurrencies that exist causes investors to be observant in making the right choices. In this study, the Promethee method was used I and II to determine the rank of 7 virtual currencies. Promethee I is a partial assessment method while Promethee II is a complete assessment method. The data used for ranking is obtained from the questionnaire "sentiment on the performance of cryptocurrencies". The results of the cryptocurrency performance analysis showed that the investment commodity of the most recommended in a row is Bitcoin with a net flow value of 0.33267, Cardano 0.14267, Ethereum 0.04800, Ripple 0.04733, Stellar -0.04733, Litecoin -0.04767 and Dogecoin -0.47567.
Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method Utami, Tri Mar'ati Nur; Novitasari, Dian Candra Rini; Setiawan, Fajar; Ulinnuha, Nurissaidah; Farida, Yuniar; Sari, Ghaluh Indah Permata
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28906

Abstract

Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions. Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error. Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.
Perbandingan Metode Extreme Learning Machine (ELM) dan Kernel Extreme Learning Machine (KELM) Pada Klasifikasi Penyakit Cedera Panggul Aisah, Siti Nur; Dian Candra Rini Novitasari; Farida, Yuniar
Jurnal Fourier Vol. 12 No. 2 (2023)
Publisher : Program Studi Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/fourier.2023.122.69-78

Abstract

Nyeri punggung bawah merupakan sebuah masalah kesehatan yang umum terjadi di dunia dan termasuk penyebab utama kecacatan.  Di Indonesia  pada tahun 2019 Hernia menduduki peringkat kedelapan penyakit terbanyak dengan jumlah kasus 292.145. Selain Hernia ganguan atau penyakit yang terjadi pada tulang panggul juga disebabkan karena menderita penyakit Spondylolithesis. Penelitian ini bertujuan untuk mengklasifikasi penyakit cedera panggul menggunakan Extreme Learning Machine (ELM) dan Kernel Extreme Learning Machine (KELM). Hasil uji coba terbaik yaitu dengan Nilai akurasi, sensitivitas dan spesifitas yaitu 90.25%, 88.66%, dan 92.22% untuk metode KELM.
Forecasting Population of Madiun Regency Using ARIMA Method Farida, Yuniar; Farmita, Mayandah; Ulinnuha, Nurissaidah; Yuliati, Dian
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 7, No 3 (2022): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i3.16156

Abstract

The high population growth of the Madiun Regency can cause population density that can have implications for other problems, both in terms of social, economic, welfare, security, land availability, availability of clean water, and food needs. This study aims to predict the population growth of Madiun Regency using the ARIMA method. The ARIMA (Autoregressive Integrated Moving Average) method is popular for forecasting time series data, which is reliable because the calculation process is done gradually. This study uses annual population data of Madiun Regency from 1983 to 2021 and produces an ARIMA forecasting model (0,2,1) with a MAPE value of 8.42%. The results of this study are expected to be used as information from the Madiun Regency government in anticipating the emergence of problems caused by the population level of Madiun Regency in the future.
Implementation of Capital Asset Pricing Model in Optimal Portfolio Formation on IDX High Dividend 20 Auditiyah, Cellyn; Farida, Yuniar; Utami, Wika Dianita
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.27799

Abstract

The IDX High Dividend 20 (IDX HIDIV20) is an Indonesian stock index known for its high dividend payouts, appealing to passive income investors. However, annual changes and fluctuating stock prices present challenges, necessitating diversification strategies. This study aims to create an optimal portfolio to balance returns and risks amidst market volatility on the IDX High Dividend 20 stock index. This research uses the Capital Asset Pricing Model (CAPM) method. The CAPM determines the relationship between risk and an asset's expected rate of return, especially shares. This model helps in evaluating whether an asset or investment provides sufficient returns commensurate with its risk. In this study. We used weekly stock price data and composite stock prices from Yahoo Finance and BI interest rates taken from Bank Indonesia from January 2020 to December 2023. The research findings found that there were 6 out of 12 samples forming the optimal portfolio, namely ITMG (28.0%), ADRO (16.6%), BMRI (29.2%), BBNI (13.7%), BBCA (11.8%), and BBRI (0.6%) with a portfolio return of 0.41% and a portfolio risk level of 0.16%. The study emphasizes the importance of diversification for investors, particularly in volatile markets, to manage risks and enhance returns. It also highlights the strategic value of investing in high-dividend stocks for consistent income and portfolio stability, offering practical insights for optimizing investment strategies.
PEMODELAN ARUS LALU LINTAS DAN WAKTU TUNGGU TOTAL OPTIMAL DI PERSIMPANGAN JL. JEMUR ANDAYANI AHMAD YANI SEBAGAI UPAYA MENGURAI KEMACETAN Farida, Yuniar; Fanani, Aris; Purwanti, Ida; Wulandari, Luluk; Zaen, Nanida Jenahara
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (958.491 KB) | DOI: 10.30598/barekengvol14iss3pp387-396

Abstract

One crossroad of ​​Surabaya whose high level of congestion is the crossing of Jemur Andayani – Ahmad Yani Street. It needs to Improve traffic management, geometric, and signal time to obtain optimal traffic performance. The purpose of this study is to make a model of traffic flow and determine the optimal total waiting time at the crossing of Jemur Andayani – Ahmad Yani using Compatible Graph. Compatible graphs are two sets where vertices indicate objects to be arranged and edges indicate compatible pairs of objects. Compatible traffic flow is two traffic flows which if both of them run simultaneously can run safely and not collide. The results of the optimal waiting time calculation using a compatible graph assuming the left turn following the lamp is 75 seconds. While the optimal total waiting time by assuming the left turn not following the lights is 60 seconds. The optimal total waiting time is smaller than the actual total waiting time currently applied at Frontage Ahmad Yani street, which is 170 seconds by assuming turn left following the lights.
Implementation of LSTM Method on Tidal Prediction in Semarang Region Ambadar, Panreshma Rizkha; Novitasari, Dian C Rini; Farida, Yuniar; Hafiyusholeh, Moh; Setiawan, Fajar
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8932

Abstract

Semarang is the capital of the Central Java province, located in the north and directly adjacent to the Java Sea. Having an almost flat land condition with a slope of about 0-2%, Semarang City has the opportunity to experience tidal flooding. The occurrence of tides does not have a fixed period. So, it is necessary to predict the height of the tide and the ebb of the seawater. Thus, this research aims to predict tides in the Semarang area using the LSTM method. The data used is tidal data in Semarang waters from 2020 to 2024. The advantage of the LSTM method is its ability to effectively remember time series data or data with long-term dependence. LSTM can store past information using special cells contained in its structure. This research on tidal prediction using the LSTM method with 70% training data trial batch size 32 and epoch 200 obtained the smallest error value, namely the MAE value of 0.0388 and MAPE of 0.0313 which is the best LSTM result.
Breast Cancer Classification Based on Mammogram Images Using CNN Method with NASNet Mobile Model Pramesti, Diah Devi; Farida, Yuniar; Novitasari, Dian Candra Rini; Wibowo, Achmad Teguh
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 3 (2025): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.98187

Abstract

In Indonesia, the type of cancer that contributes to the highest death rate is breast cancer, so there is a great need for early examination, clinical examination, and screening, which includes mammography. Mammography is currently the most effective method for detecting early-stage breast cancer. This study aims to classify breast cancer cells based on mammogram images. The method used in this research is CNN (Convolutional Neural Network) with the NASNet Mobile model for classifying three classes: normal, benign, and malignant. The CNN method can learn various input attributes powerfully so that CNN can obtain more detailed data characteristics and has better detection capabilities. This research obtained the most optimal model based on the percentage of accuracy, sensitivity, and specificity values of 99.67%, 98.78%, and 99.35%, respectively. This research can be used to help radiologists as considerations in making breast cancer diagnosis decisions.