Forecasts marine weather on Java sea using hybrid methods: TS-ANFIS

Adyanti, Deasy Alfiah; Asyhar, Ahmad Hanif; Novitasari, Dian Candra Rini; Lubab, Ahmad; Hafiyusholeh, Moh.

doi:10.1109/eecsi.2017.8239162

Cited by 10 publications

(9 citation statements)

References 6 publications

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“…Pemodelan matematika sebagaimana yang dimaksud tentunya tidak hanya dilakukan untuk masalah pendistribusian barang dan jasa, akan tetapi juga pada aspek yang lain. Sebagai contoh terapan pemodelan matematika untuk mitigasi bencana [6], peramalan cuaca laut [8] dan lain sebagainya. Selain pemodelan matematika, hal yang diperlukan adalah suatu metode pengambilan keputusan yang dapat mendukung proses eksekusi model matematka yang sudah dibuat.…”

Section: Pendahuluanunclassified

Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

Faisol

Makruf

2017

JMM

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AbstrakProses distribusi produk merupakan suatu upaya untuk menyampaikan suatu produk ketangan konsumen dengan sistem yang terencana dan terprogram. Metode Cluster merupakan pengelompokan lokasi pasar yang terdekat, selanjutnya dilakukan analisa stentang lokasi fasilitas potensial melalui central of gravity. GVRP (Generalized Vehicle Routing Problem) salah satu algoritma dalam metode cluster. Dalam GVRP ini dideskripsikan penentuan rute untuk meminimalkan biaya distribusi yang diperlukan. GVRP adalah generalisasi dari VRP, sehingga titik dari graf dipartisi menjadi beberapa set titik tertentu, yang disebut cluster [2]. Pada penelitian ini dilakukan modifikasi model GVRP untuk kasus kendaraan multi kapasitas yang dapat menentukan rute dan meminimalkan biaya distribusi. Diambil kasus pada UD. Damai Asih untuk penyebaran batik tulis Madura ke 25 kabupaten di Jawa Timur. Dari hasil running menggunakan MATLAB 7.8.0 didapatkan efesiensi biaya distribusi sebesar 8.71% dari biaya awal sebelum dilakukan pengclusteran berdasarkan jarak dan kapasitas maksimal mobil sebesar Rp. 6,969,480.00. Setelah dilakukan pengclusteran berdasarkan jarak dan kapasitas maksimal mobil diperoleh biaya sebesar Rp. 6.365.500.00. Nilai efesiensi paling tinggi diperoleh pada cluster empat, sedangkan nilai efesiensi terendah diperoleh pada cluster delapan. Adanya efesieinsi biaya dikarenakan jarak tempuh yang berbeda pada proses pengclusteran. Kata Kunci : GVRP, Batik Tulis Madura, Distribusi Produk AbstractProduct distribution process is an effort to convey a product of consumer handlebar with planned and programmed system. Cluster method is a grouping of the nearest market location, then analyzed the location of potential facilities through central of gravity. GVRP (Generalized Vehicle Routing Problem) is one of the algorithms in the cluster method [1]. In the GVRP describes the route determination to minimize the required distribution costs. GVRP is a generalization of VRP, so the point of the graph is partitioned into several sets of specific points, called clusters [2]. In this research, modification of GVRP model for multi-capacity vehicle case can determine the route and minimize the cost of distribution. Taken case on UD. Damai Asih for the distribution of Madura write batik to 25 districts in East Java. From the results of running using MATLAB 7.8.0 obtained the efficiency of the distribution cost of 8.71% of the initial cost before doing the clustering based on distance and maximum capacity of the car of Rp. 6,969,480.00. After the filtering based on the distance and maximum capacity of the car obtained a cost of Rp. 6.365.500.00. The highest value of efficiency is obtained in cluster four, while the lowest efficiency value is obtained in cluster eight. The existence of cost efficiency is due to the different mileage in the clustering process.

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Section: Pendahuluanunclassified

Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

Faisol

Makruf

2017

JMM

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“…The ANFIS with time series analysis is one of the intelligent systems that can be used to predict with good accuracy in all fields [2] [3] [4]. As in the field of meteorology, ANFIS is quite good in forecasting maritime weather system [5].…”

Section: Introductionmentioning

confidence: 99%

“…ANFIS is a method that can handle complex and nonlinear systems through learning algorithms and numerical data (time series) [5], ANFIS can also adapt to atmospheric variables through the neuron system of Artificial Neural Networks (ANN) in ANFIS [5]. This can be seen from researches about predictions using the ANFIS Time Series model.…”

Section: Introductionmentioning

confidence: 99%

“…Some of them are research conducted by Agrawal et al on Indian weather forecasting using ANFIS and ARIMA based Interval Type-2 Fuzzy Logic Model [6]. And then, Babu, et al who comparison of ANFIS and ARIMA model for weather Forecasting [7], then research by Adyanti et al who implements the time series -ANFIS in predicting maritime weather in the Java Sea [5].…”

Section: Introductionmentioning

confidence: 99%

“…Based on the researches that have been developed, maritime weather predictions made only using the model ANFIS design grid partition (genfis1) [5]. Whereas in designing ANFIS models, there are three fuzzy inference system structures namely grid partition (genfis1 function), subtractive clustering (genfis2 function) and fuzzy c-means (FCM or genfis3 function) [3] [8] [9] [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal ANFIS Model for Forecasting System Using Different FIS

Adyanti¹,

Novitasar²,

Asyhar³

et al. 2018

EECSI

Self Cite

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Adaptive Network Based Fuzzy Inference System (ANFIS) with time series analysis is one of the intelligent systems that can be used to predict with good accuracy in all fields like in meteorology's field. However, some researches on prediction or forecasting do not emphasize the structure of the ANFIS fuzzy inference system. Thus, in this research, the optimization of the ANFIS model for forecasting maritime weather was carried out by analyzing the exact initialization determination in the three ANFIS fuzzy inference structures, they are grid partition, subtractive clustering, and fuzzy cmeans clustering. The input variable used in this research is each variable for the previous two hours, one hour, and at a time and the output of this system is the prediction of one hour, six hours, twelve hours and one day ahead of the ocean current speed (cm/s) and wave height (m) using all three FIS ANFIS approaches. Based on the results, the smallest goal error (RMSE and MSE) of the three FIS ANFIS approaches used for predicting the current speed and wave height, the best model is produced by Subtractive Clustering. It can be seen that Subtractive Clustering produces the smallest RMSE and MSE error values.

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Development of a Cyber-Physical System for Neurofuzzy Prediction of the Concentration of the Contained Prime During Transportation of Oil Wells Emulsion

Sagdatullin

Degtyarev

2022

Cyber-Physical Systems: Intelligent Models and Algorithms

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Forecasts marine weather on Java sea using hybrid methods: TS-ANFIS

Cited by 10 publications

References 6 publications

Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

Optimal ANFIS Model for Forecasting System Using Different FIS

Development of a Cyber-Physical System for Neurofuzzy Prediction of the Concentration of the Contained Prime During Transportation of Oil Wells Emulsion

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