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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknik Industri EKSAKTA: Journal of Sciences and Data Analysis Jurnal Matematika Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Information Systems Engineering and Business Intelligence JITEK (Jurnal Ilmiah Teknosains) Jurnal Matematika: MANTIK JMPM: Jurnal Matematika dan Pendidikan Matematika JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Unisda Journal of Mathematics and Computer Science (UJMC) International Journal of Computing Science and Applied Mathematics Zeta - Math Journal Multitek Indonesia : Jurnal Ilmiah Mathvision : Jurnal Matematika Systemic: Information System and Informatics Journal Applied Technology and Computing Science Journal Specta Journal of Technology Indexia International Journal of Data Science, Engineering, and Analytics (IJDASEA) J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat)
Dinita Rahmalia, Dinita
Universitas Islam Darul 'Ulum Lamongan
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Veterinary

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Analytic Hierarchy Process (AHP) dan Fuzzy TOPSIS pada Pemilihan Himpunan Pairing Terpilih dari Jadwal Penerbangan Dinita Rahmalia; Awawin Mustana Rohmah; Nuril Lutvi Azizah
JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Vol 4, No 1 (2020): October
Publisher : Industrial Engineering, Engineering of Faculty, Universitas Kadiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/jatiunik.v4i1.922

Abstract

In the flight industry, there are two highest costs such as fuel cost and crew cost. The crew cost is affected by pairings selected from flight schedule. This research will explain about selecting the set of selected pairings using Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS). Before using either Fuzzy AHP or Fuzzy TOPSIS, it will be formed collection of the set of selected pairings using greedy algorithm. After collection of the set of selected pairings is formed, then we determine goal and criteria. The goal is selecting the set of selected pairings from some alternatives. For each the set of selected pairings, there are some criterions such as the number of deadhead, the number of pairing A2, the number of pairing A3, the number of pairing A4, the number of pairing A5, and the number of pairing A6. Based on simulation results, both AHP and Fuzzy TOPSIS can select and give the rank of priority in entire the set of selected pairings.  Pada industri maskapai penerbangan, terdapat dua biaya yang sangat besar yaitu biaya bahan bakar dan biaya kru. Biaya kru dipengaruhi oleh pairing yang terpilih dari jadwal penerbangan. Pada penelitian ini akan dilakukan pemilihan himpunan pairing terpilih menggunakan metode Analytic Hierarchy Process (AHP) dan Fuzzy Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS). Sebelum menggunakan AHP atau Fuzzy TOPSIS, akan dibentuk kumpulan dari himpunan pairing terpilih menggunakan greedy algorithm. Setelah kumpulan himpunan pairing terpilih terbentuk, maka dibentuk goal dan kriteria. Goal adalah memilih himpunan pairing terpilih dari beberapa alternative. Pada setiap himpunan pairing yang terpilih, terdapat beberapa kriteria seperti jumlah deadhead, jumlah pairing A2, jumlah pairing A3, jumlah pairing A4, jumlah pairing A5, dan jumlah pairing A6. Berdasarkan hasil perhitungan, metode AHP dan Fuzzy TOPSIS dapat memilih dan memberi peringkat prioritas pada pemilihan himpunan pairing terpilih.
Estimation of Exponential Smoothing Parameter on Pesticide Characteristic Forecast using Ant Colony Optimization (ACO) Dinita Rahmalia
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 18, ISSUE 1, February 2018
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol18.iss1.art6

Abstract

Pest in agriculture can raise plant disease and fail to harvest. The pest problem in agriculture can be solved by using pesticide. Pesticide usage must be done proportionally. So, the manufacturer should fix standard pesticide active ingredient in pesticide production. Forecast is a prediction of some future evens. In forecast problem, there are any parameters which should be determined. Parameters can be estimated by exact method or heuristic method. Ant Colony Optimization (ACO) is inspired from the cooperative behavior of ant colonies, which can find the shortest path from their nest to a food source. In this research, we use heuristic method like ACO to estimate exponential smoothing parameter on pesticide active ingredient forecast and pesticide sample weight forecast. From the simulation, on the first iteration, all ants choose parameter randomly. At the optimization process, we update pheromone until all ants choose the similar parameter so that process converges and variance approaches to zero. The optimal exponential smoothing parameter can be applied in forecasting with minimum sum of squared error (SSE).
Vaksinasi dan Treatment pada Predator-Prey dengan Dua Jenis Pemangsa yang Salah Satunya Terinfeksi Khozin Mu'tamar; Dinita Rahmalia; Sutimin Sutimin
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 19, ISSUE 2, August 2019
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol19.iss2.art4

Abstract

Predator-prey adalah model matematika yang menggambarkan perilaku interaksi dua spesies, satu diantaranya merupakan pemangsa dan satu lainnya sebagai mangsa. Populasi pemangsa biasanya berada di level lebih atas dibandingkan level mangsa pada rantai makanan. Oleh karena itu, populasi pemangsa lebih sedikit dan rentan akan kepunahan baik karena penyakit ataupun kalah persaingan. Pada artikel ini, dikembangkan model predator-prey dengan dua jenis pemangsa dan salah satunya terinfeksi penyakit. Untuk mencegah penyebaran, diberikan tindakan vaksinasi dan pengobatan yang dirumuskan menggunakan Pontryagin Minimum Principle (PMP). Analisis kestabilan dilakukan secara lokal untuk menunjukkan tindakan vaksinasi dan pengobatan berpengaruh terhadap sifat kestabilan. Terakhir, simulasi dilakukan secara numerik guna melihat perilaku model dan performa vaksinasi dan treatment yang diberikan
Peramalan Nilai Tukar Petani Kabupaten Lamongan dengan Arima Mohammad Syaiful Pradana; Dinita Rahmalia; Ericha Dwi Ayu Prahastini
Jurnal Matematika Vol 10 No 2 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2020.v10.i02.p126

Abstract

Agriculture is a sector that has a significant role for the Indonesian economy. In Lamongan Regency, about 35.71 percent of the workers depends on the primary agricultural sector, so it is not surprising that the agricultural sector is the basis of growth, especially in rural areas. Agricultural development is oriented towards improving the welfare of farmers. One of the measurements the level of farmer welfare is by calculating the Farmer Exchange Rate. It is the relationship between the produce sold by farmers and the goods and services purchased by farmers. Seeing how important this Farmer Exchange Rate is, predicting the value of Farmer Exchange Rate in the following year will be very useful. The results of this value can be a benchmark to anticipate all situations in the following years and how to control the rising value of Farmer Exchange Rate so as to improve the welfare of the people of Lamongan. From the results of the analysis and discussion, food plants have a low NTP value, namely ?100 per month for a period of 3 years and have the highest Farmer Exchange Rate reduction in 2019 of 10.25%.
Penyelesaian Positif Model Penyebaran Virus Ebola Antar Dua Wilayah Awawin Mustana Rohmah; Dinita Rahmalia
Jurnal Matematika Vol 10 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2020.v10.i01.p122

Abstract

A Model describing the epidemic spread of the Ebola virus disease in region 1 and region 2 can be formed in a mathematical model, one of which is the SEIR endemic model. To form a mathematical model it is necessary to know the phenomenon of the spread of the Ebola virus, namely the large number of infected populations in an area which is not only caused by infected individuals in one area but can be caused by individuals traveling from one region to another. In this case, the SEIR model is analyzed for existence and uniqueness. Before doing the Analyze, the SEIR model was simplified. Then lipschitz was determined, so that an analysis of existence and uniqueness could be carried out. This shows that the SEIR model has a unique solution. Furthermore, a positive solution is determined in the model, to show that the SEIR model has a continuous and dynamic flow. Based on these results, it was found that the SEIR model in the spread of the Ebola virus had dynamic and a continuous flow.
Application Bat Algorithm for Estimating Super Pairwise Alignment Parameters on Similarity Analysis Between Virus Protein Sequences Dinita Rahmalia; Teguh Herlambang
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 6, No 2 (2020): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v6i2.14323

Abstract

There were many diseases caused by viruses or bacteria. the virus or bacteria can mutate so that they could result the new disease. Sequence alignment was important so that it could be used to research genetic diseases and epidemics. In this reseach, we took case study of dengue virus and zika virus. To see the similarity between original virus and the mutation virus, it wass required the alignment process of two virus sequences. The method used for aligning two virus sequences was Super Pairwise Alignment (SPA). Due to the similarity value depended on SPA parameters, in this research we would apply heuristic method, such as Bat Algorithm (BA) algorithm to optimize SPA parameters maximizing similarity value as objective function. BA was the optimization method which was inspired by the behavior of bats in using sonar called echolocation to detect prey, avoid obstacles. From the BA simulations, we could obtain optimal SPA parameters resulting maximum similarity value between two aligned each of dengue virus and zika virus protein sequences in approaching.
Fertilizer Production Planning Optimization Using Particle Swarm Optimization-Genetic Algorithm Dinita Rahmalia; Teguh Herlambang; Thomy Eko Saputro
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (297.382 KB) | DOI: 10.20473/jisebi.5.2.120-130

Abstract

Background: The applications of constrained optimization have been developed in many problems. One of them is production planning. Production planning is the important part for controlling the cost spent by the company.Objective: This research identifies about production planning optimization and algorithm to solve it in approaching. Production planning model is linear programming model with constraints : production, worker, and inventory.Methods: In this paper, we use heurisitic Particle Swarm Optimization-Genetic Algorithm (PSOGA) for solving production planning optimization. PSOGA is the algorithm combining Particle Swarm Optimization (PSO) and mutation operator of Genetic Algorithm (GA) to improve optimal solution resulted by PSO. Three simulations using three different mutation probabilies : 0, 0.01 and 0.7 are applied to PSOGA. Futhermore, some mutation probabilities in PSOGA will be simulated and percent of improvement will be computed.Results: From the simulations, PSOGA can improve optimal solution of PSO and the position of improvement is also determined by mutation probability. The small mutation probability gives smaller chance to the particle to explore and form new solution so that the position of improvement of small mutation probability is in middle of iteration. The large mutation probability gives larger chance to the particle to explore and form new solution so that the position of improvement of large mutation probability is in early of iteration.Conclusion: Overall, the simulations show that PSOGA can improve optimal solution resulted by PSO and therefore it can give optimal cost spent by the company for the  planning.Keywords: Constrained Optimization, Genetic Algorithm, Linear Programming, Particle Swarm Optimization, Production Planning
KLASTERISASI DATA PERTANIAN DI KABUPATEN LAMONGAN MENGGUNAKAN ALGORITMA K-MEANS DAN FUZZY C MEANS Arif Rohmatullah; Dinita Rahmalia; Mohammad Syaiful Pradana
Jurnal Ilmiah Teknosains Vol 5, No 2 (2019): JiTek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (276.66 KB) | DOI: 10.26877/jitek.v5i2.4254

Abstract

Di Indonesia, terdapat beberapa pekerja sebagai petani sebagai matapencaharian karena kebutuhan pokok pada pangan dan memiliki lahan pertanian yang luas. Karena terdapat perbedaan  luas lahan pertanian dan hasil produksi pertanian, maka diperlukan klasterisasi pada data pertanian. Tujuan klastering adalah untuk mengidentifikasi suatu kelompok data dari populasi data untuk menghasilkan sifat-sifat dari data itu sendiri. Pada penelitian ini akan digunakan dua metode yaitu : algoritma K-Means dan algoritma Fuzzy C Means (FCM). Algoritma K-Means dan algoritma FCM dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian. Pada algoritma K-Means, titik pusat klaster diupdate sehingga menghasilkan jumlahan euclidean distance yang minimum. Pada algoritma FCM, derajat keanggotaan (the degree of membership) diupdate sehingga menghasilkan nilai fungsi objective yang minimum. Berdasarkan hasil simulasi, kedua metode tersebut dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian.
Weight Optimization of Optimal Control Influenza Model Using Artificial Bee Colony Dinita Rahmalia; Teguh Herlambang
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 4, No 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.024 KB) | DOI: 10.12962/j24775401.v4i1.2997

Abstract

Influenza is disease which can be contagious through contact with infected individual. There are two types of control strategies to bound the spread of disease: prevention action for controlling susceptible and treatment for controlling infected. Optimal control is used for minimizing the number of infected individual, the cost of prevention action and the cost of treatment. Due to the cost of objective function depends on weight, in this research we will apply Artificial Bee Colony algorithm to optimize weight minimizing cost of objective function. The simulations show that the number of infected with control is lower than without control. Furthermore, we also obtain optimal weight related to cost of prevention action and treatment.
PREDIKSI JUMLAH HOTEL DAN RESTAURANT TUTUP AKIBAT DAMPAK COVID-19 MENGGUNAKAN BACKPROPAGATION DAN ADAPTIVE NEURO FUZZY Dinita Rahmalia; M. Yushak Anshori; Teguh Herlambang; Denis Fidita Karya
Indexia : Informatics and Computational Intelligent Journal Vol 3 No 2 (2021): Vol. 3 No. 2 (2021)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.468 KB) | DOI: 10.30587/indexia.v3i2.3038

Abstract

Corona Virus Disease (Covid-19) telah menjadi bencana dunia karena menyerang banyak korban di seluruh dunia dan mengakibatkan kematian. Karena virus tersebut menyerang di beberapa negara termasuk Indonesia, pemerintah Indonesia membuat keputusan untuk menutup hotel dan restaurant sebagai pencegahan Covid-19. Pada penelitian ini, metode prediksi akan dilakukan menggunakan Backpropagation dan Adaptive Neuro Fuzzy. Pada prediksi jumlah hotel dan restaurant yang tutup menggunakan Backpropagation dan Adaptive Neuro Fuzzy, dibutuhkan beberapa input seperti jumlah korban di Jakarta, jumlah korban di Indonesia, dan jumlah korban di dunia. Backpropagation dan Adaptive Neuro Fuzzy dapat menghasilkan prediksi jumlah hotel dan restaurant yang tutup mendekati nilai target. Simulasi diterapkan dengan membagi dataset ke dalam data training (80%) dan data testing (20%). Dari simulasi Backpropagation, Backpropagation dapat menghasilkan prediksi jumlah hotel dan restaurant yang tutup pada data training dengan optimal RMSE adalah 9,2422 dan data testing dengan optimal RMSE adalah 8,9419. Dari simulasi Adaptive Neuro Fuzzy, Adaptive Neuro Fuzzy dapat membuat prediksi jumlah hotel dan restaurant yang tutup pada data training dengan optimal RMSE adalah 0,5324 dan testing data dengan optimal RMSE adalah 5,3198.
Co-Authors Abdul Muhith Adrianto, Dian Andy Suryowinoto Arif Rohmatullah Arif Rohmatullah, Arif Awawin Mustana Rohmah Dennis V. Madrigal Dian Adrianto Dieky Adzkiya Elin Rias Tuti Ericha Dwi Ayu Prahastini Fajar Annas Susanto Fathul Fuad Attamini Hendro Nurhadi Husenti, Nadya Karya, Denis Fidita Khozin Mu'tamar Kresna Oktafianto Kresna Oktafianto Luluk Faridah M. Faris Naufal Hamdani M. Yushak Anshori Mohamad Yusak Anshori Mohammad Naufal Abdi Mohammad Syaiful Pradana, Mohammad Syaiful Muhammad Syaiful Pradana Muhsin Nasrul Fawa’idl Nur Aini Nuril Lutvi Azizah Sholikhah, Minhatin Nisaatus Sigit Pancahayani Siti Mutmainnah sutimin sutimin Teay Shawyun Teguh Herlambang Thomy Eko Saputro Tomasouw, Berny Pebo