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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer UNEJ e-Proceeding Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTAM (Jurnal Teori dan Aplikasi Matematika) Contemporary Mathematics and Applications (ConMathA) Tensor: Pure and Applied Mathematics Journal InEJ: Indonesian Engagement Journal Moneter : Jurnal Keuangan dan Perbankan

Herry Suprajitno

Departemen Matematika Fakultas Sains Dan Teknologi, Universitas Airlangga

Author-ID : 3399169

Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Materials Science & Nanotechnology Mathematics Social Sciences

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Optimasi Bobot K-Means Clustering untuk Mengatasi Missing Value dengan Menggunakan Algoritma Genetica Bain Khusnul Khotimah; Muhammad Syarief; Miswanto Miswanto; Herry Suprajitno
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021844912

Nilai yang hilang membutuhkan preprosesing dengan teknik imputasi untuk menghasilkan data yang lengkap. Proses imputasi membutuhkan initial bobot yang sesuai, karena data yang dihasilkan adalah data pengganti. Pemilihan nilai bobot yang optimal dan kesesuaian nilai K pada metode K-Means Imputation (KMI) merupakan masalah besar, sehingga menimbulkan error semakin meningkat. Model gabungan algoritma genetika (GA) dan KMI atau yang dikenal GAKMI digunakan untuk menentukan bobot optimal pada setiap cluster data yang mengandung nilai yang hilang. Algoritma genetika digunakan untuk memilih bobot dengan menggunakan pengkodean bilangan riel pada kromosom. Model hybrid GA dan KMI dengan pengelompokan menggunakan jumlah jarak Euclidian setiap titik data dari pusat clusternya. Pengukuran kinerja algoritma menggunakan fungsi kebugaran optimal dengan nilai MSE terkecil. Hasil percobaan data hepatitis menunjukkan bahwa GA efisien dalam menemukan nilai bobot awal optimal dari ruang pencarian yang besar. Hasil perhitungan menggunakan nilai MSE =0.044 pada K=3 dan replika ke-5 menunjukkan kinerja GAKMI menghasilkan tingkat kesalahan yang rendah untuk data hepatitis dengan atribut campuran. Hasil penelitian dengan menggunakan pengujian tingkat imputasi menunjukkan algoritma GAKMI menghasilkan nilai r = 0.526 lebih tinggi dibandingkan dengan metode lainnya. Penelitian ini menunjukkan GAKMI menghasilkan nilai r yang lebih tinggi dibandingkan metode imputasi lainnya sehingga dianggap paling baik dibandingkan teknik imputasi secara umum. AbstractMissing values require preprocessing techniques as imputation to produce complete data. Complete data imputation results require the appropriate initial weights, because the resulting data is replacement data. The choice of the optimal weighting value and the suitability of the network nodes in the K-Means Imputation (KMI) method are big problems, causing increasing errors. The combined model of Genetic Algorithm (GA) and KMI is used to determine the optimal weights for each data cluster containing missing values. Genetic algorithm is used to select weights by using real number coding on chromosomes. GA is applied to the KMI using clustering calculated using the sum of the Euclidean distances of each data point from the center of the cluster. Performance measurement algorithms using the fitness function optimally with the smallest MSE value. The results of the hepatitis data experiment show that GA is efficient in finding the optimal initial weight value from a large search space. The results of calculations using the MSE value = 0.04 for K = 3 and the 5th replication. So, GAKMI resulted in a low error rate for mixed data. The results of research using imputation level testing performed GAKMI produced r = 0.526 higher than the other methods. Thus, the higher the r value, the best for the imputation technique.

Image Encryption Technique Based on Pixel Exchange and XOR Operation Kiswara A. Santoso; Fatmawati Fatmawati; Herry Suprajitno
UNEJ e-Proceeding 2016: Proceeding The 1st International Basic Science Conference
Publisher : UPT Penerbitan Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Recently the information system develops quickly, especially information system via internet. It’s happened because the Internet can be used by anyone, anywhere and anytime. The information on the Internet has various types of data such as text, video, audio, and image/photo. Although we can access the Internet easily, but the data which transfered through internet isn’t safe. It caused by hacker, someone who manipulate information so that data become diﬀerent with the original. Many eﬀorts have been done to make the data that transmitted over the Internet to be secure, for example make the coding, disguise or hide data into other media. In this paper we intend to present the results of research about image encryption techniques to increase the security of data (image) so that safe if the data is transfered via the internet. This encryption using symmetric-key. The key is 4 BIT or a real number between 0 15. This key will be processed by each pixel in the image using XOR operation. The next step the BIT of pixels are devided into two part, LSB (least signiﬁcant bit) and MSB (Most signiﬁcant bit). Both will be exchanged if the conditions have completed. We do that to get better results, that is ﬁle size of the image encryption is smaller than the original image. The results of this research are image encryption have signiﬁcant diﬀerences with the original image, it can be proved by correlation between both images. Another advantage of this coding technique is the image encryption ﬁle size smaller than the original image ﬁle size so it can speed up of image transfer. Decode result of this coding technique is good enough, it can be seen from the mean square error (MSE) between the image encryption that has been restored to its original form and the original image. All the manufacturing process of encoding techniques have been simulated and analyzed using software MATLAB 2012a.

Penerapan Algoritma Kunang-Kunang pada Open Vehicle Routing Problem (OVRP) Ihda Septiyafi; Herry Suprajitno; Asri Bekti Pratiwi
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 1 (2019)
Publisher : Universitas Airlangga

This paper aims to solve Open Vehicle Routing Problem using Firefly Algorithm. Open Vehicle Routing Problem (OVRP) is a variant of Vehicle Routing Problem (VRP) where vehicles used to serve customers do not return to the depot after serving the last customer on each route. The steps of the Firefly Algorithm to handle OVRP are data input and initialization parameters, generating the initial population for each firefly, sorting population sources, calculating the value of the objective function and light intensity, comparing the intensity of light, performing movement, setting the best fireflies as g-best, doing random movement in the best fireflies as long as the maximum number of iterations has not been met. The program used to complete OVRP using the Firefly Algorithm is Borland C ++ and implemented in 3 case examples, namely small data with 18 customers, moderate data with 50 customers, and large data with 100 customers with the best total mileage of 211, 344 , 970.62, and 2531.83. The results obtained from the program output indicate that the more the number of iterations and the number of fireflies, then the results of the objective function (total mileage) obtained tend to be better so that these parameters affect the value of the objective function. While the absorption coefficient value (g) does not give effect to the value of the objective function.

Hybrid Artificial Neural Network with Extreme Learning Machine Method and Cuckoo Search Algorithm to Predict Stock Prices Piping Prabawati; Auli Damayanti; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

This thesis aims to predict the stock prices, using artificial neural network with extreme learning machine (ELM) method and cuckoo search algorithm (CSA). Stock is one type of investment that is in great demand in Indonesia. The portion ownership of stock is determined by how much investment is invested in the company. In this case, stock is an aggressive type of investment instrument, because stock prices can change over time. In this case, ELM is used to determine forecasting values, while CSA is applied to compile and optimize the values of weights and biases to be used in the forecasting process. After obtaining the best weights and biases, the validation test process is then carried out to determine the level of success of the training process. The data used is the daily data of the stock price of PT. Bank Mandiri (Persero) Tbk. the total is 291 data. Furthermore, the data is divided into 70% for the training process is as many as 199 data and 30% for the validation test as many as 87 data. Then compiled pattern of training and validation test patterns is 198 patterns and 82 patterns. Based on the implementation of the program, with several parameter obtained the result of MSE training is 0.001304353, with an MSE of validation test is 0.0031517704. Because the MSE value obtained is relatively small, this indicates that the ELM-CSA network is able to recognize data patterns and is able to predict well.

Flower Pollination Algorithm (FPA) to Solve Quadratic Assignment Problem (QAP) Derby Prayogo Samdean; Herry Suprajitno; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

The purpose of this paper is to solve Quadratic Assignment Problem using Flower Pollination Algorithm. Quadratic Assignment Problem discuss about assignment of facilities to locations in order to minimize the total assignment costs where each facility assigns only to one location and each location is assigned by only one facility. Flower pollination Algorithm is an algorithm inspired by the process of flower pollination. There are two main steps in this algorithm, global pollination and local pollination controlled by switch probability. The program was created using Java programming language and implemented into three cases based on its size: small, medium and large. The computation process obtained the objective function value for each data using various values of parameter. According to the pattern of the computational result, it can be concluded that a high value of maximum iteration of the algorithm can help to gain better solution for this problem.

Solving Close-Open Mixed Vehicle Routing Problem Using Bat Algorithm Atika Dwi Hanun Amalia; Herry Suprajitno; Asri Bekti Pratiwi
Contemporary Mathematics and Applications (ConMathA) Vol. 2 No. 1 (2020)
Publisher : Universitas Airlangga

The purpose of this research is to solve the Close-Open Mixed Vehicle Routing Problem (COMVRP) using Bat Algorithm. COMVRP which is a combination of Close Vehicle Routing Problem or commonly known as Vehicle Routing Problem (VRP) with Open Vehicle Routing Problem (OVRP) is a problem to determine vehicles route in order to minimize total distance to serve customers without exceed vehicle capacity. COMVRP occurs when the company already has private vehicles but its capacity could not fulfill all customer demands so the company must rent several vehicles from other companies to complete the distribution process. In this case, the private vehicle returns to the depot after serving the last customer while the rental vehicle does not need to return. Bat algorithm is an algorithm inspired by the process of finding prey from small bats using echolocation. The implementation program to solve was created using Java programming with NetBeans IDE 8.2 software which was implemented using 3 cases, small data with 18 customers, medium data with 75 customers and large data with 100 customers. Based on the implementation results, it can be concluded that the more iterations, the smaller total costs are obtained, while for the pulse rate and the amount of bat tends not to affect the total cost obtained.

Hybrid Crow Search Algorithm - Simulated Annealing untuk Menyelesaikan Vehicle Routing Problem with Time Windows Bella Pristianisa Subari; Asri Bekti Pratiwi; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 2 No. 2 (2020)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v2i2.23854

Penulisan artikel ini bertujuan untuk menyelesaikan permasalahan Vehicle Routing Problem with Time Windows (VRPTW) dengan menggunakan Hybrid Crow Search Algorithm (CSA) dengan Simulated Annealing (SA). Hybrid CSA dengan SA adalah gabungan dari kedua algoritma dengan cara melakukan proses CSA kemudian hasil terburuknya diperbaiki dengan proses SA untuk sepuluh iterasi pertama. Proses algoritma ini dimulai dengan inisialisasi parameter, membangkitkan posisi dan memori awal, menghitung fungsi tujuan, memperbarui posisi gagak, menghitung fungsi tujuan posisi baru gagak, update memori gagak, menentukan solusi terburuk dari posisi gagak kemudian dilakukan modifikasi, hasil modifikasi dengan SA menggantikan solusi terburuk pada posisi gagak, proses berlanjut sampai maksimal iterasi dipenuhi dan menentukan solusi terbaik dari memori gagak. Berdasarkan hasil implementasi pada tiga tipe data dapat disimpulkan bahwa semakin banyak jumlah iterasi, jumlah gagak, dan proses Simulated Annealing maka nilai fungsi tujuan yang diperoleh cenderung semakin baik, sedangkan nilai probabilitas kewaspadaan (AP) tidak memberikan pengaruh pada solusi permasalahan.

Penyelesaian Container Stowage Problem untuk Kontainer Ukuran 20 Feet menggunakan Whale Optimization Algorithm Quinn Nathania PJY; Asri Bekti Pratiwi; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 2 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i2.29670

This paper has purpose to solve Container Stowage Problem (CSP) for 20 feet container using Whale Optimization Algorithm (WOA). CSP is a problem discussing about how to stowage a container on the ship where the purpose to minimize the unloading time. Moreover, 20 feet container is one of container types. WOA is a recently developed swarm-based metaheuristic algorithm that is based on the bubble net hunting maneuver technique of humpback whales for solving complex optimization problems. WOA had three procedures, first encircling prey, second bubble-net attacking method or exploitation phase, and third search for prey or exploration phase. WOA application program or resolving solve CSP for 20 feet container was made by using Borland C++ programming language which was implemented in three cases types of CSP data, first, the small data taking about nine containers with the number of bays, rows and tiers, respectively, are 4, 4, 4. The second and third data was medium data and big data with 62 containers and 95 containers each data, and had the number of bays, rows and tiers, respectively, are 14, 4, 5. After executing the program can be concluded the unloading time will be better if the number of whales is larger, while the number of iterations and the number of parameter control for shape of a logaritma spiral don’t affect the solution.

Penerapan Seagulls Optimization Algorithm untuk Menyelesaikan Open Vehicle Routing Problem Laula Ika Setya Rahman; Asri Bekti Pratiwi; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 4 No. 1 (2022)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v4i1.34549

This paper aims to solve the problem of Open Vehicle Routing Problem using Seagulls Optimization Algorithm. Open Vehicle Routing Problem (OVRP) is a variation of Vehicle Routing Problem (VRP) which will not return to the depot after visiting the last customer, is different from VRP which requires the vehicle to return to the depot because the company have insufficient number of vehicles for the distribution of products to customers so they must to rent vehicles and this OVRP aims to minimize the total cost of distributing products with the shortest optimal distance to meet the demands of each customer with private vehicles and rental vehicles. Seagulls Optimization Algorithm (SOA) is the algorithm inspired by the behaviour of seagulls in migrating and ways of attacking the pray of seagulls in nature. In general, the process begins with generating the initial position, evaluating the objective function, the migration process, the attacking process to get a new position, compare the objective function for the new position and the old position, update the position and save the best seagulls in each iteration until the maximum iteration is met. The program used to complete OVRP with Seagulls Optimization Algorithm is Borland C++ and implemented using 3 case examples, small data with 18 customers, medium data 50 customers and large data 100 customers. Based on the implementation results, it can be concluded that the higher number of seagulls, iterations and the smaller the control variable value tend to effect minimum cost gained.

PELATIHAN PENGOLAHAN KUNYIT MENJADI SERBUK MINUMAN SIAP SEDUH UNTUK MENINGKATKAN KREATIVITAS DAN EKONOMI MASYARAKAT DUSUN GEMBES DESA SLAHUNG KECAMATAN SLAHUNG Zeni Murtafiani; Yayuk Wahyuni; Herry Suprajitno
InEJ: Indonesian Engagement Journal Vol 2, No 1 (2021)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) IAIN Ponorogo

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pengetahuan, kreativitas dan keterampilan masyarakat Dusun Gembes, Desa Slahung Kec. Slahung, Kabupaten Ponorogo untuk mengolah kunyit menjadi menjadi minuman siap seduh. Kegiatan dilaksanakan dua kali bertempat di rumah Bapak Kasun dan di rumah Bapak Kepala Desa dengan melibatkan 20 orang pada tahap pertama, dan 40 orang pada tahap kedua. Pada kegiatan ini digunakan metode penyuluhan interaktif dan demonstrasi dengan melalui tiga tahap, yakni tahap persiapan, pelaksanaan dan evaluasi. Hasil pelaksanaan kegiatan menunjukkan terjadinya peningkatan pengetahuan sasaran tentang kunyit serta pengolahannya menjadi minuman siap seduh. Sasaran juga tertarik untuk mengonsumsi dan memproduksi sendiri minuman rempah yang didemonstrasikan, dan akan mempraktekkan penjualan bubuk kunyit siap seduh untuk meningkatkan taraf ekonomi masyarakat. Masyarakat juga antusias untuk menyampaikan pengetahuan yang diperoleh kepada orang lain di Dusun Gembes.This community service activity aims to increase the knowledge, creativity and skills of the people of Gembes Hamlet, Slahung Village, Kec. Slahung, Ponorogo Regency to process turmeric into a ready-brewed drink. The activity was carried out twice at the house of Mr. Kasun and at the house of the Village Head, involving 20 people in the first stage, and 40 people in the second stage. In this activity, interactive counseling and demonstration methods are used through three stages, namely the preparation, implementation and evaluation stages. The results of the implementation of the activity showed an increase in target knowledge about turmeric and its processing into a brewed drink. are also interested in consuming and producing their own spice drinks which are demonstrated, and will practice selling turmeric powder ready to brew to improve the economic level of the community. The Gembes Village community is also enthusiastic about passing on their knowledge to others.

Co-Authors Anatasia Naomi Asri Bekti Pratiwi, Asri Bekti Atika Dwi Hanun Amalia Auli Damayanti Bain Khusnul Khotimah Bella Pristianisa Subari Derby Prayogo Samdean Edi Winarko Fatmawati Fatmawati Fatmawati Fatmawati Fatmawati, Fatmawati Ihda Septiyafi Kiswara A. Santoso Laula Ika Setya Rahman Miswanto Miswanto Miswanto Muhammad Syarief Piping Prabawati Quinn Nathania PJY Riwayadi, Eko Siti Sarah Syaharuddin Syaharuddin Syaharuddin Syaharuddin Yayuk Wahyuni Zeni Murtafiani

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