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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal IPTEK Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Teknologi Informasi dan Terapan (J-TIT) JEECS (Journal of Electrical Engineering and Computer Sciences) West Science Social and Humanities Studies Science Information System and Technology Semar: Jurnal Pengabdian Kepada Masyarakat
Eko Prasetyo
Universitas Bhayangkara Surabaya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Social Sciences Other

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Eye Black Circle of Milkfish Segmentation on Hsv Color Space Eko Prasetyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 1 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i1.143

Abstract

One of the popular fish consumed by the people is milkfish. The freshness of milkfish can be observed from eyecondition. maka segmentasi lingkatan hitam mata ikan bandeng penting dilakukan we conduct experiment in milkfishimage segmentation to get region of interest in eye circle. Kami mengusulkan frame work untuk segmentasilingkaran mata ikan bandeng menggunakan filter spasial pada komponen Hue dan Value ruang warna HSV. Byusing 10 milikfish images, we get segmentation performance with average of precision 84.04%. But we get badperformance in recall, because achieve recall 43.08%.
Instant Cement Forming Using Holt-Winter (case Study: CV Trijaya Abadi) Devit Hari Firmanto; Eko Prasetyo; Mas Nurul Hamidah
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 1 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i1.145

Abstract

CV.Trijaya Abadi is an industry that produces cement, and make various innovations by producing instant cement. Itis often the case with errors in doing the forecasting is if the amount of production is produced too much while thedemand is small it will cause losses for the company as well as vice versa if the demand a lot while the productionwill be a bit disappointment of consumers resulting in the company losing konsakuya. know the amount of instantcement production in the next period. The method used for forecasting in this research is Exponential SmoothingHolt-Winters method with multiplyative seasonal method and additive seasonal method. The alpha, beta and gammavalues used are 0.9, 0.1, and 0.1. With the value of these parameters are able to produce the value of MSEamounting to 52347.63 and MAPE value of 6,649 is forecasting in 2016 for multiplyative seasonal method. Foradditive seasonal method, the value of MSE is 50560.88 and MAPE value of 6,619 forecasting in 2016. So it isconcluded that it is more accurate to use the Holt-Winters additive seasonal method in 2016 forecasting of instantcement.
Clasification System of Library Book Based on Similarity of The Book Title Using K-Means Method (case Study Library of Bhayangkara Surabaya) Arif Mardi Waluyo; Eko Prasetyo; Arif Arizal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 1 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i1.146

Abstract

In the grouping of book data in the library of Universitas Bhayangkara Surabaya at this time, the grouping is stillbased on the title and the existing field. So that resulted in the laying of some books whose title is not in accordancewith the field of place. To facilitate the grouping of library books, in this research will provide a solution by doingthe grouping of books based on the similarity of the title using K-Means method with the distance dissmilarity. Thedata are grouped a number of 500 titles in the library of Bhayangkara University Surabaya. The data will beprocessed through the Pre-processing process first of each book title by using the Information Retrieval Systemwhich results in the basic word. The basic word that will be used as a feature in the process of grouping so that canbe known similarity. The result of the research is that it can be concluded that the application of Library BookGrouping System Based on Similarity of Book Title Using K-Means Method (Case Study of Bhayangkara LibrarySurabaya) is suitable for data that has been specified on each title. And some processes there are clusters that arealways consistent in putting the book data in accordance with the similarity. Of all test results that have the bestsilhouette value is on using the value of K = 7, ie in the process to 1 with the value of silhouette = 0.2221
Implementation of Naive Bayes Method in Classification of Breast Cancer Disease Alamsyah; Eko Prasetyo; R Dimas Prasetyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i1.162

Abstract

Less knowledge of early symptoms of breast cancer and how to deal with it early and the number of specialist doctorswho are still limited is one factor contributors because of the increasing number of people affected by breast cancerdisease. The development of breast cancer disease classification system aims to predict the early diagnosis of breastcancer disease in users or patients into two categories of malignant or benign. The initial diagnoses of this systemprediction variable include Clump Thickness, Uniformity of Cell Size, Uniformity of Cell Shape, Marginal Adhesion,Single Epithelial Cell Size (Single Epithelial Cell) Size), Bare nuclei, Bland Chromatin, Normal nucleoli, Mitosis Usingthe naive bayes method to process diagnostic data in patients, the results of this system test show that the system isable to predict and classify breast cancer disease into two categories (malignant or benign) with the amount of datatesting of 500 data. With the output of malignant or YA and benign or NO, the system is able to predict with an accuracyvalue of 98%.
System Prediction Production PT.Vico Indonesia Using Method Holt Winters Riyan Sukma Sasongko; Eko Prasetyo; Rani Purbaningtyas
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i1.166

Abstract

Problem that Taken in this study is the process of forecasting oil and gas production in accordance so that companiescan know the prediction of the amount of oil and gas in the future. The method used to determine production predictionis Holt-Winters forecasting method. In testing the system will do the comparison of alpha, beta and gamma. Using thealpha value = 0.2, beta = 0.1 and gamma 0.5 to get better multiplicative forecast for oil and gas data. And to get thesmaller error difference compared to the smaller alpha (α), beta (β) and gamma (γ) then the smaller the differencewill be. The Multiplexative Spring Method and the Seasonal Additive Method are good enough for oil and gasproduction data
Decision Support System for The Purchase of A Printer in Hi-Tech Mall Method Using Fuzzy Tahani Sutrisno; Eko Prasetyo; Rani Purbaningtyas
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v1i2.171

Abstract

With the availability of many brands and types of printers sold by shops in hi-tech Mall resulted in consumers ' difficulties in selecting the printer as needed. In addition, the seller is also complicated in helping consumers to choose the printer that will be purchased. The existence of this, research is trying to build a printer purchase decision support system using fuzzy method tahani implemented in the form of an informative website. The printer then purchase SPK tested to 15 people the user is divided into 5 testing query, where on every test there are three categories i.e. inkjet, color laser and laser mono. Furthermore, the results of these tests are compared with the opinion of the user regarding the printer that match criteria you selected, and the obtained results of 67% user opinions match up with the results of the recommendation given by the system.
Classification of Diabetes Disease Using Naive Bayes Case Study : Siti Khadijah Hospital Ida Lailatul Qurnia; Eko Prasetyo; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v1i2.177

Abstract

Less knowledge about symptoms and how to treat the disease of diabetes mellitus as well as a number of specialist diabetes mellitus which is still limited is one of the causes of the growing number of people affected by the disease. Diabetes disease classification system development aims to predict the type of diabetes patient or user who already suffer from diabetes mellitus. Therefore this system is made to diagnose the type of diabetes through laboratory test results, namely in the form of gender, age, disease history, family history, systolic, diastolic tensi tensi, temperature, pulse, blood sugar, fasting blood sugar JPP and Random blood sugar. That is by using the method of naive bayes as a method to process data on the patient's diagnosis. Test results of this system indicates that the system is able to predict the type of diabetes in patients, from the amount of data as much as 200 patient data, with an output that is the form of Diabetes Without Complications, Diabetes Type II and Normal but obtained the lowest accuracy rating of 39% and the value of the highest accuracy of 80%.
Forecasting the Number of Brick Production Using the Method of Exponential Smoothing Holt-Winter (case Study: PT Sik Krian) Afif Nuzia Al-Asadi; Eko Prasetyo; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v1i2.178

Abstract

PT. SIK is an industry that produces a light brick type of brick. At a certain period, some companies are rising and the decline in demand which is quite significant. This research aims to know the condition of the company to overcome the overstock in the warehouse. The methods used to conduct forecasting in this research is a method of Exponential Smoothing Holt-Winter with seasonal multiplicative component and the addition of seasonal. The value of alpha, beta and gamma used is 0.6, 0.1, and0.5. With the value of the parameter is capable of producing the best MSE values with the value 1 in forecasting the year 2011 in October for seasonal multiplicative component, and the value of 0.006 in MAPE and the same month. For the addition of a seasonal best MSE values obtained on forecasting in 2013 in February with the value and worth of 5.016 MSE MAPE 0.013. The results of this research, the company was able to reduce the buildup of inventory and maximizing production for the coming period without having to fear a shortage of stock and overstocking.
K- Support Vector Nearest Neighbor: Classification Method, Data Reduction, and Performance Comparison Eko Prasetyo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 1 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v1i1.180

Abstract

The use of data mining in the past 2 decades in harnessing the data sets become important. This is due to the information given outcome becomes very important, but the big problem are the obstacles data mining task is a very large amount of data. A very large number indeed specificity of data mining in extracting information, but the amount of too big data also cause decrease the performance. On the issue of classification, data that are not positioned on the decision boundary becomes less useful and make classification method is not efficient. K-Nearest Neighbor Support Vector present to answer the problem that data is normally owned by very large data. K-SVNN able to reduce the amount of very large data with good accuracy without degrading performance. Results of performance comparisons with a number of classification method also proves that K-SVNN can provide good accuracy. Among the five comparison methods, K-SVNN got in the big 3 methods. K-SVNN difference accuracy to other methods less of 0.66% on the data set Iris and 20:29% on the data set Wine.
Pembuatan Keripik Pisang Bu Sami Penguatan UMKM Dengan Pengembangan Varian Rasa Produk Keripik Pisang di Desa Dayurejo Kecamatan Prigen Kabupaten Pasuruan M. Febryansyah Hadi Putra; Rizka Ardiana Fitrianti; Eko Prasetyo
Semar: Jurnal Pengabdian Kepada Masyarakat Vol 1 No 1 (2025): Semar: Jurnal Pengabdian Kepada Masyarakat
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/semarjpkm.v1i1.1

Abstract

Kripik pisang adalah camilan populer yang memiliki cita rasa manis dan gurih pada produk keripik pisang milik Bu Sami Di Desa Dayurejo Kecamatan Prigen Kabupaten Pasuruan, memiliki permasalahan yaitu kurangnya inovasi pada produk sehingga tujuan dari kegiatan ini  membantu meningkatkan kualitas produk dengan memberikan inovasi varian rasa baru. Hasil dari kegiatan ini respon pasar dari hasil upaya percobaan pemasaran di Pasar Sruworejo, Hutan Cempaka, Desa Dayurejo, adanya variasi rasa menunjukkan banyak dilirik dan diminati oleh pengunjung pasar hal ini membuktikan bahwa inovasi varian rasa pada keripik pisang Bu Sami berhasil semakin menarik minat konsumen.
Co-Authors Achmad Irfan Ferdiansyah Achmad Kiki Qushayri Wahyu Kusuma Adiananda Adiananda Afif Nuzia Al-Asadi Agus Mahmudi Ahmad Sarif Hikmawan Alamsyah Amirullah, Amirullah Anis Suryaningrum Ari Tria Widagda Arif Arizal Arif Mardi Waluyo Azziyati Nur Bambang Teguh Wicaksono Budi Endarto Chastine Fatichah Devit Hari Firmanto Diana Rapitasari Dita Mustika Anggraeni Efilah Risqi Maulana Erwin Dwi Riyanto Fardanto Setyatama Haryono Haryono Ida Lailatul Qurnia Indah Epriliati M Mahaputra Hidayat M. Febryansyah Hadi Putra M. Mahaputra Hidayat Mas Nurul Hamidah Mochammad Muchid Nanik Suciati R Dimas Adityo R Dimas Prasetyo R. Dimas Adityo Rahmawati Febrifyaning Tias Rahmawati Febriyaning Tias Rani Pubaningtyas Rani Purbaningtyas Rifki Fahrial Zainal Riyan Sukma Sasongko Rizka Ardiana Fitrianti Sona Ahmad Susanto Sutrisno Syariful Alim Wahyu Dyah Rizki Septiana Wildansyah Rokhmana Putra Wiwiet Herulambang