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All Journal Techno.Com: Jurnal Teknologi Informasi JEECS (Journal of Electrical Engineering and Computer Sciences)

Wiwiet Herulambang

Universitas Bhayangkara Surabaya

Author-ID : 4102391

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 18 Documents Claim Missing Document

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Deteksi Penyakit Mata Pada Citra Fundus Menggunakan Convolutional Neural Network (CNN) Rarasmaya Indraswari; Wiwiet Herulambang; Rika Rokhana
Techno.Com Vol 21, No 2 (2022): Mei 2022
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/tc.v21i2.6162

Pada tahun 2020, terdapat 1,1 milyar orang yang mengalami kehilangan penglihatan di seluruh dunia. Jumlah ini diproyeksikan akan terus bertambah hingga mencapai 1,76 milyar orang pada tahun 2050. Penyebab utama kebutaan untuk anak-anak dan remaja adalah penyakit mata, yang dapat dicegah apabila dilakukan deteksi dan penanganan lebih dini. Oleh sebab itu, pada penelitian ini diusulkan metode berbasis Convolutional Neural Network (CNN) untuk mendeteksi penyakit mata pada citra fundus. Metode yang diusulkan menggunakan metode transfer learning dengan arsitektur jaringan MobileNetV2 sebagai base model. Arsitektur head model yang diusulkan, yang terdiri dari lapisan global average pooling dan diikuti oleh 2 lapisan fully-connected, mampu memberikan akurasi yang paling tinggi dan efisiensi paling baik dibandingkan dengan arsitektur head model lainnya. Eksperimen pada dataset citra fundus yang terdiri dari 601 citra dengan berbagai macam penyakit mata menunjukkan bahwa metode yang diusulkan mampu memberikan performa yang baik dengan nilai akurasi sebesar 72%, precision sebesar 72%, recall sebesar 72%, dan F1-score sebesar 72%. Hasil eksperimen menunjukkan bahwa metode yang diusulkan dapat memberikan akurasi yang lebih tinggi dan lebih efisien dibandingkan dengan menggunakan arsitektur CNN lainnya, seperti ResNet50V2, InceptionV3, InceptionResNetV2, VGG16, dan VGG19.

Reagent Stock Prediction Using Monte Carlo Method At Populer Clinical Laboratory Surabaya Farah Dibba; Wiwiet Herulambang; Fardanto Setyatama
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 7 No. 2 (2022): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Prediction is important as decision are made earlier. Information are needed before prediction is optimallydone. Company operational supply can be predicted and depicted in computerized process. By doing so, a decisionbased on past probabilities could be made efficiently. In the simulation, stock of goods is important. Reagent stockprediction could be done by using Monte Carlo method. Monte Carlo method is one of a tool that can be used toanalyze common uncertainty in reagent stock procurement. The result of Monte Carlo prediction can help companyto determine the future amount of reagent stock. In this research, the forecast results 95,83% accuracy by using 2022annual stock data.

Design of Expert System Diagnosis of Catfish Disease with Forward Chaining Method Erwin Dwi Riyanto; Eko Prasetyo; Rifki Fahrial Zainal; Rani Pubaningtyas; Fardanto Setyatama; Wiwiet Herulambang; Syariful Alim; Rahmawati Febriyaning Tias
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 7 No. 1 (2022): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

The expert system can be used as a means for consulting and assisting experts and catfish breeders who areexperiencing problems in identifying catfish diseases and their solutions. So that this expert system can be accessedeasily by anyone and anywhere connected to the internet network, this expert system is made web-based. The MySQLdatabase used in this system will store facts that were built using the PHP programming language. Likewise, systemdevelopment is only limited to diagnosing catfish diseases. The output of this system is in the form of diseaseinformation in catfish and how to handle it. The form of research used by the author is a literature study and is appliedto experimental research. The software development method used by the author is to use the Forward Chaining methodwhich consists of rules. The results of the research that have been made, it is found that this website and expert systemmake it easy for ordinary people or beginners to cultivate catfish in order to produce healthy and superior catfish.

Implementation of Intelligent Parking System Using IoT-Based Devices (case Study of Galaxy Mall Surabaya) Weka Sadya Wasana; R. Dimas Adityo; Wiwiet Herulambang
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 6 No. 2 (2021): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Many parking spaces available today generally require drivers to find their own location empty parking. Especially in parking lots located in large areas such as the Galaxy Mall area Surabaya. This will cause problems getting parking location information because drivers are not uncommon have to circle the parking building to get an empty parking location. The problem can avoided if the driver already knows the state of the parking location in the area to be seven. Driver can find out the availability of vacant parking locations in the destination area. In this case, we need a a system that can help drivers find vacant parking locations. Internet of things is a a concept or program by which an object has the ability to transmit or transmit data through the network without using the help of computers and humans. Internet of things or often called IoT is currently experiencing many developments. From the test results it can be concluded that the average Raspberry Pi boot delay on this system is 221.1 seconds. Sensor, From the test results it can be concluded that the average delay in scanning the QR Code using a Raspberry Pi camera at the entrance bar is 59.3 seconds, From the test results it can be concluded that the average delay in scanning QR Code using a camera The Raspberry Pi on the exit bar is 59.4 seconds

Mapping and Prediction of Community Health Level in The East Java Region Using ANN Backpropagation Method Wiwiet Herulambang; Fardanto Setyatama; Muhammad Choirul Nurrohim
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 6 No. 1 (2021): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Predicting the level of public health in an area is very important to know the development of public health in order to give consideration to local governments in making policies that can increase the level of health and health services for the community. So we need a system that is able to make predictions and describe the development of public health in the years to come. The data used in the study were the percentage of the population who had health complaints and outpatient treatment for a month, the percentage of households that had access to proper sanitation, the percentage of households that had access to decent drinking water sources, the percentage of poor people, the average length of schooling, infant mortality rate, number of health centers and life expectancy. Backpropagation neural network method is a method that is often used in forecasting or prediction. Where this method can identify activities based on past data. Past data will be studied by neural networks so that they have the ability to make decisions on data that has never been studied. This method is expected to provide a prediction of the level of health by studying data from previous years. The results of this study produced a predictive map of the level of public health in the East Java region in 2019, 2020 and 2021 based on the model obtained from the training results with an epoch of 100 and an MSE value of 0.0173254.

System for Determining House Credit Recipients Based on Data of Cooperative Members Using Simple Additive Weighting (SAW) Wiwiet Herulambang; Fardanto Setyatama; Muhammad Zulfikkih
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 2 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

PMS Employee Cooperative is a savings and loan cooperative which aims to provide storage and loan services to employees who work at PT. Pro Manunggal Solusi and does not yet have a Decision Support System (SPK). A decision support system is needed in determining the eligibility of cooperative loans to employees. This study aims to help simplify and accelerate and minimize errors that occur in the cooperative borrower feasibility assessment process. The method used for this decision is to use the Simple Additive Weighting (SAW) method. Six criteria are used for the loan eligibility assessment process, namely criteria 1 (Loan size), criterion 2 (Loan Purpose), criterion 3 (Salary), criterion 4 (Position), criterion 5 (Age), criterion 6 (Period of service). Based on the results of the calculation, it can be concluded that each loan employee will be approved according to the ranking and is limited by the balance. If the balance is sufficient, the loan will be approved, but if the balance is less, the loan will be rejected. Of the total value of the ranking results, loans approved with a sufficient balance were Susanto (0.82) with a 12.13% chance, Sentot Sudiyantono (0.80) with a probability of 11.83%, and Siswandi (0.73) with big chance 10.80%.

Decision Support System for Giving "joint Degree Program" School of Bhayangkara Surabaya University Using Analyticalal Hierarchy Process (AHP) Method Irine Ratih Paramitha; Wiwiet Herulambang; Syariful Alim; Arif Arizal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 1 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

The granting of scholarships to students is carried out by universities based on their achievements. In awarding scholarships, universities often have difficulty in determining prospective scholarship recipients, so it is found that the distribution of scholarships is not precisely due to a manual system for determining scholarships. Decision support system is an information system intended to assist the University in solving the problem of awarding Academic Achievement Scholarships. One method that can be used in a decision support system is Fuzzy Analitycal Hierarchy Process ( F-AHP) with the Chang model approach (1996). The criteria used are GPA, Achievement, Parents' Work, Parental Dependents and Semesters. From the results of experiments conducted the results of calculations from the application and manual checking from the ubhara get 100% presentation in determining the recipient of the scholarship. Resulting in the ranking of student grades, ten students with the highest grades in each faculty will receive an Academic Achievement Improvement scholarship.

Forecasting Omset Printing of Printing Sales in CV Sembilan Jaya with Neural Network Method Reni Vivit Ayu Mawarti; Wiwiet Herulambang; R Dimas Adityo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Forecasting is a process for estimating several needs in the future which includes needs in order to meet thedemand for goods and services. Neural Network Backpropagation Method is a time series forecasting method. Thepurpose of this study is to predict the turnover results in the next period obtained by CV. Nine Jaya every week. Thisstudy uses sales data obtained from the printing of food boxes, shoe boxes, watch boxes from January 2014 toDecember 2018. The results of this forecasting are done using the Neural Network method, the smallest MSE valueobtained is 0.004211 with 1000 times iteration and learning rate 0.2. The MSE value obtained meets the condition orcondition value as a good forecasting method because it is able to meet the MSE value requirement <0.1.

Analysis of Sales Information System (case Study: Mr. Token) Agnes Fridawati; Wiwiet Herulambang; Arif Arizal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

At present the marketing that is in Mr. The token is done manually which is come directly to Mr.Token tooffer the products offered. The purpose of this study the authors analyze and design a sales information system Mr.Tokens to increase sales. Appropriate title taken is the analysis of sales information systems on Mr. Token. With theoccurrence of these constraints, the author tries to analyze the database by observing the database design. The purposeof this thesis is the researcher wants to be able to analyze the database in the company Mr. Token. And from the resultsof this study the results achieved are saving time of 12.6% and increasing turnover of 19.2%

Clustering for Searching Type of House Suitable for New Consumer Candidates Using K-Means Clustering Method (case Study of PT. Maxima Jaya Perkasa) Wiwiet Herulambang; Eko Prasetyo; Azziyati Nur
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

For some Indonesian people, housing is one of the secondary needs, so that in choosing the right housingmust be in accordance with the wishes of consumers. With the existence of PT. Maxima Jaya Perkasa, which waspioneered since 2012, in which the data on housing sales in the company has increased rapidly each year. Then datamining analysis can be done using the K-means Clustering method. K-means Clustering is a method of clustering nonhierarchicaldata which seeks to partition existing data into two or more groups. This method partitioned the data intogroups so that the data with the same characteristics were entered into the same group and the data with differentcharacteristics were grouped into other groups. This study uses data such as salary income, age, status, house pricesand mortgage payments. The results of this study were conducted twice using 12 training data training data and 100training data plus 1 as test data and obtained an accuracy value of 83% and error of 17%.

Co-Authors Agnes Fridawati Arif Arizal Ayu Purnamasari Azziyati Nur Budi Santoso Devi Ayu Ariyanto Diana Nur Arofah Dwiki Ashari Kusumawardhana Eko Prasetyo Erwin Dwi Riyanto Farah Dibba Fardanto Setyatama Irine Ratih Paramitha M Mahaputra Putra Muhammad Choirul Nurrohim Muhammad Zulfikkih R Dimas Adityo R. Dimas Adityo Rahmawati Febriyaning Tias Rani Pubaningtyas Rani Purbaningtyas Rarasmaya Indraswari Reni Vivit Ayu Mawarti Retantyo Wardoyo Rifki Fahrial Zainal Rika Rokhana Syariful Alim Syariful Alim Weka Sadya Wasana

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