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Ekstraksi Ciri Bentuk pada Citra Bergerak Menggunakan Teknik Batas Tepi Wahyu Supriyatin
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 1 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i1.3725

Computer vision sebagai pengembangan dari pengolahan citra membutuhkan informasi yang sesuai. Citra dua dimensi atau tiga dimensi yang akan digunakan dalam proses pengolahan citra memerlukan perbaikan sehingga dapat menampilkan ciri atau informasi yang dibutuhkan. Ekstraksi ciri merupakan salah satu tahapan preprocessing citra. Ekstraksi ciri dapat berupa bentuk, warna atau tekstur. Penelitian ini membahas tentang ektraksi ciri bentuk menggunakan teknik batas (boundary-based). Ekstraksi ciri bentuk digunakan untuk mengenali bentuk objek dari citra tiga dimensi (video) yang digunakan. Teknik batas dalam penelitian ini menggunakan edge detection prewitt. Pengujian menggunakan tiga video sebagai objek yang diperoleh dari library Matlab. Pengujian dilakukan dengan tools Simulink Matlab. Hasil pengujian ekstraksi ciri bentuk dengan deteksi tepi prewitt berhasil menampilkan objek yang ada dalam video. Objek berhasil dikenali serta background yang ada dalam video juga berhasil terdeteksi. Prewitt menghasilkan tepi yang jelas dan halus pada objek, sehingga ekstraksi ciri bentuk yang dilakukan dapat mengenali objek seperti aslinya.

Palm oil extraction rate prediction based on the fruit ripeness levels using C4.5 algorithm Wahyu Supriyatin
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.714.92-100

Oil palm plantations are one of the main keys in supporting Indonesia’s economic growth. The rising consumption needs for palm oil products make it necessary to carry out data mining activities to increase CPO production. The maturity factor of palm fruit dramatically affects the quality of the oil extraction content (CPO yield) produced. This study aims to investigate the effect of fruit ripeness on the yield of CPO by using a data mining classification method with a decision tree. The algorithm used to generate decision tree classification is the C4.5 algorithm. The implementation of the C4.5 algorithm in the study was carried out using the Rapid Miner Studio 5.2 tools. The results shows that the yield of CPO is influenced by the attributes of the condition of the long and ripe fruit, the condition of the long and overripe fruit, the normal condition of the fruit and the age of 3-6 years and the condition of the fruit of normal and age of 7-10 years. Decision tree C4.5 algorithm generates 8 rules with 4 rules showing a high production value, which means that the four rules affect the yield of CPO.

ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN OPTICAL FLOW DAN BACKGROUND ESTIMATION PADA KAMERA BERGERAK Wahyu Supriyatin
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.452.191-199

Object tracking is one of computer vision. Can be developed into various based applications like human computers interface, video compression and security system. Object tracking is used to identified objects within background and identify the number of objects that a cross. Algorithm for this object tracking use optical flow method and background estimation. Testing is carried out using a moving camera placed in a car. It's using parameter values for each Algorithm. The test is used three videos from the Matlab. Simulink Profile Report that optical flow method had Recorded Total Time better than the background estimation with 100 seconds duration. The optical flow Testing method successfully identified the car object. And background testing didn't succeed in identified and to differentiate an object to it’s background. The object test recorded from the distance with a camera, to examined how many the background was and the speed of cars.

Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak Wahyu Supriyatin
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.541.112-120

Computer vision is one of field of image processing. To be able to recognize a shape, it requires the initial stages in image processing, namely as edge detection. The object used in tracking in computer vision is a moving object (video). Edge detection is used to recognize edges of objects and reduce existing noise. Edge detection algorithms used for this research are using Sobel, Prewitt, Robert and Canny. Tests were carried out on three videos taken from the Matlab library. Testing is done using Simulik Matlab tools. The edge and overlay test results show that the Prewitt algorithm has better edge detection results compared to other algorithms. The Prewitt algorithm produces edges whose level of accuracy is smoother and clearer like the original object. The Canny algorithm failed to produce an edge on the video object. The Sobel and Robert algorithm can detect edges, but it is not clear as Prewitt does, because there are some missing edges.

Comparative Analysis of Tracking Objects Using Optical Flow and Background Estimation on Silent Camera Wahyu Supriyatin; Winda Widya Ariestya; Ida Astuti
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

Tracking and object is one of the utilizations on the field of the computer vision application. Object tracking utilization as a computer vision in this study is used to identify objects which exist within a frame and calculate the number of objects passing within a frame. The utilization of computer vision in various fields of application can be used to solve the existing problems. The method used in object tracking is by comparison between optical flow estimation method with background method. The test is conducted by using a still camera for both methods by making changes to the parameter values used as a reference. The results of the tests, conducted on the three video objects by comparing the two methods show a Total Recorded Time better than those of the background estimation method, being smaller than 100 seconds. Testing both methods successfully identifies the object tracking and calculates the number of passing cars.

MARKETING STRATEGY FOR THE DETERMINATION OF STAPLE CONSUMER PRODUCTS USING FP-GROWTH AND APRIORI ALGORITHM Winda Widya Ariestya; Wahyu Supriyatin; Ida Astuti
Jurnal Ilmiah Ekonomi Bisnis Vol 24, No 3 (2019)
Publisher : Universitas Gunadarma

The demand for staple products that vary among customers makes it necessary for the store to determine how the marketing strategy should be. Data mining are known as KDD (Knowledge Discovery in Database) is to digging up valuable knowledge from the data. Research purpose is to identify the right marketing strategy to sales the goods. The marketing strategy is took by analyze how much consumers demand for basic needs. The algorithms used in this research are FP (Frequent Pattern)-Growth and A-priori Algorithm. Finding combinations patterns between itemset using the Association Rule. FP-Growth algorithm is an algorithm that been used to determining a set of data in a data set that often appears on the frequency of the itemset. the KDD stages study are data cleansing, data integration, data selection, data transformation, data mining, pattern evaluation and knowledge presentation. the Testing used Rapidminer software with a minimum confidence value of 0.6 and a minimum support of 0.45. FP-Growth algorithm obtained 5 rule conclusions while Apriori Algorithm obtained 3 rule conclusions. The FP-Growth algorithm make a better decision rules than a priori algorithms in determining of marketing strategies, because it produces more decisions on how the goods sold.

Application of Naive Bayes Algorithm to Analysis of Free Fatty Acid (FFA) Production Based on Fruit Freshness Level Wahyu Supriyatin; Yasman Rianto
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 20, No 1 (2023): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v20i1.6293

Cooking oil is a basic need for everyone who is used to process food ingredients. The use of cooking oil repeatedly and continuously by heating at high temperatures can increase the free fatty acid levels in the oil. The more the oil is reused, the higher the free fatty acid content. Testing the levels of FFA in oil can be done using the FFA test, because FFA can affect the selling price of CPO when it is marketed. In addition, FFA affects the levels of free fatty acids of CPO. This study aims to determine the analysis of FFA production in palm oil products based on the level of freshness of the fruit. The research was conducted by classifying data mining using the NaÃ¯ve Bayes Algorithm. The NaÃ¯ve Bayes algorithm was used to determine whether FFA production had an effect on fruit freshness, fruit quality and fruit soiling. The research was conducted using RapidMiner Studio 9.10 tools. The results of the research from the distribution table show that the value of the FFA attribute obtained 2 conditions, namely super conditions and normal conditions. Where each of these attributes is influenced by the variables of fruit freshness and fruit quality. Probability accuracy results from 60 training data and 40 testing data used are 92.50% for super FFA conditions.

ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE Wahyu Supriyatin
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v17i2.2002

Computer vision same function as human eye, the ability to see or look objects passing by. Object tracking is one of computer vision. Object tracking aims is to recognize and identifying object pass and determine how many.This research was conducted by comparing the two algorithms in Optical Flow, the Horn-Schunck and the Lucas-Kanade algorithm. The test was carried out using two videos obtained from the Matlab library. The resolution of the video used in this study is same, 120x160. The camera used to pick up the objects in this study is placed in one position. The test is carried out using simulation parameters specified in each algorithm. Both algorithms successfully recognize and detect objects and can count how many objects are in a frame. In the same testing duration time simulation makes the Lucas-Kanade algorithm have a faster total record time than Horn-Schunck in recognizing and detecting of objects.

Application of Naive Bayes Algorithm to Analysis of Free Fatty Acid (FFA) Production Based on Fruit Freshness Level Wahyu Supriyatin; Yasman Rianto
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 20, No 1 (2023): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v20i1.6293

Cooking oil is a basic need for everyone who is used to process food ingredients. The use of cooking oil repeatedly and continuously by heating at high temperatures can increase the free fatty acid levels in the oil. The more the oil is reused, the higher the free fatty acid content. Testing the levels of FFA in oil can be done using the FFA test, because FFA can affect the selling price of CPO when it is marketed. In addition, FFA affects the levels of free fatty acids of CPO. This study aims to determine the analysis of FFA production in palm oil products based on the level of freshness of the fruit. The research was conducted by classifying data mining using the NaÃ¯ve Bayes Algorithm. The NaÃ¯ve Bayes algorithm was used to determine whether FFA production had an effect on fruit freshness, fruit quality and fruit soiling. The research was conducted using RapidMiner Studio 9.10 tools. The results of the research from the distribution table show that the value of the FFA attribute obtained 2 conditions, namely super conditions and normal conditions. Where each of these attributes is influenced by the variables of fruit freshness and fruit quality. Probability accuracy results from 60 training data and 40 testing data used are 92.50% for super FFA conditions.

Analysis the Level of Experience of Technology Users’ Perspectives on LinkedIn Websites Ibrahim, Aghi Kalam; Supriyatin, Wahyu; Rianto, Yasman
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 21, No 2 (2024): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v21i2.9998

LinkedIn is a web-based application that can be used by job seekers, both new users and professional users. LinkedIn website is not only used by job seekers but can be used for various other activities. Application user experience is a major assessment of the quality of the software. LinkedIn website user experience can be seen by measuring the website using several aspects. This research aims to analyze the website user experience using the User Experience Questionnaire (UEQ) method. Measurement using the UEQ method is seen by using six aspects of the measurement scale, namely attractiveness, clarity, efficiency, accuracy, stimulation and novelty. Data collection in the study was carried out using a questionnaire given to 41 respondents totaling 26 questions. The questionnaire data will be processed using UEQ Data Analysis Tools. The results of UEQ measurements with benchmark comparisons show four aspects that are in the below average category, namely attractiveness, efficiency, stimulation and novelty. While two aspects are in the bad category, namely clarity and accuracy. So it is necessary to develop and improve the LinkedIn website by developers related to aspects that are in the bad category. The two bad aspects have a value of 0.58 for the clarity aspect and 0.53 for the accuracy aspect.

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