Articles
<![CDATA[Simulasi Monte Carlo dalam Mengidentifikasi Peningkatan Penjualan Tanaman Mawar ]]>
<![CDATA[Dian Cyntia Dewi]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 3, No. 2 (June 2021) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v3i2.67
<![CDATA[Roses are one of the most popular types of plants in the community. The sale of roses at the flower shop of 5 siblings is increasingly in demand. Identifying the increase in sales is important in analyzing sales progress. At the present time the seller can only see a manual increase in sales that are most in demand. This study aims to determine predictions of the increase in sales of rose flowers with a monte carlo simulation accurately and accurately. The data that will be processed in this study in the last 2 years, namely 2018 and 2019, rose plants obtained at the 5 Brothers Flower Shop in Solok City. There are several types of roses in the predicted sales level. Then the data will be converted into the probability distribution into cumulative frequency and followed by generating random numbers so that they can determine random numbers. Next, we will group the boundary intervals of the random numbers that have been obtained and continue with the simulation process so that the simulation results and percentage accuracy are obtained using the Monte Carlo method. The results of this study on data processing from 2019 to 2020 have an accuracy of 90%. So this research is very appropriate in identifying the increase in sales for the following year. The design of this system determines the amount of increased sales of goods using the monte carlo method in a flower shop of 5 siblings. Monte Carlo simulations can be used to identify specific sales increases. The results obtained are quite accurate using the Monte Carlo method.]]>
<![CDATA[Sistem Penunjang Keputusan dalam Penentuan Prioritas Pembanguanan Menggunakan Metode Trus Base dengan Topsis ]]>
<![CDATA[Beni Aktavera]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal Informatika Ekonomi Bisnis Vol. 2, No. 4 (December 2020) ]]>
Publisher : <![CDATA[SAFE-Network ]]>
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DOI: 10.37034/infeb.v2i4.76
<![CDATA[Village communities need empowerment in order to develop community welfare and independence to increase attitudes, knowledge, behavior, skills, and priority needs of the village community, including development. villages must be done well in an effort to community village. Village development has an context. Research is to assist Merangin district in making decisions to determine priorities for sub-district development, Merangin Regency which refers to the Regional Long-Term Development Plan (RPJPD). 2018-2019 and 2020 budgets while the decision-making method to solve existing problems is to use increased public participation using a trust-based (trust-based). With the TOPSIS (Technique For Others Preference by Similarity to Ideal Solution) method. With the method to be used, this system can provide information in the form of proposals which are prioritized to be implemented which are aligned with the Regional Long-term Development Plan (RPJPD) and the National Medium Term Development Plan (RPJMN) so that village development can be carried out properly, the TOPSIS method used was able to overcome the weaknesses in the old system and gave 90% accurate results in determining the development priorities of Merangin Regency using the method TOPSIS, and the application of the topsis method for this system could contribute to the results of ranking alternative development priorities in Kab. Merangin to the maximum.]]>
<![CDATA[Development of Mastoid Air Cell System Extraction Method on Temporal CT-scan Image ]]>
<![CDATA[Syafri Arlis]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 3 (2022): Juni 2022 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v6i3.4090
<![CDATA[Mastoiditis is disease that to infection of the mastoid bone cavity that affects the size of the air cell system of the temporal bone. Visually, the information temporal CT image mastoid bone has can assist medical experts in viewing the mastoid air cell system (MACS), but the fact that medical personnel are experiencing difficulties in determining the size MACS is due to the many different characteristics and objects overlap, so that in the measurement of the area, precise and accurate results have not been obtained. This study aims to separate the object of the MACS with the development of extraction. The proposed method uses Morphology and Regionprops operations. The dataset used in the testing process is 347 of 5 patients indicated for Mastoiditis. The results obtained can calculate the area of MACS for each test image. Based on image testing, the area of the smallest MACS in this study was 0.589 cm2 and the largest was 6.183 cm2. This, the smaller the size of the MACS indicates the severity of infection, so this study can help medical personnel make decisions and take appropriate treatment actions.]]>
<![CDATA[Penentuan Mutu Kelapa Sawit Menggunakan Metode K-Means Clustering ]]>
<![CDATA[Andri Nofiar]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal KomtekInfo Vol. 5 No. 3 (2018): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v5i3.26
<![CDATA[The classification of the quality of palm oil in PT Tasma Puja is still done by laboratory testing and then the data is saved manually in Excel. The method of grouping takes time and allows data to be lost. With the development of knowledge, it can be replaced by a data mining approach that can be used to classify the quality of palm oil based on its standards. The k-Means clustering method can be applied to classify the quality of palm oil based on water, dirt and free fatty acids. The data used is the quality data of palm oil in December 2017 as many as 31 data with criteria of good, very good and not good. The test results contained 3 clusters, namely cluster 0 for good categories amounted to 12 data, cluster 1 for very good category amounted to 13 data and cluster 2 for less good categories amounted to 6 data. The k-Means clustering method can be used for data processing using the concept of data mining in grouping data according to criteria.]]>
<![CDATA[Identification Of Palm Using Otsu Method and Mathematical Morphology to Open House Doors Identifikasi Telapak Tangan Menggunakan Metode Otsu Dan MorphologynMatematika Untuk Membuka Pintu Rumah ]]>
<![CDATA[Mahdiasa Sholihin]]>;
<![CDATA[M. Arif]]>;
<![CDATA[M.Hafiz Alfansury]]>;
<![CDATA[Nindi Misyahdul Yuzi]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal KomtekInfo Vol. 7 No. 2 (2020): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v7i2.70
<![CDATA[The biometrics system is an individual recognition technology using human body parts or behavior. Palm and fingerprints, each biometrics example based on body parts and human behavior. Image matching is a way to identify images. This research uses biometric technology, a system that performs image matching based on human body parts by matching test images received with training images contained in a database. The image used is the palm of the hand. The use of the palm because the palm has unique characteristics, is difficult to fake and tends to be stable. There are 10 samples of the palm image that will be used using the Otsu method and the Math Morphology method, which were previously filtered using a median filter and turned into grayscale. From 10 different samples showing different results with an average similarity level of 96.28%, the method proves that the palm joints are a characteristic that is owned by everyone, and it also proves that the palm can also used as an alternative to protect privacy, not just fingerprints for home security.]]>
<![CDATA[Pengembangan Ekstraksi dalam Identifikasi Kelainan Gigi pada Citra Dental X-ray imaging (DXRI) ]]>
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal KomtekInfo Vol. 9 No. 1 (2022): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v9i1.283
<![CDATA[Dental X-ray imaging (DXRI) has been developed as a basis for dental professionals and professionals around the world to assist in detecting abnormalities in tooth structure. The results of the radiographs assist the imaging assessment to provide a thorough clinical diagnosis and preventive examination of the tooth structure. However, the results of the image analysis from DXRI are not sufficient, it is still necessary to use image processing and analysis methods to extract relevant information. The purpose of this study was to analyze the image of teeth on Dental X-rays by using the image extraction method. The results of this study were able to identify abnormalities in the teeth with a high success rate, namely an average of 83.33% based on testing of 10 dental images. The results of the development of the algorithm have been able to provide optimal results in identifying abnormalities in normal and abnormal teeth. Overall, the results of this study can be used as a medical reference for further medical treatment for dental abnormalities.]]>
<![CDATA[Image Edge Detection Capture Zoom for Facial Recognition Using Gradient Operators ]]>
<![CDATA[Febri Hadi]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal KomtekInfo Vol. 9 No. 3 (2022): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v9i3.303
<![CDATA[Imagery on edge detection is a process that will display the edges of an image. Basically, edge detection is one of the techniques for the analysis of image quality in the spatial domain and is also one of the initial process in digital image processing. Edge detection serves to detect the border line of an object contained in the image. This study aims to identify and recognize face pattern objects in the capture zoom image. To perform face identification begins with collecting image data, image processing, image edge detection, thinning of the image, and identification process using the template matching method. The method used in edge detection uses 3 methods, namely Sobel, Roberts and Prewitt which are gradient operators to detect edges in facial images. The dataset used is image capture zoom. The trial was carried out in two stages, namely the identification of the face shape and the identification of the edges of the face. The conclusion of the study is that the Roberts operator is the operator that finds the least edge patterns in facial images than the other two operators, namely Prewitt and Sobel. Meanwhile, the Sobel operator produces edge patterns that are better in quality and quantity than using the Roberts and Prewitt operators.]]>
<![CDATA[Teknik Segmentasi untuk Mengidentifikasi Kelainan Jantung pada Citra Rontgen Dada ]]>
<![CDATA[Febri Aldi]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Jurnal KomtekInfo Vol. 9 No. 3 (2022): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v9i3.307
<![CDATA[The annual death toll from heart disease is 17.5 million people. Currently, heart disease is a prevalent condition that kills a lot of people and shortens people's lives. Life is based on the work of the heart, since the heart is a much-needed part of our body where life is impossible. Heart disease affects heart function and can lead to death or annoy the patient before deathThe use of contemporary medical imaging methods like computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI), as well as X-rays, is now commonplace. These methods enable non-invasive qualitative and quantitative assessment of the anatomical structure and function of the heart and support diagnosis, disease monitoring, treatment planning, and prognosis. The purpose of this study is to find heart problems in patients. The data used in this study were chest X-rays of patients with normal heart conditions and chest X-rays of abnormal heart patients obtained from the kaggle website. Segmentation techniques are used to process these cardiac images. Segmentation is the process of separating between an object and another object or between objects and the background contained in an image. Then the calculation of the area of the heart area is carried out using the extraction of morpological and regional features method characteristics with an algorithm that has been developed. The results of this study can identify heart defects through the process of measuring the area of the heart normal and abnormal. So that it produces a good accuracy rate of 85%. This segmentation technique is proven to be very good so that it can be a medical reference to perform further medical actions against abnormalities in the heart.]]>
<![CDATA[Optimalisasi Tunjangan Kinerja Pegawai pada Badan Kesatuan Bangsa dan Politik Kabupaten Karimun Menggunakan Metode Monte Carlo: Array ]]>
<![CDATA[Eri Haryadi]]>;
<![CDATA[Sumijan]]>;
<![CDATA[Julius Santony]]>
<![CDATA[ Jurnal Ilmiah Komputasi Vol. 19 No. 2 (2020): Jurnal Ilmiah Komputasi Volume: 19 No. 2, Juni 2020 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian Kepada Masyarakat ]]>
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DOI: 10.32409/jikstik.19.2.87
<![CDATA[Badan Kesatuan Bangsa dan Politik Kabupaten Karimun melaksanakan pembayaran tunjangan berbasis kinerja. Pemberian tunjangan ini harus terbuka dan transparan sesuai dengan prestasi kinerja pegwai. Penelitian ini bertujuan untuk menentukan kriteria yang tepat dalam perhitungan bobot kinerja, sehingga pemberian tunjangan sangat tepat. Penelitian ini akan menetapkan bobot kinerja pegawai sebagai acuan dalam pembayaran tunjangan kinerja setiap bulan. Data yang diolah dalam penelitian ini adalah nilai absensi dan nilai capaian kinerja setiap pegawai. Data ini dirangkum menjadi data sasaran kinerja pegawai dengan jumlah Pegawai Badan Kesatuan Bangsa dan Politik Kabupaten Karimun sebanyak 23 (dua puluh tiga) orang. Metode yang digunakan dalam penelitian ini adalah Monte Carlo. Hasil dari pengujian penelitian ini dapat menentukan prediksi sasaran kinerja pegawai yang akurat dengan tingkat akurasi 99%. Dengan ketepatan penelitian ini, maka ketepatan dalam penentuan tunjangan kinerja sangat tepat, sehingga penelitian ini menjadi acuan dalam meningkatkan kinerja pegawai secara tepat.]]>
<![CDATA[Metode k-means clustering untuk mengukur tingkat kedisiplinan pegawai (studi kasus di pemerintah kabupaten padang pariaman) ]]>
<![CDATA[Rezki -]]>;
<![CDATA[Sarjon Defit]]>;
<![CDATA[Sumijan]]>
<![CDATA[ Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Riau ]]>
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DOI: 10.37859/coscitech.v4i1.4728
<![CDATA[Knowledge Discovery In Database (KDD) is a process of converting raw data into useful data in the form of information. Data mining is a technique of digging up hidden or hidden valuable information in a very large data collection (database) so that an interesting pattern is found that was previously unknown. Clustering is a method in data mining in which data objects that have similarities or the same characteristics are grouped into one group and those that are different are grouped into another group. One aspect of discipline that can be used to evaluate employee performance is attendance. The k-means method is used to classify employee discipline levels and then describes the values that have been obtained to generate new knowledge regarding data patterns on employee discipline levels. The attendance data is clustered into 3, namely to measure low, medium, and high levels of discipline. After carrying out the calculation process, the 41 employee samples produced 3 iterations, and the final result was 3 clustering, namely cluster 1 of 10 employees with low discipline, cluster 2 of 7 employees with moderate discipline, and cluster 3 of 24 employees with high discipline. This is intended so that leaders can find out which employees have high, medium and low levels of discipline so that they can provide appreciation or rewards and sanctions in order to maintain and improve their discipline so that service to the community can be optimal and the vision and mission of the local government can be achieved. Keywords: KDD, Data Mining, K-Means Clustering Method, Discipline]]>
