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<![CDATA[PEMBERDAYAAN UMKM BERBASIS TEKNOLOGI INFORMASI DAN KOMUNIKASI KABUPATEN KENDAL MENUJU PASAR GLOBAL ]]>
<![CDATA[Supri Hadi]]>;
<![CDATA[Agustinus Fritz Wijaya]]>;
<![CDATA[Birmanti Setia Utami]]>
<![CDATA[ Jurnal Informatika Vol 12, No 1 (2016): Jurnal Teknologi Komputer dan Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2016.121.422
<![CDATA[Free trade can not be dammed again, so the impact on local businesses in particular products SME have to be able to compete with foreign products because it is supported by information and communication technology (ICT), which consists of the online market. KKN-PPM FTI UKSW was carried out to community groups businesses incorporated in the SME Kabupaten Kendal, Central Java, was carried out with methods of mentoring and development applications online market. The purpose of this program is to provide ICT field for the empowerment of the perpetrators of the SME. KKN-PPM program results are the SME capable of using ICT in particular basic creative multimedia designer label to product packaging, design content market online, and can make your business, as well as brend is able to manage the online market site independently, so the product SME Kabupaten Kendal as a potential area capable of leading to the global market.]]>
<![CDATA[SEGMENTASI WARNA CITRA DENGAN DETEKSI WARNA HSV UNTUK MENDETEKSI OBJEK ]]>
<![CDATA[Benedictus Yoga Budi Putranto]]>;
<![CDATA[Widi Hapsari]]>;
<![CDATA[Katon Wijana]]>
<![CDATA[ Jurnal Informatika Vol 6, No 2 (2010): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2010.62.81
<![CDATA[Deteksi objek pada suatu citra 2 dimensi merupakan suatu proses yang cukup kompleks untuk dilakukan oleh karena itu diperlukan suatu pendekatan visi komputer (computer vision) sehingga bagian objek yang diinginkan dapat dikenali komputer dengan akurat. Penelitian ini akan memaparkan penerapan metode segmentasi warna dengan deteksi warna HSV oleh Giannakopoulos untuk menghasilkan objek segmen citra berupa blob sehingga dapat terdeteksi komputer. Berdasarkan hasil pengujian dan analisa diperoleh kesimpulan bahwa kontrol pengguna dalam hal penentuan sampel warna dan toleransi warna berperan penting dalam proses segmentasi; sampel warna akan menghasilkan nilai acuan warna sebagai acuan segmentasi dan toleransi warna digunakan sebagai jangkauan filter dalam proses segmentasi. Proses deteksi objek akan mengolah segmen warna yang dihasilkan oleh proses segmentasi sehingga dapat diketahui banyaknya objek terdeteksi, luas area dan titik pusat tiap objek.]]>
<![CDATA[Implementasi Prinsip Usability F-Shape Pattern Pada Konten Website ]]>
<![CDATA[Jimmy Hendisaro Zebua]]>;
<![CDATA[Restyandito Dito]]>;
<![CDATA[Lucia Dwi Krisnawati]]>
<![CDATA[ Jurnal Informatika Vol 8, No 1 (2012): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2012.81.113
<![CDATA[Website as a medium of information can not be separated from website content itself. How visitors get the information they want is very dependent on the placement of such information. This research which involve the design and testing of respondents concluded that in general, users tend to read using n “F” pattern , therefore the lay out of the most important content must be placed on both the recommended reading area of the “F” pattern. This research is using the Informatics Engineering’s website as case study and propose a better design to improve the readibility of the information based on “F” pattern. Kata Kunci : Website, F-Pattern, Konten Website, Usability]]>
<![CDATA[VERIFIKASI AKUN DATABASE DENGAN PENERAPAN METODE TEMPLATE MATCHING PADA KARATERISTIK WAJAH PERSONAL ]]>
<![CDATA[Ginting Pebrindanov]]>;
<![CDATA[Widi Hapsari]]>;
<![CDATA[Yuan Lukito]]>
<![CDATA[ Jurnal Informatika Vol 11, No 1 (2015): Jurnal Teknologi Komputer dan Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2015.111.427
<![CDATA[The identification of account is a step to keep the important data secure. Nowadays, it can be done by using username and password, but, after see the reality, the using of username and password can’t keep the data secure from the thief. Because of that, the verification of the characteristic of personal face can be a solution to change the using username and password. The method that can be used for verification is template matching.It is implemented in four features of personal face, such as left eye, right eye, nose and lips. The four images of each feature will be extracted with wavelet haar method. The feature extraction will be done during template taking process and verification. The result of this research, the result of verification is determined by two factors, such as the distance between face and web camera is different when the template taking process and the verification process and the diferrent brightness condition when the template taking process and the verification proccess. The threshold value that has been decided is not really able to block the unregistered data. Then the accuracy of the verification activity is still low and it is still not able yet to identify an account well.]]>
<![CDATA[APLIKASI GENERATOR SCRIPT BASIS DATA BERORIENTASI OBYEK ORACLE 10g ]]>
<![CDATA[Titus Adi Prasetyo]]>
<![CDATA[ Jurnal Informatika Vol 5, No 1 (2009): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2009.51.72
<![CDATA[Dengan berkembangnya pemodelan basis data yang di dasarkan pada konseppemodelan berbasis obyek, maka diperlukan aplikasi yang mampu digunakan untukmemodelkan basis data berorientasi obyek yang selama ini belum pernah dibangun.Aplikasi yang dibangun di beri nama Rum dan mampu digunakan untuk memodelkan basisdata berorientasi obyek dan melakukan generate pemodelan tersebut ke dalam SQL diOracle 10g. Analisis dilakukan pada hasil kuesioner yang disebarkan kepada beberapatester yang mencoba menggunakan Rum. Kesimpulan yang diperoleh antara lain, SQL hasilgenerate Rum mampu di eksekusi dengan benar di basis data Oracle 10g. Dan yang keduaberdasarkan respon pengguna yang melakukan testing terhadap Rum, bahwa Rum memilikikelemahan di sisi interface. Dan yang terakhir adalah pengguna yang memiliki latarbelakang pengetahuan pemodelan berbasis obyek dan basis data Oracle 10g yang baikakan sangat membantu menggunakan Rum.]]>
<![CDATA[SUBSTRAKSI BACKGROUND DAN DETEKSI BAYANGAN PADA CITRA GRAYSCALE SEKUENSIAL ]]>
<![CDATA[Binarahandra R.E]]>;
<![CDATA[Widi Hapsari]]>;
<![CDATA[Junius Karel Tampubolon]]>
<![CDATA[ Jurnal Informatika Vol 7, No 2 (2011): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2011.72.104
<![CDATA[Ekstraksi objek pada suatu citra grayscale dengan background yang tidak tetap merupakan hal yang rumit sehingga membutuhkan pendekatan dengan computer vision. Penelitian ini menerapkan proses substraksi background dan deteksi bayangan untuk mendapatkan bentuk dari objek yang diinginkan. Proses substraksi bayangan membutuhkan background model yang diperoleh dari pengolah citra sekuensial input dari pengguna. Tujuan dari background model ini adalah untuk menentukan pengelompokan piksel sebagai background atau sebagai objek. Proses deteksi bayangan akan mengkalkulasikan nilai piksel objek dengan background model menggunakan normalized cross-correlation (NCC) untuk melihat apakah nilai objek adalah suatu penguatan nilai dari background model yang menandakan piksel tersebut adalah bayangan. Penelitian ini akan mengimplementasikan metode tersebut dan menganalisa hasil serta pengaruh input pengguna untuk mendapatkan hasil substraksi background dan deteksi bayangan yang optimal. Kata kunci : computer vision, substraksi background, deteksi bayangan]]>
<![CDATA[PENGENALAN AKSARA BALI DENGAN PENDEKATAN METODE DIRECTION FEATURE DAN AREA BINARY OBJECT FEATURE ]]>
<![CDATA[Ni Made Ari Pratiwi]]>;
<![CDATA[Widi Hapsari]]>;
<![CDATA[Theresia Herlina R.]]>
<![CDATA[ Jurnal Informatika Vol 9, No 1 (2013): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2013.91.142
<![CDATA[The rise of technology has been contributing advances to science, and to human being in making jobs far much easier to do, including pattern recognition. This research focused on character recognition by developing a system capable to recognise images of printed Balinese traditional character, which has a distinct feature of having perceptually similar characters, where each others are often differentiated only by a small stroke or a curve. The system itself took several processes to recognise a character. First, the image containing Balinese characters is preprocessed. Afterwards, two object features are extracted from the image: Direction and Binary Object Area. Both features then tested for similarity using Euclidean distance with the same features already obtained from the control images. From 573 characters tested to the system, 559 are recognized as characters and 526 are correctly recognized as the right character, which yields an overall accuracy of 91.8%. Recognition results are dependent to character spacing condition.]]>
<![CDATA[ANALISIS TEKSTUR PADA CITRA MOTIF BATIK UNTUK KLASIFIKASI MENGGUNAKAN K-NN ]]>
<![CDATA[Kristian Adi Nugraha]]>;
<![CDATA[Widi Hapsari]]>;
<![CDATA[Nugroho Agus Haryono]]>
<![CDATA[ Jurnal Informatika Vol 10, No 2 (2014): Jurnal Teknologi Komputer dan Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2014.102.332
<![CDATA[Indonesian’s Batik is one of culture heritage that recognized around the world. Batik has many variations of pattern based on their region. In this research, Batik would be used as subject for texture feature extraction. The value of this feature extraction would be used for classification using K-Nearest Neighbor (K-NN) method. Texture Feature Extraction components that used in this research were Entropy, Correlation, Homogeneity, and Energy. This research will investigate which component would give dominant effect for Batik’s pattern recognition. Batik pattern used in this research is pattern from Yogyakarta region. There are four patterns namely Ceplok, Parang, Semen, and Nitik. The result showed that there was no component from Texture Feature Extraction that gave dominant effect (average = 53,96%). Component with the highest value of accuracy is Correlation with a percentage of 55,83%. Whereas for K-NN classification, the best accuracy is 60% for K = 5.]]>
<![CDATA[ALGORITMA STEEPEST ASCENT HILL CLIMBING UNTUK MENYELESAIKAN MASALAH PENUGASAN ]]>
<![CDATA[Daisy Ika Christiana]]>;
<![CDATA[Gloria Virginia]]>;
<![CDATA[Joko Purwadi]]>
<![CDATA[ Jurnal Informatika Vol 4, No 1 (2008): Jurnal Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2008.41.40
<![CDATA[Penugasan adalah penetapan tugas pada tiap pekefia dan tugasnyaagil mendapat hasilyang paling baik, yaitu dengan hasil akhir maksimal dan waktu yang minimal. Masalahpenugasan memiliki syarat satu pekerja hanya mengerjakan satu tugas dan sebaliknya satutugas hanya dikerjakan oleh satu pekerja. Penugasan adalah bagian dari bidang ilmu RisetOperasi (Operation Research ), yang biasa digunakan untuk mencari hasil maksimal atauminimal. Sistem yang akan dibuat ini didukung oleh dua bidang ilmu, yaitu riset operasi dankecerdasan buatan.Dalam bidang ilmu kecerdasan buatan terdapat algoritma yang bisadigunakan untuk memecahkan masalah maksimalisasi yaitu Algoritma Sfeepesf Ascent HillClimbing.Sistem yang dibuat digunakan untukn mencari hasil akhir yang maksimal dari kapasitassuatu produksi. Masukkan berupa jumlah mesin, jumlah pekerja, dan jumlah produksi (matrikkapsitas), prosesnya dilakukan dengan mengkombinasikan hasil perhitungan matrik kapasitasmenggunakan teori penugasan, dan mencari hasil terbaik dengan algoritma Steepest AscentHill Climbing. Hasil perhitungan ditampilkan dalam bentuk rekap iterasi, perhitungan waktuproses, dan komposisi pekerja dan tugasnya. Hasil perhitungan penugasan menggunakanAlgoritma Steepest Ascent Hill Climbing telah diujicoba dengan perhitungan secara sistem danmanual, dan mendapatkan hasil akhir yang sama, jadi bisa dikatakan sistem cukup akurat.]]>
<![CDATA[Implementasi Transformasi Haar Wavelet untuk Deteksi Citra Jeruk Nipis yang Busuk ]]>
<![CDATA[Lidya Andriani Sunjoyo]]>;
<![CDATA[R. Gunawan Santosa]]>;
<![CDATA[Kristian Adi Nugraha]]>
<![CDATA[ Jurnal Informatika Vol 12, No 2 (2016): Jurnal Teknologi Komputer dan Informatika ]]>
Publisher : <![CDATA[Universitas Kristen Duta Wacana ]]>
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DOI: 10.21460/inf.2016.122.498
<![CDATA[Lime is a fruit that has been widely cultivated and used in Indonesia. Many products use this fruit in the production process. The process of sorting fruit is undeniably a very substantial early process. It is necessary for large-scale be aware of this in term of result and time required for the sorting process. Pattern Recognition is a discipline that focuses on classifying or picturing an object based on characteristics or main attribute of the object. In this research, the author implements Haar Wavelet Transformation method by characteristic extraction based on colour and texture , performs classification using K-Nearest Neighbor (k-NN) to detect indication of rotten lime and the grade of k on k-NN so the accuracy of the result could be acquired. Based on analysis result, Haar Wavelet Transformation method is able to be implemented to detect the indication of rotten lime and most optimal accuracy level of this system reaches the number of 85 percent.]]>
