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All Journal Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) International conference on Information Technology and Business (ICITB) jurnal Teknologi Informasi Magister Jurnal Teknoinfo Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
handoyo widi nugroho
Institut Informatika Dan Bisnis Darmajaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Utilization of Content Base Image RetrievalTechnique Based Sketch for Facial Recognition Muhammad Said Hasibuan; Handoyo Widi Nugroho; Suhendro Yusuf
Prosiding International conference on Information Technology and Business (ICITB) 2016: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 2
Publisher : Proceeding International Conference on Information Technology and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

As the rising up Including terrorist crimes in our society due to issues politics, economy, poverty, religion and ethnic conflicts. Many ways and techniques have been tried to crack down Reviews those crimes, but unfortunately the Efforts to seize person or group of suspected criminal is far from our expectation. Face recognition is one of techniques Introduced by many Researchers for the last Decades with many methods and approaches they tried to Recognize a person based on his or his faces. Some of the methods such as face recognition with Query by Example (QBE) using shape, color, and texture to match a query face with the face in the database; however the result is not good enough to Recognize the faces. One of the problems of face recognition by QBE is sometime we do not have a picture or a face image to the make QBE. In order to sort it out the problem, in this research we will try to introduce of face recognition method by generating a face image by a face sketch.Many sketch based face recognition was Introduced by some Researchers and experts, but most of reviews their methods have been applied directly inputting a sketch into a database the which is very costly and Involved a complex algorithm. In addition to the research, we are applying our proposed method compressed into face images, as the compressed images will save storage and unsumming the algorithm. KEY WORDS: Query by Example, Face recognition, criminal 
ANALISA PERBANDINGAN KINERJA ALGORITMA C4.5 DAN ALGORITMA K-NEAREST NEIGHBORS UNTUK KLASIFIKASI PENERIMA BEASISWA Agung Purwanto; Handoyo Widi Nugroho
Jurnal Teknoinfo Vol 17, No 1 (2023): Vol 17, No 1 (2023): JANUARI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i1.2370

Abstract

Penugasan beasiswa adalah masalah manajemen operasi yang dihadapi administrator universitas, yang biasanya diselesaikan berdasarkan pengalaman pribadi administrator. Penelitian ini mengusulkan metode insentif yang terinspirasi oleh pemrograman dinamis untuk menggantikan proses pengambilan keputusan tradisional dalam penugasan beasiswa. Tujuannya adalah untuk menemukan skema penugasan beasiswa yang optimal dengan ekuitas tertinggi sambil memperhitungkan kendala praktis dan persyaratan ekuitas Metodologi yang digunakan dalam menentukan penerima beasiswa di Universitas Muhammdiyah Pringsewu adalah dengan membandingkan tahapan Algoritma C.45 dan Algoritma K-Nearest Neighbors. Dari beberapa data sampel calon penerima dari jurusan Sistem Informasi dan telah dihasilkan berdasarkan perhitungan Algoritma K-Nearest Neighbors memiliki performansi yang lebih baik yaitu presisi 98,72%, akurasi 97,66% dan nilai recall 99,50%, dengan hasil AUC sebesar 0,997 sedangkan C4,5 algoritma. mencapai 98,9% dengan nilai  precision 89,73%, nilai recall 100,00% dan hasil AUC 0,956. Kata Kunci: Beasiswa,Klasifikasi,C4.5, K-Nearest Neighbors
PERBANDINGAN KINERJA ALGORITMA DATAMINING UNTUK PREDIKSI KELULUSAN MAHASIWA Sadimin Sadimin; Handoyo Widi Nugroho
Jurnal Teknoinfo Vol 17, No 2 (2023): Vol 17, No 2 (2023) : JULI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i2.2619

Abstract

Along with the development of technology, especially the development of increasingly large data storage. One organization that has large data storage is an educational organization. Educational organizations use data to obtain information, especially information about students. Student data has many attributes so that we can make predictions such as predictions of student performance, predictions of scholarship recipients and predictions of student graduation. Data mining methods in education are classified into five dimensions, one of which is prediction, such as predicting output values based on input data. From the results of the research conducted from the initial stage to the testing stage of the application of the C4.5 Algorithm, the accuracy results are higher than Naïve Bayes because in its classification stage, C4.5 processes attribute data one by one. The difference is with naïve Bayes which is influenced by the amount of data used, the comparison of the amount of training and testing data. The feasibility of the model obtained is supported by the high accuracy, precision, recall and AUC obtained from the two algorithms that have been tested. The C4.5 algorithm has an accuracy rate of 79.91%, 89.06% precision and 81.38% recall and an AUC value of 0.823. Meanwhile, Naïve Bayes has an accuracy rate of 76.95%, precision of 75.95% and recall of 98.38% and an AUC value of 0.838.
Analisis Kepuasan Pengguna Pijar Sekolah SMK Kesuma Bangsa Dengan EUCS Dan TAM Rendy Ismail; Handoyo Widi Nugroho
JURNAL FASILKOM Vol 14 No 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6830

Abstract

Dengan bantuan Pijar Sekolah, institusi pendidikan dapat menciptakan kurikulum digital yang menarik dan menyenangkan. Buku Digital Interaktif merupakan salah satu dari ribuan sumber daya digital yang tersedia di Pijar Sekolah, Buku Digital, Video Pembelajaran, hingga Laboratorium Virtual yang dapat digunakan oleh seluruh siswa untuk menunjang pembelajaran di sekolah. PLS merupakan klasifikasi metode pemodelan persamaan struktural SEM, dan analisis SEM merupakan kombinasi dari analisis regresi, analisis faktor, dan analisis jalur. Margin of error penelitian ini sebesar 95%. Untuk mengetahui kepuasan terhadap Aplikasi Pijar Sekolah menggunakan Technology Acceptance Model TAM dan End User Computing SatisfactionUCS. Populasi penelitian ini adalah pengguna Pijar Sekolah, pengambilan sampel menggunakan Rumus Slovin, analisis data menggunakan SmartPLS versi 3.2.9 dengan PLS-SEM. Hasilnya, dari tujuh hipotesis yang diajukan, dua hipotesis diterima dan lima lainnya ditolak. Jadi faktor yang mempengaruhi kepuasan pengguna adalah kemudahan penggunaan dan format. Hasil penelitian ini menunjukkan gambaran kepuasan pengguna terhadap sistem Pijar Sekolah. Bagi peneliti selanjutnya agar dapat melakukan pengembangan model dengan menambahkan variabel terhadap kepuasan pengguna, yaitu variabel perceived enjoyment yaitu untuk mengetahui bagaimana kenyamanan pengguna saat menggunakan sistem.
Co-Authors Abdi Darmawan Abdul Lathif Sampurna, Abdul Lathif Agung Purwanto Febri Suganda Hary Sabita Idris Asmuni M Said Hasibuan Muhamad Muslihudin Muhammad Nur Ikhsanto, Muhammad Nur Rendy Ismail Riko Herwanto Sadimin Sadimin Siti Mukodimah Wasilah Wasilah Y. Suhendro Yan Aditiya Pratama Yusuf, Suhendro