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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) COPING (Community of Publishing in Nursing) Sistemasi: Jurnal Sistem Informasi Creative Information Technology Journal SISFOTENIKA Jurnal Sains Dan Teknologi (SAINTEKBU) Jurnal Komputer Terapan CogITo Smart Journal Jurnal Eksplora Informatika specta: Journal of Photography, Arts, and Media JUTEKIN (Jurnal Manajemen Informatika) Jurnal Ilmiah Sinus CCIT (Creative Communication and Innovative Technology) Journal METIK JURNAL Technologia: Jurnal Ilmiah G-Tech : Jurnal Teknologi Terapan Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat CAHAYA tech Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknimedia: Teknologi Informasi dan Multimedia JNANALOKA DEVICE Jurnal Pengabdian Seni Jurnal Ekonomi dan Teknik Informatika EXPLORE Techno Jurnal Permata Indonesia Panggung JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Kusrini Kusrini
STMIK AMIKOM Yogyakarta
Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Evaluasi Kualitas Web Portal STT Dharma Iswara Madiun Menggunakan Metode McCall Andria Andria; Kusrini Kusrini; Armadyah Amborowati
JURNAL EKONOMI DAN TEKNIK INFORMATIKA Vol 4 No 2 (2016): Jurnal Ekonomi dan Teknik Informatika
Publisher : Politeknik Sawunggalih Aji

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (315.057 KB)

Abstract

This research aimed to evaluate web portal STT Dharma Iswara Madiun using McCall with a discussion of the quality factor is included in product operations consisting of five factors of quality of correctness, reliability, efficiency, integrity, and usability as well as analysis of data using the formula of quality factors and metrics and use some help tools. This study uses research instruments in the form of questionnaires and some application tools. The results showed how good the quality of the web portal STT Dharma Iswara Madiun, and any proposals that may be submitted to the portal web developers to develop more qualified web portal. Keywords—Quality Evaluation, Web Portal, McCall
Prediksi Nilai Dan Waktu Kelulusan Mahasiswa Menggunakan Metode Svm (Studi Kasus: Universitas KH A Wahab Hasbullah Jombang Mochamad Fadillah Abdullah; Kusrini Kusrini; M. Rudyanto Arief
SAINTEKBU Vol. 14 No. 01 (2022): Vol. 14 No. 01 January 2022
Publisher : KH. A. Wahab Hasbullah University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/saintekbu.v14i01.1096

Abstract

Kelulusan mahasiswa merupakan salah satu yang harus diperhatikan karena masuk dalam Standar Penjaminan Mutu Internal suatu perguruan tinggi . Fakultas Teknologi Informasi merupakan salah satu fakultas yang di universitas KH A Wahab Hasbullah Jombang. Untuk kelulusan terdapat standar yang akan dicapai oleh fakultas tersebut yaitu waktu studi selama 4 tahun dan IPK minimal 3,00. Untuk dapat mencapai mutu kelulusan tersebut dibutuhkan suatu prediksi tingkat kelulusan dengan standar yang telah ditetapkan untuk mahasiswa yang masih menjalankan studi sehingga dapat dilakukan antisipasi dari awal sehingga dapat menanggulangi terjadinya permasalahan dalam bidang akademik. Untuk memprediksi tingkat kelulusan dan IPK standar tersebut digunakan metode data mining dengan fungsi klasifikasi. Metode klasifikasi yang digunakan menggunakan metode SVM. Perangkat yang digunakan untuk mengolah data yaitu software Rapid Miner.
PENENTUAN DOMAIN MENINGKATKAN TATA KELOLA TEKNOLOGI INFORMASI DI DINAS KOMUNIKASI, INFORMATIKA DAN STATISTIK KABUPATEN KEPULAUAN TALAUD MENGGUNAKAN COBIT 4.1 Maykel Sonobe; kusrini kusrini; Asro Nasiri
Jurnal Explore Vol 12, No 1 (2022): JANUARI
Publisher : Universitas Teknologi Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (849.92 KB) | DOI: 10.35200/explore.v%vi%i.493

Abstract

Dinas Komunikasi Informatika dan Statistik (KOMINFOTIK) Kabupaten Kepulauan Talaud yang terletak di JL.Bui Batu, Kompleks Perkantoran Pemerintahan Kabupaten Talaud, Kota Melonguane, Kabupaten Talaud, Provinsi Sulawesi Utara adalah instansi yang bertugas membantu pemerintah daerah dalam bidang komunikasi,informasi dan statistik untuk keperluan instansi yang lain sehingga mempermudah pelayanan kepada masyarakat. Seperti maintenance jaringan, website, penyedia pembuatan aplikasi yang dibutuhkan oleh instansi yang lain. Sesuai dengan tugas yang dijalankan sehingga membutuhkan dukungan kebijakan tata kelola yang baik untuk mengoptimalkan pelayanan. Audit tata kelola IT dengan menggunakan COBIT framework sudah sering di laukakan dan hasil yang di rekomendasikan bisa membantu. Sehingga tata kelola TI menjadi lebih baik. Tata kelola TI adalah tanggung jawab dan wewenang untuk mengambil keputusan yang benar. Standar umum yang biasa digunakan untuk mengevaluasi IT adalah COSO, COBIT, ITIL, ISO, NSA dan INFOSEC. Control Objectives for Information and Related Technology (COBIT). Kerangka kerja COBIT 4.1 yang digunakan dalam penelitian ini. Domain yang ditentukan berdasarkan IT goals dan Business yaitu Plan and Organize (PO): PO2, PO4, PO5, PO7, PO8, PO10, Acquire and Implement (AI): AI3, AI5 Deliver and Support (DS): DS6, dan Monitoring and Evaluate (ME): ME1, ME4
Classification of Mango Fruit Quality Based on Texture Characteristics of GLCM (Gray Level Co-Occurrence Matrices) with Algorithm K-NN (K-Nearest Neighbors) Wahyu Wijaya Widiyanto; Eko Purwanto; Kusrini Kusrini
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 20, No 1 (2019): Techno Volume 20 No.1 April 2019
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v20i1.3816

Abstract

Proses klasifikasi kualitas mutu buah mangga dengan cara konvensional menggunakan mata manusia memiliki kelemahan di antaranya membutuhkan tenaga lebih banyak untuk memilah, anggapan mutu kualitas buah mangga antar manusia yang berbeda, tingkat konsistensi manusia dalam menilai kualitas mutu buah mangga yang tidak menjamin valid karena manusia dapat mengalami kelelahan. Penelitian ini bertujuan untuk klasifikasi kualitas mutu buah mangga ke dalam tiga kelas mutu yaitu kelas Super, A, dan B dengan computer vision dan algoritma k-Nearest Neighbor. Hasil pengujian menggunakan jumlah k tetangga 9 menunjukan tingkat akurasi sebesar 88,88%.Kata-kata kunci— Klasifikasi, GLCM, K-Nearest Neighbour, Mangga
Image Similarity Searching Use Multi Part Cutting And Grayscale Color Histogram Sofyan Pariyasto; Kusrini Kusrini; Hanif Al Fatta
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 20, No 1 (2019): Techno Volume 20 No.1 April 2019
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v20i1.3817

Abstract

The use of information technology in everyday life continues to increase so rapidly. This is inseparable from the role of researchers, especially in the field of information technology. Information technology has become a necessity so that it is widely used in the fields of education, trade, livestock and even to the agricultural sector. One of the obstacles that is needed is to check all activities involving information systems, especially when there is data in the form of images. Problems that arise are usually needed by humans to check and sort items that have been carried out by humans. This is the background of this research to help reduce activities involving humans. The process of finding the similarity of images in computer vision can be used in several fields such as education, retail, and other fields. In the field of computer vision education can be utilized for the automatic absence process through face recognition, in terms of retailing, it can be used for sorting through object detection. The process of finding similarities between images that are queries and dataset images will be the subject of research, and the process of calculating similarities between queries and datasets will be discussed step by step. The method used in the search process is by calculating the shortest distance between query images and dataset. The steps taken are the extraction feature and then RGB to gray color conversion. The next stage is to cut the image into four parts which will then be calculated the distance of the ecludian. The final part will calculate the performance of the algorithm using the matrix confusion method, so that the test results are in the form of error rates, precision, and accuracy. The trial process uses 30 data using 1000 datasets. In the test results obtained information in the form of recall of 1, 0.66 accuracy and 0.66precision.Keywords: Image Similarity, Histogram Image Grayscale, Ecludiance Distance.
Searching Similarity Digital Image Using Color Histogram Wahyu Wijaya Widiyanto; Kusrini Kusrini; Hanif Al Fatta
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 20, No 1 (2019): Techno Volume 20 No.1 April 2019
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v20i1.3818

Abstract

In the era of globalization and modernization, as now, information technology is widely used in the fields of education, trade, animal husbandry, agriculture and even to the legal sector. One branch of science in the field of information technology that is growing rapidly is computer vision. One of the important roles of computer vision in everyday life is the use of computer vision. This can be applied in terms of face recognition, object detection, and can be applied to group images based on the order of similarity of the image, the ability of computer vision is applied to facilitate human work in selecting from several images to find the most similar images. In this study described the process of finding the similarity of an image with other images through several stages of research flow, the method used is to use RGB values that have been converted to grayscale, then the eucludian distance distance is calculated to determine the value of proximity of an image while calculating performance accuracy algorithm using confusion matrix. The search trial process resulted in an accuracy rate of 0.42, precision of 0.42 and recall 1 of 1000 datasets and 30 random data were taken. Found images that differ in color and shape but when converted into histograms the data has a fairly high similarity to the query. The disadvantage of this research is that images that have histograms similar to queries are displayed as similar images even though the reality is that images are very different from colors and shapes.Keywords: computer vision, similiarity, eucludian distance, grayscale, histogram
PERBANDINGAN RESPONSE TIME DATA TRANSAKSI ANTARA KONEKTIVITAS SISTEM PEMBAYARAN PADA BTN SYARIAH DENGAN BPD JATENG SYARIAH Marta Ardiyanto; Kusrini Kusrini; Anggit Dwi Hartanto
Device Vol 13 No 1 (2023): Mei
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/device.v13i1.4372

Abstract

Dalam penerapan sistem informasi pembayaran terintegrasi pada Universitas Duta Bangsa Surakarta secara host to host menggunakan layanan web service dengan perbankan dapat membantu meningkatkan aksesibilitas transaksi pembayaran biaya pendidikan mahasiswa. Transaksi yang selama ini berjalan melalui jaringan terintegrasi belum dilakukan evaluasi terkait time response data setiap satu transaksi berjalan. Dalam penelitian ini akan dibahas mengenai berapa time response yang dibutuhkan untuk menyelesaikan transaksi pada dua bank rekanan yang bekerja dengan universitas diantaranya Bank BPD Jateng Syariah dan Bank BTN Syariah. Evaluasi ini bertujuan untuk memberikan gambaran terkait berapa time response dari masing-masing bank rekanan saat memproses transaksi pembayaran pada sistem terintegrasi untuk kemudian hasilnya dapat digunakan sebagai bahan evaluasi dalam pengembangan sistem terintegrasi antara universitas dengan bank rekanan. Berdasarkan hasil pengujian didapatkan hasil response time server Bank BPD Jawa Tengah Syariah memiliki waktu response time lebih sedikit dibandingkan dengan Bank BTN Syariah. Yang berarti bahwa Transaksi pembayaran biaya pendidikan mahasiswa universitas duta bangsa Surakarta lebih cepat melalui Bank BPD Jawa Tengah Syariah dengan waktu transaksi paling cepat adalah 0 detik dan transaksi paling lama adalah 2 menit 20 detik dari mulai proses transaksi hingga flagging response dari bank ke sisi server universitas
Penerapan model InceptionV3 dalam klasifikasi penyakit ayam Muhammad Salimy Ahsan; Kusrini Kusrini; Dhani Ariatmanto
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2023.v4-no02-55-62

Abstract

Chicken disease is one of the problems that can have a very significant impact on chicken farmers, in addition to having an impact on the farm itself, chicken disease can also have an impact on the surrounding environment. Lack of knowledge about the symptoms and diseases that occur in chickens, makes some chicken breeders treat and treat diseases in a traditional way. This method often takes a long time and is prone to errors. In this study, technology will be used to classify chicken diseases by utilizing a deep learning model from the Convolutional Neural Network (CNN) architecture, namely InceptionV3. In carrying out the process of classifying chicken diseases, using a dataset of chicken feces images with a number of 8067 Healthy, Salmonella, Coccidiosis, and Newcastle disease. In the research process, three experimental scenarios were carried out using 20 epochs, 50 epochs and 100 epochs. From the experimental results, using a value of 100 epochs produces the highest accuracy value with a value of 94.05%.
Analisis Perbandingan Kinerja Algoritma Apriori, FP-Growth dan Eclat dalam menemukan Pola Frekuensi pada Dataset INA-CBG'S Eka Wahyu Pujiharto; Kusrini Kusrini; Asro Nasiri
CogITo Smart Journal Vol. 9 No. 2 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i2.547.340-354

Abstract

Setiap fasilitas kesehatan seperti rumah sakit, klinik dan puskesmas yang bekerjasama dengan BPJS wajib melakukan klaim pembiayaan atas perawatan kesehatan terhadap pasien menggunakan tarif INACBG’s  (Indonesian - Case Based Groups). Tarif INACBG’s merupakan paket layanan yang didasarkan kepada pengelompokan diagnosa penyakit yang menggunakan kode ICD-10. Penelitian ini bertujuan menemukan pola frekuensi pada dataset INA-CBG’s terutama  kombinasi diagnosa agar diketahui kombinasi diagnosa apa saja yang sering muncul untuk bahan evaluasi lebih lanjut oleh pihak manajemen fasilitas kesehatan. Penelitian ini membandingkan kinerja Algoritma Apriori, FP-Growth dan Eclat. Nilai Akurasi Lift Ratio dan Rule Asosiasi ketiga algoritma didapatkan nilai yang sama, tetapi untuk waktu komputasi dan pemakaian memori pada Algoritma Eclat lebih banyak daripada Algoritma Apriori dan Fp-Growth, maka dapat disimpulkan bahwa Algoritma FP-Growth dan Apriori lebih cocok untuk dijadikan solusi dalam menemukan pola frekuensi pada dataset INACBG’s.
Identification of Lumpy Skin Disease in Cattle with Image Classification using the Convolutional Neural Network Method Thedjo Sentoso; Fachri Ardiansyah; Virginia Tamuntuan; Sabda Sastra Wangsa; Kusrini Kusrini; Kusnawi Kusnawi
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.2569

Abstract

One of the problems often faced by cattle farmers is related to diseases in their cattle where one of the cattle diseases whose transmission rate is very fast is Lumpy Skin Disease (LSD). Currently, to identify the health of livestock, especially in cattle, is still very dependent on experts and of course this takes time, resulting in delays in the prevention and treatment of diseases in cattle, especially this LSD disease. The Convolutional Neural Network (CNN) algorithm is one of the algorithms can used for image classification of cows whether the cow is healthy or Lumpy. The stages of this research start from problem identification, literature study, data collection, algorithm implementation, testing, and performance evaluation results of the algorithm on cattle disease data. In this research, testing was conducted using three architectures for CNN: VGG16, VGG19, and ResNet50. The results of the experiment showed that VGG16 was the most effective architecture compared to VGG19 and ResNet50, with a training accuracy of 95.31% and a loss value of 0.1292, as well as a testing accuracy of 96.88% and a loss value of 0.102.
Co-Authors Abdul Malik Zuhdi Abdul Rokhim Achmad Yusron Arif Agung Jasuma Agung Nugroho Aisha Alfani Aji Susanto Anom Purnomo Andayani Andayani Andi Sunyoto Andria Andria Anggit Dwi Hartanto Aprison Wolla Gole Ari Suhartanto Arif Fajar Solikin Arif Fajar Solikin Armadyah Amborowati Asro Nasiri Assani, Moh. Yushi Azis Wahyudi B, Isdayani Christin Nandari Dengen DHANI ARIATMANTO Dina Maulina Dwinda Etika Profesi Eka Wahyu Pujiharto Eka Yulia Sari Eko Purwanto Elfrida Ratnawati Elik Hari Muktafin Elvis Pawan Emha Taufiq Luthfi Erfan Tongalu Eva Oktaviani Fachri Ardiansyah Fareza Aditiyanto Nugroho Ferry Wahyu Wibowo Firmanda Fasya Hamada Zein HANIF AL FATTA Hasan, Nur Fitrianingsih Henderi . Heri Abijono Irfan Purwanto Jhoanne Fredricka Jimmy H Moedjahedy Junaidi Sabtu Kusnawi Kusnawi Lili Kartikawati M Rudyanto Arief M Vaizul Rahman M. Afriansyah M. Rudyanto Arief M. Syukri Mustafa Marta Ardiyanto Maykel Sonobe Mochamad Fadillah Abdullah Muchamat Zainal Arifin Muhamad Kurniawan Muhammad Agus Muljanto Muhammad Alfariz Muhammad Fahmi Muhammad Fajar Apriyanto Muhammad Firdaus Abdi Muhammad Rudyanto Arief Muhammad Salimy Ahsan Musthofa Galih Pradana Mutiara Dwi Anggraini Neno, Friden Elefri Norhikmah Norhikmah Pamekas, Bondan Wahyu Rahmat Saleh Sukur Rifqi Hammad Ririn Putri Damaiyanti Riska Dwi Handayani Sabda Sastra Wangsa Siti Nurhayati Siti Solekhah Sofyan Pariyasto Sri Lestari Rahayu Sri Yanto Qodarbaskoro Thedjo Sentoso Uli Rizki Virginia Tamuntuan Wahyu Nur Alimyaningtias Wahyu Wijaya Widiyanto Wira Dimuksa Wiwi Widayani Yeyen Dwi Atma Yustian Servanda Zenal Muttaqin Zeni Muhamad Noer