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All Journal International Journal of Electrical and Computer Engineering Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) CESS (Journal of Computer Engineering, System and Science) Jurnal Inspiration JOIV : International Journal on Informatics Visualization Creative Information Technology Journal SISFOTENIKA Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Komtika (Komputasi dan Informatika) RESEARCH : Computer, Information System & Technology Management DoubleClick : Journal of Computer and Information Technology JurTI (JURNAL TEKNOLOGI INFORMASI) Voice Of Informatics Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Multitek Indonesia : Jurnal Ilmiah JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Ilmiah Sinus Informasi Interaktif Majalah Ilmiah Bahari Jogja CCIT (Creative Communication and Innovative Technology) Journal TAFAQQUH: Jurnal Hukum Ekonomi Syariah Dan Ahwal Syahsiyah Infotekmesin Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Respati Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Perangkat Lunak Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia JNANALOKA Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Journal of Technology and Informatics (JoTI) SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Ekonomi dan Teknik Informatika Literasi Nusantara Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Techno Innovative: Journal Of Social Science Research Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Teknomatika: Jurnal Informatika dan Komputer Tafaqquh : Jurnal Hukum Ekonomi Syariah dan Ahwal Syahsiyah Explore Jurnal Teknologi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika) Jurnal Bisnis Digital dan Sistem Informasi
Hanif Al Fatta
Universitas Amikom Yogyakarta
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Use of Fulltext Indexing to Improve Data Search Efficiency in MYSQL Databases Ahmad Hajar; Ema Utami; Hanif Al Fatta
SISFOTENIKA Vol 12, No 2 (2022): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/jst.v12i2.1264

Abstract

 The process of searching for data is one of the needs of the system that is needed. With the more data, the search process will take longer. There are many ways to speed up the data search process, one of which is by utilizing the Full text index feature in the MySQL database. In this study, a search query will be tested on tables that have been indexed and on tables that have not been indexed. Researchers use the like operator to search for data on tables that are not indexed. Meanwhile, in the table given the index, the researcher uses a full text search with the match against syntax. The results of this study indicate that the full text search on a table that has been given an index is faster than a table that is not indexed. When the number of data is 466,000, searching in a non-index table takes 2,638.97 milliseconds. Meanwhile, the indexed table takes 89.14 milliseconds. Then the impact of giving an index to the table is that the insert process takes longer than the table that is not indexed. In the product index table when the data is 466,000, the insert time is 6,560.69 milliseconds. While the product non index table is 420.96 milliseconds. In future research, it is expected to look for other query testing methods and find out the accuracy between like operator and match against.
PENGUJIAN SISTEM PANGKALAN DATA PERGURUAN TINGGI PADA KOPERTIS WILAYAH VII JAWA TIMUR Tika Dedy Prastyo; Kusrini Kusrini; Hanif Al Fatta
Jurnal DutaCom Vol 5
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (175.507 KB)

Abstract

Penelitian bertujuan untuk mengetahui (1) faktor-faktor apa saja yang akan diuji pada sistem pangkalan data perguruan tinggi (PDPT), (2) bagaimana pengujian sistem pangkalan data perguruan tinggi (PDPT) dilakukan, (3) apakah hasil dari pengujian sistem pangkalan data perguruan tinggi (PDPT) tersebut, (4) rekomendasi apa yang dapat diberikan dengan diadakannya penelitian ini. Obyek penelitian adalah sistem PDPT dan operator PDPT pada masing-masing perguran tinggi swasta di lingkungan Kopertis Wilayah VII Jawa Timur, sampel dipilih dengan cara stratified random sampling. Pengumpulan data menggunakan kuesioner yang indikatornya disusun dengan studi pendahuluan tentang TAM. Penelitian menyimpulkan bahwa hipotesis yang dikemukakan mendukung diskusi hasil penelitian yang dibangun berdasarkan asumsiasumsi TAM, kesimpulan ini semakin mempertegas bahwa faktor utama penerimaan adalah kemudahan dan kebermanfaatan yang dirasakan oleh pengguna produk teknologi.
RANCANG BANGUN PENGEMBANGAN SISTEM INFORMASI STRATEGIS UNTUK MENINGKATKAN DAYA SAING PERGURUAN TINGGI Sri Sumarlinda; Abidarin Rosidi; Hanif Al Fatta
Jurnal DutaCom Vol 3
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2078.422 KB)

Abstract

Penelitian ini bertujuan untuk membuat sistem informasi strategis yang dibuat dan dikembangkan dari sistem informasi manajemen perguruan tinggi ( SIM-PT) yang ada pada saat penelitian dilakukan dan berdasarkan Rencana Strategis (Renstra) Institusi. SIM-PT yang ada terdiri dari Sistem Informasi Pendaftaran, Sistem Informasi Keuangan, Sistem Informasi Akademik, Sistem Informasi Perpustakaan, Sistem Informasi Sarana & Prasarana, Sistem Informasi Kepegawaian dan Sistem Informasi Alumni. Berdasarkan basis data dari ke tujuh Sistem Informasi tersebut dikembangkan Sistem Informasi Strategis dengan menggunakan bahasa pemrograman PHP dan database MySQL. Hasil dari Sistem Informasi Strategis ini adalah berupa informasi strategis yang merupakan hasil pengolahan dan query data dari masing-masing sistem informasi yang dapat digunakan oleh Direktur untuk bahan pertimbangan dalam mencapai Rencana Strategis perguruan tinggi berdasarkan visi dan misi institusi
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
SOCIAL DISTANCING DETECTION FINDING OPTIMAL ANGLE WITH YOLO V3 DEEP LEARNING METHOD Mutiara Dwi Anggraini; Kusrini Kusrini; Hanif Al Fatta
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.390

Abstract

The COVID-19 pandemic has had a profound impact on all aspects of society. One of the implementations that the government has so far carried out is using masks and maintaining social distance. Over time, social distancing is difficult to control because people are now getting booster vaccines, but some have not. One way to overcome this problem is with a social distance detector system that detects the number of people and the distance of human objects from one another in an area. This study aims to apply in the office area, or the public. This research is one of the developments of a social distancing detector application that produces an optimal angle in using the application. So the program can detect the entirety of the object with optimal accuracy. Angle is very influential in taking the image to be processed in the system. This study uses the python language with the YOLOv3 library. This study got the best results,and the mean average precision in 90%:10% didapatkan dengan learning rate 0,001 dengan nilai mAP 54,11%, deteksi pada saaat penggujian sebesar 100%. Percobaan sudut terdapat 00.150.300, 450.600 dengan total 50 data video testing. Sudut optimal yang didapatkan pada penelitian ini adalah 00.150.300. Hal ini membuktikan bahwa sudut pengambilan video atau peletakan kamera sistem social distancing.
Prediksi Kapasitas Kargo Pada Bandara Deo Sorong Muhammad Surahmanto; Ema Utami; Hanif Al Fatta
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 8 No. 1 (2022): Oktober 2022
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v8i1.1912

Abstract

Kota Sorong memiliki letak yang strategis sehingga menjadi pintu keluar masuk dan transit ke Provinsi Papua Barat. Kota Sorong memiliki Bandara Domine Eduard Osok (DEO) yang melayani penerbangan berjadwal domestik dan Penerbangan perintis. Aktiftas pengiriman barang yang akan keluar ataupun menuju kota sorong dan sekitarnya otomatis akan terpusat di Bandara DEO. Untuk memastikan kelancaran aktifitas Kargo di Bandara DEO, pihak bandara harus memastikan kesiapan fasilitas layanan Kargo termasuk mengantisipasi jika kedepannya volume kargo semkin meningkat. Untuk itu diperlukan penelitian mengenai peramalan kapasitas kargo. Hal ini bertujuan untuk menghasilkan suatu sistem prediksi kapasitas kargo di bandara DEO dengan hasil data numerik. Metode ARIMA (Autoregressive Integrated Moving Average ) merupakan salah satu metode prediksi atau peramalan yang dapat menghasilkan ramalan-ramalan berdasarkan sintesis dari pola data secara historis. Metode ini memiliki tingkat kedekatan yang tinggi serta nilai kesalahan yang kecil dikarenakan proses perhitungan secara bertahap. Dengan menggunkan data volume kargo harian pada Bandara DEO tahun 2018, peneliti mencoba melakukan permodelan prediksi meggunakan model ARIMA. Dengan melakukan pengujian uji t ADF serta melakukan visualisasi menggunakan koefisien Autocorrelation Function (ACF) dan Partial Autocorrelation Function (PACF). Untuk melihat performa model menggunakan nilai RSS. Dari hasil penelitian, didapatkan bahwa model yang dibuat dapat melakukan prediksi dengan baik.
IMPLEMENTASI METODE SELEKSI FITUR MENGGUNAKAN ARTIFICIAL BEE COLONY PADA KLASIFIKASI RETINAL NERVE FIBER LAYER Aam Shodiqul Munir; Andi Sunyoto; Hanif Al Fatta
PENDIDIKAN SAINS DAN TEKNOLOGI Vol 10 No 2 (2023)
Publisher : STKIP PGRI Situbondo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47668/edusaintek.v10i2.782

Abstract

Damage to Retinal Nerve Fiber Layer can Cause Glaucoma. Glaucoma is an inflammation of the optic eye which is characterized by progressive deterioration of Optic Nerve Head and field of view. Problems that require a classification solution are hindered by the large data dimensions. Artificial Bee Colony is one of the evolution algorithms widely used for feature selection and optimization. Gray level Coocurrence matrix is used as a feature extraction method, the Artificial bee colony method is used as a feature selection and Support Vector Machine used as Classification. The proposed method using Artificial Bee Colony gets improved Accuracy compared to method without using Artificial Bee Colony. The results obtained by the proposed method were 95% for accuracy, 95.9% for specificity and 93.7% for sensitivity where methods that did not use Artificial Bee Colony obtained an accuracy of 93.8%, Specificity sebsar 90.3% and Sensitivity of 92.6%.
Prediksi Jumlah Kunjungan Wisatawan Kabupaten Lombok Barat Menggunakan Algoritma Long Short Term Memory (LSTM) M. Imam Budi Laksamana; Ema Utami; Hanif Al Fatta
TAFAQQUH: Jurnal Hukum Ekonomi Syariah Dan Ahwal Syahsiyah Vol. 6 No. 2 (2021): Meningkatkan pemahaman dan wawasan tentang hukum Islam
Publisher : LP2M Sekolah Tinggi Ilmu Syariah Darul Falah Mataram

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

Abstract

Kabupaten Lombok Barat merupakan salah satu wilayah di Indonesia yang memiliki daya tarik tersendiri bagi wisatawan lokal maupun internasional. Salah satu sektor yang paling terdampak besar terhadap intensitas kunjungan wisata adalah hotel. Untuk meningkatkan diperlukan upaya yang tepat untuk memelihara objek wisata sehingga dapat menjadi daya tarik bagi wisatawan. Dalam upaya pemeliharaan objek wisata, Dinas Pariwisata Lombok Barat perlu melakuakan analisa dan prediksi kedatangan wisatawan lokal maupun internasional, dalam prosesnya analisa dan prediksi, pemerintah kabupaten Lombok Barat melakukan pengumpulan data kunjungan wisatawan dari setiap pintu masuk objek wisata yang dimana pada prosesnya memerlukan waktu yang cukup lama dan membutuhkan sumber daya manusia yang cukup tinggi. Untuk mengatasi permasalahan tersebut dilakukan proses prediksi menggunakan sistem komputasi dengan machine learning agar nantinya waktu yang dibutuhkan dalam analisa dan prediksi menjadi lebih singkat dan kebutuhan akan sumber daya manusia yang tinggi bisa teratasi. Metode yang akan diterapkan dalam prediksi adalah Long Short Term Memory (LSTM), atribut dan nilai yang digunkan dalam model LSTM adalah nilai input layer 1, lalu nilai epochs 100 dan batch size 1, berdasarkan hasil pengujian yang dilakukan pada penelitian ini, Long Short Term Memory (LSTM) memiliki performa yang kurang baik dalam memprediksi jumlah kunjungan wisata kabupaten Lombok Barat menggunakan data rentang waktu bulanan dari tahun 2017-2021, hal ini dibuktikan dengan hasil uji evaluasi yang dilakukan dengan mencari nilai Root Mean Square Error (RMSE), dimana hasil model prediksi akan dikatakan baik jika memiliki nilai error yang lebih kecil. dimana nilai Root Mean Square Error (RMSE) yang dihasil dalam penelitian ini cukup tinggi yaitu 10479,30.
PENGUKURAN KUALITAS SISTEM INFORMASI INVENTARIS ASET UNIVERSITAS MUHAMMADIYAH BENGKULU MENGGUNAKAN METODE MCCALL Khairullah Khairullah; Bambang Soedijono; Hanif Al Fatta
Informasi Interaktif Vol 2, No 2 (2017): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1048.523 KB)

Abstract

Measurement of Inventory Information System Asset University of Muhammadiyah Bengkulu conducted to measure the quality of asset inventory information system application of Muhammadiyah University of Bengkulu based on user perception using McCall method. The measurement process of asset inventory information system of Muhammadiyah University of Bengkulu is done by several stages of measurement using several quality factors on the McCall method namely; correctness, reliability, efficiency, integrity and usability to know how far the quality and level of user utilization of the current asset inventory information system. The measurement process using the McCall method involves 18 respondents, where the results of this application measurement get the percentage of total quality of 68.4% and included in the good category. However, further development is needed to improve user utilization and the quality of the inventory asset information system itself better. Keywords : Pengukuran, Kualitas, McCall, Inventaris Aset
Co-Authors AA Sudharmawan, AA Aam Shodiqul Munir Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Abidarin Rosidi Agam Saka Jati Agus Susilo Nugroho Agustin, Tinuk Ahmad Hajar Alva Hendi Muhammad Alvhinia Meinda Amitaba Anas, Syukron Andi Sunyoto Anggie Ariawan Dewa Putra Anggit Dwi Hartanto Anggraini, Resti Kusuma Annas Al Amin Arief Setyanto Bambang Soedijono Bambang Soedijono W A Bambang Soedijono, Bambang Barnea, Samson Barnea, Samson Bayu Setiaji Bety Wulan Sari Chan Uswatun Khasanah Chriscel Novian Christian Budi Andrianto, Christian Budi Constantin Menteng Darmanto, Darmanto Dewa Saksana, Jidan Dhana Aulia Ayu Kurniawan Dimas Setiawan Donni Prabowo Dwi Sari Widyowaty Ema Utami Eri Sasmita Susanto Faisal Reza Pradhana Fajar Dwi Insani Fandli Supandi Fatimah Nur Arifah Fauji Maulana Ramlan, Fauji Maulana Firstyani Imannisa Rahma Fitriana, Frizka Gori, Takhamo Hadi Sucipto Hafidh Rezha Maulana Hari Agung Budi Santoso Hasan, Nur Fitrianingsih Hendra Kurniawan HENDRA SETIAWAN Hery Maryanto Hidayat Hidayat I Gede Ngurah Arya Indrayasa I Gede Ngurah Arya Indrayasa I Gede Ngurah Arya Indrayasa Imam Adi Nata Khairullah Khairullah Kristama, El Johan Kurniasari, Iin Kusrini Kusrini, K M Suyanto M Suyanto M Suyanto M. Imam Budi Laksamana M. Imam Budi Laksamana M. Nuraminudin M. Suyanto M. Suyanto M. Suyanto M. Suyanto, M. Made Ayu Dusea Widyadara - Universitas Nusantara Kediri, Made Ayu Dusea Widyadara Maksom, Zulisman Moch Ali Machmudi Moh Taufik H Mohammad Suyanto Muhammad Resa Arif Yudianto Muhammad Surahmanto Mutiara Dwi Anggraini NABILA OPER Noor Abdul Haris Noto Narwanto Nugroho Setio Wibowo Nugroho, Rakhmat Prasetyo Agung Nur Khasan Nurmasani, Atik Olivia Maria Inacio Tavares Pamungkas, Prima Giri Pradipta, Dody Purwidiantoro, Moch. Hari Purwoko, Agus Raditya Maulana Anuraga Rahman, Aulia Tegar Rakhma Shafrida Kurnia Risa Helilintar Riska Dwi Handayani Rizki Mawan Safagi, Ardian Yuligar Saifudin, Saifudin Saputra, Artha Gilang Saputra, Artha Gilang Setia Wardani Setiawan, Hendi Siti Rihastuti Sofyan Pariyasto Sri Lestari Rahayu Sri Ngudi Wahyuni Sri Sumarlinda Sugihandono, Agus Sutanto, Yudi Suyanto, M Suyanto, M Teguh Cahyono Tigus Juni Betri Tika Dedy Prastyo Tri Nugroho, Arief Tukan, Ewaldus Ambrosius Turah Suhono Tutik Maryana Wahyu Sindu Prasetya Widiyanto, Wahyu Wijaya Wijaya, Tri Amri Wing Wahyu Winarno Wira Dimuksa Wiwi Widayani Yetman Erwadi Yulia Rahmi Yuliana Yuliana Yusuf Fadlila Rachman Zakaria, Mohd Hafiz Zul Hisyam