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JUITA : Jurnal Informatika
Published by Universitas Muhammadiyah Purwokerto
ISSN : 20869398     EISSN : 25798901     DOI : 10.30595/JUITA
Core Subject : Science,
Computer Science & IT
UITA: Jurnal Informatika is a science journal and informatics field application that presents articles on thoughts and research of the latest developments. JUITA is a journal peer reviewed and open access. JUITA is published by the Informatics Engineering Study Program, Universitas Muhammadiyah Purwokerto. JUITA invites researchers, lecturers, and practitioners worldwide to exchange and advance knowledge in the field of Informatics. Documents submitted must be in Ms format. Word and written according to author guideline. JUITA is published twice a year in May and November. Currently, JUITA has been indexed by Google Scholar, IPI, DOAJ, and has been accredited by SINTA rank 2 through the Decree of the Director-General of Research and Development Strengthening of the Ministry of Research, Technology and Higher Education No. 36/E/KPT/2019. JUITA is intended as a media for informatics research among academics, practitioners, and society in general. JUITA covers the following topics of informatics research: Software engineering Artificial Intelligence Data Mining Computer network Multimedia Management Information System Digital forensics Game
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 316 Documents
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A Deep Learning Using DenseNet201 to Detect Masked or Non-masked Face Faisal Dharma Adhinata; Diovianto Putra Rakhmadani; Merlinda Wibowo; Akhmad Jayadi
JUITA : Jurnal Informatika JUITA Vol. 9 No. 1, May 2021
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1047.417 KB) | DOI: 10.30595/juita.v9i1.9624

Abstract

The use of masks on the face in public places is an obligation for everyone because of the Covid-19 pandemic, which claims victims. Indonesia made 3M policies, one of which is to use masks to prevent coronavirus transmission. Currently, several researchers have developed a masked or non-masked face detection system. One of them is using deep learning techniques to classify a masked or non-masked face. Previous research used the MobileNetV2 transfer learning model, which resulted in an F-Measure value below 0.9. Of course, this result made the detection system not accurate enough. In this research, we propose a model with more parameters, namely the DenseNet201 model. The number of parameters of the DenseNet201 model is five times more than that of the MobileNetV2 model. The results obtained from several up to 30 epochs show that the DenseNet201 model produces 99% accuracy when training data. Then, we tested the matching feature on video data, the DenseNet201 model produced an F-Measure value of 0.98, while the MobileNetV2 model only produced an F-measure value of 0.67. These results prove the masked or non-masked face detection system is more accurate using the DenseNet201 model.
Sistem Informasi Geografis Pemetaan Kantor Polisi Wilayah Kota Pekanbaru Provinsi Riau Sukamto Sukamto; Elfizar Elfizar; M Bimo Septiono
JUITA : Jurnal Informatika JUITA Vol. 5 Nomor 2, November 2017
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (905.298 KB) | DOI: 10.30595/juita.v5i2.1857

Abstract

Abstract  This research discusses about the Geographical Information System (GIS) mapping of Police Station in the city of Pekanbaru in  Riau province. The absence of information about the existence of digital spread Police Station in the city of Pekanbaru that makes people want to take care of these needs when police agencies Pekanbaru be hampered because it takes a long time to find the police station .. It is underlying this research. SIG provides information to the public regarding the location and type Police Station in the city of Pekanbaru, so as the public will more easily find the Police Station to take care of the police office purposes. Besides GIS also helps the police Pekanbaru in determining the crime- prone locations occur so police can take preventive measures or planning to build a new police station. The information systems using programming language HTML, CSS, JQuery, PHP, XML, and Google Maps,  and then MySQL as a database. To design the system using System Flowchart, Data Flow Diagram, and Entity Relation Diagram.  Keywords : Mapping of Police station, Geographical Information System,
Pembangunan Aplikasi Pelaporan Perijinan dengan Online Analytical Processing (OLAP) Dimara Kusuma Hakim
JUITA : Jurnal Informatika JUITA Vol. 1 Nomor 3, Mei 2011
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (344.354 KB) | DOI: 10.30595/juita.v1i3.439

Abstract

Business licensing data in a district that has been collected in a database, it will be useful when it is analyzed, so a lot of important information will be obtained. The government need a system that can help them to analyze data easily. Online Analytical Processing (OLAP) is an implementation of Data warehousing that can help reporting and analyzing well. OLAP can map the data with cube dimensions, each dimension can be easily compared, so the decision maker can find the problems that faced easily and quickly. Some of the problems that solved in this research are : Progress Report on Company Registration in several years, the Number of Companies by the type of business, Development of Investment, the number of SIUP by District, , the number of SIUP by business class, the number of license based on its type, Construction Permit (IMB) in several years, and the Number of Disorders Permits (HO) by several classification. Reporting application in data Licensing are built in this research with OLAP technology.  Based on the Chi-Square testing performed for business licensing data which contain 100-1161 records, the Chi-Square value are 45,89 – 80, greater than Chi-Square table (13,28), there is significantly different for time consuming between SQL and OLAP.  When data are reduced for 90 records, the Chi-Square value is 2.01, less than Chi-Square table, there is no significantly different for time consuming between SQL and OLAP
Pengembangan Prototype Aplikasi Pendukung Penerbitan KJP Heri Satria; Danang Sutrisno; Kursehi Falgenti
JUITA : Jurnal Informatika JUITA VoL. 7 Nomor 1, Mei 2019
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (941.008 KB) | DOI: 10.30595/juita.v7i1.3566

Abstract

Penerbitan KJP menjadi beban tambahan bagi sekolah-sekolah di DKI Jakarta. Pekerjaan seleksi penerimaan KJP menjadi berat karena banyaknya pemohon, sedangkan sumberdaya manusia yang memiliki keahlian dalam mengolah data terbatas. Proses seleksi menemui banyak kendala diantaranya sering terjadi kesalahan dalam menginput data karena kurangnya ketelitian. Dalam mengantisipasi permasalahan tersebut, penerbitan KJP di sekolah memerlukan  aplikasi pendukung untuk memperlancar penginputan data. Penelitian ini bertujuan membangun prototype aplikasi pendukung penerbitan KJP di sekolah-sekolah yang ada di wilayah DKI Jakarta. Data pendukung pembuatan prototype ini peroleh di dua sekolah, yaitu  SMUN 80 Jakarta dan SMP Darrosta Jakarta. Metode yang digunakan dalam penelitian ini adalah System Development Life Cycles dengan model water fall. Hasil penelitian berupa Aplikasi Pendukung penerbitan KJP untuk memudahkan sekolah dalam mengolah data. Basis data penerima KJP diambil dari sistem DAPODIK.  Pengajuan Penerima KJP tidak perlu langsung diinput secara online, untuk menghindari kesalahan input data operator cukup melakukan sinkronisasi data pada aplikasi pendukung dengan sistem KJP Online. Fitur sinkronisasi ini belum bisa dijalankan karena harus melalui ijin UPT Pusat Pelayanan Pendanaan Personal dan Operasional Pendidikan (P4OP) Dinas Pendidikan PEMDA DKI Jakarta.
Rancang Bangun Sistem Informasi Nilai Mata Pelajaran Berbasis Web dan SMS Gateway Akhsin Rifai; Hindayati Mustafidah
JUITA : Jurnal Informatika JUITA Vol. 2 Nomor 4, Nopember 2013
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1255.695 KB) | DOI: 10.30595/juita.v2i4.828

Abstract

Score at the agency school is one measure of the success of students in learning the material presented. To provide score transparency to students and parents needed an information system score subjects in an easy and fast data access. In fulfilling these conditions, build-up lesson score information system of Web and SMS Gateway Based. The system is built using Gammu software and using the programming language PHP. By using SMS to obtain the score of the data is expected to provide convenience for parents to monitor learning outcomes of their children’s in school.
Prediksi Kelompok UKT Mahasiswa Menggunakan Algoritma K-Nearest Neighbor Sukamto Sukamto; Yanti Adriyani; Rizka Aulia
JUITA : Jurnal Informatika JUITA Vol. 8 Nomor 1, Mei 2020
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1343.462 KB) | DOI: 10.30595/juita.v8i1.6267

Abstract

Penelitian ini bertujuan untuk memprediksi UKT yang akan dibayarkan oleh calon mahasiswa khususnya program studi S1 Sistem Informasi FMIPA Universitas Riau dengan menggunakan metode K-Nearest Neighbor (K-NN). Kriteria yang digunakan yaitu penghasilan kotor, penanggung uang kuliah, jumlah tanggungan yang tercantum dalam kartu keluaga, status tempat tinggal, keadaan dinding tempat tinggal, keadaan atap tempat tinggal, total luas kepemilikan lahan dan biaya pemakaian listrik sebulan. Adapun kelompok UKTnya adalah UKT1, UKT2, UKT3, UKT4, UKT5 dan UKT6. Data yang digunakan adalah mahasiswa S1 FMIPA Universitas Riau tahun angkatan 2016, 2017, dan 2018. Perbandingan untuk data latih dan data uji adalah 90% : 10%. Tingkat keakuratan dari klasifikasi yang didapat sebesar 84,21%.Kata-kata kunci: Klasifikasi, K-Nearest Neighbor, UKT
Kalkulasi Bantuan Korban Bencana Alam Menggunakan Sistem Pakar Khotimul Anwar; Hindayati Mustafidah
JUITA : Jurnal Informatika JUITA Vol. 4 Nomor 1, Mei 2016
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (871.887 KB) | DOI: 10.30595/juita.v4i1.1183

Abstract

Menentukan bantuan korban bencana alam merupakan hal yang sangat penting, supaya kebutuhan korban bencana alam dapat tercukupi dengan baik. Hal ini dimaksudkan supaya bantuan yang diterima korban bencana alam lebih tepat sasaran. Sistem yang akan dibangun ini diharapkan dapat membantu dalam menetukan kebutuhan korban bencana alam. Metode yang digunakan dalam pengembangan sistem ini adalah Sistem Pakar Runut Maju (Forward Chaining). Metode ini digunakan karena sesuai dengan kondisi yang ada dilapangan. Data - data yang diolah meliputi data jenis bencana, status korban, dan jenis bantuan. Data – data tersebut kemudian diolah menggunakan Sistem Pakar Runut Maju (Forward Chaining) sehingga menghasilkan keluaran berupa bantuan korban bencana alam.
Evaluasi Kinerja Transformasi pada Image Warping dalam Pemprosesan Citra Mosaic dengan Objective Fidelity Criteria Kuat Indartono; Dhanar Intan Surya; Rizki Wahyudi
JUITA : Jurnal Informatika JUITA Vol. 5 Nomor 1, Mei 2017
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1031.161 KB) | DOI: 10.30595/juita.v5i1.1472

Abstract

Citra mosaik adalah gabungan beberapa citra yang memiliki bagian berkesesuaian sehingga membentuk citra dengan visualisasi yang lebih lebar. Tahapan pada citra mosaik dapat dibagi dalam tiga tahap: pertama, inisialisasi titik pada pasangan citra, kedua image warping, dan ketiga penggabungan citra. Beberapa permasalahan yang ada pada citra mosaik yaitu deformasi geometris, registrasi citra dan komposisi citra. Tujuan dari penelitian ini adalah untuk mengukur kinerja transformasi Perspective. Pada penelitian ini digunakan metode pendekatan, dengan fokus pada pencarian transformasi terbaik dalam tahap image warping. Pengujian pada penelitian ini dilakukan secara obyektif dengan menghitung error (nilai MSE dan nilai PSNR) antara citra mosaic dengan citra asli yang sudah di transformasi. Hasil perhitungan nilai MSE dan nilai PSNR pada citra mosaic dengan transformasi perspective pada Benteng Van Der Wijck Gombong dengan Nilai MSE  sebesar 551,8171 dan Nilai PSNR sebesar 20,7129 dB. Pencahayaan yang tidak sama antara masing-masing citra tidak mempengaruhi hasil pembentukan citra mosaic, akan tetapi secara estetika pada daerah sambungan terlihat kurang baik.  
Pengembangan Media Pembelajaran Berbasis Komputer pada Pokok Bahasan Himpunan Guna Meningkatkan Pemahaman Mahasiswa Eka Setyaningsih; Hindayati Mustafidah
JUITA : Jurnal Informatika JUITA Vol. 1 Nomor 2, Nopember 2010
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (528.886 KB) | DOI: 10.30595/juita.v1i2.414

Abstract

This Research is depended on the students study results are lower in Set Subject, those are caused by their small knowledge level.  In this research is conducted to develop interactive computer base learning media especially in set topic. The goal of this learning media development is to assist the student in comprehending in set topic, because this media provides some interactive menus that facilitate the students to use it.  This research uses literature study method about how to compile the computer base learning media and set topic. The stages of this research are analyzing set books, designing the model of computer base learning media, and compiling the computer program. Result of this research is a learning media in the form of interactive computer program which can be used by students as an assist tool to learn the set topic. This media is consisted of two main parts, they are theory and problem practice. At the theory part, students can learn the theory of set, while at problem practice part students can exercise to do the practice problem about set. At this part is also provided with scoring, that is if answer given by real correct student, hence media will give the score and correct signal. This matter can be used to know whether students have mastered the set topic or not yet. Thereby, it is expected a student will continue to exercise the practice problem till reaches the optimum understanding level.
Cyberbullying Detection Modelling at Twitter Social Networking Ika Yunida Anggraini; Sucipto Sucipto; Rini Indriati
JUITA : Jurnal Informatika JUITA Vol. 6 Nomor 2, November 2018
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (891.398 KB) | DOI: 10.30595/juita.v6i2.3350

Abstract

Cybercrimes often happened in social networking sites. Cyber-bullying is a form of cybercrime that recently trended in one of popular social networking sites, Twitter. The practice of cyber-bullying on teenager can cause depression, murderer or suicidal thoughts and it needs a preventing action so it will not harmful to the victim. To prevent cyber-bullying a text mining modelling can be done to classify tweets on Twitter into two classes, bullying class and not bullying class. On this research we use Naïve Bayes Classifier with five stages of pre-processing : replace tokens, transform case, tokenization, filter stopwords and n-grams. The validation process on this research used 10-Fold Cross Validation. To evaluate the performance of the model a Confusion Matrix table is used. The model on 10-Fold Cross Validation phase works well with 77,88% of precision , 94,75% of recall and 82,50% of accuracy with +/-5,12%  of standard deviation.

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