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Contact Name
Hindayati Mustafidah
Contact Email
jurnal.juita@gmail.com
Phone
+6285842817313
Journal Mail Official
jurnal.juita@gmail.com
Editorial Address
Gedung Fakultas Teknik dan Sains Universitas Muhammadiyah Purwokerto Jl. K.H. Ahmad Dahlan, Dukuh Waluh, Kembaran, Banyumas, Central Java, Indonesia
Location
Kab. banyumas,
Jawa tengah
INDONESIA
JUITA : Jurnal Informatika
ISSN : 20869398     EISSN : 25798901     DOI : 10.30595/JUITA
Core Subject : Science,
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
Articles 316 Documents
Rancang Bangun Aplikasi untuk Menentukan Jalur Terpendek Rumah Sakit di Purbalingga dengan Metode Algoritma Dijkstra Abdul Ghofur Wibowo; Agung Purwo Wicaksono
JUITA : Jurnal Informatika JUITA Vol. 2 Nomor 1, Mei 2012
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3368.619 KB) | DOI: 10.30595/juita.v2i1.607

Abstract

Application of  Dijkstra's algorithm  is an  application made  to  determine the shortest path of hospital in  Purbalingga where the starting point comes from  a single point, namely  the town square of Purbalingga. The system is made with Microsoft Visual Studio 2005 and Microsoft SQL Server 2005.There are two types of hospitals in Purbalingga, such us public hospital and maternal hospital. On the main page, user can specify the type of hospital first before determining the choice of destination hospital. After that, user can know the shortest way to go. There is also a digital map in order to facilitate user into the hospital and information obtained is more informative. On the admin page is used to add data path information, hospital data and map data. Besides, the data path and hospital data can be changed if an error occurs. To determine the shortest path from each hospital, administrator must enter data into  the  system calculated  to form and then saved to the database, which will be used as a user's  information  can be obtained after choosing the destinationhospital
Komparasi Algoritma K-Nearest Neighbor dan Naiive Bayes Pada Pengobatan Penyakit Kutil Menggunakan Cryotheraphy Herlambang Brawijaya; Samudi Samudi; Slamet Widodo
JUITA : Jurnal Informatika JUITA VoL. 7 Nomor 2, November 2019
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.541 KB) | DOI: 10.30595/juita.v7i2.5609

Abstract

Pengobatan penyakit kutil menggunakan Cryotheraphy merupakan salah satu jenis pegobatan penyakit kutil yang direkomendasikan oleh beberapa pakar kesehatan. Metode yang digunakan dengan menggunakan nitrogen cair untuk pembekuan pada penyakit kutil. Dalam penelitian ini dilakukan komparasi pengujian model dengan menggunakan K-Nearest Neighbor dan Naiive Bayes untuk prediksi pengobatan penyakit kutil. Dalam proses pengujiannya, peneliti menggunakan aplikasi rapidminer untuk mengolah data dan melakukan pengujian. Hasil pengujian yang telah dilakukan menunjukkan pengujian menggunakan model K-Nearest Neighbor (K-NN) didapat nilai akurasi terbaik adalah 90,00% dengan nilai AUC sebesar 0,500 sedangkan hasil pengujian menggunakan model Naiive Bayes didapat nilai akurasi lebih kecil dibandingkan dengan model K-NN yaitu 86,67% dengan nilai AUC sebesar 0,932. Berdasarkan pengujian yang sudah dilakukan dapat disimpulkan bahwa model K-Nearest Neigbor memiliki tingkat akurasi lebih baik dibandingkan dengan model Naiive Bayes dalam prediksi pengobatan penyakit kutil menggunakan Cryotheraphy. 
Sistem Pakar Untuk Menyusun Formula, Kandungan Gizi, dan Harga Pakan Ikan Suwarsito Suwarsito; Hindayati Mustafidah
JUITA : Jurnal Informatika JUITA Vol. 3 Nomor 2, Nopember 2014
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.294 KB) | DOI: 10.30595/juita.v3i2.858

Abstract

Development of expert system has been widely applied to various fields of study, including education (for tutorial), academics, medicine (to diagnose the disease either man or animal), and so on. In this study applied expert system to compile a formula feeding fish include nutrient and estimated price of the feed raw material. The system was built using backward chaining using Turbo C++ programming language. This system is interactive. User should answer the system’s question of type and age of the fish, as well as a range of feed raw materials around, the user will get the required nutrient content information as well as advice on solutions in the form of formula feed and how much raw material feed is needed as well as the estimated price
Integrasi Framework Kivy dan Webix pada Pembangunan Framework Mobile Web Easy Development System(Integration Kivy and Webix Framework in Easy Development System Mobile Web Framework) Nina Setiyawati; Vio Ayu Oktavia Putu Warisman
JUITA : Jurnal Informatika JUITA Vol. 8 Nomor 2, November 2020
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (979.521 KB) | DOI: 10.30595/juita.v8i2.7464

Abstract

Pada dunia retail era sekarang, kemampuan untuk lebih meminimalkan biaya pengeluaran dengan inovasi teknologi modern menjadi salah satu poin penting dalam mendongkrak kemajuan bisnis. Hal tersebut diakibatkan karena perubahan kecil pada teknologi informasi dapat membantu mempercepat kinerja dan meningkatkan pendapatan. Salah satu perusahaan retail terbesar di Indonesia, PT. Sumber Alfaria Trijaya, Tbk (Alfamart) membangun sebuah framework berbasis web menggunakan framework Webix pada Front-End dan Python pada Back-End untuk dapat mengakomodasi perpindahan dari aplikasi server on-premises ke cloud computing. Namun, beberapa kendala ditemukan seperti dibutuhkannya waktu yang relatif lama ketika diakses melalui peramban smartphone, serta kode program dapat dilihat oleh siapapun ketika aplikasi berjalan pada browser. Oleh karena itu pada penelitian ini dibangun framework yang lebih fleksibel yaitu Mobile Web Easy Development System (M-EDS) yang dapat diakses oleh developer untuk mengembangkan aplikasi mobile web berbasis android dan iOS, serta pengguna akhir untuk mengakses aplikasi yang dikembangkan. M-EDS dapat mengakomodasi aktivitas pengguna seperti dapat mengakses Web-Based Framework dengan satu kali klik.  Dari sisi pengembang, Web M-EDS dapat membantu agar kode program aplikasi tidak dapat dilihat oleh pihak yang tidak bertanggung jawab
Improving Neural Network Performance with Feature Selection Using Pearson Correlation Method for Diabetes Disease Detection April Firman Daru; Mohammad Burhan Hanif; Edi Widodo
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 (759.462 KB) | DOI: 10.30595/juita.v9i1.9941

Abstract

Diabetic or silent killer diseases are an alarming scourge for the world and are classed as serious diseases. In Indonesia, the increase in diabetics occurred by 2% in vulnerable times between 2013 to 2018. This affects all sectors, both medical services and the financial sector. The Neural Network method as a data mining algorithm is present to overcome the burden that arises as an early detection analysis of the onset of disease. However, Neural Network has slow training capabilities and can identify important attributes in the data resulting in a decrease in performance. Pearson correlation is good at handling data with mixed-type attributes and is good at measuring information between attributes and attributes with labels. With this, the purpose of this study will be to use the Pearson correlation method as a selection of features to improve neural network performance in diabetes detection and measure the extent of accuracy obtained from the method. The dataset used is diabetes data 130-US hospital UCI with a record number of 101767 and the number of attributes as many as 50 attributes. The results of this study found that Pearson correlation can improve neural network accuracy performance from 94.93% to 96.00%. As for the evaluation results on the AUC value increased from 0.8077 to 0.8246. Thus Pearson's Correlation algorithm can work well for feature selection on neural network methods and can provide solutions to improved diabetes detection accuracy.
Success Information System Analysis in Dapodikdas Purbalingga Using Delone and Mclean Model Dwi Krisbiantoro; Retno Waluyo
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 (671.308 KB) | DOI: 10.30595/juita.v5i2.1638

Abstract

This study aims to analyze the relationship between the variables determining the success of information systems proposed by DeLone and McLean on the information system of DAPODIKDAS. Data collection technique used was questionnaire. Hypothesis testing used was with simple regression analysis technique. The biggest variable relation was the relationship between Service Quality variables and Intention to Use, while the biggest variable influence was the influence of Service Quality variables on Intention to Use. The smallest variable relationship was the relationship between intention to use variables against Net Benefit, while the smallest variable influence was the influence of Intention to Use variables against Net Benefit.
Sistem Pakar untuk Mengidentifikasi Jenis-Jenis Kayu Uning Lestari
JUITA : Jurnal Informatika JUITA Vol. 1 Nomor 4, Nopember 2011
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.884 KB) | DOI: 10.30595/juita.v1i4.440

Abstract

Application of expert system currently has entered most aspects of human life. The purpose of creation of expert system is adopting an expert knowledge into computer applications in order to solve the real problem that can only be resolved by experts. The process of identifying a type of wood can only be done by experts that are experienced in the identification and properties of wood. This study adopts the expert’s knowledge of identification and properties of wood in computer application that produced an expert system to identify the wood based on the physical characteristics of wood including wood general characteristics yields the color, pattern, texture, direction of the fiber, gloss, the impression of sense, violence. Wood anatomical characteristics of leaf width is includes: kinds of cells and functions, vessels, vessels of the distribution, composition, shape of vessel perforation vessel, the contents of fields (parenkima and wooden fingers), growing place and durability class. This research uses a rule-based reasoning and forward chaining inference engine. Knowledge base gained from interviews with experts the identification and properties of wood, as well as literature supporting literature. This computer application system was created by using Delphi 7.0. From the testing that has been done obtained a conclusion that the expert system application that is created is capable of identifying type of wood based on the physical properties of wood are entered by the user
Implementasi Algoritma Rabin-Karp untuk Pendeteksi Plagiarisme pada Dokumen Tugas Mahasiswa Asvarizal Filcha; Mardhiya Hayaty
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 (483.482 KB) | DOI: 10.30595/juita.v7i1.4063

Abstract

Perkembangan pada dunia teknologi informasi mengakibatkan perguruan tinggi mengurangi penggunaan kertas sehingga banyak tugas mahasiswa yang dikumpulkan dalam bentuk digital. Penggunaan digital menyebabkan semakin mudahnya mahasiswa untuk melakukan plagiarisme. Sehingga diperlukan sebuah sistem untuk melakukan pemeriksaan plagiarisme pada dokumen tugas antar mahasiswa dengan cepat dan tepat. Metode yang dapat digunakan adalah menggunakan algoritma Rabin-Karp. Algoritma Rabin-Karp memiliki keunggulan pencarian string dengan pola yang panjang. Algoritma Rabin-karp dalam sistem ini memiliki langkah - langkah text preprocessing yang terdiri case folding, tokenizing, punctuation removal, stopword removal dan stemming. Hasil dari text preprocessing inilah yang akan di proses menggunakan algoritma Rabin-karp. Hasil dari metode ini adalah nilai kemiripan dari tugas - tugas mahasiswa yang dihitung menggunakan dice coefficient. Perhitungan akurasi dengan melakukan 20 perbandingan antara sistem pendeteksi plagiarisme dan software Plagiarisme Checker X menggunakan confusion matrix menghasilkan tingkat keakuratan sebesar 90%.
Fuzzy Quantification System untuk Menganalisis Pengaruh Minat, Motivasi Belajar dan Tingkat Kehadiran Siswa terhadap Prestasi Belajar di SMA Muhammadiyah 1 Purwokerto Ridho Muktiadi; Septian Ari Wibowo; Windaru Windaru
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 (349.87 KB) | DOI: 10.30595/juita.v2i4.830

Abstract

One of benchmarks to know the capabilities a person is through grades of their studies. Grades can be affected by various factors, such as interest, motivation and attendance. This research aims to analyze the effect of interests, motivation and attendance levels on learning achievement in students of SMA Muhammadiyah 1 Purwokerto, by using Fuzzy Quantification Theory I to explains qualitative value such as interest and motivation in the form of questionnaires filled in range of value [0 1]. The results of this research shows that there are effects between indicators, that is responsive study is an indicator with the highest contribution to the achievement of study, with the presence of more than 128. Contribution value to indicator of responsive learning is 40.8885 μ [x] to the weight category at 72.2419 μ [x] that influence student achievement (final grade). And there is influence of indicator of learning motivation, which is the indicator shows the high interest that provide additional contributions on learning achievement with the highest attendance of over 129. Contributions of an indicator high interest valued 40.8404μ[x] to the weight category of 72.1938μ[x] that influence student achievement
Japanese Hiragana Handwriting Pattern Recognition Using Template Matching Correlation Method Imam Riadi; Abdul Fadlil; Putri Annisa
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 (1056.24 KB) | DOI: 10.30595/juita.v9i1.7082

Abstract

Hiragana is one of the traditional Japanese letters used to translate native Japanese words. The introduction of an object requires a learning process, which is obtained through the characteristic in the form of unique features on similar objects, but manually it is quite difficult to distinguish these letters. This writing explains the discussion system to differentiate between hiragana letters starting from preprocess namely grayscale and threshold, then segmenting and normalization, while image classification uses the Template Matching Correlation method. The results of tests carried out assessing the test rate of around 76% using the Matching Template Correlation method. While the remaining 14% indicates that the object identified does not match the intended results.

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