JUITA : Jurnal Informatika
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
<![CDATA[Prototype Model Sistem Pendukung Keputusan Berbasis Fuzzy Logic Metode Mamdani untuk Pemilihan Lulusan Terbaik di Universitas Muhammadiyah Purwokerto ]]>
<![CDATA[Feri Wibowo]]>;
<![CDATA[Dwi Aryanto]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 3 Nomor 3 Mei 2015 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v3i3.868
<![CDATA[Fakultas Teknik Universitas Muhammadiyah Purwokerto (UMP) dalam memberikan penghargaan bagi lulusan terbaik ke-1 sampai ke-3, dilaksanakan pada saat acara Yudisium berlangsung. Pengambilan keputusan untuk menentukan lulusan terbaik di nilai dengan beberapa faktor, antara lain faktor nilai IPK, lama studi mahasiswa, jumlah nilai dibawah nilai “C” dan sebagai tambahan yaitu skor TOEFL (Test of English as a Foreign Language) dan keaktifan mahasiswa. Metode yang digunakan untuk mendukung pengambilan keputusan pemilihan lulusan terbaik adalah Fuzzy Logic metode Mamdani, yang akan menghasilkan keputusan yang proporsional karena sistem yang dibangun terlebih dahulu didefinisikan sekumpulan aturan yang mengakomodir permasalahan yang ada. Setelah Prototype Model Sistem Pendukung Keputusan Berbasis Fuzzy Logic Metode Mamdani terbuat, dilakukan uji coba menggunakan data lulusan Fakultas Teknik UMP periode Oktober 2013/2014. Berdasarkan hasil uji coba dihasilkan data lulusan terbaik ke-1 sampai ke-3 dengan bobot mamdani masing-masing 66.08, 65.52, dan 65.35. Hasil uji coba tersebut dapat menjadi dasar pengambilan keputusan lulusan terbaik khususnya di Fakultas Teknik UMP menggunakan bantuan sistem pendukung keputusan berbasis fuzzy logic metode mamdani]]>
<![CDATA[Halaman Pengelola ]]>
<![CDATA[Juita Juita]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 4 Nomor 2, November 2016 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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<![CDATA[Sistem Pendukung Keputusan Penentuan Jenis Tindakan Preventif untuk Daerah dengan Kejadian Luar Biasa Penyakit di Kabupaten Banyumas ]]>
<![CDATA[Ridho Muktiadi]]>;
<![CDATA[Sri Kusumadewi]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 6 Nomor 1, Mei 2018 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v6i1.1943
<![CDATA[Kejadian Luar Biasa Penyakit atau biasa disebut KLB Penyakit, merupakan suatu kejadian munculnya penyakit atau meningkatnya jumlah penderita penyakit yang terjadi pada waktu tertentu di suatu daerah. Penanganan secara cepat diperlukan terhadap daerah yang terjangkit KLB penyakit, agar dapat menekan jumlah penderita pada daerah tersebut dan membatasi penyebaran penyakit. Penelitian ini mempunyai tujuan memberikan solusi tindakan preventif terhadap KLB penyakit dengan disertai peringatan dugaan terjadinya KLB penyakit pada suatu daerah, serta informasi lokasi daerah terjadinya KLB penyakit yang ditampilkan di dalam map. Tindakan preventif yang diberikan terhadap KLB penyakit merupakan hasil komputasi sistem yang menerapkan metode CBR (Case Based Reasoning), dimana metode tersebut merupakan metode yang menggunakan solusi dari kasus-kasus yang pernah terjadi sebelumnya untuk dicari kemiripan dengan kasus yang sedang terjadi. Terdapat empat siklus dalam metode CBR, yaitu: retrieve, reuse, revise dan retain yang telah berhasil diimplementasikan pada sistem ini dengan menggunakan bahasa pemrograman PHP untuk membantu dalam memberikan tindakan preventif terbaik terhadap KLB penyakit. Kata kunci : Preventif KLB penyakit, CBR, Peringatan KLB penyakit, Lokasi KLB penyakit]]>
<![CDATA[Rekomendasi Pembelian Televisi Menggunakan Basis Data Fuzzy Tahani ]]>
<![CDATA[Abdul Azis]]>;
<![CDATA[Hindayati Mustafidah]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 2 Nomor 1, Mei 2012 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v2i1.608
<![CDATA[By using a standard database, one can handle data that is for sure. But in fact often required the existence of handling the data is sketchy on the system database. Then to resolve the issue can be used the concept of fuzzy logic. This research will implement the concept of fuzzy logic Tahani Model into databases, or commonly called Fuzzy Database Tahani Model. That is, a data base system which can handle data that is fuzzy. The problem will be solved is the process of television recommendation that is most appropriate for users (prospective buyer television). The television recommendation is given on that has fire strength or level of conformity with the criteria of selection of numbers 0 (zero) up to the number 1 (one). The research is expected to help the prospective buyer television in determining which best suits his criteria]]>
<![CDATA[Application Design for Food and Beverage Online Delivery System Based of Android Framework ]]>
<![CDATA[Abdul Manan]]>;
<![CDATA[Victor Wiley]]>;
<![CDATA[Thomas Lucas]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA VoL. 7 Nomor 2, November 2019 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v7i2.5645
<![CDATA[Providing good services and satisfaction to customer is main concern on online business. As technology is developed rapidly, many online restaurants has sought user-friendly platform to serve their customer. The purpose of this research is to build an Android-based online order application for online delivery restaurant. We added features of outlets distribution and product promos. We also developed a more user-friendly interface as new design. Through Waterfall development method, we design the application which based of android APP Inventor framework. Based on the assessment result of four aspect (e.g., software engineering defect, learning design, visual communication), we got average scores of 2.45, 3.40, 3.35 and 3.07. The assessment results showed that our application design is eligible to be implemented for real situation with fairly eligible score. It is recommended that the application is implemented with partial improvement especially on the software engineering debugging to get a more decent score.]]>
<![CDATA[Analisis Perbandingan Penggunaan Fungsi Random Mysql dan Fungsi Random Java Class Library pada Aplikasi CBT ]]>
<![CDATA[Achmad Fauzan]]>;
<![CDATA[Tito Pinandita]]>;
<![CDATA[Harjono Harjono]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 3 Nomor 2, Nopember 2014 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v3i2.859
<![CDATA[Computer Based Test (CBT) merupakan suatu aplikasi yang digunakan dalam penyelenggaraan ujian berbasis computer dengan kelebihan dapat menyajikan pertanyaan dan pilihan jawaban secara acak sehingga menghindari kemungkinan terjadinya kecurangan yang dilakukan oleh peserta ujian. Penelitian ini melakukan pengujian fungsi random terhadap aplikasi CBT berbasis Java dan database server MySQL dengan objek perbandingan yaitu fungsi random MySQL dan fungsi random Java Class Library. Variabel yang digunakan dalam penelitian yaitu waktu akses pertanyaan dan kombinasi pertanyaan dan pilihan jawaban yang sama. Pengujian dilakukan dengan cara memodelkan fasilitas yang menampilkan halaman pertanyaan dan pilihan jawaban untuk mengetahui waktu akses munculnya pertanyaan dan kombinasi yang dihasilkan. Hasil perhitungan diuji melalui pengujian kesamaan rata-rata untuk mengetahui perbedaannya. Setelah dilakukan pengujian, diketahui bahwa terdapat perbedaan pada waktu akses pertanyaan menggunakan fungsi random MySQL dengan fungsi random Java Class Library. Rata-rata waktu akses pertanyaan dengan fungsi random MySQL sebesar 41650473.6250 nanosecond adalah lebih lama dibandingkan rata-rata waktu akses pertanyaan dengan fungsi random Java Class Library sebesar 35905823.7431 nanosecond. Namun kombinasi pertanyaan dan pilihan jawaban yang sama pada pertanyaan dengan fungsi random MySQL sebesar 63.6% adalah lebih kecil dibandingkan dengan penggunaan fungsi random Java Class Library yang mencapai persentase sebesar 65.1%.]]>
<![CDATA[Data Mining for Potential Customer Segmentation in the Marketing Bank Dataset ]]>
<![CDATA[Maulida Ayu Fitriani]]>;
<![CDATA[Dany Candra Febrianto]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 9 No. 1, May 2021 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v9i1.7983
<![CDATA[Direct marketing is an effort made by the Bank to increase sales of its products and services, but the Bank sometimes has to contact a customer or prospective customer more than once to ascertain whether the customer or prospective customer is willing to subscribe to a product or service. To overcome this ineffective process several data mining methods are proposed. This study compares several data mining methods such as Naïve Bayes, K-NN, Random Forest, SVM, J48, AdaBoost J48 which prior to classification the SMOTE pre-processing technique was done in order to eliminate the class imbalance problem in the Bank Marketing dataset instance. The SMOTE + Random Forest method in this study produced the highest accuracy value of 92.61%.]]>
<![CDATA[The Empirical Comparison of Machine Learning Algorithm for the Class Imbalanced Problem in Conformational Epitope Prediction ]]>
<![CDATA[Binti Solihah]]>;
<![CDATA[Azhari Azhari]]>;
<![CDATA[Aina Musdholifah]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 9 No. 1, May 2021 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v9i1.9969
<![CDATA[A conformational epitope is a part of a protein-based vaccine. It is challenging to identify using an experiment. A computational model is developed to support identification. However, the imbalance class is one of the constraints to achieving optimal performance on the conformational epitope B cell prediction. In this paper, we compare several conformational epitope B cell prediction models from non-ensemble and ensemble approaches. A sampling method from Random undersampling, SMOTE, and cluster-based undersampling is combined with a decision tree or SVM to build a non-ensemble model. A random forest model and several variants of the bagging method is used to construct the ensemble model. A 10-fold cross-validation method is used to validate the model. The experiment results show that the combination of the cluster-based under-sampling and decision tree outperformed the other sampling method when combined with the non-ensemble and the ensemble method. This study provides a baseline to improve existing models for dealing with the class imbalance in the conformational epitope prediction.]]>
<![CDATA[Implementasi Metode MADM Model Yager untuk Seleksi Penerima Beasiswa PPA ]]>
<![CDATA[Muhammad Nurtanzis Sutoyo]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 5 Nomor 2, November 2017 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v5i2.1630
<![CDATA[Setiap peserta didik pada setiap satuan pendidikan berhak mendapatkan beasiswa bagi yang berprestasi yang orang tuanya tidak mampu membiayai pendidikannya. Salah satunya adalah Beasiswa Peningkatan Prestasi Akademik (Beasiswa-PPA). MADM adalah suatu metode yang digunakan untuk mencari alternatif optimal dari sejumlah alternatif dengan kriteria tertentu. Salah satu metode MADM adalah Model Yager. Berdasarkan hasil penelitian dan pembahasan bahwa metode MADM Model Yager dapat menyeleksi calon penerima Beasiswa-PPA]]>
<![CDATA[Diagnosa Penyakit Ikan Menggunakan Sistem Pakar ]]>
<![CDATA[Suwarsito Suwarsito]]>;
<![CDATA[Hindayati Mustafidah]]>
<![CDATA[ JUITA : Jurnal Informatika JUITA Vol. 1 Nomor 4, Nopember 2011 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v1i4.441
<![CDATA[Background from this research is too much of disease case groaning fish in Indonesia. Most farmers feel to confuse to look for various possible solutions. Reading of reference books and or visit upon the expert of fish disease likely not possible because that too much need time and energy and also expense, whereas fish which is being come down have to be immediately handled. According to the mentioned, this research develops an expert system which can be a consultant that capable to diagnose in fish disease cause and can give an advice to overcome the disease. This Expert system is called FISHEXP. This research is a development study, whichoperationally steps are: knowledge acquisition, knowledge representation using backward chaining, making shell in a computer program using Borland C++ programming language, and system examination.FISHEXP developed for 6 forms composed by 1 main form and 5 child forms for consultancy, adding rules, displaying rules on computer monitor, showing what that system FISHEXP is, and give the explanation of how to operate it. There are 3 main menus in FISHEXP that represent a user interface between user and the system. Among the menus, Consultancy is the prime menu cause shows the work of the FISHEXP system]]>
