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All Journal Telematika Sistemasi: Jurnal Sistem Informasi Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Komputasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Manajemen Informatika dan Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Infortech Infotech: Jurnal Informatika & Teknologi Reputasi: Jurnal Rekayasa Perangkat Lunak JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Penelitian dan Pengabdian Masyarakat Jotika
Ali Mustopa, Ali
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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Journal : Paradigma

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Pengaruh Media Terhadap Pengambilan Keputusan Dalam Menjalankan Program Keluarga Berencana Dengan Algoritma Decision Tree Ali Mustopa; Siti Khotimatul Wildah; Ganda Wijaya; Windu Gata; Sarifah Agustiani
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (64.58 KB) | DOI: 10.31294/p.v22i2.8141

Abstract

Indonesia has become one of the countries with a diverse population so that it has the potential to experience social change, one of which is the influence of the media. Media is an information content that is almost a part of human life. One of the impacts of the media is in the health sector, one of which is in determining the Family Planning program. Family planning is one of the Indonesian government programs designed to reduce the speed of population growth. Since the implementation of the Family Planning Program in Indonesia many tools have been used to prevent pregnancy, namely contraception. Selection of a good contraction is certainly one important thing to plan. In determining good kotrasespi certainly there are influences from various things one of which is the media. Measurement of the influence of the media in determining the Family Planning program can be known by applying data mining. Research conducted with data mining uses a standard methodology called the Cross-Industry Center Process for Data Mining (CRISP-DM). The use of decissin tree in this study was done by comparing the same method by looking at the results of three models namely Split Validation, Cross Validation and Decision Tree Split. The results of Split Validation produce an accuracy of 90.50%, Cross Validation produces an accuracy of 91.58% and Decision Tree Split produces an accuracy of 89.83%. The best results are obtained by using cross validation where with the results of research on 1473 records the accuracy value is 91.58% and the AUC value is 0.690, where the results are obtained from the calculation of the True Positive (TP) 1328, False Negative (FN) ) 36, False Positive (FP) is 88 and True Negative (TN) 21. Exposure to the media is said to be good or influential if they do not have children and are Muslim and educate their husbands in junior high school with a low standard of living but the wife has a college education.  Keywords: Family Planning, Media Exposure, Data Mining, Decision Tree.
PENERAPAN ALGORITMA J48 UNTUK DETEKSI PENYAKIT TIROID Sarifah Agustiani; Ali Mustopa; Andi Saryoko; Windu Gata; Siti Khotimatul Wildah
Paradigma Vol 22, No 2 (2020): Periode September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1113.664 KB) | DOI: 10.31294/p.v22i2.8174

Abstract

Impaired thyroid function is often difficult to identify because the symptoms are not specific. The symptoms of thyroid disorder are very similar to various complaints due to modern lifestyles so it is often overlooked. As a result, patients often do not notice a problem and do not have to consult a doctor. Therefore, there is a study that implements methods to predict the disease which will facilitate the patient in diagnosing and early detection of thyroid levels. This research aims to predict against thyroid disease with the data used is the secondary data obtained from the UCI repository, this data is about the patient data affected by thyroid disease, while the method uses the J48 algorithm because in some studies, the J48 algorithm is proven to have good performance in detecting an illness, as well as producing high value of Accuasy and AUC. The stage of data analysis is based on the CRISP-DM method while algorithm testing is done with Weka tools. Results of the test obtained an accuracy value of 99.645%, and a AUC value of 0.992 thus the accuracy has Excellent Classification level.
Co-Authors Abdul Hamid Abdul Latif Abdul Latif Abdul Latif Agung Sasongko Agus Junaidi Agustiani, Sarifah Ahmad Fachrurozi Andi Saryoko Antonius Yadi Kuntoro Desyandri Desyandri Ganda Wijaya Hendri Mahmud Nawawi Hermanto Hermanto Lady Agustin Fitriana Laksono Trisnantoro M Rangga Ramadhan Saelan Maysaroh, Maysaroh Mochammad Abdul Azis Muhammad Fahmi Julianto Muhammad Iqbal Muhammad Iqbal Muhammad Rezki Muhammad Rifqi Firdaus Muhammad Sony Maulana Nanik Wuryani Nuraeni Herlinawati Pribadi, Denny Rabiatus Sa’adah Rahmat Hidayat Rangga Sanjaya Risdiansyah, Deni Rizka Dahlia Rizky Ade Safitri Rusda Wajhillah Siti Khotimatul Wildah Sopiyan Dalis Suharyanto Suharyanto Umi Khultsum Wahyu Nugraha Wahyutama Fitri Hidayat Windu Gata Windu Gata Yoseph Tajul Arifin Yudhistira Yudhistira Yudhistira