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All Journal Telematika Sistemasi: Jurnal Sistem Informasi Jurnal Informatika Indonesian Journal on Software Engineering (IJSE) Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Komputasi Jurnal Techno Nusa Mandiri JATI (Jurnal Mahasiswa Teknik Informatika) Infotech: Jurnal Informatika & Teknologi Jurnal PkM (Pengabdian kepada Masyarakat) Reputasi: Jurnal Rekayasa Perangkat Lunak SPEED - Sentra Penelitian Engineering dan Edukasi JUSTIN (Jurnal Sistem dan Teknologi Informasi)

Siti Khotimatul Wildah

Universitas Bina Sarana Informatika

Author-ID : 2545817

Arts Humanities 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

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DETEKSI PENYAKIT ALZHEIMER MENGGUNAKAN ALGORITMA NAÃVE BAYES DAN CORRELATION BASED FEATURE SELECTION Wildah, Siti Khotimatul; Agustiani, Sarifah; S, M. Rangga Ramadhan; Gata, Windu; Nawawi, Hendri Mahmud
Jurnal Informatika Vol 7, No 2 (2020): September 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Alzheimer merupakan kelainan berupa penimbunan plak atau protein tidak normal dalam otak sehingga menyebabkan hilangnya sel neuron dan menjadi salah satu pemicu penyakit demensia yang dapat mengakibatkan terhambatnya aktivitas sehari-hari karena penurunan daya ingat,kesulitan dalam berkomunikasi, tidak dapat berpikir jernih, terjadinya perubahan sikap dan perilaku hingga menimbulkan hilangnya kemampuan untuk mengurus diri sendiri. Di negara berpenghasilan tinggi penyakit ini diakui berada pada peringkat ke 7 sebagai penyakit fatal yang berujung pada kematian. Akan tetapi hingga saat ini belum ditemukan obat yang dapat menyembuhkan penyakit Alzheimer. Oleh sebab itu pentingnya deteksi dini agar dapat memulai untuk merencanakan perawatan dan kebutuhan medis yang memadai. Penelitian ini bertujuan untuk melakukan deteksi penyakit Alzheimer dengan menerapkan metode klasifikasi NaÃ¯ve Bayes dan seleksi atribut menggunakan Correlation Based Feature Selection pada dataset OASIS Longitudinal. Tahapan analisa data menggunakan metode CRISP-DM. Hasil penelitian ini, menunjukan bahwa pada pengujian algoritma NaÃ¯ve Bayes nilai akurasi yang didapatkan sebesar 93,83%, dan kurva ROC yang terbentuk memiliki nilai AUC sebesar 0,937% sedangkan pada pengujian algoritma NaÃ¯ve Bayes dan Correlation Based Feature Selection menghasilkan nilai akurasi sebesar 94,64% dan kurva ROC yang terbentuk memiliki nilai AUC sebesar 0,945%. Sehingga dapat disimpulkan bahwa penerapan algoritma NaÃ¯ve Bayes dan metode Correlation Based Feature Selection dapat meningkatkan nilai akurasi.

Sistem Pendukung Keputusan Pemilihan Tempat Usaha Potensial dengan Metode SAW (Studi Kasus : SahabatLink Tasikmalaya) Hendri Mahmud Nawawi; Yudhistira Yudhistira; Ali Mustopa; Siti Khotimatul Wildah; Sarifah Agustiani; Muhammad Iqbal
Indonesian Journal on Software Engineering (IJSE) Vol 7, No 1 (2021): IJSE 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v7i1.9990

Memutuskan tempat untuk membuka usaha adalah hal yang sangat penting dan wajib diperhatikan saat akan memulai bisnis baru atau membuka cabang, sejumlah faktor penting diperhitungkan supaya dapat meminimalisir resiko kerugian di masa yang akan datang sehingga tujuan dari bisnis yaitu meningkatkan keuntungan bisa dicapai secara maksimal, pada penelitian ini sejumlah faktor dicatat dan dijadikan sebagai kriteria untuk menilai tempat usaha yang layak dan potensial berdasarkan hasil observasi dan pengamatan di lapangan pada tempat usaha dengan merk dagang SahabatLink dengan menggunakan metode Simple Additive Weight. Konsep metode SAW adalah mencari penjumlahan terbobot berdasarkan rating kinerja dari setiap alternatif yang ditambahkan dengan banyak kriteria. Hal ini yang menjadikan metode ini tepat digunakan untuk menentukan keputusan memilih tempat usaha potensial dengan banyak kriteria diantaranya akses, visibilitas, lalu lintas, persaingan, jarak ke tempat keramaian, tempat parkir, biaya sewa, ekspansi dan konduktivitas. Hasil akhir dari penjumlahan kriteria inputan dengan metode SAW dapat menjadi rekomendasi bagi pihak manajemen untuk membuka tempat usaha berdasarkan nilai alternatif yang paling tinggi.

Penerapan Metode Pembelajaran Menggunakan Ekstraksi Fitur dan Algoritma Klasifikasi untuk Identifikasi Pengenalan Iris Rahmat Hidayat; Sarifah Agustiani; Siti Khotimatul Wildah; Ali Mustopa; Rizky Ade Safitri
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 7, No 2 (2021): JTK-Periode Juli 2021
Publisher : Universitas Bina Sarana Informatika

Iris mata terletak di antara kornea mata dan lensa mata, yang berfungsi untuk mengontrol intensitas atau jumlah cahaya yang masuk dengan cara melebarkan dan mengecilkan pupil. Setiap orang memiliki iris yang berbeda dan memiliki stabilitas sepanjang hidup, kecuali terjadi kerusakan yang tidak disengaja pada iris seperti terjadi kecelakaan. Tujuan dari penelitian ini adalah untuk melakukan pengklasifikasian dan identifikasi pengenalan citra iris dengan menggunakan metode pembelajaran atau machine learning. Metode yang diusulkan dalam penelitian ini adalah penerapan ekstraksi fitur seperti HOG, Hu-Moments, dan Haralick dengan algoritma klasifikasi yang terdiri dari LR, LDA, KNN, RF, CART, NB, dan SVM. Berdasarkan hasil pengujian yang telah dilakukan dalam mengklasifikasikan iris dapat disimpulkan bahwa penggunaan ekstraksi fitur sangat berpengaruh pada nilai akurasi yang dihasilkan. Dalam hal ini nilai akurasi terbaik diperoleh dari penggabungan ekstraksi fitur HOG dan haralick pada algoritma Random Forest dengan nilai akurasi sebesar 81.38℅.

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

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

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.

Klasifikasi Penyakit Daun Padi menggunakan Random Forest dan Color Histogram Sarifah Agustiani; Yoseph Tajul Arifin; Agus Junaidi; Siti Khotimatul Wildah; Ali Mustopa
Jurnal Komputasi Vol 10, No 1 (2022)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v10i1.2961

Indonesia is an agrarian country, which is a sector that plays an important role most of the Indonesian population makes agriculture the main focus, but the function of rice fields into housing or industry has resulted in a decrease in rice production, in addition to pests, diseases, unfavorable weather, Irrigation is not smooth resulting in less than the maximum yield. For this reason, it is necessary to have technology that can implement the process of detecting rice leaf disease in order to provide information to farmers about rice leaf damage. The most modern approach today can be done with machine learning or deep learning by using various algorithms to improve recognition and accuracy in the detection and diagnosis of plant diseases. Based on this, this study aims to propose a method of classifying rice leaf diseases in order to provide information to farmers about rice leaves which are expected to reduce the disease by detecting the disease early so as to increase rice production. In this study, the classification process is carried out using the augmented image, then the Color Histogram feature extraction method is applied, and the classification is carried out using the Random Forest algorithm. In addition, this study also conducted several comparisons, including feature extraction and yahoo to get the results, and the highest results reached 99.65% of the proposed method.

Feature Extraction With Forest Classifer To Predicate Covid 19 Based On Thorax X-Ray Results Ali Mustopa; Hendri Mahmud Nawawi; Sarifah Agustiani; Siti Khotimatul Wildah
Sistemasi: Jurnal Sistem Informasi Vol 11, No 2 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Coronavirus 19 (COVID-19) is a highly contagious infection caused by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a new virus for which no cure has been found, marked by the increasing death rate worldwide. Coronavirus disease which can cause pneumonia which attacks the air sacs of the lungs with symptoms of dry cough, sore throat to acute respiratory distress (ARDS) that occurs in COVID-19 patients. One of the ways to detect the virus is by detecting chest X-rays in the patient. Over the past decade's mechine learning technology has developed rapidly and is integrated into CAD systems to provide accurate accuracy. This research was conducted by detecting thoracic radiographs using feature extraction Hu-Moments, Harralic and Histogram and detecting the best accuracy with a classification algorithm to detect the results of COVID-19. The study was conducted by testing the dataset obtained from the Kaggle repository which has images, namely 1281 X-rays of COVID-19, 3270 X-rays Normal, 1656 X-rays of pneumonia, and X-rays of bacteria-pneumonia 3001. In general, this research is included in the Good category because it produces the highest accuracy by the Random forest classification algorithm where the accuracy result is 84% and the standard deviation is 0.015847. In addition, the research also produced Kappa of 0.713. The results of this accuracy are carried out in several stages, namely by feature extraction in the form of hu-moments, Harralic and histogram. In this study, the best results were given by the Random forest algorithm with feature extraction Histogram and Hu-Moment.

PERBAIKAN CITRA OBJEK BAWAH AIR DENGAN MENGGUNAKAN METODE IMPLEMENTASI WHITE BALANCING DENGAN MODEL GREY WORLD (WBGW) Suharyanto .; Siti Khotimatul Wildah; Sandra Jamu Kuryanti - Universitas BSI
SPEED - Sentra Penelitian Engineering dan Edukasi Vol 14, No 3 (2022): Speed Juli 2022
Publisher : APMMI - Asosiasi Profesi Multimedia Indonwsia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55181/speed.v14i3.770

Abstrak: Citra objek bawah air memiliki kualitas citra yang gelap dan kurang baik dikarenakan kedalaman dari sebuah objek citra yang diambil. faktor pencahayaan memiliki peranan penting dari sebuah kualitas citra yang diambil. Perbaikan citra objek bawah air nantinya digunakan sebagai pengawasan lingkungan bawah air maupun pencarian objek-objek yang berada di dasar laut. Penelitian ini bertujuan untuk memperbaiki kualitas citra objek bawah air dengan menggunakan pemrosesan citra dan menerapkan penyeimbang warna putih menggunakan metode white balancing dengan model grey world (WBGW). Hasil penelitian dievaluasi dengan menggunakan fitur Root Mean Squared Error (RMSE) dimana hasil yang diberikan cukup siginificant dengan meningkatnya keypoint yang didapatkan dari sebuah citra.Kata Kunci: Perbaikan Kualitas Citra, Citra Bawah Air, Image Processing, White Balance, Gray World. Abstract: The image of underwater objects has a dark and poor image quality due to the depth of the object image taken. The lighting factor has an important role in the quality of the image taken. Image improvement of underwater objects will be used for monitoring the underwater environment as well as searching for objects on the seabed. This study aims to improve the image quality of underwater objects by using image processing and applying white balance using the white balancing method with the gray world (WBGW) model. The results of the study were evaluated by using the Root Mean Squared Error (RMSE) feature where the results given were quite significant with increasing keypoints obtained from an image.Keywords: Image Enhancement, Underwater Image, Image Processing, White Balance, Gray World.

IMPLEMENTATION OF THE RIJNDAEL ALGORITHM ON WEB-BASED WHISTLEBLOWING SYSTEM Abdul Latif; Ai Ilah Warnilah; Siti Khotimatul Wildah
Techno Nusa Mandiri Vol 19 No 2 (2022): TECHNO Period of September 2022
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v19i2.3861

In carrying out its responsibilities, an employee works for an agency or company and also works with his colleagues, whether they are co-workers or their own superiors. So it is very important for an employee to gain trust in his work environment. If there is a violation or behavior that deviates from an employee in the work environment, then there must be someone who reports it but of course by protecting the identity of the reporter. Based on these problems, the authors make and design a web-based whistle blowing application to protect the identity of people who report violations that occur in their work environment. This whistle blowing web is created using cryptographic algorithm methods. Cryptographic algorithms work by disguising data or information into a form of password that has no meaning. The author uses the Rijndael algorithm to encrypt the complainant's data. So that by using the Rijndael algorithm on this web-based Whistleblowing system, the data or reporting information will be safe in the database and it is hoped that an optimal system will be created for data and information security

VISUALISASI KETERSEDIAAN JADWAL PADA WEBSITE SISTEM RESERVASI FOTOGRAFI: STUDI KASUS: FIDZPHOTOGRAPHY SUKABUMI Siti Khotimatul Wildah; Rusda Wajhillah; Abdul Latif; Sarifah Agustiani; Ali Mustopa
JATI (Jurnal Mahasiswa Teknik Informatika) Vol 7 No 1 (2023): JATI Vol. 7 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v7i1.6073

Fidzphotography merupakan jasa penyedia fotografi untuk berbagai acara seperti pernikahan, ulang tahun, lamaran, prewedding maupun acara lainnya. Sistem reservasi fotografi pada Fidzphotography dilakukan secara online melalui Whatsapp, Line maupun Instagram atau dengan mendatangi langsung kantor tempat beroperasi. Sistem yang berjalan memiliki sedikit kekurangan karena data reservasi yang kurang terorganisir karena pencatatan masih dilakukan secara konvensional dan belum adanya sistem yang dapat memfasilitasi rekap data tersebut secara menyeluruh. Permasalahan lain yang timbul adalah kurangnya informasi mengenai ketersediaan jadwal dimana pelanggan diharuskan konfirmasi terlebih dahulu kepada pihak Fidzphotography apabila ingin melakukan reservasi. Berdasarkan permasalahan tersebut dibuatlah sebuah website yang bertujuan sebagai tempat pengelolaan reservasi dimana jadwal reservasi ditampilkan secara visual agar lebih memudahkan pelanggan dalam mendapatkan informasi mengenai ketersediaan jadwal maupun kemudahan dalam pemilihan tanggal reservasi tanpa perlu melakukan konfirmasi terlebih dahulu. Pembuatan website menggunakan metode waterfall dikarenakan metode ini memiliki konsep yang terstruktur dan terorganisir sehingga proses pembuatan website dapat dilakukan dengan penjadwalan yang jelas. Website sistem reservasi fotografi ini dilengkapi dengan notifikasi pesan SMS setelah melakukan pemesanan dan juga memudahkan pemilik jasa fotografi dalam mengelola laporan pemesanan

Co-Authors Abdul Latif Abdul Latif Abdul Latif Agung Sasongko Agus Junaidi Agustiani, Sarifah Ahmad Al Kaafi Ali Mustopa, Ali Andi Saryoko Ari Abdilah Ganda Wijaya Gata, Windu Hendri Mahmud Nawawi Ikrom Mauludin Salam Laksono Trisnantoro Maysaroh, Maysaroh Muhammad Sony Maulana Nanik Wuryani Nawawi, Hendri Mahmud Pribadi, Denny Rahmat Hidayat Rizky Ade Safitri Rusda Wajhillah S, M. Rangga Ramadhan Sandra Jamu Kuryanti - Universitas BSI Sanggayasa Sanggayasa Sopiyan Dalis Suharyanto . Suharyanto Suharyanto Suparni Suparni Warnilah, Ai Illah Windu Gata Windu Gata Yoseph Tajul Arifin Yudhistira Yudhistira

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