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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi JOIN (Jurnal Online Informatika) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Weny Mistarika Rahmawati
Politeknik Elektronika Negeri Surabaya
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Nursing Public Health Social Sciences Other

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Journal : INTEGER: Journal of Information Technology

 1 
Implementing Hidden Markov Model to Predict Foreign Exchange Movement Himawan, Tri Swasono; Indriyani, Tutuk; Rahmawati, Weny Mistarika
INTEGER: Journal of Information Technology Vol 3, No 1 (2018): Maret
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (356.096 KB) | DOI: 10.31284/j.integer.2018.v3i1.140

Abstract

Investment refers to personal bussiness. So many people have got profit from investment both real and non real sectors. Foreign Exchange (FOREX) is the example of non real sector. The currency fluctuation of FOREX usually occurs and this causes many investors fooled by the pattern of currency fluctuation. Finally, they get lost and even lost capital. Hidden Markov Model was implemented in this research to predict the movement of FOREX of 8 currencies. The data were trained by Baum-Welch algorithm and predicted by Forward algorithm. The trial obtained the average MAPE (Mean Absolute Precentage Error) of 8 currencies which was relatively small (0.0038082% belongs to high and 0.0040706% belongs to low), less than 1%. The currency of USD/IDR has the smallest error score among the other tested currencies. Its average MAPE was 0.0032624% and the average deviation was 42. Thus, this system is well proven to predict the movement of currency.
Meningkatkan Akurasi Perkiraan Waktu Proyek Perangkat Lunak Dalam COCOMO II Dengan Mengubah Nilai Parameter Putri, Rahmi Rizkiana; Rahmawati, Weny Mistarika
INTEGER: Journal of Information Technology Vol 4, No 1 (2019): May
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (225.243 KB) | DOI: 10.31284/j.integer.2019.v4i1.485

Abstract

Good management of software projects can be obtained through accurate time estimates. When estimating less accurate time it will affect the lack of effective management of the software project and the entire process during project development. Barry Boehm, an inventor of COCOMO, has developed the COCOMO 1 cost driver that has an effect on the accuracy of the estimated time results. But if you only use the COCOMO II cost driver, it is still far from the accuracy of the desired results. Therefore it is necessary to change the values of parameters C and D for estimated time. Changes in parameter values are done by decreasing the initial gradation by 0,1 so that the approximate results become more optimal and close to the original values. Based on the implementation of the proposed method, the results show that the error decreases to% when compared to using only the COCOMO I and COCOMO II cost drivers without changing parameter values. So that the accuracy of the estimated project time can increase.
Meningkatkan Akurasi Perkiraan Waktu Proyek Perangkat Lunak Dalam COCOMO II Dengan Mengubah Nilai Parameter Rahmi Rizkiana Putri; Weny Mistarika Rahmawati
INTEGER: Journal of Information Technology Vol 4, No 1: May 2019
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2019.v4i1.485

Abstract

Good management of software projects can be obtained through accurate time estimates. When estimating less accurate time it will affect the lack of effective management of the software project and the entire process during project development. Barry Boehm, an inventor of COCOMO, has developed the COCOMO 1 cost driver that has an effect on the accuracy of the estimated time results. But if you only use the COCOMO II cost driver, it is still far from the accuracy of the desired results. Therefore it is necessary to change the values of parameters C and D for estimated time. Changes in parameter values are done by decreasing the initial gradation by 0,1 so that the approximate results become more optimal and close to the original values. Based on the implementation of the proposed method, the results show that the error decreases to% when compared to using only the COCOMO I and COCOMO II cost drivers without changing parameter values. So that the accuracy of the estimated project time can increase.
Implementing Hidden Markov Model to Predict Foreign Exchange Movement Tri Swasono Himawan; Tutuk Indriyani; Weny Mistarika Rahmawati
INTEGER: Journal of Information Technology Vol 3, No 1 (2018)
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2018.v3i1.140

Abstract

Investment refers to personal bussiness. So many people have got profit from investment both real and non real sectors. Foreign Exchange (FOREX) is the example of non real sector. The currency fluctuation of FOREX usually occurs and this causes many investors fooled by the pattern of currency fluctuation. Finally, they get lost and even lost capital. Hidden Markov Model was implemented in this research to predict the movement of FOREX of 8 currencies. The data were trained by Baum-Welch algorithm and predicted by Forward algorithm. The trial obtained the average MAPE (Mean Absolute Precentage Error) of 8 currencies which was relatively small (0.0038082% belongs to high and 0.0040706% belongs to low), less than 1%. The currency of USD/IDR has the smallest error score among the other tested currencies. Its average MAPE was 0.0032624% and the average deviation was 42. Thus, this system is well proven to predict the movement of currency.
Deteksi PCOS pada Wanita Menggunakan Explanatory Data Analysis (EDA) dan Support Vector Machine (SVM) Rahmawati, Weny Mistarika; Edelani, Renovita
INTEGER: Journal of Information Technology Vol 10, No 1 (2025): April
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2024.v10i1.7595

Abstract

Polycistic Ovarium Syndrom (PCOS) merupakan gangguan hormonal yang terjadi pada Wanita usia produktif dan bisa mengakibatkan infertilitas. PCOS sendiri belum diketahui penyebab pastinya tetapi factor genetic dan pola hidup merupakan factor yang dapat memengaruhi seorang Wanita terkena PCOS. Penelitian ini bertujuan melakukan deteksi PCOS berdasarkan data yang terdiri dari umur, indeks masa tubuh, level testosterone serta jumlah folikel. Data awal yang didapat memiliki distribusi yang tidak baik atau bisa dikatakan tidak seimbang. Peneliti melakukan Explanatory Data Analysis (EDA) pada tahap awal dengan membuat scatterplot untuk mencari korelasi setiap fitur dengan kelas target. Hasilnya ada fitur keteraturan haid yang nilai kealpaannya sangat mempengaruhi deteksi PCOS sehingga dilakukan penghapusan data  pada nilai null pada fitur tersebut. Setelah itu dilakukan klasifikasi Support Vector Machine (SVM) untuk memisahkan kelas terdiagnosa PCOS atau tidak. Beberapa kernel SVM diujikan untuk mengetahui hasil terbaik yang bisa dihasilkan. Evaluasi dilakukan dengan menghitung akurasi, precision, recall dan f1-score pada confussion matrix yang terbentuk. Hasil dari penelitian menunjukkan bawa kernel polynomial memberikan hasil klasifikasi terbaik dengan akurasi sebesar 89,62%, precision 81,08%, recall 88,23% dan f1-score 84,5%. Penelitian ini mengonfirmasi bahwa kombinasi EDA dan SVM dapat digunakan sebagai pendekatan yang efektif dalam mendukung deteksi PCOS.
Co-Authors Adi, Agung Prasetya Ahsan, Ahmad Syauqi Andre Yuldian Afandi Aprilia, Aries Aries Aprilia Asmara, Rengga Azhara, Khanza Fadila Desy Intan Permatasari, Desy Intan Deviana, Jesica Ayu Dian Septiani Santoso Dwi Putra Marbun Edelani, Renovita Entin Martiana Kusumaningtyas Febri Liantoni Febri Liantoni, Febri Gusti Eka Yuliastuti Haqiki, Nour Himawan, Tri Swasono Kaisul Fuqara Dewanda Leksana, Bayu Hadi Maftahatul Hakimah Maftahatul Hakimah, Maftahatul Matthew Dailey Mu'arifin Mubtada’i, Nur Rosyid Muhaimin, Rizal Muhammad Teguh Septiyan Nour Haqiki Nour Haqiki Putri, Rahmi Rizkiana Rahmi Rizkiana Putri Septiyawan Rosetya Septiyawan Rosetya Wardhana Septiyawan Rosetya Wardhana Setyorini, Fitri Tri Swasono Himawan Tukadi Tukadi, Tukadi Tutuk Indriyani Yuliana Setiowati, Yuliana