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All Journal Media Statistika Jurnal Sains dan Seni ITS Epsilon: Jurnal Matematika Murni dan Terapan TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Chemical Reaction Engineering & Catalysis Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) BAREKENG: Jurnal Ilmu Matematika dan Terapan Inferensi Journal of Applied Sciences, Management and Engineering Technology (JASMET) Proceeding ISETH (International Summit on Science, Technology, and Humanity) Sewagati Journal of Research on Community Engagement

Santi Wulan Purnami

Department Of Statistic, Faculty Of Science And Analytical Data, Institut Teknologi Sepuluh Nopember, Surabaya

Author-ID : 349299

Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 32 Documents Claim Missing Document

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Articles

Title

Model Evaluation for Logistic Regression and Support Vector Machines in Diabetes Problem Baiq Siska Febriani Astuti; Neni Alya Firdausanti; Santi Wulan Purnami
Inferensi Vol 1, No 2 (2018): Inferensi
Publisher : Department of Statistics ITS

Machine learning is a method or computational algorithm to solve problems based on data that already available from the database. Classification is one of the important methods of supervised learning in machine learning. Support Vector Machine and Logistic Regression are some supervised learning methods that can be used both for classification and regression. In datamining process, Preprocessing is an important part before doing further analysis. In preprocessing data, feature selection and deviding training and testing data are important part of preprocessing data. In this research will be compared some evaluation model of deviding method for training and testing data, namely Random Repeated Holdout, Stratified Repeated Holdout, Random Cross-Validation, and Startified Cross-Validation. Evaluation model would be implying in logistic regression and Support Vector Machines (SVMs). From the analysis, can be concluded that by selecting features can improve the accuracy of classification with logistic regression, but opposite of Support Vector Machines (SVMs). For training and testing data pertition method can not be sure what method is better, because each method of partition training and testing data using the concept of random selection. Model evaluation cannot sure influence to increase best perform for SVMs model in particular this case.

Indeks Prognostik Pada Pasien Kanker Serviks di RSUD dr. Soetomo Surabaya Menggunakan Model Regresi Cox Extended Nur Arifiyani; Santi Wulan Purnami
Inferensi Vol 3, No 1 (2020): Inferensi
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v3i1.6880

Saat ini masalah yang rentan dihadapi oleh wanita adalah timbulnya sel kanker dalam tubuh. Tak lain adalah kanker leher Rahim atau biasa disebut kanker serviks. Kanker serviks merupakan kanker yang disebabkan oleh infeksi virus HPV (Human Papillomavirus). Virus tersebut menyerang dalam tubuh wanita dikarenakan beberapa factor. Peningkatan kejadian kanker serviks semakin bertambah namun diagnosis dini atau inisiasi melakukan pengobatan kurang diperhatikan oleh masyarakat, sehingga berpengaruh pada prognosis buruk pasien kanker serviks. Dalam penelitian ini digunakan metode regresi Cox Extended untuk mengetahui prognosis pasien dimasa datang yang disebut prognostik indeks. Hasil penelitian menunjukkan model yang signifikan terhadap ketahanan hidup pasien kanker serviks dengan metode regresi Cox Extended adalah variabel jenis pengobatan lainnya atau pasien kanker serviks tidak melakukan pengobatan kemoterapi, operasi, tranfusi PRC, dan kombinasi antar ketiga jenis pengobatan tersebut. Prognosis pasien yang tidak melakukan jenis pengobatan tersebut memiliki resiko terjadinya meninggal sangat tinggi dibandingkan pasien yang melakukan kemoterapi, operasi, tranfusi PRC, dan kombinasi antar ketiga jenis pengobatan tersebut yang memiiliki resiko terjadinya meninggal rendah.

Regresi Cox Proportional Hazard Untuk Analisis Survival Pasien Kanker Otak di C-Tech Labs Edwar Technology Tangerang Izdiharti Noni Pertiwi; Santi Wulan Purnami
Inferensi Vol 3, No 2 (2020): Inferensi
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v3i2.7727

Kanker otak adalah pertumbuhan sel-sel otak yang tidak terkendali yang terjadi di otak. Di Indonesia kanker otak merupakan salah satu kanker terbanyak pada anak. Meskipun demikian, tumor ini dapat terjadi pada umur berapapun. Risiko kanker otak meningkat seiring dengan bertambahnya usia. Berbagai treatment dilakukan sebagai usaha untuk memperpanjang ketahanan hidup pasien kanker otak, seperti operasi, kemoterapi, radioterapi, pengobatan herbal, dan ECCT. ECCT merupakan metode untuk mengobati kanker menggunakan sumber gelombang elektrostatis intensitas rendah (<30Vpp) dan frekuensi rendah (<100KHz) yang dipasang pada pakaian yang dipakai setiap hari oleh pasien. Pasien disarankan melakukan konsultasi untuk memeriksa kinerja alat dan perkembangan penyebaran sel kanker. Penelitian ini bertujuan untuk mendapatkan faktor yang mempengaruhi model survival pasien kanker otak berdasarkan faktor treatment dan faktor resiko seperti usia dan jenis kelamin. Model regresi Cox PH digunakan karena semua variabel telah memenuhi asumsi PH. Data yang digunakan yaitu pasien yang melakukan konsultasi lebih dari 6 bulan. Berdasarkan pemodelan dengan menggunakan regresi Cox PH menghasilkan variabel yang berpengaruh terhadap waktu survival pasien kanker otak yaitu frekuensi konsultasi dan radioterapi. Didapatkan bahwa setiap bertambahnya 1 kali konsultasi resiko untuk mengalami kematian semakin turun sebesar 1,15 kali dan pasien kanker otak yang memiliki riwayat radioterapi memiliki resiko untuk meninggal 3 kali lebih besar daripada pasien yang tidak memiliki riwayat.

Predicting Popularity of Movie Using Support Vector Machines Dwi Rantini; Rosyida Inas; Santi Wulan Purnami
Inferensi Vol 2, No 1 (2019): Inferensi
Publisher : Department of Statistics ITS

There are many movies performed, from low until high rating, which is the movie maybe popular or not popular. If many people watched that movie maybe it is popular, in other hand if a movie is watched by a little person so that movie can called as not popular movie. Popularity of movie can determined by several factors, such as likes, ratings, comments, etc. To determine popular or not popular of movie based on features, will use two classification methods that is logistic regression and Support Vector Machine (SVM). In this research, the data are Conventional and Social Media Movies Dataset 2014 and 2015. To get the best model and without ignoring the principle of parsimony, will do feature selection. The selected features are genre, sentiment, likes, and comments. That features will be used to classify the popularity of movies. This research used two classification methods namely logistic regression and Support Vector Machine (SVM). When used logistic regression, the accuracy is 77.29%, while used SVM the accuracy is 83.78%. Based on the accuracy of both methods, it is found that SVM gives the highest accuracy for CSM dataset. The highest accuracy is obtained from the SVM method with non-stratified holdout training-testing strategy.

Co-Authors Abima Aunur Rochman Achmad Choiruddin Achmad Sjafii Ahmad Zaini Alfajriyah, Aimmatul Ummah Almuhayar, Mawanda Angga Dwi Mulyanto Anindya Apriliyanti Pravitasari Arief Kurniawan Arina Nur Afifah Ayu Mayliawati Baiq Siska Febriani Astuti Balami, Abdul Malik Bambang Widjanarko Otok Boedinugroho, Hanny Choiruddin, Achmad Cindy Cahyaning Astuti Diah Puspito Wulandari Diah Puspito Wulandari Dian Puspita Hapsari Didik Prasetyoko Diyah Herowati Dwi Rantini Edina, Almira Ivah Epa Suryanto Fandiantoro, Dion Hayu Farizi Rachman Febrisutisyanto, Ady Felinda Arumningtyas Ferriastuti, Widiana Fiscy Aprilia Rahmanika Fithriasari, Kartika Fitria Nur Aida Fourina Ayu Novianti H. Holilah Harmin Sulitiyaning Titah Hasliza Bahruji Ida Ayu Sevita Intansari Ika Wuryanti Febrina Wuryanti Imam Utoyo Irhamah - Izdiharti Noni Pertiwi Jerry D. T. Purnomo Juniastuti, Susi Kurnia Dwi Inayati Millatur Rodliyah Mukti Ratna Dewi Neni Alya Firdausanti Nur Arifiyani Nur Iriawan Nurcahyati Akbar Kusumawardani Nurfain Nurfain Nurul Qomariyah Purhadi Purhadi Rahmawati, Novi Agung Riza Inayah Rosyida Inas Santi Puteri Rahayu Saputri, Prilyandari Dina Setyo Purnomo Shofi Andari Shofi Andari Siska P Wibisono Siti Holis Sumartini Sri Hartati Selviani Handayani Sri Pingit Wulandari Sukur, Edi Sulasih, Dian Eka Apriana Sutikno Sutikno Tannassia Winda Adharina Taufik Azmi Titie Prapti Oetami Utoyo, Imam Yoyok Setyo Hadiwidodo Yoyon Kusnendar Suprapto Zeni Rahmawati

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