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All Journal EKSAKTA: Journal of Sciences and Data Analysis AdMathEdu : Jurnal Ilmiah Pendidikan Matematika, Ilmu Matematika dan Matematika Terapan Media Farmasi : Jurnal Ilmu Farmasi (Journal Of Pharmaceutical Science) Jurnal Fourier Jurnal Profesi Medika: Jurnal Kedokteran dan Kesehatan Delta: Jurnal Ilmiah Pendidikan Matematika Jurnal Berdaya Mandiri
Sugiyarto Surono
universitas Ahmad Dahlan
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IMPLEMENTASI ALGORITMA SPECTRAL CLUSTERING UNTUK ANALISIS SENTIMEN Qonitat Rohmah Hidayati; Sugiyarto Surono
Delta: Jurnal Ilmiah Pendidikan Matematika Vol 9, No 1 (2021): Delta : Jurnal Ilmiah Pendidikan Matematika
Publisher : Universitas Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31941/delta.v9i1.1229

Abstract

Data mining is a study that collects, cleans, processes, analyzes and benefits from data. One of the techniques known in data mining is the Spectral Clustering technique. Spectral clustering is a technique that follows the Connectivity approach, where this method classifies points that are connected or directly adjacent. The purpose of this study is to determine the level of public sentiment towards the 2017 Jakarta Pilkada using the Spectral Clustering method. The test data was obtained from the scraping process on Twitter from October 1, 2016 to April 20, 2017. In this study, input data consisting of tweet data and output data were used in the form of sentiments that have been clustered into 3, namely positive, negative and neutral. Obtained 4571 negative data, 1899 neutral data and 1588 positive data. with the highest possible win rate in the first round on Ahok. In the second round with 2205 data, 604 positive tweets were obtained, 1123 neutral data, 479 negative data for negative tweets. In the second round Anies Baswedan received higher positive and lower negative responses than Candidate Ahok, so that the chances of winning against Anies Baswedan were higher than Ahok.
DISKRITISASI EQUAL-WIDTH INTERVAL PADA NAIVE BAYES (STUDI KASUS: KLASIFIKASI PASIEN TBC) Hariyani Hariyani; Sugiyarto Surono
AdMathEdu : Jurnal Ilmiah Pendidikan Matematika, Ilmu Matematika dan Matematika Terapan Vol 10, No 2: Desember 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/admathedu.v10i2.20129

Abstract

Klasifikasi Naive Bayes merupakan teknik untuk memprediksi probabilitas keanggotaan suatu kelas dengan menerapkan teorema Bayes. Klasifikasi Naive Bayes akan lebih baik jika menggunakan data yang berbentuk kategorik, sehingga dalam penelitian ini digunakan diskritisasi equal-width interval pada Naive Bayes untuk mengubah data yang berbentuk numerik menjadi kategorik. Tujuan dari penelitian ini adalah untuk menerapkan metode Naive Bayes dengan diskritisasi equal-width interval dalam mengklasifikasi pasien TBC di Puskesmas Sewon 1. Hasil penelitian ini menunjukkan akurasi sebesar 100% dengan perbandingan data training dan data testing sebesar 80%:20% dan 90%:10%, sehingga klasifikasi Naive Bayes dapat dikategorikan baik dalam mengklasifikasi pasien TBC.
Rough Set Theory for Dimension Reduction On Machine Learning Algorithm Rani Nuraeni; Sugiyarto Surono
Jurnal Fourier Vol. 10 No. 1 (2021)
Publisher : Program Studi Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dimension reduction is a method applied in machine learning sector to significantly improve the efficiency of computational process. The application of high number variables in certain dataset is expected to be able to provide more information to analyze. However, this application of high number of variables will impacted on the computational time and weight linearly. Dimension reduction method serves to transforming the high dimension data into much lower dimension without significantly reduce the initial information and characteristic provided by the initial data. Core and Reduct is a method acquired through the concept of Rough Set. Dataset functioning as the input and output on Machine Learning can be perceived as informational system. The objective of this research is to determine the impact of the dimension reduction application on machine learning algorithm on the reduction of computational time and weight. Core and Reduct will be applied in few popular machine learning method such as Support Vector Machine (SVM), Logistic Regression, and K-Nearest Neighbors (KNN). This research applied on 5 UCI machine learning dataset which are Iris, Seeds, Years, Sonar, and Hill-Valley. Furthermore, Machine learning metrics such as Accuracy, Recall, Precision, and F1-Score also observed and compared. This research resulted in the conclusion that Core and Reduct is able to decrease the computational time up to 80% and maintain the value of each evaluation model.
A Survival Analysis with Cox Regression Interaction Model of Type II Diabetes Mellitus in Indonesian Simeftiany Indrilemta Lomo; Sugiyarto Sugiyarto; Endang Darmawan
Jurnal Profesi Medika : Jurnal Kedokteran dan Kesehatan Vol 15, No 1 (2021): Jurnal Profesi Medika : Jurnal Kedokteran dan Kesehatan
Publisher : Fakultas Kedokteran UPN Veteran Jakarta Kerja Sama KNPT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33533/jpm.v15i1.2942

Abstract

Type II diabetes mellitus is a metabolic syndrome characterized by hyperglycemia. Diabetes is still one of the world's health threats where the number of people with disabilities and mortality rates continue to increase over time. This study aims to analyze the survival of patients with type II diabetes mellitus as well as factors that affect it using survival analysis.  This study used medical record data of type II diabetes mellitus patients undergoing treatment for the period 2015-2019 at PKU Muhammadiyah Gamping Hospital and PKU Muhammadiyah Hospital Yogyakarta.
PENGEMBANGAN PLATFORM PROMOSI UMKM DALAM RANGKA MENDUKUNG KEGIATAN KOTAGEDE SMART DISTRICT Sugiyarto Surono; Yudi Ari Adi; Nursyiva Irsalinda
Jurnal Berdaya Mandiri Vol. 3 No. 1 (2021): Jurnal Berdaya Mandiri (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (243.75 KB) | DOI: 10.31316/jbm.v3i1.1212

Abstract

Usaha mikro kecil dan menengah (UMKM) merupakan salah satu penggerak roda perekonomian di masyarakat. Kotagede merupakan salah satu kecamatan di kota Yogyakarta yang memiliki UMKM dengan jumlah 497 usaha. Dalam upaya mempromosikan dan mempublikasikan produk-produk yang ada di Kecamatan Kotagede dan menunjang program Kecamatan Kotagede menuju Smart District maka diperlukan analisis khusus UMKM Kecamatan Kotagede untuk menciptakan suatu Platform yang memuat informasi UMKM baik pelaku maupun produk yang dihasilkan serta fasilitas lain yang dibutuhkan oleh pelaku UMKM maupun masyarakat. Hasil analisis data UMKM yang telah dilakukan menunjukkan bahwa UMKM dengan modal dibawah Rp. 250.000.000 sebesar 80%. Oleh karena itu, dalam rangka mengembangkan UMKM diwilayahnya pihak kecamatan sebaiknya membuat platform perizinan untuk mempermudah proses perizinan UMKM.
Penerapan K-Means untuk Clustering Berdasarkan Tingkat Keparahan COVID-19 di Rumah Sakit Swasta Indonesia: Penerapan K-Means untuk Clustering Berdasarkan Tingkat Keparahan COVID-19 Kathina Deswiaqsa; Endang Darmawan; Sugiyarto Sugiyarto
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 2, August 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss2.art5

Abstract

In December 2019, coronavirus (COVID-19) caused by SARS-CoV-2 was first discovered in Wuhan, China. This virus has a high transmission rate and can be transmitted through droplets, airborne, and aerosols. The clinical manifestations are very diverse ranging from mild, moderate, and severe. Therefore, this study aims to conduct a clustering of the spread of the Covid-19 pandemic to facilitate the identification and handling. The method of the K-Means algorithm can be used as a method to obtain the desired clustering. The implementation and evaluation were conducted using RapidMiner tools and Davies Bouldin Index (DBI) respectively. Furthermore, the data sources by Kangdra (2020) were used with a total sample of 110 for the period March-June 2020. The results showed that the optimal cluster is located at k: 2 with a DBI value: 0,094 as the lowest value. Therefore, the cluster is strong since a smaller DBI value gives a better cluster. The clustering obtained is Cluster 1 and 2 with mild and moderate severity. The results are expected to facilitate a better zone identification of the COVID-19 severity level and rising people awareness.
An overview of Covid-19 patients with and without comorbid Diabetes Mellitus at Surabaya Hajj general hospital Uswatun Hasanah; Endang Darmawan; Sugiyarto Sugiyarto
Media Farmasi: Jurnal Ilmu Farmasi Vol 19, No 2: September 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.208 KB) | DOI: 10.12928/mf.v19i2.23246

Abstract

Diabetes mellitus (DM) is one of the most common comorbidities found in patients infected with Covid-19 with severity and death. To obtain an overview of Covid-19 patients with and without comorbid DM. A retrospective cohort study, taking subjective data on Covid-19 patients with and without DM at Surabaya Hajj general hospital for the period of March 2020 to June 2021. Data analysis using the Chi-square test was to determine differences in both test variables. The death of Covid-19 patients with comorbid DM was found with the condition in which the average random blood glucose (RBG) increased by >150 mg/dl (286 mg/dl), as well as in recovered patients (197 mg/dl); meanwhile, patients without comorbid DM died with also an increase in the RBG value (166 mg/dl). Male patients were found to be more prone to get infected with Covid-19 than female patients. It can be concluded that there was no significant difference in the severity of cases in Covid-19 patients with comorbid DM and without comorbid DM. Deaths due to Covid-19 in patients with comorbid DM or without comorbid DM occurs due to the increasing blood glucose value by >150 mg/dl.
Co-Authors Ditya Ayu Natalia Endang Darmawan Endang Darmawan Endang Darmawan Endang Darmawan Hariyani Hariyani Kathina Deswiaqsa Nursyiva Irsalinda Qonitat Rohmah Hidayati Rani Nuraeni Salafudin Salafudin Simeftiany Indrilemta Lomo Suparman suparman Ummu Wachidatul Latifah USWATUN HASANAH Yudi Ari Adi, Yudi Ari Zhurwahayati Putri