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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
S Saifullah
STIKOM Tunas Bangsa, Pematangsiantar, Sumatera Utara, Indonesia
Computer Science & IT Control & Systems Engineering

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Sistem Pendukung Keputusan Pemilihan Rumah Sakit Terbaik Di Kota Pematangsiantar Dengan Menggunakan Metode TOPSIS Sanri Sunervia Yunika Damanik; S Saifullah; Riki Winanjaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.62

Abstract

A hospital is a place where health services are provided by doctors, nurses and other health professionals. Health is the most important thing that every human wants to survive in doing all activities. The importance of this health encourages the government and the private sector to build quality hospitals so that people can access health needs. However, it is not only quality that is desired by the community, but satisfaction in providing fast services, supporting facilities and hygiene and safety are needed by the community so that the healing process feels happy and safe. To find out which hospital has the provision of health services desired by the community, a decision support system is needed. Decision support system is a system that can be used as a tool assist in the selection of hospitals that are in charge based on criteria desired by the community. The method used by researchers is the Topsis method. This method was chosen because it is able to select alternatives from several alternatives based on predetermined criteria. The results of this study are an average value of each alternative and criteria that will be ranked as the best hospital in Pematangsiantar. Based on the results of these tests can be a foundation that can help the community in choosing the provision of hospital services for the healing process.
Penerapan Metode K-Means Dalam Mengelompokkan Banyaknya Desa/Kelurahan Menurut Jenis Pencemaran Lingkungan Hidup Berdasarkan Provinsi Agus Tiranda Sipayung; S Saifullah; Riki Winanjaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.35

Abstract

Environmental pollution is hazardous for every living thing; environmental pollution can cause an imbalance in the environment or existing ecosystem. This study discusses the grouping of villages according to the type of environmental pollution based on the provinces in Indonesia. The method used is DataMining with the K-means Clustering algorithm. By using this method, the data obtained can be grouped into 2 clusters. This study uses secondary data, namely data obtained through intermediary media recorded on the Central Bureau of Statistics website with the URL address: http://www.bps.go.id. The results obtained in this study are grouping environmental pollution into 2 clusters, namely the highest cluster and the lowest cluster. In this research, it is hoped that it can provide input to related government parties to pay more attention to the provinces included in the highest cluster to tackle environmental pollution in the province.
Implementasi Data Mining Dalam Mengelompokkan Jumlah Penduduk Miskin Berdasarkan Provinsi Menggunakan Algoritma K-Means Yuni Radana Sembiring; S Saifullah; Riki Winanjaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 2 (2021): Edisi April
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i2.67

Abstract

Poverty is a certain condition that is below the standard line of minimum needs, good for food and non-food. Poor households generally have a greater average number of members compared to households that only have members who have fewer members. This situation is followed by the low level of education of household heads and workers who generally only work in the agricultural sector. Factors such as education, labor, health, fertility, housing, and the environment are a picture of the level of people’s welfare which is tought to affect the amount of proverty. This study used data sourced from the Central Bureau of statistics the year 2007-2019. The method used is Datamining the K-Means Clustering, Clustering is a method used in datamining the how it works find and classify data that has a semblance and characteristics of data between one another with the data. Using this algorithm the data already obtained can be grouped into Clusters based on this data. This data can be entered to the local Government to recommend to the Government so that the Government can handle the number of poor people in this country.
Penerapan Algoritma K-Means Dalam Pengelompokan Penerimaan Imunisasi Dasar Lengkap Menurut Provinsi Rico Hermanto Manurung; Muhammad Ridwan Lubis; S Saifullah
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 2, No 1 (2021): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v2i1.54

Abstract

Immunization is a form of immune system or immune to disease. The process of giving immunizations gives the body immunity to be immune to disease. With routine immunization improves the quality of children's health. According to data from the official Government website, the lowest percentage of children aged from 12 to 23 months who received immunization is 40% at the provincial level in Indonesia. This research was conducted by grouping the minimum level of immunization from 2015 to 2018 using the K-means method. The data obtained are grouped into 2 Clusters starting from the lowest and highest. The author obtains data from the official website of Government which addresses https://bps.go.id. The conclusion of this study concludes that there is still a lack of child immunization in Indonesia, so that there is an expectation that the Government in every region in Indonesia be more active for the welfare of children's health.
Co-Authors Agus Tiranda Sipayung Muhammad Ridwan Lubis Rico Hermanto Manurung Sanri Sunervia Yunika Damanik Winanjaya, Riki Yuni Radana Sembiring