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Journal : Jurnal Pilar Nusa Mandiri

ANALISA FITUR TEKSTUR NUKLEUS DAN DETEKSI SITOPLASMA PADA CITRA PAP SMEAR Riana, Dwiza
Jurnal Pilar Nusa Mandiri Vol 9 No 2 (2013): PILAR Periode September 2013
Publisher : PPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (549.489 KB) | DOI: 10.33480/pilar.v9i2.144

Abstract

Currently, the identification of Pap smear cells in the early detection process of cervical cancer is still an important stage of the process. The ease of detecting Pap smear cells will be very helpful in the introduction of cell abnormalities. Pap smear cell images consist of parts of the nucleus and cytoplasm. Proper analysis of parts of the nucleus and cytoplasm will facilitate the process of identifying cell abnormalities. This study presents Pap smear cell texture analysis on the pap smear cell nucleus and segmentation of the cytoplasmic area. Texture analysis was performed on 250 cell images of the nucleus. While cytoplasmic segmentation was performed for 887 cytoplasmic cell images. Senua cell image used has class categories categorized into seven classes. Three classes of them are normal cell image class categories that include: Normal Superficial, Normal Intermediate, and Normal Columnar, and the other four classes are abnormal cell image class categories which include: mild dysplasia, moderate dysplasia, severe dysplasia, and carcinoma Di There. The method used for texture analysis using 8-bit grayscale. And using the second sequence of Gray Level Co-occurrence Matrix (GLCM) statistics, with contrast, correlation, energy, homogeneity, and entropy features. Cytoplasmic detection uses edge detection and some morphological analyzes. The results showed that the numerical results of all the texture of the nucleus for each class of Pap smear image had slightly different properties. As for the results of cytoplasmic detection showed that the stage of the proposed detection process results in a clean area of the cytoplasm and can be detected well
PROXY SERVER SEBAGAI WEB FILTERING Widanto, Frantina Andri; Riana, Dwiza
Jurnal Pilar Nusa Mandiri Vol 3 No 4 (2007): Periode Maret 2007
Publisher : PPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (984.373 KB)

Abstract

A proxy server is a kind of buffer between your computer and the Inter-net resources you are accessing. They accumulate and save files that are most often requested by thousands of Internet users in a special database. Therefore, proxy servers are able to increase the speed of your connection to the Internet. A proxy server may already contain information you need by the time of your re-quest, making it possible for the proxy to deliver it immediately. The overall in-crease in performance may be very high. Also, proxy servers can help in cases when they want to filter any web resource users access like a web full violent , pomografi, hacking or cracking. This research give a way to buffer between us-ers computer and the Internet resources users are accessing with sguid applica-tion with GNU/Linux base. Proxy server with application Squid is a Internet gate-way to accessing Internet for server GNU/Linux base with client that using win-dows XP base.
DIAGNOSIS OF CORONAVIRUS DISEASE 2019 (COVID-19) SURVEILLANCE USING C4.5 ALGORITHM Wiguna, Wildan; Riana, Dwiza
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Publishing Period for March 2020
Publisher : PPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v16i1.1293

Abstract

Coronavirus Disease 2019 (COVID-19) has become a pandemic in Indonesia as a non-natural disaster in the form of disease outbreaks which must be undertaken as a response. The Ministry of Health in the Republic of Indonesia published a guidebook for prevention and control of COVID-19 in its response efforts. This guideline is intended for health officials as a reference in preparing for COVID-19. This handbook contains early detection and response activities to identify conditions of PDP, ODP, OTG, or confirmed cases of COVID-19. The efforts made are adjusted to the world situation progress from COVID-19 which is monitored by the World Health Organization (WHO). From the results of documentation studies that have been carried out on the COVID-19 pandemic in Indonesia, there are several problems that must be resolved from the prevention of the disease outbreak COVID-19. Lack of knowledge and awareness of the general public in the prevention and control of COVID-19 is one of the factors increasing the spread of that virus in Indonesia. Furthermore, there are difficulties in carrying out surveillance, early detection, contact tracing, infection prevention or control, and risk communication or people empowerment. This is due to the lack of implementation and testing on artificial intelligence methods for COVID-19 diagnosis that can be used by the public. The purpose of this research is to make a diagnosis of surveillance classification which includes PDP, ODP, and OTG using the C4.5 algorithm. The results showed that the diagnosis of the COVID-19 surveillance category using the C4.5 algorithm was successfully modeled into a decision tree with PDP, ODP, and OTG classification. The testing process in a confusion matrix with 3 (three) classes produces an accuracy rate of 92.86% which is included in the excellent classification category.