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Pane, Rahmadhani
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Computer Science & IT

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Data Mining Clustering Korban Kejahatan Pelecehan Seksual dengan Kekerasan Berdasarkan Provinsi Menggunakan Metode AHC Sundari, Mitha Amelia; Pane, Rahmadhani; Rohani, Rohani
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3499

Abstract

Sexual harassment is one of the most common crimes in Indonesia recently. Acts of sexual harassment can occur in everyday life regardless of time, whether at work, on the street, or at home. Women are often the victims of sexual harassment, although men can experience the same. Perpetrators of sexual harassment can come from people we don't know, people who have hatred, even people we care about. Lack of religious and moral education, and technological developments that allow easy access to pornographic content are contributing factors to sexual harassment. To overcome this problem, fast action is needed in places where sexual harassment often occurs through socialization so that people are more vigilant when they are in these places. Apart from that, it is necessary to improve security in the area and provide consultation places such as psychologists. To identify places that are prone to sexual harassment in Indonesia, a data mining method is applied by utilizing previous data. The clustering method used is AHC using the complete linkage mode (longest distance) between the initial clusters. The final results of this research involve a manual process and the appropriate RapidMiner application, so that new clusters can be formed using RapidMiner. There are 5 provinces included in cluster 0, then there are 17 provinces in cluster 1, and 12 provinces in cluster 2
Analisis Perbandingan Sistem Pakar dalam Mendiagnosa Penyakit Limfoma Hodgkin Menggunakan Algoritma Teorema Bayes dan Certainty Factor Mahendra, Muklis; Pane, Rahmadhani; Rohani, Rohani
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3560

Abstract

Disease is a major challenge in the medical world. Accurate and timely diagnosis is a crucial key in disease management, including in cases of cancer. One type of cancer that affects the lymphatic system in the body is Hodgkin's lymphoma, which is also considered a rare disease. Typically, this disease occurs in adolescents and adults. Hodgkin's lymphoma requires serious treatment, although there are also cases of successful recovery. The importance of accurate and timely diagnosis in diagnosing Hodgkin's lymphoma is a critical factor in planning effective treatment and providing a favorable prognosis for patients. This study aims to perform a comparative evaluation of the Bayesian Theorem and Certainty Factor methods in diagnosing Hodgkin's lymphoma by comparing both methods. Diagnosing this disease is challenging for an expert due to the similarity of symptoms with other lymphoma diseases, which adds complexity. Therefore, this research provides an alternative to facilitate diagnosis by utilizing a system that can determine the level of certainty of a disease based on available data, including symptoms, expert values, and user values. After conducting research by comparing the two algorithms, Bayesian Theorem and Certainty Factor, various processing stages were implemented according to the established algorithm. The Bayesian Theorem algorithm yielded a result of 77.7%, while the Certainty Factor algorithm produced a higher value of 94.1%. The comparison between the Bayesian Theorem and Certainty Factor methods shows that the Certainty Factor method is more accurate in diagnosing Hodgkin's lymphoma and can be used in further research
Co-Authors Mahendra, Muklis Rohani Rohani Sundari, Mitha Amelia