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Journal : J-SAKTI (Jurnal Sains Komputer dan Informatika)

Penerapan Algoritma C.45 Untuk Menentukan Tingkat Kepuasan Pelanggan Kartu Telkomsel Prabayar Sikumbang, Erma Delima; Ariani, Fattya; Handayani, Tiwi; Ramanda, Kresna; Sukmana, Sulaeman Hadi; Supriyatna, Adi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.492

Abstract

Telkomsel is an operator mobile phone company that provides services for mobile phone users. The mobile phone Operator creates a small SIM card for the customer by means of having to be inserted into each phone to get access to the service. One of the most used mobile operators and belongs to the largest category in Indonesia is Telkomsel. In This study implemented algorithm method C. 45 in deciding customer satisfaction against the use of prepaid Telkomsel cards. This type of research is to implement data mining concept by involving as many as 100 user data of prepaid Telkomsel card through the dissemination of questionnaires. There is an attribute in each variable that affects customer satisfaction including: price, promotion, product quality and service quality. Based on manual calculation results and with the help of the RapidMiner studio 9.7 software is known to be the root is a variable quality service with the highest gain value of 0.266396957 and results classification accuracy value of 0.9655 so that belongs to the classification category is very good
Clustering Koridor Transjakarta Berdasarkan Jumlah Penumpang Dengan Algoritma K-Means Supriyatna, Adi; Carolina, Irmawati; Janti, Suhar; Haidir, Ali
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.259

Abstract

Transportation is one of the facilities that make it easy for humans to carry out activities to move places using vehicles that are driven by humans or machines. Based on data obtained from data.jakarta.go.id, the number of Transjakarta bus passengers in corridors 1 to 13 of 2017 amounted to 114,239,960, and in 2018 there were 121,918,964 passengers. The algorithm used in this research is K-Means Cluster, which is implemented using Microsoft Excel and Rapidminer Studio. The purpose of this study is to cluster Transjakarta corridors based on the number of passengers divided into 3 clusters: high, medium, and low. The results of data processing show that the Transjakarta corridor data cluster is based on the number of passengers using the K-Means cluster algorithm using Microsoft Excel and Rapidminer Studio to produce 3 clusters, namely cluster 1 with the highest number of passengers, one corridor, cluster 2 with the number of passengers being nine corridors and cluster 3 or 0 with a low number of passengers there are three corridors. The highest number of passengers is corridor one which serves the Blok M - Kota route, indicating that the Blok M - Kota route is the most used by Transjakarta passengers.
Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil Supriyatna, Adi; Mustika, Wida Prima
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 2, No 2 (2018): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (776.13 KB) | DOI: 10.30645/j-sakti.v2i2.78

Abstract

Warts is a skin health problem that is generally characterized by the appearance of small, rough-textured lumps on the skin surface caused by a virus that is human papilloma virus (HPV). One technique of treatment of wart disease is immunotherapy, this method is a treatment by boosting the immune system to overcome the disease of warts. Naive bayes and Support Vector Machine (SVM) is a method of data mining algorithm used to classify. The aim of this study was to compare the Naive bayes algorithm with Support Vector Machine (SVM) in predicting the success of immunotherapy treatment method in the treatment of wart disease. Tests conducted using the method of Naive bayes and Support Vector Machine (SVM) using the R programming language, then the results are used to do the comparison. The results of this study revealed that the Naive bayes method has superior prediction capability compared to Support Vector Machine (SVM) because Naive bayes can predict all class instances correctly with the accuracy level of 1.