Della Zilfitri
Sekolah Menengah Kejuruan Negeri 1 Lintau Buo

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Algoritma K-Means Clustering dalam Optimalisasi Komposisi Pakan Ternak Ayam Petelur Felka Andini; Della Zilfitri; Yosep Filki; Muhammad Ridho
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.289 KB) | DOI: 10.37034/jsisfotek.v5i2.168

Abstract

In Indonesia, the laying hens business sector experiences many obstacles, farmers often face instability between the price of chicken eggs and the price of feed which tends to always increase. The income received by farmers is not proportional to the cost of feed incurred. The production cost of laying hens can be reduced if there is an increase in feed efficiency. Maintenance of laying hens lies in the provision of feed, water, physical conditions and the state of the cage. Feed is the main source of energy for laying hens. The problem of feed in laying hens must meet the quality and quantity of the feed itself so that the effect is very real and clear on egg production. Feed nutrition must also meet the needs of laying hens. Feeding laying hens without paying attention to the quality of the feed can result in the growth and productivity of chickens being not optimal. Combining feed is an effort that can be made to produce a quality feed composition. This research was conducted to compile the composition of laying hens' feed using the K-Means Clustering algorithm. The K-Means Clustering method is an algorithm used by researchers to group or cluster data on laying hens feed into several clusters by using the nutritional content of each feed as an attribute. In this study, the data analyzed was data on the nutritional content of laying hens feed consisting of attributes such as protein, fat, crude fiber, calcium and phosphorus. This study will produce 3 clusters of feed types consisting of highly optimal clusters, optimal clusters and less than optimal clusters. This research is expected to be used as a recommendation by laying hens in compiling the composition of laying hens to maintain the quality of the eggs produced.
Data Mining Tingkat Kepatuhan Pasien Tuberkulosis dalam Menjalani Pengobatan Mengunakan Agloritma C4.5 Muhammad Ridho; Della Zilfitri; Felka Andini; Yosep Filki
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.752 KB) | DOI: 10.37034/jsisfotek.v5i2.170

Abstract

The high number of TB cases in the work area of ​​the Bukittinggi City Health Service Puskesmas Nilam Sari. The number of patients who do not comply with TB treatment. This study was conducted to determine the level of patient compliance in undergoing TB treatment so that the results of the study become input for medical personnel in charge of TB at Nilam Sari Health Center in policy making. The C4.5 method was used in this study to classify the data of compliant and non-adherent TB patients in undergoing treatment at the Nilam Sari Health Center. The data from TB patient visits to the Puskesmas were analyzed using the C4.5 method to obtain new knowledge from the TB patient visit data to the Puskesmas. The data analyzed consisted of attributes of the visit schedule, environmental distance, age which influenced the decision criteria for the level of adherence of TB patients in undergoing treatment at the Nilam Sari Health Center. The decision criteria for the results of TB patient visits consist of "Complied" and Non-Complied" which refers to the decision criteria for the TB patient's visit schedule. Tests conducted on the training data of the visit schedule of the attribute that most influence the decision on the level of adherence of TB patients in undergoing treatment. The implementation of the results using Weka 3.6.9 software and produces an accuracy of compliant patients of 13.4615% and accuracy of non-adherent patients of 86.5385%. The results of the classification method C.4.5 were greater in patients who were not compliant than patients who were obedient in undergoing TB treatment at the Nilan Sari Health Center. The test results have been able to help medical personnel in the Bukittinggi City Health Office work area in undergoing treatment to be able to make a policy for handling TB cases in the future.