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Rustam, Suhardi
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Computer Science & IT

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AKADEMIK DATA MINING (ADM) K-MEANS DAN K-MEANS K-NN UNTUK MENGELOMPOKAN KELAS MATA KULIAH KOSENTRASI MAHASISWA SEMESTER AKHIR Rustam, Suhardi; Annur, Haditsah
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.487.260-268

Abstract

University as an educational institution plays an important role in producing graduates. In addition, institutions such as universitas ichsan Gorontalo save the data set. These Data include about student academic data.In the academic field, every semester, increasing the amount of data recorded with data from academic activities. It is like there is a Tsunami of data which indicate that these data are very abundant but do not give any knowledge that is not beneficial to the university, especially the faculty except the knowledge administrative. Universitas ichsan Gorontalo with the number of students reached 9000 people which is accompanied by the number of graduates is still less than ideal any period graduate, it is necessary to apply the pattern determination grade concentration courses effective for the achievement ability of students, academic Data will be used namely the data of the students 2016-2017 who has taken class subjects concentration. The application of K-Means algorithm and K-Means KNN where K=2 result in a cluster for grouping of a Class Focus on the students semester end and each cluster has a predictive value for the second klustering such, the Value of the resulting Accuracy of Algorithms KNN, namely the AUC (Area Under The Curve) =1, the Value of CA=1, the value of F1=1, the value of the precision=1 and recall=1, and the value of accuracy as the best value.
E-Commerce untuk Penjualan Arang Tempurung berbasis Android Rustam, Suhardi; Sumarni, Sumarni
ILKOM Jurnal Ilmiah Vol 12, No 3 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i3.657.200-207

Abstract

Pengolahan limbah kelapa di gorontalo utara umumnya diolah secara tradisional yang tidak jelas kualitasnya, sehingga menyebabkan keragaman olahan limba kelapa sangat tinggi. Penumpukan Limbah kelapa dan pengelolaan yang tidak memenuhi standar sehingga tidak memiliki nilai ekonomis bagi masyarakat. Pada permasalahan ini maka diperlukan adanya Pembinaan kepada para petani kelapa di gorontalo utara. Oleh karena itu menyajikan pembuatan aplikasi kepada petani kelapa dalam bentuk e-commerce yang mampu memberikan kemudahan menjual untuk para petani kelapa dengan tampilan yang menarik. E-commerce yang terdapat dalam bentuk aplikasi android, fokus penelitian untuk merancang e-commerce penjualan melalui handphone dalam memasarkan produk arang tempurung dari limbah kelapa.  Sehingga pada penelitian ini ditemukan beberapa permasalahan yang menjadi fokus penelitian untuk menangani tentang kesulitan para petani kelapa memasarkan produk arang tempurung dari limbah kelapa dan masih banyak petani yang sulit memaksimalkan pemasaran di internet melalui handphone. Ruang lingkup penelitian ini adalah perancangan e-commerce dengan media internetnya adalah handphone, sehingga permasalahan pada penerapan e-commerce arang tempurung menjadi mudah untuk diimplementasikan. Hasil penelitian ini setelah perancangan e-commerce ini dapat membantu masyarakat untuk mengatasi kesulitan memasarkan produk turunan kelapa atau produk limbah kelapa yang telah memberikan nilai ekonomi dan sebagai sumber alternatif penghasilan ekonomi keluarga atau komunitas masyarakat pada aspek pemasaran digital.
Klasifikasi Topik Tugas Akhir Mahasiswa menggunakan Algoritma Particle Swarm Optimization dan K-Nearest Neighbor Sumarni, Sumarni; Rustam, Suhardi
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.604.168-175

Abstract

Problems the Topic of the final project is a form of scientific writing that contains the results of observations from a study of the problems that occur with the use of methods related to the particular field of science. Every student in every program of study must draw up a final project. However, before embarking on writing the final project, each student must have the topic area as a destination, the step of selection the topic of final project is an initial step before working on the final task. One way to get the final task is to see the value of general courses as well as courses, concentration majors, the value of which dominate the is is decent to scope the research topic. this research is conducted on the application of the method of K-Nearest Neighbor (KNN) for categorization of the value of the courses of concentration for the coverage of the research topic, topic the entire value in the dataset will be classified by KNN and in the optimization with the Particle swarm Optimization algorithm (PSO). The experimental categorization of the final project is built with the training data Mahasiswa Universitas Ichsan Gorontalo that has been classified previously and test data derived from the entire value of the courses is not yet known categories. The results of the experiments, the value of the resulting accuracy of algorithms KNN, namely the value of the best accuracy with K=3, K Folds = 10 has an accuracy that is 72.46% and the Algorithm of KNN-PSO best accuracy with K=3, K Folds = 10 has an accuracy that is 89.86%, shows the accuracy is better by using the optimization algorithm
Co-Authors Haditsah Annur Sumarni Sumarni