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PROGRAM PENGEMBANGAN KEWIRAUSAHAAN MAHASISWA DAN ALUMNI STMIK KAPUTAMA SECARA ONLINE Ambarita, Indah; Sihombing, Anton; Buaton, Relita
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.980

Abstract

Developed countries in general are the countries that have many entrepreneurs because they can create jobs, reduce unemployment and contribute to state revenue. Technological development has a correlation with lifestyle and behavior. The internet is not only used to access information, but is also used for business facilities and buying and selling transactions. Currently conventional marketing is less than optimal. Therefore, entrepreneurs are directed to utilize information technology or commonly called commercial electronics as a medium of promotion and sale. This has become a huge opportunity for students or alumni of computer science such as STMIK Kaputama students and alumni. Small and Medium Enterprises (SMEs) in many regions are successful in terms of production, but they have problems in terms of marketing and sales. This has the potential to be developed by young, new and creative entrepreneurs by involving students and alumni to synergize with SMEs and entrepreneurs to deal with online marketing and sales issues, so that market and sales are increasing. The solution provided is making entrepreneurship training by providing various life skills and adding insight into entrepreneurship, e-commerce training, graphic design training, mentoring and supervision. Thus, students and alumni are generally interested in entrepreneurship, and are more easily trained to become entrepreneurs because in lectures they already have basic knowledge of entrepreneurship and computer science and help the government to create jobs and reduce unemployment.Keywords: Increasing entrepreneurship, increasing sales of SMEs, online entrepreneurship, e-commerce
RESERVASI DAN BILLING POST OF TRANSACTION RESTAURANT GRAHA KARDOPA BINJAI SECARA ONLINE Aula, Nurhasanah; Fauzi, Achmad; Pardede, A M H; Maulita, Yani; Buaton, Relita
Majalah Ilmiah Kaputama Vol 4, No 1 (2020): EDISI JANUARI 2020
Publisher : STMIK Kaputama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hotel Graha Kardopa is a Hotel located in Binjai, North Sumatra. System Information about reservation and billing in this Hotel still use manual system, where the way is still be regarded very slowly. To facilitate the processing of billing in need of Information System Reservation and Billing Post Of Transaction Restaurant Graha Kardopa Binjai. Based on the problems that have been in carefully by the author, the authors designed the Information Systems Reservation And Billing Post Of Transaction Restaurant Graha Kardopa Binjai. The result of this research is to facilitate the processing of Reservation and Billing Restaurant Hotel Graha Kardopa Binjai. The purpose of this Final Project is to make an Information System Reservation and Billing Post Of Transaction Restaurant Graha Kardopa Binjai, by using PHP and MySql-based programming Web that can help the process of restaurant reservation processing to be effective and efficient.
IDENTIFIKASI JENIS BUNGA MENGGUNAKAN EKSTRAKSI CIRI ORDE SATU DAN ALGORITMA MULTI SUPPORT-VECTOR MACHINES (MULTISVM) Teuku Reza Pahlefi; Relita Buaton; Nurhayati Nurhayati
Jurnal Informatika Kaputama (JIK) Vol 5, No 1 (2021): Volume 5, Nomor 1 Januari 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v5i1.418

Abstract

Flowers are a means of generative reproduction of closed seed plants. In the flower sections there are various or also types of parts in the flower, each of which has different functions in each part of the flower, so that a long and broad discussion is needed regarding the parts of the flower on a daily basis. day is also used to refer to a structure which is botanically known as compound interest or inflorescence. Compound interest is a collection of flowers collected in one bouquet. In this context, the unit of interest that makes up compound interest is called a floret. Flower is actually a modification of the leaves and stems to support a closed fertilization system. The fertilization system is closed, namely because the ovule is protected in the ovary or ovary and this is also another characteristic. The purpose of this study was to classify 12 Banten batik motifs using the SVM method. The research was carried out in several stages, namely resizing to equalize the dimensions of the image, grayscale to simplify the image by converting it to a gray level image, median filter to remove noise in batik, and feature extraction as input for classification using SVM. The classification results using SVM order 1 is 85%, and for order 2 is 87.2.
PEMANFAATAN DUA METODE CLUSTERING DAN ASSOCIATION RULE TERHADAP PRESTASI BELAJAR BERDASARKAN NILAI MATA PELAJARAN SISWA Yuyun Arnia; Yani Maulita; Relita Buaton
Jurnal Informatika Kaputama (JIK) Vol 4, No 1 (2020): VOLUME 4 NOMOR 1, EDISI JANUARI 2020
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v4i1.228

Abstract

Data mining is a series of processes to extract new information from a pile of data. Student learning achievements are the results obtained by students after undergoing the learning process. There are quite a lot of data on student achievement in SMK Taman Siswa Binjai. But the student data has not been utilized to the maximum, making it difficult for the School to monitor the progress of students in the school. Therefore, it is necessary to create a system to find out the implementation of Data Mining based on the K-Means Clustering Method and to know the centroid distance between 1 group and other groups and to know the implementation of Data Mining based on Apriori Algorithm and to know the Support and Confidence of student learning achievement towards eye scores study, discipline, and majors. With this system can provide benefits to the school to be able to provide knowledge about student achievement while attending teaching and learning activities and to students to be able to know their learning achievements are good what needs to be improved again and can improve it again. By implementing k-means and a priori data mining of student achievement data in 2016 - 2018, there were 604 data, and from 100 data produced 3 clusters, where 1 48 data clusters, 2 24 data clusters, 3 28 data clusters, and with the algorithm a priori produce 16 rules that are formed and get the best rule, if someone has a good enough course value (70.00 - 76.99) and has enough discipline, then most likely will be in the Department of Motorcycle Engineering with a supporting value of 9% and 88% certainty value.
PERANCANGAN SISTEM PENDETEKSI BERITA HOAX MENGGUNAKAN ALGORITMA LEVENSHTEIN DISTANCE BERBASIS PHP Aprillianda Pasaribu; Marto Sihombing; Relita Buaton
Jurnal Informatika Kaputama (JIK) Vol 4, No 1 (2020): VOLUME 4 NOMOR 1, EDISI JANUARI 2020
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v4i1.229

Abstract

In the 4.0 era where the Internet is an important part of life today, information can be easily accessed anytime, anywhere. But not all information distributed through the internet is in the form of facts. Data presented by the Ministry of Communication and Information based on a survey conducted in 2018 said that as many as 800,000 sites in Indonesia indicated that non-fact or hoax news spreaders were indicated. As a result of hoax news generated is very dangerous because it attacks the minds of the human subconscious, so it is needed a system that can detect hoax news. In this study used a database containing hoax news documents. The algorithm applied is the TF-IDF algorithm to measure the weight of a word in a hoax document and combined with the Levenshtein Distance (LD) algorithm to measure the distance between words in a document. The application of the Levenshtein Distance Method in the Hoax Detection System has several stages that begin with the pre-processing of the word (prepocessing text) followed by the TF-IDF calculation phase and then the minimum distance calculation between words using the Levenshtein Distance algorithm. The result of a limit of 0.1 on 40 documents that have been classified as test data has high Precision, Recall and Accuracy values, namely Precision 1; Recall 0.71; and Accuracy 80%.
Korelasi Kecerdasan Emosional Dengan Prestasi Belajar Siswa Menggunakan Metode A Priori (Studi Kasus: SMPIT Alkaffah Binjai) Relita Buaton; Yani Maulita; Ayu Rahayu Febria
Jurnal Informatika Kaputama (JIK) Vol 1 No. 1 Tahun 2017
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v1i1.15

Abstract

Sering ditemukan siswa yang tidak dapat meraih prestasi belajar yang setara dengan kemampuan inteligensinya.Ada siswa yang mempunyai kemampuan inteligensi tinggi tetapi memperoleh prestasi belajar yang relatifrendah, namun ada siswa yang walaupun kemampuan inteligensinya relatif rendah tetapi dapat meraih prestasibelajar yang relatif tinggi. Itu sebabnya taraf inteligensi bukan merupakan satu-satunya faktor yang menentukankeberhasilan seseorang, karena ada faktor lain yang mempengaruhi, maka perlu digali dengan metode A Priori,bagaimana cara menentukan korelasi nilai kecerdasan emosional dan prestasi belajar siswa. Metodologi yangdigunakan adalah analisis pola frekkuensi tinggi dan pembentukan aturan asosiasi. Hasil yang ditemukan adalahfaktor-faktor yang paling sering terjadi dan yang paling banyak muncul secara bersamaan adalah kemampuansiswa untuk mengenal emosi diri mau bertanggung jawab atas kesalahan yang dilakukan dan kemampuan siswauntuk memotivasi diri sendiri mau mendahulukan belajar daripada bermain dan mau memperbaiki kegagalanmenjadi suatu keberhasilan dan kemampuan siswa untuk mengenal emosi orang lain mau mendengar keluhkesah teman dan Afektif mengikuti nilai-nilai yang telah ditentukan then Psikomotorik siswa ulet dalammengikuti latihan dengan nilai Support 90% dan Confidence 100%.
DATA MINING UNTUK MENENTUKAN KORELASI (CONFIDENCE DAN SUPPORT) JURUSAN SISWA PADA TINGKAT SEKOLAH MENENGAH TERHADAP INDEKS PRESTASI KUMULATIF (IPK) DI PERGURUAN TINGGI SEBAGAI SOLUSI TEPAT PEMILIHAN PROGRAM STUDI DI PERGURUAN TINGGI Relita Buaton; Anton Sihombing; Fuji Dodo Aritonang; Clara Rosa Wijaya
JSIK (Jurnal Sistem Informasi Kaputama) Vol 1, No 2 (2017)
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jsik.v1i2.29

Abstract

Beberapa faktor yang mempengaruhi mahasiswa memperoleh nilai IPK tinggi, diantaranyamahasiswa harus belajar secara maksimal di bangku kuliah dan sesuai dengan program studi yangdipilih. Salah satu faktor agar mahasiswa dapat belajar secara maksimal adalah bahwa jurusan/programstudi yang dipilih di perguruan tinggi harus diminati dan sesuai dengan bidang keahlian serta memilikikorelasi dengan latar belakang pendidikan mahasiswa. Menurut Educational Psychologist dari IntegrityDevelopment Flexibility (IDF),sebanyak 87 persen mahasiswa di Indonesia salah jurusan yang dapatmemicu pada pengangguran, tidak mampu mengikuti perkuliahan dan dampak paling buruk adalahDO(drop out). Untuk membantu mahasiswa dalam memilih jurusan, perlu dirancang sebuah sistemsecara online, sehingga semua orang dapat mengakses sebagai pendukung dalam memilihjurusan.Variable yang digunakan adalah jurusan di sekolah menengah, Program studi di PerguruanTinggi dan IPK. Sebagai tahap awal untuk basis pengetahuan data diinput dari 24 perguruan tinggiswasta dan negeri yang tersebar di provinsi yakni Sumatera Utara, terdiri dari 27 JurusanSMA/sederajat dan 65 program studi di Perguruan tinggi.Hasil yang diperoleh adalah dihasilkannyasebuah pengetahuan baru untuk membantu memilih program studi di perguruan tinggi berdasarkansupport dan confidence sesuai jurusan, mahasiswa dapat mengetahui korelasi jurusan di SMA terhadapjurusan di perguruan tinggi.
PENERAPAN METODE SAW DAN TOPSIS SEBAGAI PERBANDINGAN HASIL SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI LAHAN TAMBAK PALING TERBAIK UNTUK DIJADIKAN USAHA TAMBAK AIR PAYAU Yani Maulita; Relita Buaton; Farid Reza Malau
JSIK (Jurnal Sistem Informasi Kaputama) Vol 1, No 1 (2017)
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jsik.v1i1.24

Abstract

Banyaknya metode-metode yang tersedia pada sistem pendukung keputusan sehingga kadang membuatbingung memilih mana yang cocok penggunaaan metode yang sesuai dengan kasus sistem pendukungkeputusan. Untuk itu dibuat suatu perbandingan dari kasus sistem pendukung keputusan pemilihan lokasi lahantambak paling terbaik untuk dijadikan usaha tambak air payau untuk perbandingan hasil keputusan. Metodeyang digunakan yaitu Simple Additive Weighting (SAW) dan Topsis dengan menentukan banyaknya jumlahkriteria, jenis kriteria (Cost dan Benefit), dengan 3 alternatif. Hasil penelitian yaitu hasil perhitungan manualsama dengan perhitungan yang ada pada sistem. Setiap perhitungan dari dari metode SAW dan Topsismenunjukkan bahwa hasil keputusan pemilihan lokasi lahan tambak paling terbaik untuk dijadikan usahatambak air payau setiap metode memiliki hasil akhir yang berbeda-beda.
PARAMETER ASOSIASI UNTUK MENENTUKAN KORELASI JURUSAN DAN INDEKS PRESTASI KUMULATIF Relita Buaton; Deny Jollyta; Herman Mawengkang; Muhammad Zarlis; Syahril Effendi
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (892.061 KB) | DOI: 10.33480/pilar.v15i1.285

Abstract

One of the problems in higher education is the mistake of prospective students in majors selection. This is caused by not paying attention to the suitability of the major in the original school with the chosen major in higher education so that it impacts not only non optimal processing and learning outcomes, such as the low GPA, but also on social life, such as increasing unemployment. The selection of the right major is very important and to help prospective students in choosing it requires an online system that can be accessed by everyone and select original school majors to see conformity with majors in higher education. This system uses association rules and parameters of support and confidence in data mining. The purpose of this research is to determine the correlation between majors in the original school, majors in higher education and the achievement of the GPA through the use of support and confidence parameters that process the knowledge base in the form of an alumni database on the online system created. Training or testing was conducted on 10,254 data in the database and produced new information and knowledge that between the majors of the original school, the choice of majors in higher education and GPA had a strong correlation with the value of confidence reaching 100%.
Korelasi Faktor Penyebab Tindak Kekerasan dalam Rumah Tangga Menggunakan Data Mining Algoritma A Priori Relita Buaton; Yani Maulita; Andri Kristiawan
Jurnal Media Infotama Vol 14 No 1 (2018)
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.816 KB) | DOI: 10.37676/jmi.v14i1.468

Abstract

Badan Keluarga Berencana dan Pemberdayaan Perempuan Kabupaten Langkat Sumatera Utara merupakan suatu instansi pemerintahan yang bertanggung jawab melayani masyarakat kabupaten Langkat dalam kasus kekerasan dalam rumah tangga(KDRT). Kekerasan dalam rumah tangga sudah termasuk masalah yang umum terjadi dalam kehidupan rumah tangga. Hal ini dikarenakan kurang harmonisnya hubungan dalam rumah tangga tersebut. Semakin banyaknya masyarakat yang melakukan tindakan kekerasan, maka perlu mencari solusi dan sebuah pengetahuan baru untuk mengatasi permasalahan ini dengan korelasi faktor penyebab tindak kekerasan dalam rumah tangga menggunakan algoritma a priori untuk menghasilkan kombinasi terdekat antar variabel. Teknik yang digunakan dalam aplikasi data mining ini adalah aturan asosiasi dengan algoritma a priori. Algoritma apriori ini melakukan proses iterasi untuk menghasilkan kombinasi item yang memiliki pola frekuensi tinggi, berdasarkan nilai ambang batas support dan confidence yang diberikan oleh user. Teknik ini menganalisis kombinasi faktor penyebab terjadinya tindak kekerasan dalam rumah tangga yang sering dialami korban berdasarkan pada data korban berjumlah 307 data kekerasan dalam rumah tangga. Melalui data tindak kekerasan dalam rumah tangga yang berjumlah 307 data, telah diperoleh hasil sebanyak 74 rule. Dan dari 74 rule yang terbentuk, telah ditemukannya rule terbaik dengan keterangan yaitu, seorang ibu rumah tangga cenderung mengalami jenis kekerasan berupa kekerasan fisik yang disebabkan oleh faktor ekonomi, support 20% dan confidence 76%. Kata Kunci: Korelasi Faktor Penyebab Kekerasan Dalam Rumah Tangga, Algoritma A Priori.