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<![CDATA[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 ]]>
<![CDATA[Relita Buaton]]>;
<![CDATA[Anton Sihombing]]>;
<![CDATA[Fuji Dodo Aritonang]]>;
<![CDATA[Clara Rosa Wijaya]]>
<![CDATA[ JSIK (Jurnal Sistem Informasi Kaputama) Vol 1, No 2 (2017) ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jsik.v1i2.29
<![CDATA[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.]]>
<![CDATA[PERANCANGAN SISTEM PENDETEKSI BERITA HOAX MENGGUNAKAN ALGORITMA LEVENSHTEIN DISTANCE BERBASIS PHP ]]>
<![CDATA[Aprillianda Pasaribu]]>;
<![CDATA[Marto Sihombing]]>;
<![CDATA[Relita Buaton]]>
<![CDATA[ Jurnal Informatika Kaputama (JIK) Vol 4, No 1 (2020): VOLUME 4 NOMOR 1, EDISI JANUARI 2020 ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jik.v4i1.229
<![CDATA[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%.]]>
<![CDATA[PENERAPAN METODE SAW DAN TOPSIS SEBAGAI PERBANDINGAN HASIL SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI LAHAN TAMBAK PALING TERBAIK UNTUK DIJADIKAN USAHA TAMBAK AIR PAYAU ]]>
<![CDATA[Yani Maulita]]>;
<![CDATA[Relita Buaton]]>;
<![CDATA[Farid Reza Malau]]>
<![CDATA[ JSIK (Jurnal Sistem Informasi Kaputama) Vol 1, No 1 (2017) ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jsik.v1i1.24
<![CDATA[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.]]>
<![CDATA[PENGEMBANGAN KEWIRAUSAHAAN MAHASISWA DAN ALUMNI GUNA ERA DIGITAL ]]>
<![CDATA[Indah Ambarita]]>;
<![CDATA[Anton Sihombing]]>;
<![CDATA[Relita Buaton]]>
<![CDATA[ METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 2 No. 2 (2018): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi ]]>
Publisher : <![CDATA[Universitas Methodist Indonesia ]]>
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DOI: 10.46880/jmika.Vol2No2.pp109-115
<![CDATA[Technological advances that are always developing have a correlation with human patterns and behavior in general. Internet use is not only used to access information or news, but is also used for business facilities and buying and selling transactions. Conventional marketing or promotion is no longer optimal at this time, so that business people must also be directed to utilize information technology or commonly called commercial electronics as a medium for the promotion and sale of production goods. This opportunity becomes a huge opportunity for students or alumni in information technology or computer science such as STMIK Kaputama students or alumni. SMEs (Small and Medium Enterprises) in various regions have been successful in terms of production, but have problems in terms of marketing and sales. This has the potential to be developed by young entrepreneurs, new and creative by utilizing students and alumni so that they synergize between SMEs and entrepreneurs to handle online marketing and sales, so that market reach and sales are broad and increasing. The solution provided is to involve several stakeholders and several activities namely entrepreneurship training that is in touch with how the existing human resources are improved by providing various life skills and increasing entrepreneurial insight. E-commerce making training, making graphic design training, providing coffee bean processing equipment to instant coffee powder, guidance and supervision. With this dedication activity, it produces every year new, young and creative entrepreneurs based on science and technology that synergize with SMEs and coffee farmers, so that SMEs are greatly helped to market their products with the hope that their entrepreneurs and SMEs will increase their welfare.]]>
<![CDATA[Korelasi Kecerdasan Emosional Dengan Prestasi Belajar Siswa Menggunakan Metode A Priori (Studi Kasus: SMPIT Alkaffah Binjai) ]]>
<![CDATA[Relita Buaton]]>;
<![CDATA[Yani Maulita]]>;
<![CDATA[Ayu Rahayu Febria]]>
<![CDATA[ Jurnal Informatika Kaputama (JIK) Vol 1 No. 1 Tahun 2017 ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jik.v1i1.15
<![CDATA[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%.]]>
<![CDATA[IDENTIFIKASI JENIS BUNGA MENGGUNAKAN EKSTRAKSI CIRI ORDE SATU DAN ALGORITMA MULTI SUPPORT-VECTOR MACHINES (MULTISVM) ]]>
<![CDATA[Teuku Reza Pahlefi]]>;
<![CDATA[Relita Buaton]]>;
<![CDATA[Nurhayati Nurhayati]]>
<![CDATA[ Jurnal Informatika Kaputama (JIK) Vol 5, No 1 (2021): Volume 5, Nomor 1 Januari 2021 ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jik.v5i1.418
<![CDATA[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.]]>
<![CDATA[PEMANFAATAN DUA METODE CLUSTERING DAN ASSOCIATION RULE TERHADAP PRESTASI BELAJAR BERDASARKAN NILAI MATA PELAJARAN SISWA ]]>
<![CDATA[Yuyun Arnia]]>;
<![CDATA[Yani Maulita]]>;
<![CDATA[Relita Buaton]]>
<![CDATA[ Jurnal Informatika Kaputama (JIK) Vol 4, No 1 (2020): VOLUME 4 NOMOR 1, EDISI JANUARI 2020 ]]>
Publisher : <![CDATA[STMIK KAPUTAMA ]]>
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DOI: 10.1234/jik.v4i1.228
<![CDATA[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.]]>
<![CDATA[Mengatasi Kelemahan Internal Menggunakan Mc-Kinsey 7s Untuk Peningkatan Standar Mutu Pendidikan ]]>
<![CDATA[Deny Jollyta]]>;
<![CDATA[Relita Buaton]]>;
<![CDATA[N Novriyenni]]>;
<![CDATA[Achmad Fauzi]]>
<![CDATA[ Archive: Jurnal Pengabdian Kepada Masyarakat Vol. 1 No. 1 (2021): Desember 2021 ]]>
Publisher : <![CDATA[Asosiasi Pengelola Publikasi Ilmiah Perguruan Tinggi PGRI ]]>
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DOI: 10.55506/arch.v1i1.6
<![CDATA[Mutu sebuah sekolah ditandai dengan berjalannya sistem penjaminan mutu di internal sekolah. Pencanangan Sekolah Menengah Kejuruan Pusat Keunggulan (SMK PK) oleh pemerintah menguatkan kenyataan bahwa penjaminan mutu sekolah sangat diperlukan dalam mencapai Standar Mutu Pendidikan. Terlaksananya penjaminan mutu sekolah merupakan early warning system untuk memperbaiki kesalahan sebelum situasi semakin parah. Kesulitan yang terjadi dalam pencapaian standar adalah kurangnya kesadaran sekolah terhadap kelemahan diri sendiri. Pemicu kelemahan tidak mampu diatasi dan cenderung diabaikan. Studi ini bertujuan untuk menghasilkan sebuah model penyelesaian kelemahan internal sekolah dengan Mc-Kinsey 7s dalam mencapai mutu melalui gambaran sejumlah indikator yang disusun dalam bentuk angket. Data angket diolah menggunakan SPSS dengan hasil 33,33% dari indikator berada pada ranah Cukup, Kurang dan Sangat Kurang. Kelemahan pada indikator ini diperkuat dengan 7 elemen dari model Mc-Kinsey 7s untuk dihasilkan penyelesaian. Diharapkan penguatan melalui integrasi 7 elemen Mc-Kinsey dapat mengatasi kelemahan internal sekolah dalam menuju SMK PK yang berkualitas dan bermartabat.]]>
<![CDATA[Optimization of Higher Education Internal Quality Audits Based on Artificial Intelligence ]]>
<![CDATA[Relita Buaton]]>;
<![CDATA[Zarlis Muhammad]]>;
<![CDATA[Elviwani]]>;
<![CDATA[Ami Dilham]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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DOI: 10.53842/jaiea.v1i2.83
<![CDATA[Internal Quality Audit is an independent and documented systematic testing process to ensure that the implementation of activities in higher education is in accordance with the procedures and the results are in accordance with the standards to achieve the goals of the institution. Quality can be guaranteed by ensuring that each individual has the skills he needs to do the job properly. Quality orientation in development life in Indonesia is something that is very urgent, must be supported and developed in order to respond to the trend of global competition. There are significant differences in the accreditation and quality assurance system with the previous version, it is necessary to develop a strategy by building an artificial intelligence-based system. The method used is to build an online system by involving experts and assessors to develop concepts in accordance with the points of the 9 criteria accreditation forms, to build a digital quality audit form for matching and the level of conformity between the implementation of higher education standards and the standards set, the benefit is to help universities implement digital and intelligent based internal quality audits, know the tri dharma standards of higher education that must be improved, maintained and deviated]]>
<![CDATA[New Paradigm E-Learning Model Based on Artificial Intelligence: New Paradigm E-Learning Model Based on Artificial Intelligence ]]>
<![CDATA[Relita Buaton]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Mesra Yel]]>
<![CDATA[ Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 2 No. 1 (2022): October 2022 ]]>
Publisher : <![CDATA[Yayasan Kita Menulis ]]>
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<![CDATA[This research concerns the application of a new paradigm learning that provides flexibility for educators to formulate learning designs and assessments according to the characteristics and needs of students. To improve the quality of education in Indonesia, the government has made various breakthroughs and most recently is a new paradigm learning system to create a Pancasila student profile that accommodates all differences in students, is open to all and provides the needs needed by each individual. Therefore an application system is needed to support learning a new paradigm based on artificial intelligence, artificial intelligence plays a role in knowing the level of abilities and needs of students and follow-up learning according to the needs and abilities of students available in online learning media. With the e-learning application, a new paradigm based on intelligence is produced by smart adaptive e-learning that can accommodate each individual or student with a background of different levels of abilities, weaknesses, talents and interests with artificial intelligence and machine learning technology approaches that will identify students with a diagnostic assessment that is used as a recommendation for planning learning according to the needs and abilities of students]]>
