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Penerapan Decision Support System Dalam Menentukan Dosen Terbaik Prodi PG PAUD Menggunakan Metode AHP Hardianto, Roki; Wiza, Fana; Choiriah, Wirdah
Indonesian Journal of Computer Science Vol. 10 No. 2 (2021): Oktober 2021
Publisher : STMIK Indonesia Padang

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

Abstract

This study describes the application of a decision support system in determining the best lecturers for PAUD PG Study Program using the AHP method. The results of this study can be a reference and recommendation for the best lecturers in the Early Childhood Education Teacher Education Study Program (PG-PAUD) Faculty of Teacher Training and Education (FKIP) Lancang Kuning University. There are at least 5 criteria used in this DSS including education, functional position, rank / class, lecturer certification and scientific journals. All criteria are taken from lecturer data published online/online. The results of this study are the best lecturers who become recommendations to the leadership of FKIP or the head of the PG PAUD study program in evaluating resources. The output of this research is a journal published in a national journal.
IbM Penguatan Pemahaman Office Perkantoran Kepada Guru SD Negeri 59 Pekanbaru Roki Hardianto; Fana Wiza; Wirdah Choiriah
Diklat Review : Jurnal manajemen pendidikan dan pelatihan Vol 4 No 1 (2020)
Publisher : Komunitas Manajemen Kompetitif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35446/diklatreview.v4i1.437

Abstract

Pengabdian Kepada Masyarakat merupakan wujud nyata pengabdian tenaga pendidik (dosen) perguruan tinggi. SD Negeri 59 Pekanbaru adalah salah satu dari beberapa sekolah yang ada di Pekanbaru tenaga pengajar belum memahami dan menguasai penggunaan office perkantoran. Padahal dalam pekerjaannya sebagai guru tidak lepas dari penggunaan office perkantoran untuk laporan kepada sekolah, dinas pendidikan dan pihak terkait. Ketika diakhir semester saat pelaporan kegiatan para guru lebih memilih menyewa orang untuk penyelesaikan laporan. Seharusnya guru harus menyelesaikan tugasnya sendiri, berguna untuk menciptakan personalia yang cakap dalam suatu instansi. Kepala SD Negeri 59 Pekanbaru menyambut baik kegiatan pengabdian kepada masyarakat oleh universitas lancing kuning. Pelatihan dilaksanakan dengan metode seminar, praktek dan tanya jawab. Pelatihan difokuskan kepada penggunaan Microsoft word, excel dan powerpoint. Pelatihan diawali dengan pemaparan materi kemudian dilanjutkan dengan proses tanya jawab dan praktek langsung penggunaan Microsoft Office Perkantoran. Diakhir kegiatan dilaksanakan prosesi foto bersama sebagai media promosi dan luaran laporan Pengabdian Kepada Masyarakat oleh pemateri/dosen dan promosi bagi SDN 59 Pekanbaru.
Sistem Informasi Pengarsipan Instrumen Akreditasi Perguruan Tinggi Bayu Febriadi; Fana Wiza; Pandu Pratama Putra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i1.110

Abstract

At Lancang Kuning University, there were no facilities that could be used in the preparation of university accreditation instruments, while the need for accreditation data was greatly needed by the academics of the yellowish university in the preparation of accreditation instruments for universities and study programs so that they were still having difficulty filing and presenting form data information, plans strategic and operational and self-evaluation plan along with the documents needed during the visitation activity by the assessor of the National Accreditation Board of Higher Education (BAN-PT). With the use of information technology in the application of computerized based applications for filing and presenting accreditation data needs, it is expected to help the academic community more quickly and precisely in the data processing instrument for accreditation. It is expected that with the development of archiving applications and the presentation of accreditation instruments with the completion of the System Development Lyfe Cycle (SDLC) method in the problem analysis phase, the applications built can improve the quality of accreditation instruments in data processing that are well integrated and can be utilized at any time by the community the Lancang Kuning university.
SOSIALISASI PENGISIAN SISTER BAGI DOSEN PESERTA SERTFIKASI DOSEN TAHUN 2020 Roki Hardianto; Wirdahchoiriah Wirdahchoiriah; Fana Wiza
Jurnal Pengabdian Masyarakat Multidisiplin Vol 4 No 1 (2020): Oktober
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/jpm.v4i1.1404

Abstract

This activity is to provide assistance to the group of Lancang Kuning University lecturers, especially to the lecturers participating in the Phase I lecturer certification in 2020. The service team will explain the techniques and methods of collection starting with explaining the functions of the Sister application (www.sister.unilak.ac.id ) for lecturers both lecturer certification participants and certified lecturers. Certification participants must enter their personal data, educational history, functional position history, education implementation history, research history, service history and other supporting data. All participants explained the rules in the process of inputting data, especially the maximum size of data that can be input up to a quick trick in order to be able to input data themselves on the application. Of the 10 faculties at Lancang Kuning University, 72 lecturers can continue at stage D3 to stage D4. Whereas at stage D5 only 51 lecturers were able to proceed because of the selection process for the assessment of the system. The dedication team made WAG in guiding the data system input process in the framework of the certification process. This is done so that they can monitor and assist if there are obstacles in the certification process.
Analisis Data Lulusan dengan Data Mining untuk Mendukung Strategi Promosi Universitas Lancang Kuning Elvira Asril; Fana Wiza; Yogi Yunefri
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 6 No. 2 (2015): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.47 KB) | DOI: 10.31849/digitalzone.v6i2.94

Abstract

Abstrak- Setiap perusahaan maupun organisasi yang ingin tetap bertahan perlu untuk menentukan strategi promosi yang tepat. Penentuan strategi promosi yang tepat akan dapat mengurangi biaya promosi dan mencapai sasaran promosi yang tepat. Salah satu cara yang dapat dilakukan untuk penentuan strategi promosi adalah dengan menggunakan teknik data mining. Teknik data mining yang digunakan dalam hal ini adalah dengan menggunakan algoritma Clustering K-Means. Clustering merupakan pengelompokkan record, observasi, atau kasus ke dalam kelas-kelas objek yang mirip. K-Means adalah metode klaster data non-hirarkis yang mencoba untuk membagi data ke dalam satu atau lebih klaster. Penelitian dilakukan dengan mengamati beberapa variabel penelitian yang sering dipertimbangkan oleh perguruan tinggi dalam menentukan sasaran promosinya yaitu asal sekolah, daerah, dan jurusan. Hasil penelitian ini adalah berupa pola menarik hasil data mining yang merupakan informasi penting untuk mendukung strategi promosi yang tepat dalam mendapatkan calon mahasiswa baru. Kata kunci: Data Mining, Clustering, K-Means Abstract- Each company or organization that wants to survive needs to determine appropriate promotional strategies. Determination of appropriate promotional strategies will be able to reduce costs and achieve the goals the promotion of proper promotion. One way that can be done to determine campaign strategy is to use data mining techniques. Data mining techniques used in this case is to use a K-Means clustering algorithm. Clustering is the grouping of records, observation, or in the case of the object classes that are similar. K-Means is a method of non-hierarchical clustering of data that is trying to divide the data into one or more clusters. The study was conducted by observing some of the variables that are often considered by the college in determining the target of promotion that the school of origin, region, and department. Results of this study are interesting pattern of results in the form of data mining that is important information to support appropriate promotional strategies in getting new students. Keywords: Data Mining, Clustering, K-Means
PEMODELAN POLA HUBUNGAN KEMAMPUAN LULUSAN UNIVERSITAS LANCANG KUNING DENGAN KEBUTUHAN DUNIA USAHA DAN INDUSTRI Fana Wiza
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 7 No. 1 (2016): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (222.28 KB) | DOI: 10.31849/digitalzone.v7i1.518

Abstract

Abstrak- Pertumbuhan yang pesat dari gudang data telah menciptakan kondisi kaya akan data tapi miskin informasi. Data mining merupakan penambangan atau penemuan informasi baru dengan mencari pola atau aturan tertentu dari sejumlah data dalam jumlah besar yang diharapkan dapat menghasilkan pola yang menarik atau informasi penting dari kondisi tersebut. Dengan memanfaatkan data tracer lulusan yang dihubungkan dengan pengguna lulusan yakni dunia usaha dan industri, diharapkan dapat menghasilkan informasi tentang pola hubungan keduanya melalui teknik data mining, association rule. Kategori kemampuan lulusan di ukur dengan parameter tingkat kurang diperlukan, cukup diperlukan, diperlukan, dan sangat diperlukan dalam dunia usaha dan industri. Algoritma yang digunakan adalah algoritma apriori, informasi yang ditampilkan berupa nilai support dan confidence dari masing-masing kategori jenis kemampuan lulusan. Kata kunci: data mining, association rule, tracer lulusan, algoritma apriori Abstract- The rapid growth of the data warehouse has created conditions for rich data but poor information. Data mining is the mining or the discovery of new information by looking for certain patterns or rules of a number of large amounts of data that is expected to produce an interesting pattern or important information from the condition. By utilizing the the graduate tracer data that is associated with users of graduates, they are business and industry, are expected to produce information about the pattern of their relationship through data mining techniques, association rule. Category ability of graduates in measuring the level parameter is less necessary, reasonably necessary, needed, and is needed in the world of business and industry. The algorithm used is a priori algorithm, the information displayed in the form of support and confidence values of each category type abilities of graduates. Keywords: data mining, association rule, graduate tracer, apriori algorithm
Penerapan Data Mining Untuk Menggali Informasi Tersembunyi Dalam Big Data Nilai Mata Kuliah Elvira Asril; Fana Wiza; Taslim Taslim
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 7 No. 2 (2016): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.084 KB) | DOI: 10.31849/digitalzone.v7i2.604

Abstract

Abstrak- Jarang sekali perguruan tinggi melihat kompetensi lulusannya sebelum dilepas ke dunia nyata. Salah satu variabel yang bisa digunakan adalah nilai matakuliah yang telah diperoleh mahasiswa atau calon lulusan. Kemudian memetakan nilai matakuliah yang telah diperoleh tiap mahasiswa atau calon lulusan pada aspek kompetensi dasar lulusan Strata satu Informatika yang disusun oleh asosiasi perguruan tinggi komputer (APTIKOM) dengan menggunakan teknik data mining. Pemetaan dilakukan berdasarkan nilai matakuliah yang telah ditempuh oleh mahasiswa atau calon lulusan, dalam hal ini objek penelitian adalah mahasiswa angkatan 2012 s/d 2015 yang telah mencapai 120 sks. Daftar aspek kompetensi dasar yang digunakan adalah aspek kompetensi yang disusun oleh APTIKOM berdasarkan ACM/IEEE 2013. Kemudian dilakukan penentuan kelompok matakuliah pada tiap kompetensi tersebut. Topik-topik yang dikaji antara lain meliputi : database, data mining, association rule, apriori dan beberapa algoritma lain yang mungkin dapat digunakan, serta perangkat lunak yang digunakan untuk proses mining. Pengolahan data yang telah disiapkan menggunakan beberapa perangkat lunak bantu seperti Excel, dan Tanagra. Mining data yang telah dilakukan menghasilkan informasi mengenai kompetensi dari calon lulusan yang dapat digunakan sebagai bahan analisa untuk pengambilan keputusan. Kata kunci : kompetensi, informasi, nilai mata kuliah Abstract- Rarely college graduates look competence before being released into the real world. One of the variables that can be used is the value of the courses that have been acquired or prospective graduate students. Then mapping the value of the courses that have been taken by each student or graduate candidates on the basis of competence of graduates Strata aspects of the Information compiled by the association of colleges computer (APTIKOM) using data mining techniques. Mapping is done based on the value of the courses that have been taken by students or prospective graduates, in this case the object of study is the student of 2012 s / d in 2015 which has achieved 120 credits. List aspects of basic competencies that are used are compiled by the competence aspect APTIKOM based ACM / IEEE 2013. Then is the determination of subjects in each group that competency. Topics to be studied include: databases, data mining, association rule, a priori and some other algorithm that may be used, as well as the software used to process mining. Processing of the data which has been prepared using some assistive software such as Excel, and Tanagra. Data mining has been done to produce information concerning the competence of prospective graduates who can be used as material analysis for decision making. Keywords: competence, information, mark
Association rule mining untuk menemukan pola hubungan antara kendala menyusun skripsi dan kondisi psikologis mahasiswa Fana Wiza; Mariza Devega; Susi Handayani
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 9 No. 2 (2018): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (754.365 KB) | DOI: 10.31849/digitalzone.v9i2.1956

Abstract

Sebagian besar mahasiswa cenderung mengalami kendala dalam menyusun skripsi. Hanya sebagian mahasiswa yang berhasil mencapai tahap ujian komprehensif. Kendalanya adalah sulitnya membagi waktu antara skripsi dan aktivitas lain, sulitnya menemui dosen, sulitnya memperoleh sumber referensi, dan kurangnya sarana dan prasarana sehingga mempengaruhi kondisi psikologis mahasiswa. Beberapa mahasiswa mengalami gejala stres. sejak proses bimbingan skripsi dimulai. Penelitian ini bertujuan untuk memperoleh pola dari kendala menyusun skripsi dengan kondisi psikologis mahasiswa menggunakan association rule mining dengan algoritma apriori. Dalam konteks IPTEKS, penelitian ini bertujuan untuk mengembangkan bidang kajian data mining tentang kemampuan algoritma apriori ke arah bidang psikologi. Pola yang dihasilkan akan menggambarkan sebab akibat yaitu kendala utama apa yang dialami mahasiswa skripsi dan gejala stress yang dialami. Hal ini dapat menjadi pertimbangan mahasiswa, dosen pembimbing dan bagian akademik mencari solusi sekesainya skripsi tepat waktu. Proses analisis ini juga membuktikan bahwa association rule mining dengan apriori tidak hanya mampu menangani data belanja tetapi juga mampu menangani data bidang lainnya.” Kata kunci : komprehensif, stress, skripsi, apriori, psikologi Abstract "Most students tend to experience problems in writing a thesis. Only some students who successfully reach the comprehensive examination stage. The problem is the difficulty of dividing the time between thesis and other activities, the difficulty of meeting lecturers, the difficulty in obtaining reference sources, and the lack of facilities and infrastructure that affect the psychological condition of students. Some students experience stress symptoms. since the thesis guidance process begins. This study aims to obtain a pattern of constraints in composing a thesis with the psychological condition of students using association rule mining with a priori algorithms. In the context of science and technology, this study aims to develop a field of data mining studies about the ability of a priori algorithms towards the field of psychology. The resulting pattern will describe the cause and effect of the main constraints experienced by the thesis student and the symptoms of stress experienced. This can be considered by students, supervisors and the academic section to find solutions to complete their thesis on time. This analysis process also proves that association rule mining with a priori is not only able to handle shopping data but also able to handle other field data." Keywords: comprehensive, stress, thesis, a priori, psychological
Klasterisasi karakteristik kekerasan seksual terhadap anak dengan metode k-means cluster analysis Fana Wiza
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 10 No. 1 (2019): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.208 KB) | DOI: 10.31849/digitalzone.v10i1.2423

Abstract

“Kekerasan seksual terhadap anak sudah termasuk masalah yang sangat meresahkan di masyarakat khususnya kota Pekanbaru. Semakin banyaknya kasus tindakan kekerasan seksual terhadap anak, maka perlu mencari solusi dan sebuah pengetahuan baru untuk mengatasi permasalahan ini dengan menggali data kasus disertai karakteristik jenis kekerasan, range usia dan faktor pemicu menggunakan algoritma K-Means untuk menghasilkan pola cluster yang terbentuk berdasarkan kedekatan kriteria antar variabel. Teknik yang digunakan dalam aplikasi data mining ini adalah teknik Clustering dengan algoritma K-Means. Algoritma K-Means ini melakukan proses iterasi untuk menghasilkan pola kelompok berdasarkan kedekatan kriteria yang mirip. Teknik ini membantu menganalisis data kasus kekerasan seksual terhadap anak berjumlah 335 data kasus. Melalui data tersebut diperoleh hasil sebanyak 3 cluster. Cluster yang mendominasi adalah cluster 1 dengan kriteria jenis kekerasan seksual pencabulan pada anak di range usia 3 sampai dengan 16 tahun dengan faktor pemicu terbesar adalah kesempatan.” Kata kunci : kekerasan, seksual, k-means, clustering, data mining. Abstract “Sexual violence against children is one of the most troubling problems in the community, especially in Pekanbaru. The more cases of acts of sexual violence against children, it is necessary to find a solution and a new knowledge to overcome this problem by exploring case data along with the characteristics of violence, age range and trigger factors using the K-Means algorithm to produce cluster patterns based on the proximity of criteria variable. The technique used in data mining applications is the Clustering technique with the K-Means algorithm. This K-Means algorithm performs an iterative process to produce group patterns based on similar criteria proximity. This technique helps analyze data on cases of sexual violence against children totaling 335 case data. Through these data, there are 3 clusters of results. The cluster that dominates is cluster 1, with the criteria for the types of sexual abuse sexual abuse for children in the age range of 3 to 16 years with the greatest trigger factor is opportunity.” Keywords: violence, sexual, k-means, clustering, data mining.
Sistem Informasi Pengarsipan Instrumen Akreditasi Perguruan Tinggi Bayu Febriadi; Fana Wiza; Pandu Pratama Putra
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (760.5 KB) | DOI: 10.30645/j-sakti.v3i1.110

Abstract

At Lancang Kuning University, there were no facilities that could be used in the preparation of university accreditation instruments, while the need for accreditation data was greatly needed by the academics of the yellowish university in the preparation of accreditation instruments for universities and study programs so that they were still having difficulty filing and presenting form data information, plans strategic and operational and self-evaluation plan along with the documents needed during the visitation activity by the assessor of the National Accreditation Board of Higher Education (BAN-PT). With the use of information technology in the application of computerized based applications for filing and presenting accreditation data needs, it is expected to help the academic community more quickly and precisely in the data processing instrument for accreditation. It is expected that with the development of archiving applications and the presentation of accreditation instruments with the completion of the System Development Lyfe Cycle (SDLC) method in the problem analysis phase, the applications built can improve the quality of accreditation instruments in data processing that are well integrated and can be utilized at any time by the community the Lancang Kuning university.