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All Journal Jurnal Media Infotama METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Abdi Ilmu Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer MEANS (Media Informasi Analisa dan Sistem) Syntax: Journal of Software Engineering, Computer Science and Information Technology Journal Of Information And Technology Unimor (JITU) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Jurnal Widya Bulletin of Multi-Disciplinary Science and Applied Technology Journal of Computer Science and Informatics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Jurnal Pengabdian Pada Masyarakat METHABDI International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Indonesian Journal of Education And Computer Science Indonesian Journal of Science, Technology, and Humanities Nusantara Journal of Multidisciplinary Science Jurnal Penelitian Teknologi Informasi dan Sains Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Saturnus: Jurnal Teknologi dan Sistem Informasi Pascal: Journal of Computer Science and Informatics
Yani Maulita
STMIK Kaputama
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Application Of Data Mining Classification Of Student Ability In Learning Using The K-Means Clustering Algorithm Method (Case Study : Sd Negeri 056029 Karya Utama) Ika Indah Rahayu; Yani Maulita; Husnul Khair
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (690.073 KB) | DOI: 10.55227/ijhet.v1i3.47

Abstract

The high level of student success and the low level of student failure is a quality of the education world. The world of education is currently required to have the ability to compete by utilizing all resources owned. In addition to facilities, infrastructure and human resources, information systems are one of the resources that can be used to improve competency skills. Data mining is a process of data analysis to find a dataset of data sets. Data mining is able to analyze large amounts of data into information that has meaning for decision supporters. One process of data mining is clustering. Attributes used in the grouping of student achievement are Name, Extracurricular, Value which include UAS Value, . The case study of 20 students with distance calculation using manhattan distance, chbychep distance and euclidian distance yielded 67% accuracy. Keywords: data mining, clustering, k-means, student achievement
Application of Clustering Method For Customer Royal Data Grouping at CV. Garuda Mas Motor Binjai Putri Ladya Elvanny; Budi Serasi Ginting; Yani Maulita
International Journal of Health Engineering and Technology Vol. 1 No. 3 (2022): IJHET-SEPTEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (918.077 KB) | DOI: 10.55227/ijhet.v1i3.69

Abstract

Communication is a very important activity. Communication is carried out with the aim of exchanging information between several individuals. Communication can be done in various ways. Those who wish to communicate with each other can meet in person or through intermediaries. There are several types of media that function as intermediaries of information. You can use several media such as print media, electronic media, and online media to get various information. Digital communication in the modern era is not far from the Internet because almost all digital communication tools use the Internet. Internet needs vary greatly from old to young, because Internet needs are different, connection management is needed (Management Bandwidth) so that client requests with high connections do not interfere with clients with relatively low connection requests. One of the tools commonly used for connection management is MikroTik with the Peer Connection Queue (PCQ) feature. The reason for choosing Mikrotik is because Mikrotik has complete features at an affordable price. The importance of connection management is to maximize the connection provided by the ISP so that clients can use the Internet without buffering.
Decision Support System For Submitting Work Leave Using The Vikor Method Muhammad Rivaldi Prastowo; Yani Maulita; Suci Ramadani
International Journal of Health Engineering and Technology Vol. 1 No. 4 (2022): IJHET-NOVEMBER 2022
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.847 KB) | DOI: 10.55227/ijhet.v1i4.90

Abstract

Human resources have an important role in an office, namely as the spearhead for carrying out the organization's activities, because after all the progress and success of a company cannot be separated from the role and capabilities of good human resources. This study aims to determine the effect of work motivation (X1) and work ability (X2) variables partially and simultaneously on employee performance (Y). This type of research is explanatory research with a quantitative approach and is carried out using the genetic method. Genetics is a search technique that in computer science to find approximate solutions for optimization and Genetic search problems are particularly applied as computer simulations in which a population of abstract representations (called chromosomes) of candidate solutions (called individuals) to an optimization problem develops into a solution. - a better solution. This research was conducted on 40 permanent employees of the Binjai City Regional Civil Service Agency.
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, Januari 2020
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v4i1.351

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.
ANALISA ALGORITMA ELGAMAL DALAM PENYANDIAN DATA SEBAGAI KEAMANAN DATABASE Winda Sari; Yani Maulita; Achmad Fauzi
Jurnal Informatika Kaputama (JIK) Vol 2 No 1 (2018): Volume 2, Nomor 1, Januari 2018
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v2i1.433

Abstract

Perkembangan dunia informasi saat ini semakin cepat memasuki berbagai bidang, yang berusaha memanfaatkan teknologi informasi masa kini. Masalah keamanan dan kerahasiaan database merupakan salah satu aspek penting dari suatu sistem informasi. Sebuah informasi hanya ditujukan bagi pihak – pihak tertentu, hal tersebut terkait dengan bagaimana informasi tidak dapat di akses oleh orang yang tidak berhak. File Database adalah kumpulan file-file yang mempunyai kaitan antara satu file dengan file yang lain sehingga membentuk satu bangunan data untuk menginformasikan satu perusahaan, instansi dalam batasan tertentu untuk membentuk data baru dan informasi. Algoritma Elgamal merupakan algoritma yang diperkuat logaritma diskritnya dengan berdasarkan konsep kunci publik. Algoritma ini pada umumnya digunakan untuk digital signature, kemudian dimodifikasi sehingga bisa digunakan untuk enkripsi dan dekripsi. Pada proses ekripsi database Pesan tersebut sebelumnya harus dikonversikan dalam kode ASCII terlebih dahulu karena algoritma ElGamal menggunakan bilangan bulat dalam perhitungannya. Pesan yang dienkripsi tersebut kemudian dikirimkan kepada penerima pesan yang mempunyai kunci rahasia untuk mendekripsikan pesan yang telah dienkripsi. Keamanan algoritma Elgamal secara teknis terletak pada kesulitan perhitungan logaritma diskrit pada modulo prima yang besar, sehingga upaya untuk menyelesaikan masalah logaritma ini menjadi sulit untuk dipecahkan. Dengan menggunakan metode Algoritma Elgamal, proses enkripsi file database yang akan di enkripsi adalah isi data pada tabel (cipherteks), file database masih dapat dibuka dan dilihat akan tetapi isi data pada tabel tidak bisa dibaca, kemudian proses dekripsi untuk mengembalikan file database yang telah di enkripsi kembali menjadi file awal (plainteks).
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 (2017): Volume 1, Nomor 1, Januari 2017
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v1i1.439

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 relatif rendah, namun ada siswa yang walaupun kemampuan inteligensinya relatif rendah tetapi dapat meraih prestasi belajar yang relatif tinggi. Itu sebabnya taraf inteligensi bukan merupakan satu-satunya faktor yang menentukan keberhasilan 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 yang digunakan adalah analisis pola frekkuensi tinggi dan pembentukan aturan asosiasi. Hasil yang ditemukan adalah faktor-faktor yang paling sering terjadi dan yang paling banyak muncul secara bersamaan adalah kemampuan siswa untuk mengenal emosi diri mau bertanggung jawab atas kesalahan yang dilakukan dan kemampuan siswa untuk memotivasi diri sendiri mau mendahulukan belajar daripada bermain dan mau memperbaiki kegagalan menjadi suatu keberhasilan dan kemampuan siswa untuk mengenal emosi orang lain mau mendengar keluh kesah teman dan Afektif mengikuti nilai-nilai yang telah ditentukan then Psikomotorik siswa ulet dalam mengikuti latihan dengan nilai Support 90% dan Confidence 100%.
PENERAPAN DATA MINING PENGELOMPOKAN PESERTA BPJS KETENAGAKERJAAN BERDASARKAN PROGRAM YANG DIAMBIL MENGGUNAKAN METODE CLUSTERING Zema; Yani Maulita; Lina Arliana
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i2.166

Abstract

The implementation of the social security program is one of the responsibilities and obligations of the State, to provide socio-economic protection to the community. Indonesia, like other developing countries, develops social security programs based on funded social security, namely social security that is funded by participants and is still limited to working people in the formal sector. BPJS Ketenagakerjaan continues to improve competence in all aspects of service while developing various programs and benefits that can be directly enjoyed by workers and their families. Non-Wage Recipient Workers (BPU) are employees who carry out economic activities or businesses independently to earn income from their activities or business. The problem that hinders the length of data collection for BPJS Employment participants is the process of determining the social security program that will be taken by Non-Wage Recipient (BPU) workers from the program taken by BPJS Ketenagakerjaan participants. owned is very small and only enough for the daily needs of participants. Data Mining is a data mining process in very large amounts of data using statistical, and mathematical methods, and utilizing the latest Artificial Intelligence technology. Data mining in the process of grouping data can use a grouping method, namely the Clustering method. The system is designed with the MATLAB R2014a programming application, after testing with the system, the results obtained are that in group 1 there are 370 data, group 2 there are 359 data and group 3 there are 271 data with a total of 100 data participants.
Pemamfaatan Metode Clustering Pada Nasabah Peminjaman Modal (Studi Kasus: PT. Faderal International Finance Binjai) Wildan Yuanda Malik Sembiring; Yani Maulita; Suci Ramadani
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i2.191

Abstract

Peminjaman modal merupakan transaksi tersepakati dari dua belah pihak bermaksud meminjan uang/dana kepada seseorang atau badan usaha peminjaman. PT. Faderal International Finance Binjai sebagai salah satu satu badan usaha yang bergerak di bidang keuangan atau jasa keuangan yang menyediakan peminjaman modal dengan menjaminkan surat berhaga sebagai penjamin Dalam rekapitulasi data nasabah dalam pengelompokkan nasabah untuk mengetahui jumlah nasabah dalam peminjaman modal sering dilakukan secara komputerisasi bahkan manual yang mengakibatkan sulit dalam pengelompokkan dan mengetahui jumlah nasabah. Pada penelitian ini dalam Pemamfaatan Pada Nasabah Peminjaman Modal menggunakan metode clustering dalam nilai yang di hasilkan menggunakan program mendapatkan hasil yang berbeda - beda pada penggunaan cluster 2 dan cluster 3. maka dapat di simpulkan penggunaan metode clustering mampu mengelompokkan data nasabah peminjaman modal di PT. Faderal International Finance Binjai.
Application of the Certainty Factor Method for Diagnosing Mental Illness Disease Alta Mirah; Yani Maulita; Magdalena Simanjuntak
International Journal of Informatics, Economics, Management and Science (IJIEMS) Vol 2 No 2 (2023): IJIEMS (August 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v2i2.1208

Abstract

Mental illness is a disease that is widespread among Indonesian people. Mental illness, also known as mental health disorder, is a term that refers to various conditions that can affect a person's thoughts, moods, feelings or behavior. However, there are still many Indonesian people who do not recognize and indicate the existence of mental illness because many people do not pay attention to their mental health or those around them. the small number of psychiatrists available in each area and the costs required are also not small, causing ordinary people to be reluctant to carry out examinations with psychiatrists, this of course leads to delays in treatment which can even be fatal. To prevent the increase in sufferers of mental illness, a system is needed that can store the knowledge of experts or psychologists who understand how to handle mental illness. An expert expert system is an artificial intelligence program that combines a knowledge base with an inference system to emulate an expert. The certainty factor method is a method used to solve cases of uncertainty, where the size is based on a fact or rule that can be used in expert systems. With the existence of an expert system for diagnosing mental illness, the general public can recognize early symptoms of mental illness, so treatment can be done earlier. From the results of the trials conducted, the results of the mental illness expert system were obtained with the highest score, namely depression with a confidence value of 90.02%.
Identification of Longan Species Based on Leaf Shape Texture and Color Using KNN Classification Setia Adiyasa Lubis; Yani Maulita; Mili Alfhi Syari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.238

Abstract

This study aims to identify the type of longan based on the shape, texture and color of the leaves using KNN classification. With a method that can identify the type of longan automatically, farmers and researchers can obtain information more quickly and accurately about the type of longan that is being cultivated or studied. This can help in choosing the right variety, more efficient maintenance, and improve the quality and productivity of longan plants. This research is an experimental research consisting of eight steps, namely preparation, theoretical studies, data collection, data analysis and processing, testing and implementation and the last is the final stage. Based on research conducted at UD Mitra Tani on Jalan Madura No. 81 Kebun Lada, Kec. Binjai Utara, Binjai City, North Sumatra, the results of data analysis from longan leaves show that the most common type of longan found in the nursery is Red longan. This study was conducted to identify the dominant longan species in the population and gain a deeper understanding of the diversity of longan varieties in the region.
Co-Authors , Achmad Fauzi ., Novriyenni Achmad Fauzi Acmad Fauzi Agi Kakana Bangun Ahmad Fauzi Ahmad Kurniawan Prahadi Alanis Humairoh Alfinaty, Nurma Alta Mirah Ambarita, Indah Andika, Rio Andri Kristiawan Arisma Yulistiani Arisya, Feby Arliana, Lina Aula, Nurhasanah Aulia, Damai Aulia Br Karo Ayu Rahayu Febria Ayu Rahayu Febria Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Budi Serasi Ginting Chairmayni Pratiwi Tiwi Citra Ayu Wasih Dea Syafitri Dhea Armaya Diah Wardhani Wardhani Dicky Ananda Azhari Dieo Alfiky Ananda Dila Aulia Putri Dimas Prayogi Dina Ervianna Simarmata Dita Sahputri Elfira Iriani Esti Sundari Eva Sasmita Farid Reza Malau Farid Reza Malau Farida Hanum Fauzi, Achmad Fauziah Ningsih Fisyanda Yusmalizar Fresti Anjeli Gea, Wisda Wati Gultom, Imeldawaty Hafizh, Faisal Hermansyah Sembiring Hermansyah Sembiring I Gusti Prahmana I Gusti Prahmana Ika Indah Rahayu Intan Sari Irfan Yusuf Jecika Azzahra Jhody Alkhalis Sembiring Kadim, Lina Arliana Nur Katen Lumbanbatu Katen Lumbanbatu Khair, Husnul Kristina Annatasia Br Sitepu Kusmananda Lubis Lala Arika Leni Tri Ramadhayanti Lina Arliana Liyanti Armaya Sari Magdalena Simanjuntak Magdalena Simanjuntak magdalena simanjuntak Magdalena Simanjuntak Magdalena Simanjuntak Malau, Farid Reza Manik, Laurensia Agustin Mariza Marto Sihombing Maskanda Rizky Maulidina, Nadia Mhd Arif Permata Mili Alfhi Syari Muhammad Prabowo Hartanta Sitepu Muhammad Rivaldi Prastowo Muhammad Yusri Nadilla Ayudia Pasa Naftali, Juliana Nisrina Naufalia Santoso Novriyenni - Novriyenni, Novriyenni Nurhayati Nursakinah Nurul Elsa Fadilah Pakpahan , Victor Maruli Pakpahan, Victor Maruli Pardede, Akim Manaor Hara Pasaribu, Tioria Piper Warni Gea Prahmana, I Gusti Puteri Diyana Putri Ladya Elvanny Putri Lestari Rafli Pramudia Rahayu, Rizka Putri Rahmat Ramadhan Ramadana, Noval Ramadani, Suci Rayuni, Rayuni Retni Noviyanti Siregar Rindi Asti Ananda Rizki Irwansyah Rizky Ramadhan Rusmin Saragih, Rusmin Salsabila Khairunisa Sari, Elisa Puspita Saripurna, Darjat Selviyani, Selviyani Sembiring, Hermansyah Sembiring, Wildan Yuanda Malik Setia Adiyasa Lubis Setia Ningsih Shella Nadya Shely Eninta BR PA Sihombing, Anton Silvia, Sindy Simanjuntak, Magdalena Sinurat, Sylvia Natalia Siregar, Retni Noviyanti Siswan Syahputra Siswan Syahputra Suci Rahmadani Suci Ramadani Suci Ramadani suci ramadani Suci Ramadani Suci Ramadani Suci Ramadani Suci Ramadani Sujayanti Br.Giniting, Novia Suma Dia Syahwani Sundari, Yeni Sundari, Yeni Suria Alamsyah Suria Alamsyah Putra Surya Alamsyah Putra Syahputra , Siswan Syahputra, Suria Alam Syahputri, Heni Syari, Milli Alfhi Tarigan, Kiki Dea Ananda Tria Damayanti Wildan Yuanda Malik Sembiring wildan yuanda malik sembiring Winda Sari Yuyun Arnia Zema Zema Zema Zema