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INDONESIA
Jurnal Teknologi dan Manajemen Informatika
Published by Universitas Merdeka Malang
ISSN : 16936604     EISSN : 25808044     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Jurnal Teknologi dan Manajemen Informatika (JTMI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Merdeka Malang. JTMI terbit 2 edisi per tahun pada Januari - Juni dan Juli - Desember dengan scope ilmu komputer yang mencakup teknologi informasi, sistem informasi, dan manajemen informatika.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 4, No 1 (2018): Mei 2018" : 6 Documents clear
Penerapan Metode SDLC Waterfall Dalam Pembuatan Sistem Informasi Akademik Berbasis Web Studi Kasus Pondok Pesantren Al-Habib Sholeh Kabupaten Kubu Raya, Kalimantan Barat Yoki firmansyah; Udi Udi
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (690.776 KB) | DOI: 10.26905/jtmi.v4i1.1605

Abstract

Academic Information System is one of the information that is needed by educational institutions as one As reference for the development and achievement of teaching and learning activities. Academic information systems can also spur teachers to be more transparent in delivering learning outcomes to students and also spur students in improving learning outcomes, so that has more meaning as a communication between teachers and students. This system will also spur all to know the development of boarding school because the existing information system at Al-habib Pondok Pesantren Sholeh Bin Alwi Alhaddad, Currently, Alhabib use the manual system to data processor ex stundents, assessment and processing of academic information. With the existence of this academic information system it will facilitate the admin to provide academic information, facilitate the teacher in providing assessments of students didiknya more easily and transparently, facilitate students and parents learn mngetahui student development. The website also has feature  facilitate all obtain information relating to boarding school and will further spur all in using the internet by accessing the academic website of Pesantren Al-habib sholeh Bin Alwi Al-haddad.
APLIKASI PENGELOMPOKAN PELANGGAN PADA UMS STORE MENGGUNAKAN ALGORITMA K-MEANS MUHAMMAD ABDUL GHOFAR; YOGIEK INDRA KURNIAWAN
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.809 KB) | DOI: 10.26905/jtmi.v4i1.1772

Abstract

UMS Store is an official trading business unit owned by Muhammadiyah University of Surakarta that provides various categories of books, journals, office stationery and official marchandise. UMS Store is also a voucher exchange center for students. Of the many voucher redemption transactions and cash purchases, UMS Store has abundant data and will continue to grow over time. The abundant data if left unchecked would be a pile of only stored data. Actually, if the data is excavated will produce valuable information. UMS Store need a customer grouping application that will be used to provide continuous treatment such as giving discounts or vouchers to their best customers. This research is done to create the application, where application can make customer grouping with UMS Store data and can give recommendation through potential group that formed. This application was developed by utilizing K-means algorithm, which is one of clustering method in data mining technique. Groupings made in the application are limited to 3 large groups of data with restrictions using only student data using UMS Store vouchers. Variables used consist of NIM, year force, discount, sub total, total paid, total item and date.The results of this study is an application used to classify customers using K-means method. The results of this study indicate that if the application is used to create three groups, it will form three clusters, ie clusters of potential customers, normal customers and unlikely customer clusters.DOI: https://doi.org/10.26905/jtmi.v4i1.1772
PERBANDINGAN ALGORITMA NAZIEF & ADRIANI DENGAN ALGORITMA IDRIS UNTUK PENCARIAN KATA DASAR Adhi Prasidhatama; Kristien Margi Suryaningrum
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3267.451 KB) | DOI: 10.26905/jtmi.v4i1.1773

Abstract

Stemming is a process used to search root words. Stemming can be implemented as preprocessing in text processing. There are many stemming algorithms, one of them is Nazief Adriani and Idris. Nazief Adriani algorithm is an algorithm created by Bobby Nazief and Mirna Adriani to find the root word of Bahasa Indonesia. While the Idris algorithm is an algorithm created by Norisma Idris to find the root words of Malay language. Indonesian and Malay have similar language styles, so researchers want to find out whether the Idris algorithm can be used as one of the Indonesian stemming algorithms. To know which algorithm is better, then in this research will be explained about process speed and accuracy of result of each of those algorithm. After knowing the result of comparison of stemming algorithm, hopefully can help you in choosing which algorithm will be used for find root word of Bahasa Indonesia.DOI: https://doi.org/10.26905/jtmi.v4i1.1773
Aplikasi Prediksi Kelayakan Calon Anggota Kredit Menggunakan Algoritma Naïve Bayes Diky Alfian Kurniawan; Yogiek Indra Kurniawan
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.634 KB) | DOI: 10.26905/jtmi.v4i1.1831

Abstract

Sebagai lembaga keuangan selain bank konvensional, koperasi mempuyai peran serta dalam mengatasi perekonomian masyarakat didaerah-daerah. Kegiatan tersebut juga dilakukan oleh Koperasi Simpan Pinjam Pembiayaan Syariah Baitul Maal wa Tamwil (KSPPS BMT) “Arta Jiwa Mandiri” Wonogiri yang bergerak dalam bidang usaha kredit simpan pinjam dan pembiayaan yang berlandaskan syariah. Pada proses bidang usaha kredit simpan pinjam koperasi memiliki ketentuan dalam memilih calon anggota yang layak untuk mendapatkan modal. Hal tersebut bertujuan untuk mengatasi adanya permasalahan seperti anggota macet dalam pembayaran cicilan. Sehingga hal tersebut perlu adanya suatu aplikasi yang dapat meprediksi calon anggota kredit yang layak untuk mendapatkan pinjaman dari pihak koperasi dengan teknik data mining. Algoritma Naïve Bayes dimanfaatkan dalam kasus ini untuk memprediksi kelayakan calon anggota kredit simpan pinjam yang nantinya termasuk kategori lancar, kurang lancar atau macet waktu peminjaman. Hasil penelitian ini mendapatkan nilai Accuracy sebesar 75%, nilai Precision sebesar 84% dan nilai Recall sebesar 86%. Maka dari itu aplikasi ini dapat membantu pihak koperasi dalam mempertimbangkan calon anggota kredit yang layak untuk mendapatkan modal. DOI: https://doi.org/10.26905/jtmi.v4i1.1831
APLIKASI KLASIFIKASI PENERIMA KARTU INDONESIA SEHAT MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER Aziz Abdul Rahman; Yogiek Indra Kurniawan
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (454.914 KB) | DOI: 10.26905/jtmi.v4i1.1870

Abstract

Along with the rapid development of information technology today, the cost to meet the needs of life increasingly high, this is triggered by the amount of budget issued by the government to solve economic problems in Indonesia, especially in terms of National Welfare Guarantee. Kartu Indonesia Sehat is a card issued by the government and managed by the Badan Penyelenggara Jaminan Sosial (BPJS) to alleviate the poor for health. Existing problems such as in the distribution of the card has not been on target because of the amount of data obtained so highly possible error happens in determining the recipient of Kartu Indonesia Sehat. The concept of data mining is considered to solve the problems faced in determining the recipient community or not the recipient of Kartu Indonesia Sehat. Classification methods are able to find models that distinguish the concepts or data classes, with the spesific goal of determining the class of an unknown object label. Therefore, the Naïve Bayes algorithm could predict future opportunities based on prior experience by considering some variables such as age, last education, occupation, monthly income and dependents of children that will determine the final outcome of a decision. The result of this research is a system that will predict the people who will receive Kartu Indonesia Sehat so that the government will distribute the card accurately to the public and the acquired results from the test obtained an average accuracy rate of 94.78%, 98.86% precision and 90.98% recall.DOI: https://doi.org/10.26905/jtmi.v4i1.1870
IMPLEMENTASI DATA MINING DENGAN ALGORITMA APRIORI UNTUK MEMPREDIKSI TINGKAT KELULUSAN MAHASISWA Irham Kurnawan; Fitri Marisa; Purnomo Purnomo
Jurnal Teknologi dan Manajemen Informatika Vol 4, No 1 (2018): Mei 2018
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1174.307 KB) | DOI: 10.26905/jtmi.v4i1.1894

Abstract

Informatics Engineering Program University of Widyagama Malang has many volume of student databases. When properly excavated, so can known patterns or knowledge for a decision-making. Data that can be explored is the understanding of information about graduation students. This research to predict the passing rate of students with more efficient time, which can be known before the student graduated so that can be evaluated in their studies, especially in Informatics Engineering University of Widyagama. In this case using association methods and Apriori algorithm. This method calculates the support value that is the supporting value of an item with big golden rule 60% of the data of course grade. The results of this study to help universities improving the quality of education and help in knowing the information about the graduation rate of students based on the value of the subjects and achievement index obtained by students in Informatics Engineering course University of Widyagama MalangDOI: https://doi.org/10.26905/jtmi.v4i1.1894

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