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All Journal Jurnal Teknoin INFORMAL: Informatics Journal Jurnal Teknologi Dan Sistem Informasi Bisnis
Anief Fauzan Rozi
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Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering

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Sistem Pendukung Keputusan Seleksi Penerimaan Calon Siswa/i Baru Menggunakan Algoritma C4.5 (Studi Kasus: SDIT An-Najah Jatinom Klaten) Anief Fauzan Rozi
Teknoin Vol. 21 No. 1 (2015)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/.v21i1.3690

Abstract

Education is very important and one of the keys of the progress of a country. Basic education or elementary school is the first stage of a long journey for a student in taking his or her education. The more parents has awareness in the importance of an education so the more the parents will enroll their children to study in school. Although the number of schools in a certain place is already considered enough, admission of new students still become a unique phenomenon because number of prospective new students entering school is huge but the admission method still uses manual techniques. Whether using a test or previous level report book, the rank and decision making about the acceptance of the students is still done manually. It can also provide opportunities for certain parties to commit fraud in the admission selection from subjective point of view (outside of the fixed criteria) which makes incorrect calculation and grading so the results are not properly valid. This research would apply the rules that is formed from the decision trees on admission of new students selection process at SDIT An-Najah Jatinom Klaten. A decision tree consists of a set of rules for dividing a heterogeneous population into smaller parts, and more homogeneous with noticing to the goal variables. C4.5 algorithm is one of the algorithms used to form a decision tree. The purpose of this research is to apply the rules that are formed from the C4.5 decision tree algorithm in admission of new students selection process. The registration (log) is expected to be more structured through this system so operator can easily and quickly process the calculation and ranking the prospective new student. Service becomes more rapid, accurate, effective, and efficient in terms of time and place because the piled print files (takes place and time) can be concise (stored in the database). The results shows that the system is able to provide recommendations for the admission process based on the criteria and history that have ever happened. Based on sample data of 100 data among several criterias (religion, age, the average time from the each student’ place to the school, parents income per month, number of siblings)is is found that religious criteria have the highest gain value in the calculation of the initial node, ie by 0.367877. Finnaly, this system has been running correctly and can help the school admission committee in the selection of new candidate students.
Analisis Rekomendasi Produk Menggunakan Algoritma ECLAT Berdasarkan Riwayat Data Penjualan PT XYZ Auzan Widyan; Anief Fauzan Rozi
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 3 No 2 (2021): Juli 2021
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v3i2.296

Abstract

PT XYZ is a company that provides livestock production facilities. Sales transactions are recorded as company files, sales reports, and income statements. More than 1,500 invoices are printed every month. However, in terms of product promotion, the company have not used the analysis results from the history of sales transactions. This study aims to provide product recommendations using the ECLAT algorithm. The ECLAT (Equivalence Class Transformation) algorithm uses the concept of depth-first search to find itemsets that often appear in transactions. The research steps are interviews for data acquisition, data pre-processing, data transformation, and data mining process with the ECLAT algorithm to find frequent itemsets and use the frequent itemset results as the basis for making association rules patterns. The results of the analysis show that the system can provide recommendations for association rules effectively from 14,617 transaction history. The highest minimum support that can be used to find a combination of k-itemset is 1%. The results of the annual association rules from the transaction history in 2018-2020 show the difference in results with the highest variance occurring in 2020, namely 5 association rules. Each association rule that appears has a strong confidence value that is above 50%
Sistem Pendukung Keputusan Dalam Pemilihan Biji Kelapa Sawit Menggunakan Metode MOORA Inne Irianti Sinon; Anief Fauzan Rozi
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 3 No 2 (2021): Juli 2021
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v3i2.301

Abstract

Kelapa sawit merupakan jenis tumbuhan yang termasuk dalam keluarga tumbuhan genus elais dan arecaceae. Tumbuhan kelapa sawit banyak di tanam di Indonesia yang seb tropis. Buah kelapa sawit sendiri di fungsikan untuk diambil buahnya yang mana berfungsi sebagai bahan baku utama pembuatan minyak kelapa sawit. untuk mendapatkan hasil panen yang maksimal maka para pelaku usaha wajib memilih biji kelapa sawit terbaik, agar nantinya hasil panen yang ditentukan juga akan lebih maksimal. Berdasarakan pembahasan diatas maka didapat kan suatu masalah yaitu dalam pemilihan biji kelapa sawit yang terbaik. Berdasarkan masalah tersebut maka dibutuhkan suatu sistem informasi pendukung keputusan yang mana akan menghasilkan suatu output rekomendasi keputusan dalam pemilihan biji kelapa sawit terbaik. Dengan demikian dapat diusulkan pembuatan susatu sistem pendukung keputusan pemilihan biji kelapa sawit yang mana dalam proses perhitungannya menggunakan metode MOORA. Dari hasil uji yang dilakukan dari 5 alternatif didapatkan hasil Biji Kelapa Sawit Grad A memiliki nilai tertinggi yaitu dengan nilai 31,87.
Rekomendasi Pemilihan Minat Studi Menggunakan Metode Mamdani Studi Kasus : Program Studi Sistem Informasi FTI UMBY Anief Fauzan Rozi; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 2 No 3 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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

Abstract

Determination of the concentration / interest of study for most students can’t be applied easily. Most students still do not know exactly what their concentration is. Only for students who are smart in IPK and mature in the pattern of thinking that can determine the concentration of studies easily and not wrong target. Besides still confused and tend to choose the concentration that is not in accordance with the interests and talents of each. Confusion or the majority of students' mistakes to specialization in accordance with the ability due to the number of elective courses offered in line with the interests offered. Based on this problem, it takes a decision making tool or recommendation to the student about the concentration/interest of study whether the most appropriate according to ability. In this research will be made decision support system for recommendation of study by implementing fuzzy inference (mamdani). Where this system will provide information on the interest of the study can be selected based on the value variable. So it can help students in choosing the interests of the study in accordance with the appropriate competence and interest talent. Based on the 20 data that have been tested, obtained 19 data and 1 data that is not appropriate, thus can be calculated the performance of the system that is equal to 95%.
Rekomendasi Penentuan Target Pemasangan Iklan Facebook Ads Menggunakan Metode SAW Anief Fauzan Rozi; Suryadin Suryadin
INFORMAL: Informatics Journal Vol 4 No 2 (2019): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v4i2.10123

Abstract

In determining the interest of potential customers on Facebook, so far there are no tools and basic benchmarks as indicators that can be used as a reference for them to determine the target of online advertising. There is also no tool found in the form of software in the form of a decision support system that can help business people to process data and make decisions. The purpose of this study was to create a decision support system software for determining Facebook ads using the SAW method, with 6 criteria, namely the preferred page, likes, comments, shared, redeemed ads, ads clicked. The results of calculations using the system as well as those that have been manually calculated indicate that recreation is the best interest because it is based on a value of 14.60, with a percentage of suitability of 100%. So that the designed system can be used as a decision-making tool.
Co-Authors Auzan Widyan Inne Irianti Sinon Sidiq Purnomo, Agus Suryadin Suryadin