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PREDIKSI PINJAMAN KREDIT DENGAN SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBORS PADA KOPERASI SERBA USAHA Iriadi, Nandang; Leidiyana, Henny
PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic) Vol 1, No 2 (2013): PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)
Publisher : PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)

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Abstract

Cooperatives as a form of organization that are important in promoting economic growth . Cooperatives be an alternative for people to get funds in an effort to improve their quality of life , day-to- day needs and develop the business . No doubt , lend funds to member cooperatives will surely emerge problems , such as members of the borrower paying the overdue installment of funds , misuse of funds for other purposes , the customer fails to develop its business so as to result in cooperative funds do not flow or it can lead to bad credit . In this research will be carried out loans prediction using data mining classification Support Vector Machine and k - Nearest Neighbors were then conducted a comparison of both methods . From the test results to measure the performance of both methods using cross validation , confusion matrix and ROC curves is known that Support Vector Machine has an accuracy value of 92.67 % followed by k -Nearest Neighbors, which has a value of 88.67 % accuracy . Thus the Support Vector Machine method is included in Verry Good Clasification because it has the accuracy of 92.67 % .Keywords: comparative, Support Vector Machines, k-Nearest Neighbors, Credit Analysis Cooperatives as a form of organization that are important in promoting economic growth . Cooperatives be an alternative for people to get funds in an effort to improve their quality of life , day-to- day needs and develop the business . No doubt , lend funds to member cooperatives will surely emerge problems , such as members of the borrower paying the overdue installment of funds , misuse of funds for other purposes , the customer fails to develop its business so as to result in cooperative funds do not flow or it can lead to bad credit . In this research will be carried out loans prediction using data mining classification Support Vector Machine and k - Nearest Neighbors were then conducted a comparison of both methods . From the test results to measure the performance of both methods using cross validation , confusion matrix and ROC curves is known that Support Vector Machine has an accuracy value of 92.67 % followed by k -Nearest Neighbors, which has a value of 88.67 % accuracy . Thus the Support Vector Machine method is included in Verry Good Clasification because it has the accuracy of 92.67 % .Keywords: comparative, Support Vector Machines, k-Nearest Neighbors, Credit Analysis
ANALISIS KEAMANAN E-MAIL MENGGUNAKAN PRETTY GOOD PRIVACY Iriadi, Nandang
Paradigma - Jurnal Komputer dan Informatika Vol 13, No 1 (2011): Vol. 13 Nomor 1, Maret 2011
Publisher : AMIK BSI Jakarta

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Abstract

Electronic mail (e-mail) has haved important communication means and which. thereby, user and business has haved concerned with privasi e-mail they and turn away to second software enkripsi e-mail commercial kailable to achieve confidentiality. e-mail protocol enkripsi very susceptible towards attack ciphertext where receivers e-mail unconsciously act as" dekripsi oracle" , that attack enough proper and hence be serious attention. attack towards e-mail that sent shaped file or message without compression prety good privacy (pgp) so message or file is not guaranteed the data security, but if compression file that sent (for example, file zip that sent to use pgp), that attack stills to work and can be used to restore original data. on the other side, compression is done by software enkripsi that sendiri(bila compression file is send)ed that causes attack towards file or message that reside in safe email from attack pembajakan(hijacking) email message.  Keyword: pgp, compression pgp
KAJIAN PENERAPAN METODE KLASIFIKASI DATA MINING ALGORITMA C4.5 UNTUK PREDIKSI KELAYAKAN KREDIT PADA BANK MAYAPADA JAKARTA Iriadi, Nandang; Nuraeni, Nia
JURNAL TEKNIK KOMPUTER Vol 2, No 1 (2016): Jurnal Teknik Komputer AMIK BSI
Publisher : AMIK BSI Jakarta

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Abstract

Abstract — The banking industry has developed quite apidly, bothin terms of volume of business , mobilize public funds or credit .Data mining of the loan has great potential to explore the hiddenpatterns within a dataset of loans including loans domain . C4.5classification algorithm is the most simple , easy diimplemntasikan. However, the algorithm C4.5 still have weaknesses in handlinghigh-dimensional data in . This research aims to implement thealgorithm C4.5 with the selection of attributes so as to reduce thedimensionality of the data , and identify features in the data setwith C4.5 algorithm method . From this research, conductedmodels created with C4.5 algorithm itself already has goodaccuracy that is equal to 83.67 % with the selection process by thealgorithm C4.5 attributes .Intisari — Industri perbankan mengalami perkembangan yangcukup pesat, baik dari sisi volume usaha, mobilisasi danamasyarakat maupun pemberian kredit. Data mining mengenaipinjaman memiliki potensial besar untuk menjelajahi bagianpola yang tersembunyi dalam suatu dataset dari domainpinjaman termasuk pinjaman kredit. Algoritma C4.5merupakan pengklasifikasian yang paling sederhana, mudahdiimplemntasikan. Namun, Algoritma C4.5 masih memilikikelemahan dalam menangani data dalam dimensi tinggi.Penelitian ini bertujuan untuk menerapkan algoritma C4.5dengan seleksi atribut sehingga dapat mengurangi dimensi daridata, serta mengidentifikasi fitur dalam kumpulan data denganmetode algoritma C4.5. Dari penelitian ini yang dilakukan modelyang terbentuk dengan algoritma C4.5 sendiri sudah memilikiakurasi yang baik yaitu sebesar 83.67% dengan proses seleksiatribut oleh algoritma C4.5.Kata kunci — Data mining, Algoritma C4.5, kelayakankredit,Decision Tree
PENGARUH SISTEM PENDUKUNG KEPUTUSAN DALAM PEMILIHAN MOBIL LCGC DENGAN METODE ANALYTIC HIERARCHY PROCESS (AHP) Iriadi, Nandang; Yohana, Desy
Jurnal Khatulistiwa Informatika Vol 4, No 2 (2016): Periode Desember 2016
Publisher : AMIK BSI Pontianak

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The automotive industry in Indonesia to date has been growing rapidly, it can be seen from the increasing volume of vehicles in Indonesia. Jakarta is a city with the highest rate of vehicle purchases in Indonesia today. And in this era of globalization have a vehicle for most of the community is important and a subject matter because it can help in the move, especially work. Besides the variety of choices of vehicles available, consumers are also exposed to many criteria that influence in determining the choice of vehicles, such as design, price, spare parts, cc vehicles, fuel and facilities or features that are on offer in the vehicle. And so we need a system to process these criteria into a infromasi required by consumers. For the system to be created using AHP (Analytic Hierarchy Process).Keywords: Decision Support System, AHP, Car Selection, Expert Choice
Perancangan Sistem Informasi Penjualan Minuman Kemasan Berbasis Web Pada Toko Bambu Sejahtera Bekasi Iriadi, Nandang; Rosdiana, Nia
Jurnal Khatulistiwa Informatika Vol 5, No 1 (2017): Periode Juni 2017
Publisher : AMIK BSI Pontianak

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Abstract

Toko Bambu Sejahtera is one of the companies selling drinks are located in areas Pondokgede – Bekasi. In the Toko Bambu Sejahtera authors sale systems analysis the current operation. That is done in the company sales are still not getting maximum revenue. Income that is not necessarily, the lack of promotion and lack of strategic place makes Toko Bambu Sejahtera yet known among the public at large. Therefore, the purpose of this study is to design an information system is a web-based product sales, or better known as E-Commerce using the programming language PHP and MySQL.Keywords : CV. Bambu Sejahtera, E-Commerce, Web, MySQL.
PENERAPAN ALGORITMA KLASIFIKASI DATA MINING DALAM PENENTUAN PEMBERIAN PINJAMAN KOPERASI Iriadi, Nandang
Paradigma - Jurnal Komputer dan Informatika Vol 14, No 2 (2012): PERIODE SEPTEMBER 2012
Publisher : AMIK BSI Jakarta

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Abstract

The loan is the delivery of goods, services, or money from one party (the creditor / lender) on thebasis of trust in the other party (customer or debtor / borrower) to the appointment of a receiver topay credit to the lender on the date agreed upon by both parties. Research each loan application ishighly dependent on factors such as type of business, the economy, the intended use of the credit,the amount of credit that do not kredit.Analisa carefully and thoroughly resulted in someborrowers who have no credit given the ability to make payments so that there was nonperforming loans. In this study, using the method of C4.5 algorithm, which was applied to the data members Multipurpose Cooperative Enterprises "Ceger Jaya" that get good credit loans are problematic in the installment payment or not. From the test results to measure the performance ofthe algorithm testing using Cross Validation, Confusion Matrix and the ROC curve, it is known that the C4.5 algorithm has the highest accuracy value, which is 90.67 which is very good classification.Keywords: C 4.5, Credit Analysis, Decision Tree.
MODEL PENANGANAN E-MAIL SPAM DENGAN PENDEKATAN TEKNIK SMTPI Iriadi, Nandang
Paradigma - Jurnal Komputer dan Informatika Vol 11, No 3 (2009): Periode September 2009
Publisher : Universitas Bina Sarana Informatika

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The ability to use e-mail as essential to the ability to use the phone. E-mail system is very important thatmany people would complain if the e-mail system can not waste bekerja.E-mail (SPAM) is a problem almostall Internet users and the various efforts to control has been done. Without knowing the factors that causethe occurrence of SPAM, then this problem will still continue. This paper set forth an analysis of SPAM withSMTP Method I, to find fault in the system and the significant factors that cause other Spam.Analisisontology of the system architecture of e-mail describing the parts and systems so that such connectednesscan identify system weaknesses. Then all the significant factors associated with each other by relations ofcausality and proven method SMTPI messages sent by SMTP will be sent in the queue. SMTP will avoidreplying to the message from the queue if connected to a remote machine .. is the use of filtering solutionsthat are considered quite effective from the technical point of view. filtering is essentially aimed at helpinge-mail recipients to filter (select) which automatically e-mail right from spam e-mail, saving time andtenaga.Hasil analysis showed that not only technical factors such as the architecture of e-mail system andauthentication process that factors in SPAM, but also other factors such as less sweeping application ofsecurity policy (security policy), and economic factors such as cost of sending an e-mail is low.Keyword: E-mail, Spam, E-mail filter,SMTPI Methodics
PREDIKSI PINJAMAN KREDIT DENGAN SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBORS PADA KOPERASI SERBA USAHA Iriadi, Nandang; Leidiyana, Henny
PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic) Vol 1 No 2 (2013): September 2013
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

BSTRACTCooperatives as a form of organization that are important in promoting economic growth . Cooperatives bean alternative for people to get funds in an effort to improve their quality of life , day-to- day needs anddevelop the business . No doubt , lend funds to member cooperatives will surely emerge problems , such asmembers of the borrower paying the overdue installment of funds , misuse of funds for other purposes , thecustomer fails to develop its business so as to result in cooperative funds do not flow or it can lead to badcredit . In this research will be carried out loans prediction using data mining classification Support VectorMachine and k - Nearest Neighbors were then conducted a comparison of both methods . From the testresults to measure the performance of both methods using cross validation , confusion matrix and ROCcurves is known that Support Vector Machine has an accuracy value of 92.67 % followed by k -NearestNeighbors, which has a value of 88.67 % accuracy . Thus the Support Vector Machine method is includedin Verry Good Clasification because it has the accuracy of 92.67 % . Keywords: comparative, Support Vector Machines, k-Nearest Neighbors, Credit Analysis ABSTRAKKoperasi sebagai salah satu bentuk organisasi yang penting dalam meningkatkan pertumbuhan ekonomi.Koperasi simpan pinjam menjadi salah satu alternatif bagi masyarakat untuk mendapatkan dana dalamupaya memperbaiki taraf kehidupan, pemenuhan kebutuhan sehari-hari dan mengembangkan usaha.Tidakdipungkiri, memberikan pinjaman dana kepada anggota koperasi pasti akan muncul permasalahanpermasalahan, seperti anggota peminjam terlambat membayarkan cicilan dana, penyalahgunaan dana untukkeperluan lain, nasabah gagal mengembangkan usahanya sehingga dapat mengakibatkan dana di koperasitidak mengalir atau dapat mengakibatkan kredit macet. Dalam penelitian ini akan dilakukan prediksipinjaman kredit dengan menggunakan metode klasifikasi data mining Support Vector Machine dan kNearest Neighbor syang kemudian dilakukan komparasi kedua metode tersebut. Dari hasil pengujiandengan mengukur kinerja kedua metode tersebut menggunakan cross validation, confusion matrix dankurva ROC diketahui bahwa Support Vector Machine memiliki nilai akurasi 92.67% diikuti oleh k-NearestNeighbors yang memiliki nilai akurasi 88,67%. Dengan demikian Metode Support Vector Machine tersebuttermasuk dalam Verry Good Clasification karena memiliki nilai akurasinya sebesar 92.67%. Kata kunci: komparasi,Support Vector Machine,k-Nearest Neighbors ,Analisa Kredit  
Analisa Kepuasaan Pelanggan dalam Layanan Jasa Travel and Tour pada PT. Denar Pesona Menggunakan Metode Fuzzy Servqual Iriadi, Nandang; Priatno, Priatno; Sulistia, Putri Agnes
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 18 No 2 (2019)
Publisher : STMIK Bumigora Mataram

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Abstract

Companies like these services are important to improve the quality of services provided to customers. In this case it is very useful for companies to plan ahead. For this reason, PT. Enchantment Denar has a different way to assess customer satisfaction. In practice, the activity of evaluating the level of customer satisfaction must be done with a good and appropriate method. Fuzzy Servqual method was chosen to assess and rank the level of customer satisfaction. This study aims to determine the level of customer satisfaction with the services of PT. Enchantment Denar and analyze service factors that must be improved and quality improved. The results of the study show that the gap value is negative, it can be said that the services provided by PT. Denar Charm has not satisfied the customer's heart. Then the lowest result of the gap is -0.334 of the empahty variable and the highest result is -1.137 in the responsiveness variable. Therefore PT. Enchantment Denar must further increase the lack of results so that in the future PT. Denar Charm is very good service for the customer.