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PENERAPAN ALGORITMA C4.5 DALAM MEMPREDIKSI KETERLAMBATAN PEMBAYARAN UANG SEKOLAH MENGGUNAKAN PYTHON Victor Saputra Ginting; Kusrini Kusrini; Emha Taufiq Luthfi
(JurTI) Jurnal Teknologi Informasi Vol 4, No 1 (2020): JUNI 2020
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v4i1.1101

Abstract

Abstract – Payment of school fees is an important factor in carrying out education because payment of school fees is one of the important obligations in getting an education. Research conducted by Muqorobin, 2019 with the research title "Optimizing the Naive Bayes Method with Feature Selection Gain for Predicting Late School Payment" produces an accuracy rate of 80%, then optimization is carried out using information gain and Naive Bayes produces an accuracy rate of 90%. The research conducted will be a prediction of late payment of school fees using the C4.5 algorithm and then carried out into the form of programming using Python, so as to produce a prediction result. Information Prediction Results obtained from Python then will try to compare the level of accuracy with the dataset that has been collected using a confusion matrix. The dataset obtained from De Britto Yogyakarta High School using Python produces an accuracy rate of 73%. This research is expected to help the school in making decisions and minimize the level of late payment of school fees.Keywords - Prediction, Algorithm C4.5, Python, and Data Mining.Abstract – Pembayaran yang sekolah merupakan faktor yang cukup penting dalam melangsungkan pendidikan karena pembayaran uang sekolah merupakan salah satu kewajiban penting dalam mendapatkan pendidikan. Penelitian yang telah dilakukan Muqorobin, 2019 dengan judul penelitian “Optimasi Metode Naive Bayes Dengan Feature Selection Gain Untuk Memprediksi Keterlambatan Pembayaran Uang Sekolah” menghasilkan tingkat akurasi sebesar 80%, kemudian dilakukan optimasi dengan menggunakan information gain dan Naive Bayes menghasilkan tingkat akurasi sebesar 90%. Penelitian yang dilakukan akan dilakukan prediksi keterlambatan pembayaran uang sekolah dengan menggunakan algoritma C4.5 dan kemudian dilakukan implementasi kedalam bentuk pemrograman dengan menggunakan Python, sehingga menghasilkan keterangan hasil prediksi. Keterangan Hasil Prediksi yang didapatkan dari Python, kemudian akan coba dilakukan perbandingan tingkat akurasi dengan dataset yang sudah dikumpulkan menggunakan confusion matrix. Dataset yang didapatkan dari Sekolah Menengah Atas De Britto Yogyakarta menggunakan Python menghasilkan tingkat akurasi sebesar 73%. Penelitian ini diharapkan dapat membantu pihak sekolah dalam mengambil keputusan dan meminimalisir tingkat keterlambatan pembayaran uang sekolah.Kata kunci - Prediksi, Algoritma C4.5, Python dan Data Mining.
ANALISIS PERBANDINGAN PREDISKSI OBAT DENGAN MENGGUNAKAN METODE ABC ANALISYS DAN SVR PADA APLIKASI “MORBIS” Tutik Maryana; Kusrini Kusrini; Hanif Al Fatta
(JurTI) Jurnal Teknologi Informasi Vol 3, No 2 (2019): DESEMBER 2019
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v3i2.1016

Abstract

Permasalahan rumah sakit mengenai pengolahan persediaan obat adalah kondisi obat yang habis, dikarenakan rumah sakit dalam satu tahun mengeluarkan 33% dari biaya investasi untuk investasi obat. Untuk mengtasi permasalahan diatas rumah sakit harus memiliki pengeloaan logistic dengan baik, cara pengelolaan adalah dengan melakukan perencanaan yang baik. Penulis akan memakai algoritma ABC Analysis dan SVR. ABC Analysis akan digunakan untuk proses klasifikasi obat yaitu dengan cara membagi obat manjadi tiga kelompok utama berdasarkan kepentingan yaitu kelompok A, B dan C. Penulis akan menggunakan metodo SVR untuk menghitung prediksi obat. Hasil penelitian ini adalah ABC analisys dapat membagi  obat. Menjadi tiga bagian  yaitu kelompo A 276  item dengan presentase 22,96% dari jumlah item keseluruhan, kelompok B sejumlah 396 item dengan presentase 33,11% dan C sejumlah 528 dengan presenrase 43,94% dengan kesluruhan obat adlah 1202 item obat. Pengujian prediksi dilakukan dengan cara mengambil sample lima obat dari hasil klasifikasi. Proses perhitungan SVR adalah membandingkan metode preprocessing linier scaling dan z normalization. Hasil dari penelitian tersebut adalah MAPE menunjukan bahwa  dengan menambahkan preprocessing dengan linier scaling dapat membuat proses SVR lebih optimal dari pada menggunakan z nomrlization dan perhitungan dengan klasifikasi ABC analisys.
IMPLEMENTASI ALGORITMA APRIORI DAN FORWARD CHAINING UNTUK MENENTUKAN MAKANAN YANG TEPAT PADA PENDERITA DIABETES Agatha Deolika; Victor Saputra Ginting; Tutik Maryana; Ripto Sudiyarno; Kusrini Kusrini
(JurTI) Jurnal Teknologi Informasi Vol 3, No 2 (2019): DESEMBER 2019
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.566 KB) | DOI: 10.36294/jurti.v3i2.1080

Abstract

Abstract - The high number of diabetes patients in Indonesia is increasing. Some of the factors that cause diabetes in Indonesia include family history, obesity, aging, lack of activity and diet. Too much food containing sugar is also one of the emergences of diabetes. Most diabetics often have complications of diabetes disease and that is based on the criteria of a patient. Therefore, it is necessary to conduct research on the rule or dependence of the disease based on patient criteria and determination of diet for diabetics. In this study using a combination of a priori methods to determine the rule of disease and forward chaining to determine patient food. Based on the research tests conducted, it can be concluded that the combination of 2 methods produces a pretty good which in the a priori method uses a minimum value of support 2 and a minimum of confidence 10 and produces 10 rules with 3 combinations of items, as well as forward chaining tests that use 30 data produces an accuracy of 83 %.Keywords - Apriori Algorithm, Forward Chaining, Diabetes Abstrak - Tingginya jumlah pasien diabetes yang  terjadi di Indonesia semakin meningkat. Beberapa faktor penyebab penyakit diabetes di Indonesia anatara lain riwayat keluarga, obesitas, pertambahan usia, kurangnya aktivitas dan pola makan. Terlalu banyak makan yang mengandung gula juga merupakan salah satu munculnya penyakit diabetes. Kebanyakan penderita diabetes sering sekali terjadinya kompliksi penyait diabetes dan itu berdasarkan kreteria seorang pasien. Maka dari itu perlu dilakukan penelitian mengenai rule atau keterhungungan penyakit berdasarkan kriteria pasien dan penentuan pola makan bagi penderita penyakit diabetes. Pada penelitian ini menggunakan kombinasi metode apriori untuk menetukan rule penyakit dan forward chainning untuk mentukan makanan pasien. Berdasarkan pada pengujian penelitian yang dilakukan dapat diambil kesimpulan Kombinasi 2 metode ini menghasilkan cukup bagus yang mana pada metode apriori menggunakan nilai minimal support 2 dan minimal confidence 10 dan menghasilkan 10 rule dengan 3 kombinasi item, serta pengujian forward chaining yang menggunakan 30 data menghasilkan akurasi 83% .Kata Kunci - Algoritma Apriori, Forward Chaining, Diabetes
Pengaruh Dimensi Gambar pada Klasifikasi Motif Batik Menggunakan Convolutional Neural Network Rizki Mawan; Kusrini Kusrini; Hanif Al Fatta
(JurTI) Jurnal Teknologi Informasi Vol 4, No 2 (2020): DESEMBER 2020
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v4i2.1342

Abstract

Abstract – Indonesia is a country with many fascinating cultural assets. Batik is one of the most beautiful cultural assets that should be preserved. Batik existed with many motifs and styles and has been a significant cultural cloth for many regions spread along the Java island. This research proposed the computation for identifying three popular motifs and styles: megamendung, kawung, and parang. This research employed a Convolutional Neural Network classifier to identity those three popular batik motifs. This research used an image size of  64x64, 128x128, and 256x256  for the input images, and the influence of the size or dimension for these inputs have been analyzed. The final result showed that the highest accuracy is reached at 92.85 % on epoch = 240 and batch size = 5.Keywords  - Batik, Convolutional Neural Network, Accuracy, Dimension Abstrak - Banyak budaya di Indonesia yang masih menjadi kebanggan dan dijaga kelestarian nya. Salah satunya adalah batik. Jika berbicara tentang batik sekilas kita mengingat tentang berbagai macam motif yang dimiliki yang tersbar di Indonesia terutama di pulau Jawa. Pada penelitian kali ini motif batik yang diteliti adalah batik megamendung,batik kawung dan batik parang. Alasan pemilihan ketiga motif tersebut karena ketiga motif tersebut sangat diminati oleh khalayak ramai(Populer) , dan ketiga motif tersebut memliki makna tersendiri yang sangat mewakili masyarakat Indonesia. Tujuan dari klasifikasi batik adalah untuk mengetahui keakuratan akurasi motif batik khusus nya motif batik kawung,megamendung, dan parang. Fokus pada penelitian ini  adalah penggunaan dimensi gambar yang dapat mempengaruhi akurasi yang dihasilkan. Dimensi yang digunakan adalah 64x64,128x128, dan 256x256. Akurasi yang dihasilkan dengan menggunakan metode Convolutional Neural Network yang paling tinggi yaitu 92,85% dengan menggunakan  epoch= 240 dan batch_size=5.Kata Kunci - Batik, Convolutional Neural Network, Akurasi, Dimensi
ANALISIS KUALITAS LAYANAN E-COMMERCE MENGGUNAKAN METODE ZONE OF TOLERANCE Siti Fatonah; Kusrini Kusrini; Asro Nasiri
Informasi Interaktif Vol 3, No 3 (2018): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (342.57 KB)

Abstract

The quality of e-commerce website services must be considered because it affects the number of users who access the website and decide to buy on an e-commerce website. Shopee is one of the fast-growing e-commerce websites in Indonesia, YLKI received 101 complaints in online shopping including among them complaints from Shopee consumers. The purpose of this study is to analyze the quality of e-commerce website services based on the user's point of view and know the attributes that affect customer satisfaction on service quality based on E-Servqual dimensions, namely efficiency, availability, fulfillment, privacy, responsiveness, compensation and contacts using Zone of Tolerance methods. Data obtained from questionnaires using purposive sampling technique with the number of respondents as many as 100 respondents, then the results of the questionnaire were analyzed using the ZOT method to find out the quality of acceptable minimal services. The results of this study indicate that customers are not satisfied with the quality of service provided with priority improvements to the attributes of Shopee parties willing to bear all shipping costs in the event of a mechanism to replace goods due to Shopee's fault.   Keywords: service quality, e-servqual, ZOT.
PERANCANGAN SISTEM PAKAR FINAL CHECK MOTOR MATIC MENGGUNAKAN METODE FORWARD CHAINING STUDI KASUS AHASS 9677 Wahit Desta Prastowo; Kusrini Kusrini; Ferry Wahyu Wibowo
Informasi Interaktif Vol 4, No 2 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (406.009 KB)

Abstract

The increasing interest of consumers towards motorcycle products, especially products from Honda, is now very high. The interest in purchasing Honda matic motorcycles that continues to increase is inversely proportional to the number of technicians and service centers, resulting in an imbalance between the AHASS 9677 service service and motorcycle users. This is indicated by the accumulation of queues reaching 30 units in a day so that consumers queue for hours even though only to ask questions to find out the damage and solutions and the estimated cost of damage to the vehicle owned. Technological advances can be used as an effort to retain customers and overcome queue problems that accumulate with one way of applying artificial intelligence by making an Expert System using the Forward Chaining method that can accept damage symptom input and provide damage analysis and solutions then provide estimated service costs.   Keywords: Expert System, Honda Matic Motor, Forward Chaining.
EVALUASI TINGKAT PENERIMAAN SISTEM INFORMASI YUDISIUM MENGGUNAKAN METODE TAM Sri Handayani; Kusrini Kusrini; M. Rudyanto Arief
Informasi Interaktif Vol 2, No 2 (2017): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (706.081 KB)

Abstract

This study aims to determine the level of acceptance of judicial Information system at the Bureau of Academic Administration and Student Affairs Muhammadiyah University of Bengkulu. Population in this research are employees of BAAK, Staff of Department, Head Of Departement and students who interact directly with the judicial information system Samples taken as many as 68 respondents using slovin techniques with employee details of 28 people and 40 students. This research was conducted by using Technology Acceptance Model method by distributing questionnaire, with the number of samples were 68 respondents. Data analysis technique is done by using SEM technique and Partial Least Square (PLS) approach. The results showed that the variable Perceived Complexity Using the System positively influenced Attitude Toward Using the System and Behavioral Intention to Use the System. This variable can affect the user acceptance rate of 49.9%. Based on the results of the research, the Administrative Bureau of Academic and Student Affairs (BAAK) and Integrated Service Unit of Computer Information Technology (UPT TIK) of Muhammadiyah University of Bengkulu should improve aspects of Perceived Complexity Using the System, to increase the acceptance level of the judicium information system. Keywords: TAM Method, Evaluation of acceptance level of Yudicium Information System, SIAKAD UMB
PENERAPAN METODE AHP DALAM PENENTUAN KRITERIA SISTEM PENDUKUNG KEPUTUSAN SELEKSI PENJUAL PADA KANTIN Fandli Supandi; Kusrini Kusrini; Hanif Al Fatta
Informasi Interaktif Vol 4, No 3 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (380.887 KB)

Abstract

Canteen is one of the most important places to be owned by a particular institution including educational institutions such as universities, in the canteen itself there are sellers - sellers who are the main factors that determine the consumer's decision to the canteen. in this study we will discuss how to determine the priority weights of criteria to be used as an evaluation parameter for the selection of prospective sellers who will be accepted in a canteen. The method used is the Analytical Hierarchy Process (AHP), the stages in the AHP method begin with the process of defining the problem, making a hierarchical structure that begins with general objectives, followed by criteria and alternative choices, Creating pairwise comparison matrices, normalizing data, calculating values eigen vector and test its consistency, calculate eigen vector from each paired comparison matrix, test the consistency of hierarchy. If it does not meet with CR <0.01, the pairwise comparison process must be carried out again. The results of this study are a priority weight of each criterion that will be used for the selection process of prospective sellers in the canteen.Keywords: Canteen, AHP, criter
PREDIKSI KETERLAMBATAN PEMBAYARAN SPP SEKOLAH DENGAN METODE K-NEAREST NEIGHBOR (STUDI KASUS SMK AL-ISLAM SURAKARTA) Robi Wariyanto Abdullah; Kusrini Kusrini; Emha Taufiq Luthfii
Informasi Interaktif Vol 4, No 3 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.403 KB)

Abstract

PREDIKSI KETERLAMBATAN PEMBAYARAN SPP SEKOLAH DENGAN METODE K-NEAREST NEIGHBOR  (STUDI KASUS SMK AL-ISLAM SURAKARTA)
PENERAPAN DATA MINING DALAM MENENTUKAN PEMBINAAN KOPERASI (STUDI KASUS : DINAS KOPERASI DAN UKM KABUPATEN KOTAWARINGIN TIMUR) Yuni Ambar S; Kusrini Kusrini; Henderi Henderi
Informasi Interaktif Vol 4, No 1 (2019): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.45 KB)

Abstract

Currently coaching for cooperatives in the East Kotawaringin Regency Government is very necessary because of the existence of newly established cooperatives and those that have long been standing down and slow in the implementation of Annual Member Meetings (RAT). With the number of cooperatives currently the Cooperative Office lacks supervisory human resources, therefore cooperatives need to be taken into account that are prioritized on coaching. One way to dig data is Data Mining using statistical methods using the K-NN algorithm. In this study, the K-NN Algorithm is used in determining the Cooperative that is feasible for the coach. The results obtained from this study were to obtain the results of the classification of cooperatives that deserved coaching with an accuracy of 96.33 percent. Keywords : Coaching, Clasification, K-Nearest Neighbour
Co-Authors Abdi Firdaus Achmad Wazirul Hidayat Adadilaga Arya Priwanegara Adhien Kenya Estetikha Aditya Hastami Ruger Aflahah Apriliyani Agatha Deolika Agianto Syam Halim Agung Budi Prasetyo Agus Susilo Nugroho Ajie Kusuma Wardhana Akrilvalerat Deainert Wierfi Alfahmi Muhammad Arif Alva Hendi Muhammad Amir Bagja Andi Bahtiar Semma Andi Sunyoto Andi Suyoto Andris Faesal Anggit Dwi Hartanto Anjar Anjani Putra Anwar Sadad Aolia Ikhwanudin Arham Rahim Arief Setyanto Arif Fajar Solikin Arnila Sandi Asro Nasiri Asro Nasrini Ayu Adelina Suyono Aziz Muslim Bimantyoso Hamdikatama Candra Adipradana Dedi Gunawan Devina Ninosari Dimaz Arno Prasetio Dina Maulina Donny Yulianto Dwi Astuti Dwi Utami Dwinda Etika Profesi Eka Wahyu Sholeha Eko Pramono Elik Hari Muktafin Emha Taufiq Luthfi Emha Taufiq Luthfii Erwin Apriliyanto Fandli Supandi Fendy Prasetyo Nugroho Ferry Wahyu Wibowo Fiyas Mahananing Puri Guido Adolfus Suni Hadryan Eddy Hafidz Sanjaya, Hafidz Hanafi Hanafi Hanif Al Fatta Hasirun Hasirun Henderi . Hendrik Hendrik Heri Sismoro Hery Nurmawan Hery Siswanto I Made Artha Agastya I Putu Agus Ari Mahendra Ichsan Wasiso Idris Idris Imam Listiono Irma Darmayanti Irwan Oyong José Ramón Martínez Salio Juwari Juwari Kaharuddin Kanafi Kanafi Khoirun Nisa Khomsatun Khomsatun Kumara Ari Yuana Kusnawi Kusnawi Kusuma Chandra Kirana M rudyanto Arief M. Idris Purwanto M. Nurul Wathani M. Rudiyanto Arief M. Rudyanto Arief M. Zainal Arifin Mahmudi Mahmudi Mansur Mansur Marwan Noor Fauzy Maykel Sonobe Mei P Kurniawan Mei P. Kurniawan MEI PARWANTO KURNIAWAN Moh. Badri Tamam Muahidin, Zumratul Muh Saerozi Muhamad Fatahillah Z Muhamad Yusuf Muhammad Fajrian Noor Muhammad Mariko Muhammad Riandi Widiyantoro Muhammad Riza Eko S Muhammad Rudyanto Arief Mukti Ali Mulia Sulistiyono Muqorobin Muqorobin Muslihah, Isnawati Musthofa Galih Pradana Nanang Prasetiyantara Neno, Friden Elefri Nibras Faiq Muhammad Noor Abdul Haris Noviyanti P. Nur Hamid Sutanto Paradise, Paradise Patmawati Hasan Pawit Srentiyono Prabowo Budi Utomo Pramono Pramono Prasetio, Agung Budi Prasetyo, Adi Prastowo, Wahit Desta Reflan Nuari Retzi Yosia Lewu Ridlan Ahmad Rifan Ferryawan Ripto Sudiyarno Rita Wati Riyan Abdul Aziz Rizki Mawan Robi Wariyanto Abdullah Rona Guines Purnasiwi Rudyanto Arief Saikin Sigit Pambudi Simone Martin Marotta Siti Fatonah Siti Hartinah Siti Rahayu Siti Rokhmah Slamet Slamet Sri Handayani Sri Wulandari Sry Faslia Hamka Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudiana Sudiana Sugi Harsono Supriantara Supriantara Supriatin Supriatin Supriyati Supriyati Syaiful Ramadhan Teguh Sri Pamungkas Tito Prabowo Tri Andi Tri Anggoro Tri Haryanti Tutik Maryana Tutut Dwi Prihatin Umdatur Rosyidah Vera Wati Victor Saputra Ginting Wahyu Adie Saputro Walidy Rahman Hakim Widdi Djatmiko Winarnie Yovita Kinanti Kumarahadi Yudha Chirstianto F Yuliana Yulita Fatma Andriani Yulius Nahak tetik Yuni Ambar S Yusrinnatul Jinana triadin Yusuf Fadlila Rachman Zul Hisyam Zulkipli Zulkipli