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All Journal Jurnal Informasi dan Komputer Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK)
Kundang Karsono Juman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics Other

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ANALISIS DAN PERANCANGAN SISTEM INFORMASI PENJUALAN JASA PENCUCIAN SEPATU DAN TAS PADA SOJI SHOES AND BAG CARE BERBASIS MOBILE Dandi Ramasenjaya; Kundang Karsono Juman
Jurnal informasi dan komputer Vol 10 No 2 (2022): Jurnal Sistem Informasi dan Komputer yang terbit pada tahun 2022 pada bulan 10 (
Publisher : STMIK Dian Cipta Cendikia Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v10i2.353

Abstract

Soji Shoes and Bag Care is one of the companies engaged in shoe and bag washing services located in Central Jakarta, the Laundry Services offered are: Washing shoes and bags that are dull, yellowed, very dirty, then shoes and bags are washed clean according to customer wishes. Currently the information system provided has not been able to manage company data, marketing company services and company information, so the company is unable to reach customers and prospective customers in DKI Jakarta. In recording/entering customer data, ordering and payment requires workers to input data manually and then recap the data into Ms. Excel, changes or as required information takes a lot of time and is at risk for input errors and data loss. The method of developing information systems in this research is the Prototype Method, and to describe the problem with PIECES, then the UML diagram as a proposed system design structure uses Use Case Diagrams, Class Diagrams, Activity Diagrams and Sequence Diagrams. The programming language used is the Java language, and uses the MYSQL database. The result of this final project is the design of a mobile information system for ordering cleaning services at the Soji Shoes and Bag Care Company.
PERBANDINGAN TIGA ALGORITMA CLASSIFIER UNTUK PENENTUAN PENERIMAAN PESERTA DIDIK BARU PADA SEKOLAH MENENGAH ATAS Yulhendri; Kundang Karsono Juman
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 1 No. 3 (2021): November: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v1i3.267

Abstract

ABSTRAK New Student Admissions (PPDB) have been carried out since the 2012/2013 school year by schools that have been verified by the Ministry of Education. From the 2012/2013 school year to the 2018/2019 school year, 1279 schools have been registered and verified. The activity of accepting new students (PPDB) for SMA is not an independent one, but is not separated from various aspects. Education staff, participants, schools, school quotas, and participant scores. And one of the most important processes of new student admissions is the prediction of the selection of high school schools. The problem faced by prospective students is prediction for school selection. The predictions made so far have only focused on the passing grade of each school. However, the passing grade that is focused on only revolves around the previous year. Therefore, we need a system to predict participants in choosing schools from new student admissions activities by implementing several machine learning algorithms. Keywords: Machine Learning, Prediction, PPDB High School. Abstrak Penerimaan Peserta Didik Baru Baru (PPDB) sudah dilakukan sejak tahun ajaran 2012/2013 oleh sekolah yang sudah diverivikasi oleh Departemen Pendidikan. Dari tahun ajar 2012/2013 sampai tahun ajar 2018/2019 sudah 1279 sekolah yang sudah terdaftar dan sudah diverivikasi. Kegiatan Penirimaan peserta didik baru (PPDB) SMA bukan yang berdiri sendiri, namun tidak dipisahkan dari ber-bagai aspek. Tenanga penddika, peserta, sekolah, kuota sekolah, dan nilai peserta. Dan salah satu proses yang terpenting dari kegiatan penerimaan peserta didik baru adalah prediksi pemilihan sekolah SMA. Masalah yang dihadapi oleh para calon siswa adalah prediksi untuk pemilihan sekolah. Prediksi yang dilakukan sampai sekarang hanya terfokus pada passing grade setiap sekolah. Akan tetapi, passing grade yang di fokuskan hanya berkisar di tahun sebelum nya. Oleh karena itu, di butuhkan sebuah sistem untuk memprediksikan peserta dalam memilih sekolah dari kegiatan penerimaan peserta didik baru dengan mengimplementasi dari Beberapa Algoritma Machine Learning. Kata Kunci: Machine Learning, Prediksi, PPDB SMA.
Co-Authors Dandi Ramasenjaya Yulhendri Yulhendri