Claim Missing Document
Check
Articles

Found 4 Documents
Search

RANCANG BANGUN APLIKASI SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN PEMBIAYAAN KREDIT DI PT. CIMB NIAGA FINANCE Nofitri Heriyani; Rohmat Taufik; Ri Sabti Septarini; Ray Tri Permana
Jurnal Teknik Vol 11, No 1 (2022): Januari - Juni 2022
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v11i1.5476

Abstract

 Dampak covid 19 pada PT. Cimb Niaga Finance perusahaan bergerak dalam bidang pembiayaan kendaraan roda empat, banyak calon nasabah mengajukan restrukturisasi, oleh karena itu di butuhkan sebuah sistem pendukung keputusan untuk penilaian kelayakan penerima pembiayaan kredit, Maka dalam analisis penelitian ini menggunakan, User Requirement Specification yang terdapat kegiatan analisis perancangan prosespembuatan system pendukung keputusan dengan menggunkan metode (weight product) menggunakan indikator penilaian Dan metode pengembangan sistem yang di gunakan adalah System Development Life Cycle (SDLC), waterfall, dimana terdapat penjelasan mengenai analisis, desain, pengkodean, pengujian, dengan pemodelan fungsionalnya menggunakan Use Case diagram dan activity diagram.penelitian ini menghasilkan sutau aplikasi pendukung keputusan penilaian kelayakan kredit mobil, yang dapat membantu dalam proses pengambilan keputusan, sehingga dapat mengurangi tingkat kredit macet/bermasalah. Sehubungan dengan itu maka penulis akan mengambil judul ”Rancang Bangun Sistem Pendukung Keputusan Pemberian Pembiayaan Kredit, Pada PT.Cimb Niaga Finance”
Pelatihan Pembuatan Kerajinan Tangan Kalung Masker di Kelurahan Batuceper Arief Herdiansah; Ri Sabti Septarini; Nofitri Heriyani; Ali Firdaus; Jefry Arizky; Nur Suci Ramadhanty
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 3, No 1 (2022): Volume 3, Nomor 1, 2022
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v3i1.1925

Abstract

Kegiatan pengabdian masyarakat ini dilaksanakan dalam rangka membantu warga masyarakat kelurahan Batuceper untuk dapat memiliki kemampuan membuat kerajinan tangan sebagai salah satu solusi untuk menciptakan ide memperoleh pendapatan tambahan. Saat ini banyak warga masyarakat mengalami penurunan pendapat khususnya warga masyarakat yang memiliki pekerjaan informal yang diakibatkan karena aktifitas mencari rezeki yang terbatas karena diberlakukannya PPKM (Pemberlakuan Pembatasan Kegiatan Masyarakat) selama masa pandemic covid-19. Sasaran aktifitas pelatihan pembuatan kerajinan tangan kalung masker adalah ibu-ibu rumah tangga warga kelurahan Batuceper Kota Tangerang, yang ingin menumbuhkan kemampuan dan jiwa kewirausahaan serta keterampilan diri dalam membuat kerajinan tangan yang memiliki nilai jual. Proses pelatihan dilakukan selama 3 hari dan peneliti telah melakukan survey berkaitan dengan hasil pelatihan yang telah dilakukan dan didapatkan hasil yang sesuai dengan harapan dimana peserta pelatihan memiliki kemampuan dalam membuat kerajinan tangan kalung masker dan memahami bahwa hasil karyanya dapat dijual untuk menjadi salah satu sumber pendapatan tambahan keluarga.Kata Kunci: pelatihan, kerajinan tangan, kewirausahaan, kalung masker
MULTI-CRITERIA DECISION MAKING USING THE WASPAS METHOD FOR ONLINE ENGLISH COURSE SELECTION Nurdiana Handayani; Nofitri Heriyani; Fajar Septian; Allan Desi Alexander
Jurnal Teknoinfo Vol 17, No 1 (2023): Vol 17, No 1 (2023): JANUARI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i1.2371

Abstract

English is an international language used in communication between countries. For this reason, the ability to speak English is of added value in entering the world of work. Because of how important English is, currently many course institutions offer English courses including online learning. With so many online English courses, it requires carefulness in choosing the right course and according to your needs. To find an online English course, you need to know one by one in advance about the programs and facilities offered. This study aims to implement the Multi-Criteria Decision Making (MCDM) approach with Weighted Aggregated Sum Product Assessment (WASPAS) in a decision support system for selecting online courses. The WASPAS method is used as a multi-criteria settlement model that can minimize errors and maximize the assessment for selecting the highest or lowest scores. Based on case studies conducted using the WASPAS method in decision making, it shows that the alternative with the highest score was obtained by the British Council (A5) with a value of 0.8927, followed by English Today (A2) with a value of 0.8311, Education First (A1) with a value of 0.8302, IELC English Campus (A4) with a score of 0.7859 and Engoo English Course (A3) with a score of 0.7823. In addition, the test results from black-box testing have a value of 100%, which means the system can work as it should.
Implementation of Self-Organizing Map (SOM) Algorithm for Image Classification of Medicinal Weeds Hendra Mayatopani; Nurdiana Handayani; Ri Sabti Septarini; Rini Nuraini; Nofitri Heriyani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.4755

Abstract

Wild plants or weeds often become enemies or disturb the main cultivated plants. In its development, wild plants or weeds actually have ingredients that are beneficial to the body and can be used as medicine. However, many people still need knowledge about the types of weed plants that have medicinal properties, especially the leaves. The purpose of this research is to classify the image of weed leaves with medicinal properties based on color and texture characteristics with an artificial neural network using a Self-Organizing Map (SOM). To improve information in feature extraction, RGB and HSV color features are used as well as texture features with Gray Level Co-occurrence Matrix (GLCM). Furthermore, the results of feature extraction will be identified as groups or classes with the Self-Organizing Map (SOM) algorithm which divides the input pattern into several groups so that the network output is in the form of a group that is most similar to the input provided. The test produces a precision value of 91.11%, a recall value of 88.17% and an accuracy value of 89.44%. The results of the accuracy of the SOM model for image classification on medicinal weed leaves are in the good category.