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All Journal International Journal of Social Science Journal of Intelligent Software Systems Jurnal Teknologi Informasi
Danny Kriestanto
Universitas Teknologi Digital Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Social Sciences Other

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BINA SEJAHTERA EMPLOYEE COOPERATIVE FINANCIAL INFORMATION SYSTEM BASED ON SAK-ETAP FOR MANAGERIAL DECISIONS Heru Agus Triyanto; Danny Kriestanto; Sur Yanti
International Journal of Social Science Vol. 2 No. 4: December 2022
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/ijss.v2i4.4262

Abstract

The Bina Sejahtera employee cooperative or abbreviated as Kopkar Binatara STMIK AKAKOM has a savings and loan business unit and is also a shop division. The system was designed by creating context diagrams, level 0 DAD, relationships between tables and data dictionaries, input designs, and main menus and system views. Bina Sejahtera Employee Cooperative Financial Information System Based on SAK-ETAP Managerial Decisions only involve 2 (two) external entities, namely members and management of cooperatives. One of the outputs of this system will be the SHU report. Cooperative administrators provide data on cooperative management, position data, type of deposit data, savings transaction data, loan type data, loan transaction data, installment data, retrieval data, SHU data and obtain member reports, job reports, cooperative management reports, periodic savings reports, savings report per member, loan report per member, loan report per period, retrieval report per member, retrieval report per period, bad credit report per period, ceiling report per member, overall ceiling report, installment report per period, installment report per member, report on fines per period, interest report per period, SHU report per member, overall SHU report, Profit / Loss Report, Change in Capital Report, Balance Sheet Report from Bina Sejahtera Employee Cooperative Financial Information System Based on SAK-ETAP. The reports obtained from the system are complex but useful for managerial decisions
RANCANGAN DAN IMPLEMENTASI APLIKASI MENTORING MENGGUNAKAN FRAMEWORK LARAVEL Arrio Saputra; Muhammad Agung Nugroho; Femi Dwi Astuti; Danny Kriestanto
JuTI "Jurnal Teknologi Informasi" Vol 1, No 2 (2023): Februari 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.116 KB) | DOI: 10.26798/juti.v1i2.811

Abstract

Program Magang dan Studi Independen Bersertifikat (MSIB) di Yayasan Hasnur Centre mengharuskan mentor menulis laporan kegiatan mentoring, Pada platform website kampus merdeka mitra/PIC/HR hanya dapat melihat laporan harian maupun mingguan dari para mahasiswa magang dan laporan mentor tidak dapat dilihat oleh mitra/PIC/HR sebagai pemegang akun mitra. Sehingga pada penelitian ini membuat website mentoring platform yang mana website ini akan digunakan untuk mencatat atau menuliskan kegiatan mentoring Yayasan Hasnur Centre  Quality Internship Program (YHC QuIP) kampus merdeka yang dilakukan oleh mentor setiap hari kerja serta melampirkan dokumentasinya. Mentoring platform ini mentor dapat menuliskan kegiatan mentoring yang hanya bisa dibuat satu kali sehari akan tetapi jika mentor lupa menuliskan kegiatan mentoring pada hari itu maka akan dibuat otomatis oleh sistem, akan tetapi kegiatan mentoring hanya dapat diedit atau diubah selama dua hari sebelumnya dan kegiatan mentoring hanya dapat dihapus pada hari itu juga. Aplikasi Mentoring platform mempermudah mentor dalam menulis aktivitas/laporan/jurnal serta mempermudah HR/mitra sebagai admin untuk melihat seluruh laporan para mentor karena data yang disimpan sudah terpusat  
Polynomial Regression Method and Support Vector Machine Method for Predicting Disease Covid-19 in Indonesia Bambang Purnomosidi Dwi Putranto; Moh. Abdul Kholik; Muhammad Agung Nugroho; Danny Kriestanto
Journal of Intelligent Software Systems Vol 2, No 1 (2023): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v2i1.931

Abstract

The COVID-19 pandemic has become a major threat to the entire country. According to the WHO report, COVID-19 is a severe acute respiratory syndrome transmitted through respiratory droplets resulting from direct contact with patients. This study of data history is then processed using data mining prediction methods, namely the Polynomial Regression method compared to the Support Vector Machine method. Of the two methods will be sought the most accurate method by testing accuracy with MAE, MSE, and also MAPE to get the results of covid-19 predictions in Indonesia. Based on the comparison of test results through various scenarios against both methods, the Polynomial Regression method obtained the smallest test value, resulting in an accuracy value of MAE = 4146.025749867596, MSE = 19031800.02642069, MAPE = 0.006174164877416524. Polynomial regression is the best-recommended method
Co-Authors Arrio Saputra Bambang Purnomosidi Dwi Putranto Femi Dwi Astuti Heru Agus Triyanto Moh. Abdul Kholik Nugroho, Muhammad Agung Sur Yanti