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All Journal Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Buffer Informatika
Rio Ghaniy Septiansyah
Institut Teknologi Telkom Purwokerto
Computer Science & IT

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Digitalisasi Layanan Kesehatan Desa Grujugan Melalui Pengembangan E-Posyandu menggunakan Metode SDLC-Waterfall Haidar Fadhila Fiqa; Rendi Putra Pradana; Mochammad Hanif; Rio Ghaniy Septiansyah
Journal of INISTA Vol 5 No 1 (2022): November 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v5i1.891

Abstract

Posyandu is a basic health activity organized from, by and for the community assisted by health workers in an effort to improve the health quality of each village. Posyandu is a community-based health effort. Health information is generated from all routine programs carried out by the village posyandu. In managing the data, the information obtained is the main problem faced by the Posyandu in Grujugan Village. Limited access to information also causes villagers to be unable to control the health of their families, starting from children, mothers and the elderly. In an effort to improve the quality of information on examination results, a web-based posyandu information system called eposyandu was designed. The eposyandu application is built using the SDLC (System Develop Life Cycle) method with a waterfall model which is quite effective in software development. The results of the tests carried out on the application by the cadres showed results that were in accordance with the needs analysis and program design. The use of the eposyandu application is expected to improve the quality of the Posyandu information system in Grujugan Village.
Klasifikasi Produktivitas Pekerja Garmen Menggunakan Algoritma Random Forest: Classification of Garment Worker Productivity Using Random Forest Algorithm Luthfi Rakan Nabila; Fiqki Haidar Amrulloh; Ghilman Farhani Putra Aji; Rio Ghaniy Septiansyah; Vincentius Sagi Alban Anindyajati; Henri Tantyoko
Buffer Informatika Vol. 10 No. 1 (2024): Buffer Informatika
Publisher : Department of Informatics Engineering, Faculty of Computer Science, University of Kuningan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/buffer.v10i1.111

Abstract

Penelitian ini membahas mengenai penerapan algoritma machine learning dalam melakukan klasifikasi produktivitas pekerja garmen. Penelitian ini menggunakan dataset produktivitas garmen yang didapatkan dari situs UC Irvine Machine Learning Repository dengan rentang waktu dari tanggal 1 januari 2015 sampai 11 maret 2015 dengan total data sebanyak 1197 baris. Algoritma yang diterapkan pada penelitian ini adalah random forest dengan hyperparameter tuning untuk melakukan klasifikasi produktivitas pekerja garmen. Metodologi penelitian ini melibatkan pengolahan data seperti pemilihan fitur yang relevan, transformasi data, dan normalisasi guna mendapatkan hasil evaluasi terbaik. pada penelitian ini juga dilakukan percobaan dengan decision tree dan algoritma svm sebagai pembandingnya. Algoritma random forest mengungguli algoritma lain dengan akurasi sebesar 94.36% di mana akurasi tersebut sudah cukup bagus dalam untuk mengklasifikasi produktivitas
Co-Authors Fiqki Haidar Amrulloh Ghilman Farhani Putra Aji Haidar Fadhila Fiqa Henri Tantyoko Luthfi Rakan Nabila Mochammad Hanif Rendi Putra Pradana Vincentius Sagi Alban Anindyajati