Install: Information System and Technology Journal

Journal Title	: INSTALL: Information System and Technology Journal
ISSN	: e-ISSN 3048-1597 (online)
DOI Prefix	: Prefix 10.33859/install by
Editor in Chief	: Mambang M.Kom
Frequency	: 3 times per year (June, September, December)
Publisher	: LPPM Universitas Sari Mulia
Address	: LPPM Universitas Sari Mulia Gedung D lantai 1 Jl. Pramuka. No 02 Kota Banjarmasin, Kalimantan Selatan

INSTALL: Information System and Technology Journal Is a journal that publish by LPPM Universitas Sari Mulia and Managed By Program Studi Sarjana Sistem Informasi and Program Studi Sarjana Teknologi Informasi , Faculity Sains and Technology Univeritas Sari Mulia

INSTALL: Information System and Technology Journal by LPPM Univeristas Sari Mulia is licensed under CC BY 4.0 This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. and are immediately open access. We follow the Budapest Open Access Initiative’s (BOAI) definition of open access, meaning readers may freely read, download, copy, print, share, link to the full text of articles, or use them for any other lawful purpose.

Current Issue

Vol. 1 No. 1 (2024): INSTALL : Information System and Technology Journal

This issue of INSTALL: Information System and Technology Journal features a diverse collection of research articles from scholars across various institutions in Banjarmasin and Balikpapan, Indonesia. Contributors include authors from the Information System and Information Technology departments of Sari Mulia University, the Computerized Accounting program at Banjarmasin State Polytechnic, the Informatics department at the University of Muhammadiyah Banjarmasin, the Faculty of Engineering at Lambung Mangkurat University, and the Information System department at Kalimantan Institute of Technology. The articles cover a wide range of topics in information systems, technology, computerized accounting, and informatics, showcasing the latest advancements and technological developments in these fields. This compilation highlights the collaborative spirit and academic excellence of Indonesian universities, offering valuable insights to inform and inspire further research and practice in these domains.

DOI: https://doi.org/10.33859/install.v1i1

Published: 2024-06-05

Full Issue

Articles

Regression Regression Analysis Data for E-Sport Athletes Prediction using OSEMN Framework Analisis Regresi Data Prediksi Atlet E-Sport Menggunakan Kerangka OSEMN

Septyan Eka Prastya, Musyfia Adla, Bayu Nugraha, Yuslena Sari

1 - 8
- Full Text PDF
DOI : https://doi.org/10.33859/install.v1i1.542
Exploratory Exploratory Data Analysis (EDA) of Social Aid Recipients in Murung Raya District Central Kalimantan Province with Machine Learning Approach Analisis Data Eksplorasi (EDA) Penerima Bantuan Sosial di Kabupaten Murung Raya Provinsi Kalimantan Tengah dengan Pendekatan Machine Learning

Regina, M. Riko Anshori Prasetya, Ahmad Hidayat

9 - 14
- Full Text PDF
DOI : https://doi.org/10.33859/install.v1i1.543
IMAGE Image Segmentation Of Ornamental Plants Typical Of South Kalimantan Using The Convolutional Neural Network Method Segmentasi Citra Tanaman Hias Khusus Kalimantan Selatan Menggunakan Metode Convolutional Neural Network

Lufila Lufila, Septyan Eka Prastya, Finki Dona Marleny

15 - 22
- FULL TEXT PDF
DOI : https://doi.org/10.33859/install.v1i1.544
Clustering Clustering Of Sapodilla Fruit (Manilkara Zapota) Maturity Levels Based On Color Using K-Means Clustering Method Clustering Tingkat Kematangan Buah Sapodilla (Manilkara Zapota) Berdasarkan Warna Menggunakan Metode K-Means Clustering

Wayan Bayu Sumadika, Muhammad Syahid Pebriadi

23 - 26
- Full Text PDF
DOI : https://doi.org/10.33859/install.v1i1.546
A A Naïve Bayes Approach to Understanding Students’ Pychological Well-Being Pendekatan Naïve Bayes untuk Memahami Kesejahteraan Psikologis Siswa

Febria Sera Darnefi, M. Riko Anshori Prasetya

27 - 34
- Full Text PDF
DOI : https://doi.org/10.33859/install.v1i1.547
Diabetes Diabetes Prediction Using Flask and Decision Tree Classifier with Cross-Validation Prediksi Diabetes Menggunakan Flask dan Decision Tree Classifier dengan Validasi Silang

Nor Anisa, Anggara Kurniawan

35 - 44
- Full Text PDF
DOI : https://doi.org/10.33859/install.v1i1.548

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Current Issue

Full Issue

Articles

Regression Regression Analysis Data for E-Sport Athletes Prediction using OSEMN Framework Analisis Regresi Data Prediksi Atlet E-Sport Menggunakan Kerangka OSEMN

Exploratory Exploratory Data Analysis (EDA) of Social Aid Recipients in Murung Raya District Central Kalimantan Province with Machine Learning Approach Analisis Data Eksplorasi (EDA) Penerima Bantuan Sosial di Kabupaten Murung Raya Provinsi Kalimantan Tengah dengan Pendekatan Machine Learning

IMAGE Image Segmentation Of Ornamental Plants Typical Of South Kalimantan Using The Convolutional Neural Network Method Segmentasi Citra Tanaman Hias Khusus Kalimantan Selatan Menggunakan Metode Convolutional Neural Network

Clustering Clustering Of Sapodilla Fruit (Manilkara Zapota) Maturity Levels Based On Color Using K-Means Clustering Method Clustering Tingkat Kematangan Buah Sapodilla (Manilkara Zapota) Berdasarkan Warna Menggunakan Metode K-Means Clustering

A A Naïve Bayes Approach to Understanding Students’ Pychological Well-Being Pendekatan Naïve Bayes untuk Memahami Kesejahteraan Psikologis Siswa

Diabetes Diabetes Prediction Using Flask and Decision Tree Classifier with Cross-Validation Prediksi Diabetes Menggunakan Flask dan Decision Tree Classifier dengan Validasi Silang

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