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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Teknologi Terpadu Journal of System and Computer Engineering Jurnal Informatika Terpadu Indonesian Journal of Intellectual Publication (IJI Publication) Global Abdimas: Jurnal Pengabdian Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Journal Pharmacy and Application of Computer Sciences Advances in Computer System Innovation Journal (ACSI Journal) Indonesian Journal of Intellectual Publication (IJI Publication)
Syahrul Usman
Universitas Pancasakti Makassar, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : Journal of System and Computer Engineering

 1 
Implementasi Sistem Informasi Akademik dengan Feeder PDDikti Berbasis Android Syahrul Usman
Journal of System and Computer Engineering (JSCE) Vol 1 No 1 (2020): JSCE: Juli 2020
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47650/jsce.v1i1.76

Abstract

Abstrak Sistem Informasi Akademik (SIAKAD) merupakan instrument penting bagi penyelenggara pendidikan perguruan tinggi, Proses pelaporan seluruh aktifitas perguruan tinggi harus dilakukan pihak penyelenggara kepada DIKTI secara berkala pada tiap semester. Terimplementasinya SIAKAD pada lingkup Universitas Pancasakti Makassar sangat membantu dalam pengolahan data akademik yang komprehensif serta menjadi jaminan konsistensi dan validasi data, Seiring dengan perkembangan teknologi serta sifat mobilitas pengguna mengakibatkan penggunaan aplikasi berbasis Mobile semakin tinggi. penelitian ini bertujuan untuk membangun Aplikasi SIAKAD berbasis Adroid yang terintegrasi dengan Sistem Informasi Feeder PDDIKTI. Aplikasi ini dibagun dengan beberapa fitur seperti verifikasi biodata mahasiswa, Informasi hasil studi (KHS), mengisi kartu rencana studi (KRS), melihat jadwal perkuliahan, melihat transkrip nilai dan media informasi berupa notifikasi dari pengelola perguruan tinggi kepada mahasiswa. Penelitian ini memanfaatkan teknologi Restful web service menggunakan HTTP sebagai protocol komunikasi data dengan format JavaScript Object Notation (JSon) dan Pemrograman Java untuk Aplikasi Mobile. Hasil dari penelitian menunjukkan bahwa Aplikasi dapat terimplementasi dengan baik sehingga memudahkan para Mahasiswa dalam menjalani proses akademik dimana setiap proses pengisian data tetap terintegrasi dengan Feeder PDDIKTI secara real time.
Digitalisasi Arsip Pegawai pada Badan Kepegawaian dan Pengembangan Sumber Daya Manusia Kab. Bone Jeffry Jeffry; Syahrul Usman; Mardewi Mardewi; Nur Ayu Asrhi
Journal of System and Computer Engineering (JSCE) Vol 3 No 2 (2022): JSCE: Juli 2022
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47650/jsce.v3i2.490

Abstract

Kebutuhan akan efisiensi dan fleksibilitas pada sistem pemerintahan sangat dibutuhkan di era teknologi dan informasi seperti sekarang ini, tidak terkecuali pada Badan Kepegawaian dan Pengembangan Sumber Daya Manusia Kabupaten Bone yang mencatat seluruh berkas-berkas kepegawaian dimana seluruh sistem pemberkasan masih dilakukan secara manual yang memakan tempat dan biaya yang banyak untuk perawatn. Tujuan penelitian ini adalah untuk merancang sistem informasi digitalisasi arsip kepegawaian untuk proses percepatan pengurusan berkas kepegawaian baik dari segi kemudahan mengakses atau menyimpan berkas. Metode yang digunakan pada penelitian ini menggunakan metode waterfall untuk perancangan sistem yaitu dengan melakukan analisis kebutuhan sistem, desain sistem, penulisan kode program, pengujian program, dan implementasi program. Hasil penelitian diharapkan mampu mengatasi masalah yang dihadapi oleh BPKSDM Kabupaten Bone saat ini dan mampu mempercepat proses pemberkasan sehingga efektifitas dan efisiensi pelayanan menjadi lebih baik. Target luaran wajib penelitian ini adalah Artikel Ilmiah yang dimuat pada Jurnal Teknik Informatika Terakreditasi Sinta 5 serta luaran tambahan buku ajar. Tingkat Kesiapan Teknologi dalam penelitian ini adalah digitalisasi arsip pegawai berbasis web.
Sistem Pendukung Keputusan Penentuan Destinasi Objek Wisata Dengan Metode Simple Additive Weighting (SAW) Berbasis Web jeffry, Jeffry; aziz, firman; usman, syahrul
Journal of System and Computer Engineering Vol 5 No 2 (2024): JSCE: Juli 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i2.1339

Abstract

One of the biggest regional proceeds of the North Toraja Regency comes from the utilization of tourist objects as recreational objects whether for the local communities or the overseas. However, the lack of information and the lack of systems technology in Toraja destination caused many tourists to visited a few of the many tourism objects available. This problem causes tourists to tend to visit only a fraction of the many tourism objects. Based on these problems, we need a system that helps provide information and determine tourist objects suitable for each tourist, and the tour is more varied. This study produces a decision support system for selecting tourism objects in North Toraja using the “Simple Additive Weighting” method based on a website in the goal of assisting tourists to determine tourist place
Predictive Sparepart Maintenance Menggunakan Algoritma Machine Learning Extreme Gradiant Boosting Regressor Usman, Syahrul; Syam, Rahmat Fuadi
Journal of System and Computer Engineering Vol 5 No 2 (2024): JSCE: Juli 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i2.1418

Abstract

Spare parts are components that make up a single object that has a specific function. In car vehicles, spare parts have the function of maintaining the performance and function of the vehicle. Predictive Spare Part Maintenance is an effort to improve operational efficiency, customer service, and reduce vehicle downtime through the application of analysis and machine learning algorithms to predict spare part replacement times. A machine learning approach can be used to predict maintenance times for car spare parts, where one of the algorithms that can be used is XGBoost Regressor. Through this approach, this research aims to improve service planning by predicting spare part replacement times based on certain indicators, With the implementation of this research, it is hoped that it can increase operational efficiency in automotive after-sales services, increase customer satisfaction, reduce vehicle downtime, and improve overall service planning and most importantly can provide preventive maintenance information to customers. This research provides prediction results with R2-Score values ​​as follows: train data: 93%, Valid: 90%, Test: 90%
Performance Exploration of Tree-Based Ensemble Classifiers for Liver Cirrhosis: Integrating Boosting, Bagging, and RUS Techniques Aziz, Firman; Jeffry, Jeffry; Wungo, Supriyadi La; Rijal, Muhammad; Usman, Syahrul
Journal of System and Computer Engineering Vol 6 No 3 (2025): JSCE: July 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i3.2031

Abstract

Liver cirrhosis, as a significant chronic liver disease, exhibits a rising global prevalence, demanding more effective preventive approaches. In an effort to enhance early detection and patient management, this research proposes the development of a liver cirrhosis risk prediction model using machine learning technology, specifically comparing the performance of three ensemble tree models: Ensemble Boosted Tree, Ensemble Bagged Tree, and Ensemble RUSBoosted Tree. Utilizing clinical and laboratory data from adults with a history or risk of cirrhosis, the study reveals that Ensemble Bagged Tree achieved the highest accuracy at 71%, followed by Ensemble Boosted Tree (67.2%) and Ensemble RUSBoosted Tree (66%). Analysis of clinical and laboratory variables provides further insights into the most significant contributors to risk prediction. The findings lay the groundwork for the advancement of a more sophisticated liver cirrhosis risk prediction tool, supporting a vision of more personalized and effective preventive strategies in liver disease management
Co-Authors Abasa, Sustrin Almuhajir Haris, Almuhajir Anirwan Anirwan Arafah, Muhammad Nur Firman Aziz Fuadi Syam, Rahmat Hamdani Nur, Nur Ismail Ismail Jeffry Jeffry Jeffry Kahar Gani La Wungo, Supriyadi Lutfi Budi Ilmawan, Lutfi Budi M Rezky Armansyah Mardewi Mardewi Muh Halqi Ashar Monoarfa Muhammad Arfah Asis Muhammad Lutfi Nur Ayu Asrhi Nur Ayu Asrhi Nurdyansa Putra Yuzi Bachmid, Fadel Muhammad Qamal Qamal Rijal, Muhammad Rofiq Harun Sasmita, Dhilan Sudirman Melangi Sumardi Sumardi Syam, Rahmat Fuadi Taufik, Akbar Wijaya, Neti Septi Wungo, Supriyadi La