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All Journal snimed Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Foristek Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi dan Manajemen Informatika Prosiding SNATIF Jurnal Informatika dan Teknik Elektro Terapan Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Technomedia Journal ScientiCO : Computer Science and Informatics Journal IT (INFORMATIC TECHNIQUE) JOURNAL Advance Sustainable Science, Engineering and Technology (ASSET) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) The Indonesian Journal of Computer Science Tadulako Science and Technology Journal
Syaiful Hendra
Information Technology Department, Engineering Faculty, Tadulako University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation

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Design and Implementation of a Production Forest Monitoring Information System in Central Sulawesi Province Syahrullah, Syahrullah; Najar, Abdul Mahatir; Ngemba, Hajra Rasmita; Hendra, Syaiful
SISTEMASI Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.5073

Abstract

Kesatuan Pengelola Hutan (KPH) Dolago Tanggunung, as one of the production forest managers in Central Sulawesi, faces serious challenges such as illegal logging, forest encroachment, and a high risk of forest fires. The complexity of managing production forests in this region is further hindered by manual data collection and reporting processes, which pose significant limitations. This study develops a Production Forest Management and Monitoring Information System aimed at improving efficiency in recording and monitoring production forests using the Agile-Scrum methodology, allowing for incremental development based on user needs. The system is designed as a web-based platform with key features including data collection for fire-prone areas, illegal logging incidents, and forest encroachment, as well as integration with spatial data visualization technology. Testing results indicate that the system enhances data recording efficiency, transparency in reporting, and accelerates response to on-site incidents. The implementation of this system is expected to support data-driven decision-making and strengthen sustainable forest management.
Rancang Bangun Aplikasi Diagnosa Sexually Transmitted Diseases Menggunakan Algoritma Certainty Factor Mandra; Nouval Trezandy Lapatta; Syaiful Hendra; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4293

Abstract

This research aims to design and develop an Android application that can be used to diagnose results Sexually Transmitted Diseases using algorithms Certainty Factor. Sexually Transmitted Diseases is a sexually transmitted disease that can cause serious health impacts if not immediately identified and treated appropriately. This application is designed to help users carry out initial diagnoses independently. The method used in developing this application is the Certainty Factor algorithm, which is a rule-based decision support method. This algorithm utilizes knowledge from experts in the medical field and combines it with symptom data provided by users to produce more accurate diagnoses. The app will allow users to input suggested symptoms and generate a diagnosis based on that information. It is hoped that this application will be a useful tool in a self-directed approach to diagnosis Sexually Transmitted Diseases.
Implementation of Brute Force Algorithm for Digital Land Mapping Information System: Implementasi Algoritma Brute Force untuk Sistem Informasi Pemetaan Tanah Digital Irfan, Mohamad; Ngemba, Hajra Rasmita; Hendra, Syaiful; Syahrullah, Syahrullah; Lapatta, Nouval Trezand; Hamid, Odai Amer
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2271

Abstract

The Land Asset Mapping Information System of the Palu City Local Government was developed to streamline digital land record management and enhance public service delivery. However, users experience substantial delays averaging 3-5 minutes per query during manual data searches. This study aims to optimize search efficiency by implementing the Brute force string-matching algorithm, allowing users to retrieve precise land records through direct pattern input. A waterfall system development methodology was systematically applied across five phases: requirements analysis, system design, PHP/JavaScript implementation, White Box testing, and maintenance. The research team collaborated closely with 12 technical officers from the City Spatial Planning and Land Office to validate system requirements and evaluate real-world performance. The implementation of the Brute force algorithm reduced average search times by 68\% (from 185s to 59s) while maintaining 100\% accuracy in test datasets containing 5,000+ land records. Rigorous testing confirmed the algorithm's reliability across various edge cases, including partial matches and special character inputs. The application of the Brute force method has transformed the system's search functionality, particularly for frequent queries involving land parcel IDs and owner names. These improvements have increased daily processing capacity by 40\%, significantly benefiting urban planning and dispute resolution workflows. While demonstrating excellent performance for medium-sized datasets, the solution presents opportunities for future enhancement through hybrid approaches combining Brute force with indexing techniques for large-scale deployments beyond 50,000 records.
EXPERT SYSTEM DESIGN TO DIAGNOSE PESTS AND DISEASES ON LOCAL RED ONION PALU USING BAYESIAN METHOD Junaidi, Junaidi; Fadjryani, Fadjryani; Setiawan, Iman; Batara, Mohammad; Hendra, Syaiful; Ismail, Nurmasita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.572 KB) | DOI: 10.30598/barekengvol17iss1pp0371-0382

Abstract

Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.
Comparison of Machine Learning Algorithms for Predicting Stunting Prevalence in Indonesia Pratama, Moh. Asry Eka; Hendra, Syaiful; Ngemba, Hajra Rasmita; Nur, Rosmala; Azhar, Ryfial; Laila, Rahmah
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2097

Abstract

Stunting is a serious public health problem, especially among under-fives, which can cause serious short- and long-term impacts. Efforts to tackle stunting in Indonesia involve national strategies and development priorities. Therefore, this study aims to compare the performance of machine learning regression algorithms in predicting stunting prevalence in Indonesia. The data collected is secondary data. The data collection was done carefully, taking explicit details regarding the source, scope, extent, and analysis of the dataset, and using a careful sampling methodology. The model evaluation results show that the Random Forest Regression algorithm has the best performance, with a success rate of 90.537%. The application of this model to the new dataset shows that East Nusa Tenggara province has the highest percentage of stunting at 31.85%, while Bali has the lowest percentage at 12.07%. Visualization of the dashboard using Tableau provides a clear picture of the distribution of stunting in Indonesia. In conclusion, this research contributes to the development of science, especially in the field of machine learning and public health, and provides policy recommendations for tackling stunting in Indonesia.
Co-Authors - Ifandi A Djufri, Isdar Abdul Mahatir Najar Aimar Anand Alamsyah - Alda Nur Pradinda Andhyka, Andhyka Angraeni, Dwi Shinta Anita Ahmad Kasim Anugrah Aidin Yotolembah Anwar, Asriani Azizah Azizah Batara, Mohammad Chairunnisa Ar. Lamasitudju Chandra, Ferri Rama Delia, Fenita Deny Wiria Nugraha Dharmakirti, Dharmakirti Djohari, Riyandi Dwitama Dwi Shinta Angreni Dwi Wijaya, Kadek Agus Dwiwijaya, Kadek Agus Elyana Aulia Chandra Fadjryani, Fadjryani Hajra Rasmita Hajra Rasmita Ngemba Hamid, Odai Amer Hardianti Hardianti, Hardianti I Gusti Ngurah Agung Kade Dwi Arsana Idhamsyahreza Idhamsyahreza Indrajaya, Muhammad Aristo Ismail, Nurmasita Iswandi, A.Avri Junaidi Junaidi Junus Widjaja Kade Dwi Arsana, I Gusti Ngurah Agung Laila, Rahma Lakatjinda, Adiatma Lapatta, Nouval Trezand Liza Amalia Mandra Mohamad Irfan, Mohamad Muh Alif Alghifari Muh. Aristo Indrajaya Muhammad Jindan Muhammad Nauval Daffa Ulhaq Muhammad Yazdi Ngemba, Hajra Nouval Daffa Ulhaq, Muhammad Nouval Trezandy Lapatta Pratama, Moh. Asry Eka Putri Febrina, Annisa Rahmah Laila Raivandy, I Made Randhy Rasmita Ngemba, Hajra Risaldi Pata’Dungan, Adi Rizana Fauzi, Rizana Rizka Ardiansyah Rosmala Nur Ryfial Azhar, Ryfial Setiawan, Iman Siti Rahmawati Sri Kusumadewi Sukardi Sukardi Suryani Putri, Fadiah Syahrullah Syahrullah Syahrullah Ulhaq, Muhammad Naufal Daffa Winarta, Ardhiansyah Wirdayanti Wirdhayanti Wirdhayanti Yuri Yudhaswana Joefrie Yusuf Anshori