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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JUSIFO : Jurnal Sistem Informasi Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Technomedia Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Advance Sustainable Science, Engineering and Technology (ASSET) The Indonesian Journal of Computer Science Tadulako Science and Technology Journal Advance Sustainable Science, Engineering and Technology (ASSET)
Syahrullah
Department Of Information Technology, Universitas Tadulako
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology

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Analisis Sentimen Terhadap Presiden Terpilih Dimedia Sosial Twitter (X) Menggunakan Algoritma Support Vector Machine Ono, Jumaita; Anshori , Yusuf; Yudhaswana Joefrie , Yuri; Yazdi Pusadan, Mohammad; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4388

Abstract

The current elected presidents of Indonesia are Prabowo and Gibran, with several work programs and visions and missions that are still being discussed on various social media, especially on Twitter. Based on the problems in this research, the Support Vector Machine method was applied with the dataset used amounting to 2000 data obtained from Twitter social media using scraping techniques, and divided into five scenarios, namely positive, very positive, neutral, negative and very negative. Data were tested from 100 datasets, 500 datasets, 1000 datasets, 1500 datasets, and 2000 datasets. The accuracy results obtained from 100 data were 0.40% accuracy, 0.08% precision, and 0.20% recall. The second test used 500 data with an accuracy of 0.67%, precision of 0.33% and recall of 0.24%. The third test used 1000 data with an accuracy of 0.73%, precision of 0.52% and recall of 0.29%. The fourth test used 1500 data with an accuracy of 0.74%, precision of 0.41% and recall of 0.29%. The fifth test with the highest level of accuracy uses 2000 data, with an accuracy of 0.75%, precision of 0.47%, and recall of 0.30%
Decision Support System for the Selection of Poor Families as Recipients of Government Assistance Using the ELECTRE Method Sitti Ainul Yakin; Hajra Rasmita Ngemba; Syaiful Hendra; Syahrullah
Tadulako Science and Technology Journal Vol. 1 No. 2 (2021): Tadulako Science and Technology Journal
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v1i2.17294

Abstract

Introduction: Poverty is a global problem that is often associated with needs, difficulties, and shortages in various life circumstances. The problem that occurs in Bahodopi District, Morowali Regency where there are often problems in determining the recipients of this assistance, because it still uses subjective assessments, based on manual calculations and there is still a lot of assistance aimed at poor families and not on target. Method: Researchers conducted research with the ELECTRE method of completion based on ranking and influenced by many criteria such as Employment, Number of Dependents, Income, House Condition, and House Status. For each alternative that determines the decision by ranking the best alternative. Result and Discussion: Based on testing on this system using two tests, namely black box testing and Beta Testing. In the Blackbox testing that the author did, the results showed that each function of the components in the system had run well and correctly. In the beta testing, the author conducted a questionnaire distribution process to five respondents in the aid recipient sector who would use the application to provide an assessment of the system and 30 people in the community. Based on the questionnaire, it will be obtained how accurate or suitable it is for the system that has been created Conclusion: This system was created to facilitate decision-making in selecting poor families as recipients of government assistance so that the sub-district office can make decisions correctly with computerized data.
Design and Implementation of a Customer Relationship Management System for Medium-Sized Digital Printing Enterprises Noel Marcell Jonathan Wongkar; Wirdayanti Wirdayanti; Syahrullah Syahrullah; Rinianty Rinianty; Nouval Trezandy Lapatta
JUSIFO : Jurnal Sistem Informasi Vol 10 No 2 (2024): December
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v10i2.25023

Abstract

This study investigates the design and implementation of a Customer Relationship Management (CRM) system specifically developed to address the operational challenges faced by medium-sized enterprises in the digital printing sector, with Rio Digital Printing as a case study. The research identifies key issues such as communication gaps and the lack of real-time order tracking, which negatively impact customer satisfaction. Employing a prototyping methodology, the system was iteratively refined with active user participation, ensuring alignment with stakeholder requirements. Key features include real-time order tracking, automated notifications, and a comprehensive interactive dashboard to support data-driven decision-making. The results demonstrate that the CRM system significantly enhances operational transparency, improves customer engagement, and fosters loyalty. This study contributes to the academic discourse by addressing the underexplored application of CRM systems in small and medium-sized enterprises, presenting a scalable framework for adaptation in similar industries. The findings also provide practical implications, advocating for digital transformation as a strategy to improve competitiveness in dynamic market environments.
Architectural Analysis of the Repository Pattern in Web-Based Credit Score Conversion Assessment System Based on PermenPAN-RB No. 1 of 2023 Lapatta, Nouval Trezandy; Syahrullah
Tech-E Vol. 9 No. 2 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i2.4362

Abstract

PermenPAN-RB Regulation No. 1 of 2023 introduced a major shift in functional position assessment by emphasizing performance predicate conversion in credit score evaluation, which increases architectural demands on supporting information systems. In practice, many assessment systems remain tightly coupled and difficult to evolve when regulatory rules, integration sources, or reporting formats change. This paper presents an architecture-oriented analysis of a web-based credit score conversion assessment information system that applies the Repository Pattern as a core architectural mechanism to decouple business logic from persistence, integration, and document-generation concerns. The analysis adopts a scenario-based evaluation approach inspired by the Architecture Tradeoff Analysis Method (ATAM) and is grounded in the ISO/IEC 25010 software quality model, focusing on maintainability, modifiability, testability, scalability, and reliability. Architectural evaluation is conducted by examining layered boundaries, repository abstractions, and dependency injection mechanisms under representative regulatory-driven change scenarios, including rule adjustments, data integration extensions, and reporting modifications. The results demonstrate consistent change localization across architectural layers, where rule changes are confined to service modules, integration changes are absorbed by repository adapters, and reporting changes remain isolated within document-generation components. These findings show that repository-based architectures significantly reduce coupling, improve change isolation, and support the sustainable evolution of government information systems operating under dynamic regulatory environments.
SISTEM PERINGATAN DINI GEMPA DAN TSUNAMI MENGGUNAKAN ARTIFICIAL NEURAL NETWORK Wiwik Supriyatin; Moh. Eno Farhan; Syahrullah Syahrullah; Deny Wiria Nugraha; Yuri Yudhaswana Joefrie
Journal of Information System Management (JOISM) Vol. 8 No. 1 (2026): Juni
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2026v8i1.2484

Abstract

Penelitian ini bertujuan untuk meningkatkan keselamatan publik melalui penyediaan prediksi tsunami yang cepat dan andal dengan memanfaatkan algoritma Artificial Neural Network (ANN) dalam sistem berbasis web. Masalah utama yang diangkat adalah tingginya risiko kerugian material dan korban jiwa akibat keterlambatan informasi serta potensi false alarm pada pengolahan data konvensional. Metode penyelesaian dilakukan dengan menerapkan arsitektur jaringan saraf ANN (susuna lapisan layer 9-10-8-1) yang mengolah parameter Magnitudo, Kedalaman, Jarak ke Pantai, serta Jenis Patahan sebagai input utama. Hasil perancangan menunjukkan performa sistem yang sangat presisi, dibuktikan dengan perolehan nilai Error Akhir sebesar 0,004950 pada iterasi ke-58 yang merepresentasikan tingkat akurasi pelatihan mencapai 99,50%. Selain itu, pengujian pada skenario gempa Magnitudo 7.5 menghasilkan Probabilitas Tsunami sebesar 93,38% dengan tingkat kepercayaan tinggi. Integrasi ANN dalam platform web ini terbukti mampu menyediakan informasi yang terstruktur, akurat, dan ramah pengguna sebagai instrumen krusial dalam pengambilan tindakan tanggap bencana yang efektif.
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
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.
ANALISIS SENTIMEN MASYARAKAT DI MEDIA SOSIAL X TERHADAP MASALAH ROHINGYA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE DAN TEKNIK RESAMPLING Tri Krama; Nouval Trezandy Lapatta; Chairunnisa Ar. Lamasitudju; Syahrullah Syahrullah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6193

Abstract

Di era modern ini, penggunaan media sosial terus meningkat karena kemajuan dalam teknologi informasi dan komunikasi. X, sebagai salah satu platform media sosial populer, memungkinkan pengguna untuk berinteraksi dan berdiskusi mengenai berbagai isu, termasuk masalah pengungsi Rohingya. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap isu Rohingya di X menggunakan algoritma Support Vector Machine (SVM) dan teknik resampling untuk mengatasi ketidakseimbangan data. Metode yang digunakan meliputi oversampling dengan Synthetic Minority Over-sampling Technique (SMOTE) dan random undersampling untuk menyeimbangkan dataset. Hasil penelitian menunjukkan bahwa setelah penerapan SMOTE dan random undersampling, model SVM mencapai akurasi 89% dengan precision 0,9, recall 0,89, dan f1-score 0,89. Selain itu, penggunaan seleksi fitur dengan chi-square juga terbukti efektif dalam meningkatkan akurasi model, meskipun peningkatannya sedikit, yaitu dari 89% menjadi 90%.Temuan ini menekankan pentingnya penggunaan teknik resampling dan seleksi fitur yang tepat dalam analisis sentimen sosial yang kompleks, khususnya dalam konteks isu pengungsi Rohingya di platform X.
KLASIFIKASI JENIS KAYU BERDASARKAN CITRA SERAT KAYU MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Muhammad Rifaldi Dwimanhendra; Syahrullah Syahrullah; Yuri Yudhaswana Joefrie; Dwi Shinta Angreni; Ryfial Azhar; Deny Wiria Nugraha; Nouval rezandy Lapatta; Abdul Mahatir Najar
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5726

Abstract

Kayu merupakan sumber daya alam yang sangat penting bagi industri mebel atau furnitur. Pemilihan jenis kayu yang tepat sangat krusial dalam industri mebel untuk menentukan kualitas hasil produksi. Pemilihan kayu secara manual memiliki risiko kesalahan yang dapat berdampak negatif pada kualitas akhir produk mebel. Oleh karena itu, diperlukan penerapan teknologi untuk meminimalkan kesalahan pemilihan jenis kayu dan meningkatkan efisiensi proses produksi. Penelitian ini bertujuan membangun model klasifikasi jenis kayu (nantu, palapi, dan uru) berbasis Convolutional Neural Network (CNN) menggunakan citra serat kayu. Dataset terdiri dari 1.584 citra yang dibagi menjadi 80% data pelatihan dan 20% data pengujian. Arsitektur model CNN terdiri dari 4 lapisan konvolusi, 4 lapisan pooling, dan 2 lapisan fully-connected. Hasil pelatihan mencapai akurasi 97,06%, sedangkan hasil pengujian dan evaluasi menggunakan matriks konfusi mencapai akurasi 95,56%. Penelitian ini membuktikan bahwa CNN dapat digunakan secara efektif untuk klasifikasi jenis kayu dengan tingkat akurasi yang tinggi, sehingga dapat membantu meningkatkan efisiensi proses produksi mebel.
Pengenalan Batik Bomba Menggunakan Teknologi Augmented Reality Dengan Metode Markerless Berbasis Android Tafania Natalia Kasaedja; Anita Ahmad Kasim; Mohammad Yazdi Pusadan; Syahrullah Syahrullah; Rahmah Laila
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6128

Abstract

Batik Bomba merupakan kain tradisional khas suku Kaili yang menjadi salah satu kekayaan Sulawesi Tengah. Motif dan pola batik Bomba memiliki bentuk yang unik, dengan makna filosofis yang berlandaskan kehidupan masyarakat suku Kaili yang tersirat didalamnya. Namun pemahaman tentang ragam motif batik Bomba belum dikenal luas oleh masyarakat Sulawesi Tengah khususnya Kota Palu. Hal ini disebabkan karena media informasi untuk visualisasi kain batik Bomba masih kurang, umumnya hanya berbentuk gambar 2D yang dapat ditemui di museum atau pameran seni. Dari permasalahan tersebut, penulis bertujuan untuk memberikan informasi kepada masyarakat lokal maupun masyarakat luar mengenai filosofi motif batik Bomba secara detail dan mudah dipahami dengan memanfaatkan media teknologi Augmented Reality menggunakan metode markerless yang menampilkan objek 3D batik Bomba. Dalam pengembangan aplikasi, penulis menggunakan metode agile Extreme Programming (XP) yang akan diimplementasikan kedalam aplikasi berbasis android. Diperoleh hasil analisis pengujian menggunakan metode Blackbox Testing yang dilakukan oleh develop, dan User Acceptance Testing (UAT) melalui kuesioner yang dibagikan kepada pengguna aplikasi, bahwa aplikasi yang dikembangkan berjalan sesuai dengan fungsionalitasnya dan memperoleh skor rata-rata 107,25 (Sangat Memuaskan). Dengan demikian, aplikasi AR About Bomba dapat menjadi mediator pengenalan filosofi setiap motif batik Bomba.
Implementation Aes-128 Encryption For Enhanced Data Security In Central Sulawesi Provincial Inspectorate Imam Wahyudi; Syahrullah; Dwi Shinta Anggreni; Rahmah Laila
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.560

Abstract

One technique to secure data is to use the Advanced Encrypt on Standard (AES) 128 method. The Advanced Encrypt on Standard (AES) method can be applied in improving data security, especially at the Central Sulawesi Provincial Inspectorate. The data in question are audit reports of BOS funds (School Operational Assistance), reports of special investigations into violations of regional finances and reports of violations of civil servant discipline (PNS). The data must have a high level of security, so that it is not easily known by irresponsible parties and will have a negative impact and be misused. The conclusion in this study was obtained that, the AES-128 algorithm can be used as an alternative to the process of improving data security, namely by encryption and decryption. The results of encryption can be guaranteed as long as the symmetry key encryption is not leaked to irresponsible parties
Co-Authors Abdul Mahatir Najar Agung Stiven Cahyati Angely Ahmad Imam Abdullah Andi Hendra Anita Ahmad Kasim Budi Mulyono Deny Wiria Nugraha Dwi Shinta Anggreni Dwi Shinta Angreni Hajra Rasmita Hajra Rasmita Ngemba Imam Wahyudi Iswandi, A.Avri Kade Dwi Arsana, I Gusti Ngurah Agung Lamasitudju, Chairunnisa Mandra Merry Moh. Eno Farhan Mohammad Yazdi Pusadan Muhammad Jindan Muhammad Rifaldi Dwimanhendra Mutia Ngemba, Hajra Noel Marcell Jonathan Wongkar Nouval Daffa Ulhaq, Muhammad Nouval Trezandy Lapatta Ono, Jumaita Rahmah Laila Rahmah Laila Rinianty Rinianty Ryfial Azhar Sitti Ainul Yakin Sukardi Sukardi Syaiful Hendra Syaiful Hendra Tafania Natalia Kasaedja Tri Krama Wirdayanti Wirdayanti Wirdayanti Wiwik Supriyatin Yuri Yudhaswana Joefrie Yusuf Anshori