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Jurnal Riset Sistem dan Teknologi Informasi
Published by Universitas Aisyiyah Surakarta
ISSN : -     EISSN : 29885663     DOI : https://doi.org/10.30787/restia
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
theory and information science, information systems, information security, data processing and structure, programming and computing, software engineering, informatics, computer science, computer engineering, architecture and computer networks, robotics, parallel and distributed computing, operating systems, compilers and interpreters, games, numerical methods, mobile computing, natural language processing, data mining, cognitive systems, speech processing, machine learning, artificial intelligence, expert systems, geographical information systems, computational theory, and informatics applications in various fields.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 40 Documents
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Optimisasi Analisis Pelaksanan Pelaporan Pasien Menggunakan Sistem Informasi Rumah Sakit( SIRS) Online di Rumah Sakit Sentra Medika Sanggau Tahun 2023 Sardi, Aditiya; Wahyudi, Wahyudi
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i1.1420

Abstract

Hospital Information System is the collection, processing and presentation of hospital data throughout Indonesia. The purpose of this study was to determine the percentage of patients for the period 2022-2023 and to determine the factors that influence the implementation of patient reporting using the Online Hospital Information System (SIRS) at Sanggau Medika Center Hospital. This type of research is descriptive with a qualitative approach that aims to determine the implementation of patient reporting using the online Hospital Information System (SIRS). The results of this study are seen from the human factor, the number of officers is still lacking with the number of officers only two people. Method, there is no standard operating procedure regarding patient reporting using the Online Hospital Information System (SIRS). Machines, networks that are experiencing problems. Material, the absence of a hospital management information system has a direct impact on the effectiveness and efficiency of staff work. In conclusion, the utilization of the Online Hospital Information System (SIRS) application at Sanggau Medika Center Hospital is quite good but still not optimal, because the number of officers is still limited and the available facilities cannot fully support the utilization of the Online Hospital Information System (SIRS) in patient reporting.
Information System Strategy for Improving Academic Service Quality at UM Banjarmasin Through the Development of Academic Extension (ADEX) Innovation Application Kamarudin, Kamarudin
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i1.1650

Abstract

This research program aims to enhance academic service quality at Universitas Muhammadiyah Banjarmasin (UM Banjarmasin) through the development of an innovative application called Academic Extension (ADEX). The initiative was driven by the need to improve efficiency and integration of academic services, addressing the current inadequate systems that fail to support effective academic management. The research methodology involved three key phases: needs analysis, application development, and field testing. ADEX incorporates various features to streamline academic management, including schedule management, attendance tracking, and communication channels between faculty members and students. The implementation of ADEX has demonstrated significant improvements in both efficiency and quality of academic services at UM Banjarmasin, delivering tangible benefits to the entire academic community. Results indicate that the integration of ADEX has successfully addressed the initial challenges, providing a comprehensive solution for academic service management while enhancing the overall educational experience for both faculty and students.
Analisis Sentimen Masyarakat Terhadap Kebijakan Kenaikan Umk 6,5% Menggunakan Metode Naive Bayes Fitriyadi, Farid; Astikasari, Arsaela
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i1.1885

Abstract

Kenaikan Upah Minimum Kabupaten/Kota (UMK) sebesar 6,5% telah memicu beragam tanggapan pro dan kontra dari masyarakat di semua sektor baik dari sisi pengusaha, buruh maupun karyawan. Maka dari itu, peneliti bermaksud melakukan analisis sentimen untuk memahami respons publik terhadap kebijakan tersebut dengan menggunakan algoritma Naive Bayes. Data penelitian dikumpulkan dari media sosial seperti twitter sejumlah 395 data tweet dengan hastag #kenaikanumk, kemudian dilakukan pemrosesan dengan metodologi KDD yang selanjutnya dilakukan pelabelan otomatis menggunakan libray text bloob dan dikategorikan ke dalam tiga jenis sentimen: positif, negatif, dan netral. Berdasarkan hasil performance penelitian, analisis sentiment terhadap kenaikan UMK mendapatkan tingkat akurasi mencapai sebesar 95% yang mengindikasikan bahwa naïve bayes sangat efektif untuk menganalisis sentimen berbasis teks, presisi sebesar 32%, recall sebesar 33%, dan f-measure sebesar 32%. Sedangkan, hasil analisis terhadap sentimen menunjukkan bahwa sebagian besar sentimen masyarakat terhadap kebijakan ini bersifat netral, namun terdapat perbedaan signifikan antara kelompok masyarakat yang mendukung dan menentang kebijakan tersebut.
Analisis dan Pengujian Kerentanan Website Menggunakan OWASP ZAP Pramuja Inngam Fanani, Galih; Muhammad Amirul Mu’min; Tristanti, Novi
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i1.1886

Abstract

Penggunaan internet sedang meningkat, dengan situs web seperti mesin pencari, e-commerce, media sosial, dan portal berita yang sering diakses. Namun, situs web ini sering memiliki celah keamanan yang dapat dieksploitasi untuk ancaman siber. Oleh karena itu penelitian ini bertujuan untuk meningkatkan ketahanan web terhadap serangan siber dan memastikan pengalaman pengguna yang lebih aman, lebih andal dan data pengguna terlindungi. OWASP ZAP adalah alat keamanan yang banyak digunakan yang membantu organisasi mengidentifikasi dan mengatasi kerentanan dalam aplikasi web. Alat ini menawarkan fitur seperti pemindaian otomatis, kemampuan pengujian manual, dan fungsionalitas pelaporan yang komprehensif. Analisis kerentanan berbasis OWASP ZAP membantu mengidentifikasi tingkat keamanan aplikasi web melalui metode pemindaian pasif dan aktif, mendeteksi celah keamanan seperti injeksi SQL, skrip lintas situs, dan konfigurasi yang tidak aman. Temuan kerentanan seperti A01, A03, A04, A05, A06, A08, dan A09 yang mencakup ancaman seperti Cross-Site Scripting (XSS), Clickjacking, dan Man-in-the-Middle menyoroti pentingnya penerapan langkah-langkah mitigasi untuk melindungi keamanan situs web. Penerapan solusi seperti konfigurasi header keamanan (CSP, HSTS, dan X-Frame Options) serta perlindungan terhadap data sensitif sangat penting untuk mencegah eksploitasi. Sehingga dalam pencegahannya diperlukan penerapan protokol enkripsi, pembaruan perangkat lunak secara berkala, pelaksanaan penilaian kerentanan, dan pelatihan karyawan tentang praktik terbaik keamanan siber  
Optimalisasi Desain UI/UX untuk Meningkatkan Aksesibilitas Teknologi Digital bagi Lansia dan Penyandang Disabilitas Ario Tri Wibowo, Kresno; Suryo Murtopo, Agus
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 1 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i1.1887

Abstract

Penelitian ini bertujuan untuk mengeksplorasi tantangan yang dihadapi oleh lansia dan penyandang disabilitas dalam mengakses teknologi digital, serta untuk merumuskan rekomendasi perbaikan desain UI/UX yang lebih inklusif. Melalui survei yang melibatkan 20 responden dari berbagai kelompok usia dan jenis disabilitas, penelitian ini mengidentifikasi bahwa mayoritas responden berusia di atas 60 tahun dan mengalami berbagai kesulitan dalam membaca teks serta navigasi. Temuan ini menunjukkan bahwa desain antarmuka yang kompleks dan kurangnya perhatian terhadap prinsip aksesibilitas memperburuk pengalaman pengguna bagi kelompok rentan ini. Dengan analisis data kualitatif melalui wawancara mendalam, penelitian ini menemukan kebutuhan akan antarmuka yang lebih sederhana dan dukungan pelatihan untuk pengguna. Rekomendasi yang diusulkan meliputi peningkatan desain UI/UX dengan fitur aksesibilitas serta penyediaan pelatihan untuk meningkatkan kesadaran dan kemampuan teknologi bagi lansia dan penyandang disabilitas. Penelitian ini menekankan pentingnya penciptaan teknologi yang inklusif untuk memastikan bahwa semua individu, tanpa terkecuali, dapat memanfaatkan layanan digital secara efektif dan nyaman.
Precision Healthcare: Leveraging Value Chain Analysis of Strategic Information Systems and Information Technology to Enhance Hospital Outcomes Kamarudin, Kamarudin
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.1519

Abstract

In the healthcare digitalization era, leveraging strategic information systems (IS) and information technology (IT) through value chain analysis has emerged as a pivotal approach to enhance hospital outcomes. This study aims to develop a framework for integrating IS/IT strategies at Datu Sanggul Hospital, a Class C facility in South Kalimantan, to achieve precision healthcare delivery. The research methodology encompasses data collection via document studies, stakeholder interviews, and observations, coupled with rigorous data analysis and validation techniques. A strategic model formulates algorithms and system architectures guiding implementation of critical IS/IT initiatives like telemedicine, customer relationship management, and executive information systems. Robust IT strategies, including data center development, cloud computing, and disaster recovery planning, optimize operations and resource management. Mapping business needs to tailored IS solutions ensures precision across financial reporting, inventory management, employee training, and interdepartmental collaboration. The proposed approach aligns IS/IT strategies with operational objectives through value chain analysis, enhancing patient care quality, operational efficiency, and resource optimization. Positioning the institution for precision medicine, this framework drives innovation and improves health outcomes in healthcare's evolving landscape.
Klasifikasi Data Tak Seimbang menggunakan Algoritma Random Forest dengan SMOTE dan SMOTE-ENN (Studi Kasus pada Data Stunting) Fauziah, Anju; Julan Hernadi
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.1906

Abstract

The random forest algorithm is one of the widely used machine learning classification methods because it has the advantage of reducing the risk of overfitting while improving general prediction performance. However, for data with unbalanced classes, this algorithm lacks to achieve its best performance, particularly in predicting data in the minority class. As a result, this article proposes two resampling approaches to balance the data: the Synthetic Minority Oversampling Technique (SMOTE) and the Synthetic Minority Oversampling Technique with Edited Nearest Neighbors (SMOTE-ENN). For the data classification technique, the random forest algorithm is applied to the original data, then to the resampling results using both SMOTE as well as SMOTE-ENN. The case study was applied to stunting data consisting of 421 cases in the majority class and 79 in the minority class. An accuracy of 89% was obtained on the original data, 90% on the resampled data with SMOTE-ENN, and 91% on the resampled data with SMOTE. The best accuracy was obtained using resampling technique with SMOTE, however it was not particularly significant.
Evaluasi Sentimen Pengguna ChatGPT Menggunakan Naive Bayes: Tinjauan dari Confusion Matrix dan Classification Report Dianda Rifaldi; Tri Stiyo Famuji; Bella Okta Sari Miranda; Fauzan Purma Ramadhan; Iriene Putri Mulyadi; Vanji Saputra6; Fanani, Galih Pramuja Inngam
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.1990

Abstract

The development of artificial intelligence (AI) technology, particularly in natural language processing (NLP), has led to various innovations, including ChatGPT. Its growing popularity highlights the need for user sentiment analysis. This study evaluates user sentiment toward ChatGPT using the Naive Bayes algorithm. The dataset, obtained from Kaggle, consists of 500 labeled English tweets categorized as positive, neutral, or negative. The process involved text preprocessing, TF-IDF feature extraction, data splitting (80% training, 20% testing), and model training. The results show an accuracy of 56%, with the highest f1-score in the negative class (0.67) and the lowest in the neutral class (0.38). The model exhibits classification imbalance, with high precision but low recall in the neutral class, and high recall but low precision in the positive class. The confusion matrix further confirms frequent misclassifications between classes. These findings reflect the limitations of Naive Bayes in handling contextual relationships in text data. Improvements can be achieved through data balancing, enhanced NLP-based feature representation, and the application of more complex classification algorithms.
Metode Forward chaining untuk Deteksi Gangguan Kejiwaan Dini Bakhtiar, Muhammad Yusuf; Triyadi; Sihombing, Redo Abeputra; Fauzan Natsir
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.1996

Abstract

Mental disorders are specific conditions associated with symptoms and pain that cause disruptions in psychosocial functioning. In general, people who want to diagnose mental disorders need to meet directly with a doctor. This research aims to develop an expert system that can assist in the process of diagnosing mental disorders, where this system can produce decisions equivalent to those of a doctor, so that the public no longer needs to meet a doctor directly for initial diagnosis. This research applies the forward chaining method with 5 types of disorders and 28 types of symptoms, which is a search technique that starts with known facts, then managed with existing data and applies inference rules to reach a conclusion. Thus, the application of this method has the potential to become an innovative solution in supporting the prevention and management of mental disorders from the early stages.
Sistem Pendukung Keputusan untuk Pemilihan Sepeda Motor bagi Mahasiswa dengan Menggunakan Metode Simple Additive Weighting (SAW) Anggit Suryan Rohyan; Satria Fajar Dwi Kurniawan; Hendra Maulana; Nor Anisa
Jurnal Riset Sistem dan Teknologi Informasi Vol. 3 No. 2 (2025): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v3i2.2067

Abstract

Researchers conducted a selection process for motorcycles that align with the needs and financial conditions of students, as this process is often quite complex. This complexity arises from the wide range of options and the numerous criteria that must be considered, such as price, fuel efficiency, engine capacity, comfort level, and design aesthetics. The objective of this study is to design a Decision Support System (DSS) by implementing the Simple Additive Weighting (SAW) method to assist students in selecting the motorcycle that best fits their needs. The SAW method was chosen due to its effectiveness in handling multi-criteria decision-making problems by assigning weights to each criterion and calculating the preference value for each available alternative. The system was developed using a quantitative approach, with data collected through surveys and documentation of motorcycle specifications. The test results indicated that the system was capable of providing accurate and relevant recommendations based on user needs. Therefore, this system has the potential to serve as an effective tool in supporting students' motorcycle selection decisions.

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