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RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Published by Universitas Abdurrab
ISSN : 24772062     EISSN : 2502891X     DOI : https://doi.org/10.36341/rabit
Core Subject : Science, Engineering,
Computer Science & IT Engineering
This journal is called RABIT, where the name comes from two words namely, RAB which means Abdurrab University and IT which means information technology, it can be interpreted as a journal of this journal Journal of Informatics Engineering Study Program Pekanbaru Abdurrab University. This RABIT journal contains various sciences related to the world of computers especially information technology and information systems, namely, this journal is published twice a year where the initial publication is on January 10 while for the second issue which is on July 10.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 696 Documents
 66   67   68   69   70 
THE IMPACT OF ARDUINO CODING LEARNING ON COMPUTATIONAL THINKING SKILLS OF JUNIOR HIGH SCHOOL STUDENTS Rahmat Setiawan; Sahiruddin Sahiruddin; Firman Firman; Endra Putra Raharja
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8446

Abstract

This study aimed to examine the effect of Arduino-based coding learning on junior high school students' computational thinking skills. A quasi-experimental method with a pretest-posttest control group design was employed. Twenty junior high school students participated in the study and were divided into two groups: 10 students in the experimental group received Arduino-based coding instruction, while 10 students in the control group received conventional coding instruction. Data were collected using a computational thinking skills test administered before and after the intervention. The data were analyzed using descriptive statistics, normality and homogeneity tests, paired-samples t-tests, and an independent-samples t-test. The results showed that the experimental group's mean score increased from 58.40 to 84.60, whereas the control group's mean score increased from 57.90 to 68.30. The independent-samples t-test revealed a significant difference between the two groups (t = 6.02, p < 0.001). Furthermore, students in the experimental group achieved higher scores across all computational thinking dimensions, including decomposition, pattern recognition, abstraction, and algorithmic thinking. These findings indicate that Arduino-based coding learning is more effective than conventional coding instruction in improving junior high school students' computational thinking skills.
IMPLEMENTASI METODE SINGLE EXPONENTIAL SMOOTHING UNTUK PREDIKSI STOK BAHAN BAKU PROGRAM MAKAN BERGIZI GRATIS: IMPLEMENTATION OF THE SINGLE EXPONENTIAL SMOOTHING METHOD FOR FORECASTING RAW MATERIAL STOCK IN THE FREE NUTRITIOUS MEAL PROGRAM Dewi Prima Apriliaissabella; Retno Wardhani; M. Hasan Wahyudi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8448

Abstract

The Free Nutritious Meal Program (MBG) requires effective raw material inventory management to ensure an adequate food supply. One of the problems faced by the Nutritional Fulfillment Service Unit (SPPG) Nur Amanah 10 was determining the raw material requirements for the next period because inventory planning was still carried out manually based on estimation, leading to shortages or excess inventory. This study aimed to develop a raw material inventory forecasting system using the Single Exponential Smoothing (SES) method. Historical raw material demand data were used, and alpha values ranging from 0.1 to 0.9 were evaluated to determine the optimal parameter based on the smallest Root Mean Squared Error (RMSE). The system was developed using PHP, the Laravel framework, and a MySQL database and was tested using black box testing. The results showed that 17 out of 94 raw material types met the forecasting requirements. An alpha value of 0.1 was the most frequently selected optimal parameter, while most forecasting results produced relatively low RMSE values. The system was able to display forecasting results, the optimal alpha value, RMSE values, and detailed SES calculations, thereby assisting SPPG managers in planning raw material requirements more effectively.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PENGURUS OSIS MENGGUNAKAN METODE FUZZY TSUKAMOTO: Metode Fuzzy Tsukamoto M. Asep Thosin; Purnomo Hadi Susilo; Agus Setia Budi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8450

Abstract

The selection process of Student Council (OSIS) administrators is commonly conducted manually, which may lead to bias and inconsistency in decision-making. This study aims to develop a web-based Decision Support System (DSS) using the Fuzzy Tsukamoto method to provide a more objective and measurable recommendation for selecting OSIS members. The research employed the Research and Development (R&D) approach following the ADDIE model, which consists of analysis, design, development, implementation, and evaluation stages. The assessment of prospective OSIS members was based on six criteria: academic performance, leadership, discipline, responsibility, communication skills, and achievements in academic olympiads. The Fuzzy Tsukamoto method was implemented through fuzzification, rule-based inference, and defuzzification processes to generate final scores and rankings for each candidate. The system was tested using data from 220 prospective OSIS members. Performance evaluation was conducted by comparing the system's recommendations with the supervisor's decisions using a Confusion Matrix. The results indicate that the system is capable of producing consistent and objective candidate rankings while supporting a more effective, transparent, and accurate selection process. The implementation of a web-based DSS utilizing the Fuzzy Tsukamoto method has proven to assist decision-makers in selecting qualified OSIS members according to predefined criteria and improving the overall quality of the selection process in schools. Keywords: Decision Support System, Fuzzy Tsukamoto, Student Council (OSIS), Web-Based DSS, Confusion Matrix.
SISTEM PREDIKSI PERSEDIAAN STOK BARANG DI BUBIN CATERING MENGGUNAKAN METODE SES DAN WMA Istiana Nur Khasanah; Purnomo Hadi Susilo; Mustain Mustain
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Raw material inventory management in catering businesses required an accurate planning system to prevent stock shortages and overstock conditions that could disrupt operational activities. This study aimed to develop a web-based inventory prediction system by implementing the Weighted Moving Average (WMA) and Single Exponential Smoothing (SES) methods and to compare the accuracy of both methods using the Mean Absolute Percentage Error (MAPE). The data used in this study were historical raw material usage records from Bubin Catering covering the period from March 12, 2025, to May 8, 2025. The system was developed using the Laravel framework and included inventory management, incoming goods, outgoing goods, prediction, and detailed calculation features. The results of Black Box Testing showed that all system functions operated as expected. Based on the evaluation of five raw material samples, the WMA method produced MAPE values of 33%, 36%, 24%, 55%, and 41%, while the SES method produced the best MAPE values of 32.53%, 36.80%, 56.70%, 61.00%, and 46.60%. Overall, the WMA method produced lower prediction errors for four of the five raw material samples, whereas the SES method performed better for only one sample. Therefore, the WMA method was more suitable for predicting inventory requirements using the historical data of Bubin Catering in this study.
SISTEM PAKAR DIAGNOSA PENYAKIT AMBEIEN BERBASIS WEB MENGGUNAKAN METODE CERTAINTY FACTOR Husnul Khotimah Arif; Lilis Nur Hayati; Sugiarti
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8455

Abstract

Lack of early treatment leads many patients to seek medical attention only when they have Grade IV Internal Hemorrhoids. Without proper treatment, this condition can lead to serious complications such as severe pain and anemia due to repeated bleeding. Hemorrhoids are a medical condition characterized by swelling of the veins in the anus and lower rectum, which can cause pain, itching, and bleeding during bowel movements. Hemorrhoids include 18 symptoms and are divided into six types: grades I-IV internal hemorrhoids, external hemorrhoids, and thrombosed hemorrhoids. The purpose of this research is to develop an expert system application for diagnosing hemorrhoids to help the public determine the severity of their condition. This system is built using a knowledge base obtained from doctors who have treated hemorrhoids. The Certainty Factor method helps explain the level of confidence in a symptom based on expert knowledge, so users can obtain initial information before seeking further examination by a medical professional. From the trial of 22 samples with a comparison of the system test results with experts, there were 4 that did not match, so the system obtained a percentage of 81,82% system accuracy in diagnosing hemorrhoids, so this application makes it easier for users to diagnose the type of hemorrhoids.
COMPARATIVE ANALYSIS OF PERFORMANCE EVALUATION FOR STROKE RISK PREDICTION BASED ON CLINICAL DATA Alya Masitha; Hamid Muhammad Jumasa; Wellie Sulistijanti; Kresna Ardy Bayuaji
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8458

Abstract

Stroke is one of the leading causes of death and disability worldwide, requiring an accurate machine learning-based risk prediction approach to support early detection. This study aims to conduct a comparative evaluation of three supervised learning algorithms, namely Naïve Bayes, Random Forest, and SVM, in predicting stroke risk. The clinical dataset used consisted of 5,110 patients. Model evaluation was performed using the Stratified 5-Fold Cross Validation method, a cross-validation technique that divides the data into five subsets while maintaining the class proportions in each fold. Each subset is alternately used as test data, while the other subset is used as training data, so that all data can be used as training data and test data. Model performance was measured using accuracy, confusion matrix, and AUC-ROC metrics to assess classification performance. The results showed that Random Forest achieved the best performance with an accuracy of 95%, followed by Naïve Bayes at 86% and SVM at 75%. Based on the AUC-ROC evaluation, Random Forest also showed the most optimal performance with a value of 0.80, indicating excellent classification ability. Random Forest is the most effective algorithm in predicting stroke risk in the dataset used, so it has the potential to be the best method used to support the early stroke detection system.
DETEKSI DAN MITIGASI SERANGAN POST-EXPLOITATION PADA LINGKUNGAN CONTAINER LINUX MENGGUNAKAN CROWDSEC DAN AUDITD Julang Tahta Pratangga; Chaerul Umam; L. Budi Handoko; Wildanil Ghozi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8461

Abstract

Containerized environments present significant security challenges due to their shared kernel architecture, which may be exploited as an entry point for infiltration attacks. One common vulnerability is Command Injection, enabling post-exploitation activities that are difficult to detect using conventional signature-based mechanisms. This study aims to implement and evaluate an active mitigation mechanism based on behavioral analysis by integrating the Linux Audit Daemon (Auditd) and CrowdSec within a Podman container environment. The research adopts an Experimental Security Testing approach by developing a Custom Process Bouncer that specifically monitors the execve system call to identify process relationships and automatically terminate malicious processes. Test results against four detection scenarios demonstrate that the proposed mechanism successfully reconstructed the attack process chain through PID cascade analysis and detected six malicious processes generated during the Command Injection scenario. All identified processes were automatically terminated with precision, causing the reverse shell session to be interrupted. These findings conclude that the integration of Auditd, CrowdSec, and the Custom Process Bouncer effectively neutralizes post-exploitation activities reliant on binary file execution, though further development is required to address fileless execution tactics.
IMPLEMENTASI BARCODE PADA SISTEM ABSENSI DAN PENGGAJIAN GURU BERBASIS WEB Afin Maulana; Purnomo Hadi Susilo; Agus Setia Budi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8462

Abstract

The management of attendance and teacher payroll at TPQ Baitul Makmur Cumpleng was previously still carried out manually, causing the process of recording attendance, calculating salaries, and preparing reports to take a relatively long time and potentially cause recording and calculation errors. This research aims to implement barcode technology in a web-based teacher attendance and payroll system to improve the efficiency, accuracy, and effectiveness of administrative data management. The system development method used is the Waterfall method which includes needs analysis, system design, implementation, and testing. The system was developed using the CodeIgniter 4 Framework, PHP programming language, MySQL database, and barcode technology as a medium for teacher identification in the attendance process. Attendance data obtained through barcode scanning is automatically stored in the database and used as the basis for calculating salaries, allowances, and deductions in an integrated manner. System testing is carried out through the measurement of the level of process speed by comparing the completion time of administrative activities before and after using the system. The test results show that the system is able to speed up the attendance process, data processing, payroll calculation, and report creation compared to manual methods. In addition, the system is able to reduce recording errors, improve data accuracy, and produce more structured and accessible attendance and payroll information. Thus, the implementation of barcodes in the web-based attendance and payroll system is able to increase the effectiveness and efficiency of administrative management at TPQ Baitul Makmur Cumpleng.
ANALISIS QOS JARINGAN FIBER OPTIC POLI BEDAH RS AKADEMIK UGM DI JAM SIBUK Dymas Septa Haryanto; Imam Suharjo
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8469

Abstract

ABSTRAKImplementasi Sistem Informasi Manajemen Rumah Sakit (SIMRS) dan Rekam Medis Elektronik (RME) menuntut dukungan infrastruktur jaringan komunikasi data yang andal untuk menjamin kelancaran operasional pelayanan medis. Unit Poli Bedah di RS Akademik UGM merupakan salah satu area vital yang membutuhkan stabilitas akses data tinggi, namun unit ini sering kali menghadapi tantangan berupa degradasi performa jaringan pada periode beban trafik puncak atau jam sibuk. Penelitian ini bertujuan untuk mengevaluasi performa Quality of Service (QoS) pada infrastruktur fiber optic di unit tersebut guna memetakan kualitas transmisi data riil yang dirasakan oleh pengguna akhir. Metodologi penelitian yang diterapkan adalah pendekatan kuantitatif dengan metode deskriptif. Pengambilan data dilakukan melalui teknik packet sniffing menggunakan perangkat lunak Wireshark pada empat titik pengambilan data (satu komputer pendaftaran, satu komputer dokter, dan dua komputer perawat) selama lima hari kerja pada jam sibuk pukul 09.00 sampai dengan 14.00 WIB. Data hasil tangkapan trafik kemudian diolah secara komputasional menggunakan bahasa pemrograman Python di platform Visual Studio Code untuk menghitung parameter throughput, packet loss, delay, dan jitter berdasarkan standarisasi TIPHON. Hasil analisis menunjukkan performa jaringan di unit Poli Bedah memiliki nilai rata-rata throughput sebesar 205,79 Kbps (Indeks 1 – Kategori: Sangat Kurang), packet loss sebesar 9,62% (Indeks 3 – Kategori: Baik), delay sebesar 10,18 ms (Indeks 4 – Kategori: Sangat Baik), dan jitter sebesar 14,84 ms (Indeks 3 – Kategori: Baik). Secara keseluruhan, kualitas jaringan fiber optic di unit tersebut memperoleh nilai indeks rata-rata 2,75 yang masuk dalam klasifikasi kategori Baik. Aspek responsivitas (latensi) dan stabilitas jaringan berada pada level yang sangat memadai. Namun, kapasitas pengiriman data (throughput) menjadi hambatan utama yang perlu dioptimalkan melalui manajemen bandwidth atau peremajaan infrastruktur guna mendukung transformasi kesehatan digital yang berkelanjutan secara real-time.Kata Kunci: Fiber Optic, Quality of Service (QoS), Wireshark, TIPHON, Poli Bedah. ABSTRACT The implementation of Hospital Management Information Systems (SIMRS) and Electronic Medical Records (EMR) requires a reliable data communication network infrastructure to ensure smooth medical service operations. The Surgical Outpatient Unit at UGM Academic Hospital is a critical area requiring high data access stability; however, it frequently experiences network performance degradation during peak traffic periods or busy hours. This study aims to evaluate the Quality of Service (QoS) performance of the fiber-optic infrastructure in the unit and map the actual data transmission quality experienced by end-users. A quantitative approach using a descriptive method was employed. Data collection was conducted via packet sniffing using Wireshark software at four data collection points (one registration computer, one physician's computer, and two nurses' computers) over five working days during peak hours (09:00 to 14:00 WIB). The captured traffic data was processed in Python using Visual Studio Code to calculate throughput, packet loss, delay, and jitter parameters in accordance with TIPHON standards. Analysis results indicate that the network performance in the Surgical Outpatient Unit yielded an average throughput of 205.79 Kbps (Index 1 – Category: Very Poor), packet loss of 9.62% (Index 3 – Category: Good), delay of 10.18 ms (Index 4 – Category: Very Good), and jitter of 14.84 ms (Index 3 – Category: Good). Overall, the fiber-optic network quality in the unit had an average index score of 2.75, placing it in the "Good" category. Responsiveness (latency) and network stability were at highly adequate levels. However, data transmission capacity (throughput) emerged as the primary bottleneck requiring optimization—through bandwidth management or infrastructure upgrades—to support sustainable, real-time digital health transformation.Keywords: Fiber Optic, Quality of Service (QoS), Wireshark, TIPHON, Surgical Outpatient Unit.
PERBANDINGAN ALGORITMA KNN, SVM, DAN RANDOM FOREST DALAM KLASIFIKASI KUALITAS AIR KOLAM IKAN : COMPARISON OF K-NEAREST NEIGHBORS, SUPPORT VECTOR MACHINE, AND RANDOM FOREST ALGORITHMS FOR FISH POND WATER QUALITY CLASSIFICATION MUHAMMAD RIZKY ERI EKO JULIANTO; Catur Supriyanto
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8478

Abstract

Water quality is a critical factor in the success of fish farming because it directly affects fish growth, health, and survival. Manual water quality assessment is time-consuming and requires specialized expertise, which may lead to inaccuracies in decision-making. Therefore, this study aims to compare the performance of the K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Random Forest algorithms in classifying fish pond water quality. The dataset consisted of 4,300 samples with 14 physical and chemical water quality parameters and three water quality classes: Excellent, Good, and Poor. The research process included data preprocessing, Min-Max Scaling normalization, training and testing data splitting, model training, performance evaluation using accuracy, precision, recall, and F1-score, and model validation using 5-Fold Cross Validation. The results show that the Random Forest algorithm achieved the best performance with an accuracy of 99.30%, followed by SVM with 93.95% and KNN with 85.81%. Furthermore, the 5-Fold Cross Validation results indicate that Random Forest achieved the highest average accuracy of 98.85% with a standard deviation of 0.42, demonstrating excellent model stability and generalization capability. These findings indicate that the Random Forest algorithm is highly effective for fish pond water quality classification and has strong potential to support automated water quality monitoring and decision-making in aquaculture management.

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