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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
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IMPLEMENTASI METODE CONTENT-BASED FILTERING DENGAN PENDEKATAN EUCLIDEAN DISTANCE DALAM SISTEM REKOMENDASI PRODUK SKINCARE Euis Halimatussa’diyah; Sekti Kartika Dini
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6371

Abstract

The cosmetics industry in Indonesia is experiencing rapid growth, driven by increasing public awareness of self-care and the development of e-commerce. Skincare is one of the main segments with the largest market, but the many product choices often make it difficult for consumers to determine products that suit their preferences. In addition, the issue of overclaims on skincare which has been widely discussed since September 2024 has raised concerns among the public in choosing skincare products. In response to these conditions, this research was conducted with the aims to help users choose skincare products based on specified criteria, namely category, active ingredients, and expected benefits. The method used is Content-Based Filtering with the Euclidean Distance approach to calculate the similarity between products. The recommendation system was developed using Gradio as an interactive interface and hosted through the Hugging Face platform so that it can be accessed online. Based on three experiments conducted, an average precision value of 96.67% was obtained, which shows that the system is able to provide recommendations that are relevant to user preferences.
PENGEMBANGAN WEBSITE SEBAGAI SUMBER LAYANAN INFORMASI DI MUSEUM PERKEBUNAN INDONESIA: WEBSITE DEVELOPMENT AS A SOURCE OF INFORMATION SERVICES AT THE INDONESIAN PLANTATION MUSEUM Muhamad Dhimas Dharmawan; Muslih Fathurrahman
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6377

Abstract

This study aims to develop a website as an information service source for the Indonesian Plantation Museum’s Collections. The research is based on issues such as the lack of digital access to museum collections and insufficient descriptive information, and has social significance in expanding access to cultural information to the general public, especially the younger generation, as well as supporting the preservation of historical heritage through digital media. The study applied the Research and Development (R&D) method using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) and incorporated a User-Center Desgin (UCD) approach to understand user needs. Data were collected through a survey involving 152 museum visitors and analyzed using descriptive statistics. The findings show that 90.79% of respondents expressed a high need for digital access to collection information, with the most desired features being detailed collection descriptions, interactive media, and simple navigation. The website was developed using HTML5, CSS3, JavaScript, PHP, and MySQL. It features digital collections, gallery, museum news, activity updates, and profile pages, and includes QR code integration for offline visitors. Formative evaluation indicates that the developed website aligns with user needs and preferences. This website is expected to serve as a digital preservation tool and improve access to museum collection information through technology.
PERANCANGAN USER INTERFACE WEBSITE PONDOK PESANTREN CIPEDES AL-ASYIQIEN II MENGGUNAKAN METODE DESIGN THINKING Raden Arsaal Hafidz Nuralam; Dani Hamdani
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6379

Abstract

Pondok pesantren salafiyah pada umumnya masih menggunakan metode manual dalam penyampaian informasi. Hal itu berpotensi menimbulkan penyampaian informasi kurang efektif.  Penelitian ini bertujuan untuk merancang antarmuka pengguna (User Interface) website Pondok Pesantren Salafiyah Cipedes Al-Asyiqien II menggunakan metode Design Thinking, yang mencakup proses desain yang berfokus pada pengguna. Teknik yang digunakan adalah wawancara mendalam (in-depth interview) dengan 9 narasumber yang terdiri dari 1 ustadz, 4 santri, dan 4 wali santri. Analisis data menggunakan pendekatan deskriptif kualitatif. Hasil penelitian menunjukkan bahwa pengguna membutuhkan media yang terstruktur berupa informasi yang mudah diakses dan ramah pengguna terutama bagi yang memiliki kondisi keterbatasan teknologi. Hasil perancangan menghasilkan UI yang sederhana, responsif, dan dapat memenuhi kebutuhan pengguna. Metode Design Thinking efektif dalam menemukan kebutuhan dan menghasilkan solusi desain. Hasil dari testing yang sudah dilakukan oleh pengguna, selanjutnya akan diproses menggunakan System Usability Scale (SUS) sebagai metode evaluasi tingkat kegunaan antarmuka yang dirancang. Evaluasi menggunakan System Usability Scale (SUS) menunjukkan skor 75.8 dan 77.0 yang termasuk kedalam kategori usability baik dan dapat diterima.
PENERAPAN DESIGN THINKING DALAM PERANCANGAN PROTOTYPE UI DAN UX PADA APLIKASI PEMINJAMAN RUANGAN PKM DI UNIVERSITAS WIDYATAMA Naila Aura Addinillah; Dani Hamdani
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6380

Abstract

This research is motivated by the manual system of room rental at the Student Activity Center (PKM) of Widyatama University, which often causes problems such as unclear information on room availability and schedule conflicts. This problem is important to study because it has an impact on the efficiency of campus facility usage. Therefore, this study aims to design a prototype of a room rental application based on the Design Thinking method that focuses on user needs. The method used is Design Thinking with a descriptive qualitative approach. Data were collected through interviews, observations, and surveys, then analyzed using usability testing with the System Usability Scale (SUS) and Maze. The results of this study involved 22 participants in the usability test, consisting of 20 students as users and 2 admins as admins. Usability testing was carried out using the System Usability Scale (SUS) and Maze, with an average SUS score of 82.10 (user) and 83 (admin). This study shows that the Design Thinking approach is effective in designing a user-friendly room rental application. Based on these results, the study concluded that this application is worthy of further development. This study recommends further development at the implementation stage of web-based and mobile applications as well as expanding usability evaluation to more diverse user groups. Thus, it is expected that the designed system can be implemented in real terms to support the smooth running of student activities in the campus environment.  
SISTEM INFORMASI GEOGRAFIS UNTUK PEMETAAN LOKASI MASJID DAN MEUNASAH DI KOTA LHOKSEUMAWE MENGGUNAKAN ALGORITMA HAVERSINE BERBASIS WEBSITE: GEOGRAPHIC INFORMATION SYSTEM FOR MAPPING THE LOCATION OF MOSQUES AND MEUNASAH IN LHOKSEUMAWE CITY USING THE WEBSITE-BASED HAVERSINE ALGORITHM Agus Prayoga; Fadlisyah Fadlisyah; Hafizh Al kautsar Aidilof
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6381

Abstract

This research aims to develop a web-based Geographic Information System (GIS) that maps the location of mosques and meunasah in Lhokseumawe City, and uses the Haversine Algorithm to calculate the closest distance between users and places of worship. The main purpose of this system is to provide fast, accurate, and efficient information, especially for newcomers or residents in finding the nearest place of worship. The method used is the waterfall system development model, with system design using the Unified Modeling Language (UML) to visualize the workflow and data structure. Data is obtained through interviews with mosque administrators and the community, as well as taking coordinates using a GPS device. The test results show that the Haversine Algorithm can calculate the distance accurately and find the location of the nearest mosque or meunasah based on the user's position. However, this system has limitations because distance calculations only consider straight lines between points (geodesic), without taking into account the actual route of the road. This research concludes that a web-based GIS that integrates the Haversine Algorithm provides real-time distance information, makes it easier for people to find the nearest place of worship, and increases the accessibility of information and participation in religious activities in Lhokseumawe City.
PEMILIHAN PEMBIMBING SKRIPSI BERBASIS MACHINE LEARNING DAN KOMBINASI METODE MCDM: SELECTION OF THESIS SUPERVISORS BASED ON MACHINE LEARNING AND A COMBINATION OF MCDM METHODS Hamada Zein; Siti Hadijah Aspan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6387

Abstract

The selection of thesis advisors is a critical step in supporting students’ academic success. This study proposes the hybrid model that combines the C4.5 classification method with the AHP-SAW-TOPSIS multi-criteria decision-making approach to provide objective and systematic advisor recommendations. In the initial phase, the first advisor is selected using four classification algorithms: Decision Tree (C4.5), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) with RBF kernel, and Naive Bayes. The C4.5 algorithm achieved the highest accuracy at 95%. The second advisor is determined using AHP to assign weights to four criteria: supervision load, academic rank, seminar involvement, and research interest alignment. These weights are applied in the SAW method for normalization and initial scoring, followed by TOPSIS to produce the final ranking. The top-ranked advisor is the sixth, followed by the second and tenth. The hybrid approach offers advantages over using either Machine Learning or MCDM alone. Machine Learning excels in identifying patterns from historical data for accurate predictions, while MCDM explicitly incorporates multiple criteria and institutional preferences. Their combination creates a recommendation system that is both precise and policy-aware. Sensitivity analysis shows stable results, indicating that the assigned weights are relevant. This model supports fair, data-driven decision-making and helps reduce the administrative burden of advisor assignments at the university level.
SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI KARYAWAN KONTRAK DI RS MITRA JAMBI MENGGUNAKAN METODE WASPAS: DECISION SUPPORT SYSTEM FOR CONTRACT EMPLOYEE SELECTION AT RS MITRA JAMBI USING THE WASPAS METHOD Muhammad Hendrik Koto; Dodo Zaenal Abidin; Sharipuddin
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6388

Abstract

This research aims to develop a decision support system (DSS) to improve the efficiency and objectivity of contract employee selection at Mitra Jambi Hospital. The main problem faced by RS Mitra Jambi is the absence of a special information system for the selection of contract employees, which causes the assessment process to be manual, slow down the workflow, and tend to be subjective. This system is designed using the Weighted Aggregated Sum Product Assessment (WASPAS) method which is proven to be able to produce measurable, transparent, and accurate assessments, by integrating various assessment criteria such as Education, Competence, Motivation, and Attitude to rank candidates. The system development process follows the waterfall method, including requirements analysis, design, implementation, and black-box testing. This web-based system is built with PHP and MySQL database. The results of implementation and testing show that all system functionality runs well, is able to provide more accurate recommendations, reduce subjectivity, and increase selection effectiveness.  However, this study has limitations in data validation, namely the use of 1 real data and 29 simulated data from 30 candidates, due to the absence of comprehensive historical data recapitulation at Mitra Jambi Hospital. This system is expected to optimize the quality of selected candidates and support HR management at RS Mitra Jambi in a professional and accountable manner.
PREDIKSI GAYA BELAJAR MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN OPTIMASI HYPERPARAMETER TUNING BERBASIS WEB : PREDICTING LEARNING STYLES USING RANDOM FOREST ALGORITHM WITH WEB-BASED HYPERPARAMETER TUNING OPTIMIZATION Risma Bidayatul Hidayah; Khoiriya Latifah; Bambang Agus Herlambang
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6393

Abstract

Learning styles play an important role in supporting students' academic achievement, because a mismatch between learning methods and student learning preferences can reduce learning motivation, hinder material comprehension, and have a negative impact on academic results. To address this issue, a web-based learning style prediction system was developed in this study by applying the Random Forest approach. However, in classification problems, Random Forest often faces suboptimal classification results.  This study seeks to enhance the effectiveness of the Random Forest algorithm by applying hyperparameter tuning techniques, specifically through grid search and random search methods, in order to improve the accuracy of classifying students' learning styles.  This study uses a secondary questionnaire dataset consisting of 1,210 data samples classified based on the VAK model of learning preferences (Visual, Auditory, and Kinesthetic). The test results show that the model with hyperparameter optimization using random search can improve accuracy performance by 88% and the average cross-validation score by 86%. Compared to the default configuration model and grid search, which only achieved an accuracy of 86%, this improvement was also demonstrated by data balancing using SMOTE and data reduction using PCA, which contributed to enhancing model accuracy. Overall, this study demonstrates that grid search and random search hyperparameter optimization can optimize the Random Forest algorithm for accurately classifying students' learning styles.  
OPTIMASI JUMLAH CLUSTER PADA K-MEANS CLUSTERING MENGGUNAKAN PARTICLE SWARM OPTIMIZATION UNTUK PENGELOMPOKAN UKT MAHASISWA Ira Fazira; Zahratul Fitri; Risawandi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6396

Abstract

The determination of the Single Tuition Fee (UKT) group in higher education faces challenges in terms of distribution fairness due to the inappropriate grouping of students' socio-economic conditions. The K-Means algorithm, while effective in handling large-scale data at good computational speeds, has a drawback in determining the optimal number of clusters automatically. This study aims to implement the integration of Particle Swarm Optimization (PSO) with K-Means Clustering in the grouping of student UKT data and evaluate the improvement of the quality  of clustering produced compared to conventional methods. The study uses a dataset of 437 new students of the Faculty of Engineering in 2024 from Malikussaleh University with 8 attributes that describe family socioeconomic conditions. The research stages include pre-processing of data, determination of the optimal number of clusters using PSO, implementation of K-Means clustering with optimal K, model evaluation using Silhouette Coefficient and Davies-Bouldin Index, and model comparison using the elbow method. The results of the study showed that PSO succeeded in determining the optimal number of clusters as many as 3 clusters. The implementation of K-Means with K=3 resulted in the distribution of clusters: cluster 0 (40 students/9.2%), cluster 1 (93 students/21.3%), and cluster 2 (304 students/69.6%). Clustering quality evaluation  resulted in  a Silhouette Coefficient of 0.278062 and  a Davies-Bouldin Index of 1.430505 indicating adequate cluster formation with fairly good internal cohesion and reasonable separation between clusters. Comparison with  the conventional K-Means method  using the Elbow Method shows the advantage of PSO-K-Means with  a higher Silhouette Coefficient (0.278062 vs 0.250300) and  a competitive Davies-Bouldin Index (1.430505 vs 1.315400). This research proves that the combination of PSO and K-Means can provide a more optimal solution in the grouping of student UKT to support a fairer determination of tuition fees based on family economic ability.
PREDIKSI STOK OBAT TB DENGAN ARIMA DAN ANALISIS VOLATILITAS RESIDUAL DI PUSKESMAS BANDA SAKTI Khanifa Muslimah Siregar; Zahratul Fitri; Fajriana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6398

Abstract

Effective drug stock management is essential in healthcare services, particularly for infectious diseases such as pulmonary tuberculosis. This study aims to forecast TB drug stock using the ARIMA model and analyze residual volatility based on data from Banda Sakti Public Health Center, Lhokseumawe City. It focuses on applying predictive modeling at the primary healthcare level, which has rarely been addressed in previous studies. The dataset covers six drug types from January 2021 to December 2024. ARIMA models were selected automatically using Python and evaluated using sMAPE, MAE, and RMSE. Results show that ARIMA was successfully applied to four drug types, with sMAPE ranging from 31% to 41%, which is acceptable for short-term planning. The ARCH test produced p-values > 0.05, indicating that GARCH was not necessary. Two drug types could not be modeled due to zero-constant and sporadic data patterns. The proposed system can assist pharmacy staff in planning procurement and safety stock at the primary care level.

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