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Jurnal Sistem informasi dan informatika (SIMIKA)
Published by Universitas Banten Jaya
ISSN : 26226901     EISSN : 26226375     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal SIMIKA diterbitkan oleh Program Studi Sistem Informasi Fakultas Ilmu Komputer Universitas Banten Jaya. Jurnal SIMIKA Volume 1 Nomor 1 terbit pada bulan Agustus 2018. Jurnal SIMIKA diterbitkan dalam rentang waktu 6 bulan yang artinya dua kali dalam setahun yaitu di bulan Februari dan Agustus. Jurnal SIMIKA berisi 8 artikel yang mencangkup bidang sistem informasi dan teknologi informasi yang dimaksudkan sebagai media dokumentasi dan informasi ilmiah yang sekiranya dapat membantu para dosen, staf dan mahasiswa dalam menginformasikan dan mempublikasikan hasil penelitian, opini, tulisan dan kajian ilmiah lainnya kepada masyarakat ilmiah.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 161 Documents
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EVALUASI USER EXPERIENCE PADA APLIKASI WONDR BY BNI MENGGUNAKAN METODE UEQ DAN SUS Lestari, Indah; Saputra, Eki; Afdal, M; Nur Salisah, Febi; Syaifullah, Syaifullah
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/vksfqm62

Abstract

Wondr by BNI is a mobile banking application in Indonesia designed to support systematic financial management through three main concepts: Insight, Transaction, and Growth. Despite offering advanced features, many users complain about issues such as failed transactions, login difficulties, and slow application response times. This study evaluates the user experience of the Wondr app by combining the UEQ and SUS methods. The UEQ evaluation results show an average score of: attractiveness 1.12; clarity 1.06; efficiency 1.05; accuracy 1.07; stimulation 0.71; and novelty 0.77. Meanwhile, the SUS score of 64.6 falls into category D, “OK” on the adjective scale, and “Marginally Acceptable” on the usability scale—indicating that the app's usability is slightly below the average standard. Overall, users gave positive ratings for clarity, efficiency, accuracy, and stimulation, but attractiveness and novelty still need improvement. To date, no studies have specifically evaluated the UX of the Wondr app by combining the UEQ and SUS methods. This research contributes new scientific insights by demonstrating the app's UX performance and areas requiring improvement.
PENERAPAN MACHINE LEARNING MENGGUNAKAN ALGORITMA DECISION TREE UNTUK PREDIKSI TINGKAT KELULUSAN MAHASISWA Nst, Ely Nurhalizah; Sumijan; Nurcahyo, Gunadi Widi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/ctjbgh21

Abstract

Students are an integral part of higher education institutions, where graduation rates serve as a key indicator of academic quality and institutional effectiveness. To maintain accreditation and academic standards, universities must optimize student graduation rates. Evaluating the factors influencing graduation is crucial in identifying patterns and key determinants that contribute to academic success. This study aims to predict student graduation using Machine Learning, specifically the C5.0 Decision Tree algorithm. The findings indicate a high reliability in predicting student graduation, with an accuracy of 91.35%. The model's ability to identify on-time graduates is reflected in a recall of 93.85% for the On-Time category and 87.18% for the Delayed category. The prediction accuracy is further demonstrated by a precision of 92.42% for the On-Time category and 89.47% for the Delayed category. The F1-Score, which represents the balance between recall and precision, reaches 93.12% for the On-Time category and 88.32% for the Delayed category. These evaluation metrics indicate that the C5.0 algorithm effectively classifies students based on their likelihood of graduating with high accuracy. The predictions generated can serve as a reference for universities to identify at-risk students early, allowing the implementation of appropriate academic strategies to improve graduation rates, accreditation, and institutional quality.
ANALISIS BIG DATA BEASISWA KIP-K MENGGUNAKAN K-MEANS CLUSTERING Pebriyanti, Defi; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/34aycf56

Abstract

The Kartu Indonesia Pintar Kuliah (KIP-K) Scholarship Program is a government initiative to provide higher education access to underprivileged students. It aims to reduce educational disparities and improve access for eligible students. However, the selection process faces challenges, particularly in identifying applicants who truly need financial aid. With the increasing number of applicants each year, a Big Data-based approach is essential to enhance selection efficiency and accuracy. This study analyzes KIP-K scholarship recipients’ profiles using the K-Means Clustering method. This technique groups data based on attribute similarities, allowing an objective and data-driven selection process. The dataset, obtained from Universitas Prima Nusantara Bukittinggi (2024), consists of 479 applicants. It includes attributes such as academic performance, parental income, number of dependents, KIP-K card ownership, and achievements. Results indicate that recipients can be categorized based on document completeness, academic scores above 85, and more than three family dependents. Implementing K-Means Clustering improves the selection process by making it more objective, transparent, and efficient.
PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING DALAM PEMILIHAN MEDIA PROMOSI SEKOLAH (STUDI KASUS DI MTS LABORATORIUM UIN BUKITTINGGI) Nabila, Tuti; Nurcahyo, Gunadi Widi; Sovia, Rini
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/6he5pd48

Abstract

Schools play a strategic role in organizing learning and implementing promotional strategies to increase student enrollment. The use of information technology in promotions is crucial for enhancing institutional competitiveness. MTs Laboratorium UIN Bukittinggi faces challenges in determining the most effective promotional media among various alternatives. While several media have been implemented, the selection process lacks a systematic analytical approach, making it difficult to measure effectiveness objectively. This study applies the Simple Additive Weighting (SAW) method to determine the most effective promotional media. This study represents the first application of the SAW method for selecting school promotional media based on multi-criteria decision-making. The methodology includes defining criteria and weights, inputting alternative data, assessing suitability ratings, normalizing the decision matrix, and ranking alternatives. The dataset was collected from MTs Laboratorium UIN Bukittinggi, evaluating five media alternatives based on four criteria: promotion duration, reach, information completeness, and production cost. The results show that direct socialization achieved the highest final score of 0.91, followed by websites (0.51), banners (0.49), brochures (0.472), and social media (0.33). These findings provide practical guidance for schools in selecting promotional media that are both effective and efficient in attracting prospective students, optimizing resource allocation, and enhancing promotional impact. This study confirms that the SAW method effectively selects promotional media and can assist educational institutions in improving their promotional strategies
IMPLEMENTASI COMPOSITE PERFORMANCE INDEX DALAM MENENTUKAN SISWA BERPRESTASI DI MA ISLAMIYAH SEI KAMAH II Susilo, Widya Amanda; Ramdhan, William; Parini
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/kg28tj66

Abstract

The selection of outstanding students at MA Islamiyah Sei Kamah II was previously conducted manually and subjectively, without a structured and transparent assessment standard. The evaluation relied solely on report card scores, disregarding other factors such as attendance, non-academic achievements, and student behavior, which could impact the objectivity of the selection process. To address this issue, this study implements a Decision Support System (DSS) based on the Composite Performance Index (CPI) method to enhance accuracy and transparency in selecting outstanding students. The CPI method integrates various assessment criteria with assigned weights, including report card scores (40%), non-academic achievements (30%), behavior (20%), and attendance (10%). The system is web-based, developed using PHP and MySQL to systematically manage student data. The implementation results indicate that the developed system effectively ranks students more objectively and accurately, ensuring a fair and accountable selection process. With this system, the school can improve the quality of student evaluations and provide more appropriate recognition for high-achieving students. Future recommendations include expanding the system’s accessibility through an Android-based application to enhance usability and efficiency in managing student data.
ANALISIS HEMOROID PADA IBU HAMIL DENGAN SISTEM CERTAINTY FACTOR Damayani, Indri; Sudarmin, Sudarmin; Piliang, Rizaldi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/gztz4581

Abstract

Hemorrhoids in pregnant women are a physiological condition that often accompanies pregnancy. Women who had hemorrhoids before pregnancy are at a higher risk of developing them during pregnancy. The main concern is the possibility of bleeding, which may lead to anemia and negatively impact fetal development. To assist in analyzing the symptoms of hemorrhoids in pregnant women, an expert system was developed using the Certainty Factor method. This system aims to provide early detection and quick action recommendations for patients at Tanjungbalai General Hospital. The expert system is web-based and uses the Certainty Factor method to diagnose hemorrhoids based on symptoms entered by the user. The system calculates the confidence value of each possible disease and provides a diagnosis with a certainty percentage. Based on the CF calculation results, the highest CF value obtained is 0.7475 or 75%, indicating that the most likely diagnosis for the user’s symptoms is Internal Hemorrhoids (P01). The developed system includes features such as user registration, symptom consultation, and disease information. The administrator panel allows experts to manage disease data, symptom data, diagnostic rules, and user reports. Implemented using PHP and MySQL, this system helps pregnant women identify early symptoms of hemorrhoids, enabling timely treatment and reducing complications. By providing accurate diagnoses and suggested solutions, this expert system is expected to raise awareness and improve health outcomes for pregnant women suffering from hemorrhoids.
KLASTERING WILAYAH DI JAWA TIMUR BERDASARKAN FAKTOR UNMET NEED MENGGUNAKAN FUZZY GUSTAFSON-KESSEL Windyadari, Chrysilla Citra; Damaliana, Aviolla Terza; Idhom, Mohammad
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/5b2g7x82

Abstract

The Family Planning Program is an effort to control the rate of population growth by regulating desired pregnancies. In its realization, the family planning program faces challenges in the form of unmet need (couples of childbearing age who do not use contraception). East Java Province in 2023 was recorded as the province with the third highest number of unmet need cases in Java. One method that can be used to analyze the phenomenon of unmet need is clustering analysis. Clustering analysis will help identify areas in East Java based on the priority level of the family planning program. Fuzzy Gustafson-Kessel (FGK) is one of the clustering methods developed as a refinement of the Fuzzy C-Means method. This study implements the Fuzzy Gustafson-Kessel (FGK) method with and without Principal Component Analysis (PCA) to cluster regions in East Java based on unmet need and determinant factors such as the availability of family planning facilities and resources. The results showed that the best model was obtained when using FGK with PCA, with the highest FSI value of 0.668 and XB of 0.235 at configuration c = 4 and m = 3.5. The clusters formed consist of 5 medium priority areas, 12 low priority areas, 9 high priority areas, and 12 developing priority areas. The results of this clustering can be used as a basis for policy makers in designing more effective intervention strategies to address unmet need in East Java.
SISTEM REKOMENDASI VIDEO GAME BERBASIS USIA SEBAGAI ALAT PENGAWASAN ORANG TUA DI PLATFORM STEAM MENGGUNAKAN CONTENT-BASED FILTERING Oktavianda, Oktavianda; Efrizoni, Lusiana; Fatdha, Eiva; Asnal, Hadi
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/2wj54451

Abstract

Video recreations are a prevalent shape of amusement, particularly among children. In any case, numerous parents in Indonesia still need understanding of age appraisals for video recreations, driving to less viable supervision. This could uncover children to unseemly substance. This think about points to create an age-based video amusement suggestion framework utilizing the Content-Based Filtering strategy on the Steam dataset. The framework is planned to help guardians in selecting recreations suitable for their children. Evaluation results show the model performs very well, achieving a precision of 0.98 and a recall of 1.00. Additionally, the model records a Mean Absolute Error (MAE) of 0.469236, Mean Squared Error (MSE) of 6.440935, and Root Mean Squared Error (RMSE) of 2.537900. These findings highlight how well the system filters and suggests age-appropriate video games, assisting parents in better monitoring their kids' gaming habits.
OPTIMALISASI STRATEGI PROMOSI BERDASARKAN WAKTU DAN JENIS PRODUK MENGGUNAKAN ALGORITMA FP-GROWTH Andaranti, Arifah Fadhila; Afdal, M.; Permana, Inggih; Jazman, Muhammad; Marsal, Arif
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/dy69fk12

Abstract

Aba Mart is a convenience store that provides a wide range of daily necessities. One of the challenges faced by Aba Mart is the uncertainty in determining the optimal timing for product promotions. To address this issue, this study utilizes sales transaction data obtained from the store’s Point of Sale (POS) system, totaling 12,887 transactions recorded from March to August 2024. The dataset includes attributes such as date and product name, which were processed through attribute selection, categorization into 33 product types, conversion of dates to days, and transformation into boolean format for analysis. The study applies the Association Rule Mining (ARM) technique using the Frequent Pattern Growth (FP-Growth) algorithm to identify the relationship between the time of purchase and the types of products bought. The results demonstrate that the FP-Growth algorithm successfully identified patterns of association. By testing with minimum support values of 2%, 3%, and 4%, and a minimum confidence of 10%, the analysis produced 15 association rules in March, 11 in April, 14 in May, 13 in June, 11 in July, and 13 in August 2024. These rules have been used as a foundation for formulating more effective and targeted promotional strategies for Aba Mart.
SISTEM REKOMENDASI PEMBERIAN KAPUR DOLOMIT BERDASARKAN KADAR KEASAMAN TANAH BERBASIS INTERNET OF THINGS (IoT) Nuryani, Ely; Hasanah, Huswatun; Widyawati, Widyawati; Ruhiawati, Irma Yunita; Hidayah, Nurul
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/69yd3c35

Abstract

The green revolution helped increase food production by intensifying existing land so that it could provide synthetic nutrients. However, synthetic fertilizers make plants vulnerable to pests and other hazards. This causes living things that help decompose the soil to be vulnerable to death due to the use of synthetic pesticides. The longer the use of these pesticides causes the soil to become damaged without any improvement. One indicator is a decrease in acidity levels, which should be a neutral pH of 7. Therefore, this study created a system that can be used to detect the acidity level of agricultural land. The location of the research object is agricultural rice fields in Serang Regency, Banten Province. The equipment used to support the IoT-based system includes a soil pH sensor, NodeMCU ESP8266, 3. Switch, and 9v Battery. The system development method uses the waterfall method and is IoT-based so that soil acidity levels can be monitored remotely. Based on the trial results, the system can measure and monitor soil acidity conditions remotely easily, quickly, and accurately. This system can help and facilitate farmers in making decisions about the appropriate use of dolomite lime for land that tends to be acidic.

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