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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer SISFOTENIKA IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri INOVTEK Polbeng - Seri Informatika Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Mantik Penusa JURTEKSI Jurnal Riset Informatika Jurnal Mantik Ubiquitous: Computers and its Applications Journal Jurnal Sistem Informasi Computer Science (CO-SCIENCE) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Paradigma Info Abdi Cendekia Justika : Jurnal Sistem Informasi Akuntansi Journal of Accounting Information System Jurnal Ilmu Komputer dan Sistem Informasi The Indonesian Journal of Computer Science Jurnal Komtika (Komputasi dan Informatika) At-Tajdid: Journal of Islamic Education Jurnal Infortech
Siti Nurajizah
Universitas Bina Sarana Informatika
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

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Penerapan API WhatsApp pada Sistem Pengolahan Data Tabungan Sekolah Menggunakan Model Extreme Programming Rahmawati, Ami; Nurajizah, Siti; Yulianti, Ita
JUSTIKA : Jurnal Sistem Informasi Akuntansi Vol 2 No 2 (2022): JUSTIKA : Jurnal Sistem Informasi Akuntansi
Publisher : Program Studi Sistem Informasi Akuntansi Kampus Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/justika.v2i2.1649

Abstract

Peranan teknologi menempati posisi yang sangat penting terhadap munculnya inovasi yang positif bagi kemajuan suatu institusi terutama lembaga pendidikan. DTA Almuta'alim merupakan suatu lembaga pendidikan yang memiliki program tabungan sekolah, dimana program ini berkaitan dengan pendidikan dan ekonomi yang dilakukan sebagai upaya untuk melatih dan mendidik para siswa agar mampu mengontrol diri dalam menggunakan uang secara bijak. Dalam prosesnya, pengolahan data tabungan pada DTA ini masih dilakukan secara konvensional sehingga semakin banyaknya data yang tersimpan menyebabkan sulitnya pencarian data dan tingkat resiko kesalahan pencatatan/perhitungan menjadi lebih tinggi. Oleh karena itu, untuk mengatasi permasalahan tersebut, maka diperlukan pemanfaatan teknologi dengan membangun sebuah sistem yang dapat menunjang kegiatan program ini. Pada penelitian ini, sistem yang akan dibangun dibuat berbasis web dengan menggunakan bahasa pemrograman PHP MySQLi dan diterapkan melalui pendekatan model Extreme Programming yang terdiri dari 4 tahapan meliputi planning, design, coding dan testing. Selain itu, implementasi API WhatsApss pada sistem juga dilakukan dalam memunculkan fitur notifikasi otomatis untuk informasi transparasi saldo tabungan bagi orangtua/wali. Dengan dibuatnya sistem ini, diharapkan dapat memberikan kontribusi terhadap keberlangsungan program tabungan sekolah melalui kemudahan pengolahan data sehingga proses pengelolaannya menjadi lebih baik.
Sistem Informasi Akuntansi Penjualan Tunai Pada Toko Grosir Mukti Garut Sukabumi Saumi Ramdhani, Lis; Farlina, Yusti; Nurajizah, Siti; Ramdiani Azzahra, Dinda; Fitrika, Sonia; Yulianti, Ita
JUSTIKA : Jurnal Sistem Informasi Akuntansi Vol 4 No 2 (2024): Desember 2024
Publisher : Program Studi Sistem Informasi Akuntansi Kampus Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/justika.v4i2.7501

Abstract

Toko Grosir Mukti Garut adalah perusahaan yang bergerak dalam bidang penjualan sembako, dimana sistem pada toko tersebut masih dilakukan secara manual, mulai dari pencatatan customer, penyimpanan data yang berhubungan dengan proses penjualan hingga pembuatan laporan. Hal ini seringkali menimbulkan terjadinya kesalahan dalam pencatatan, keterlambatan dalam pencarian data ketika diperlukan dan kesulitan dalam pelaporan keuangan. Tujuan dari penelitian ini yaitu untuk membangun sistem informasi akuntansi untuk mendukung pengelolaan transaksi penjualan tunai pada toko grosir tersebut. Adapun metode pengumpulan data dilakukan meliputi observasi, wawancara, dan studi kepustakaan. Untuk mendukung pengembangan sistem pada penelitian ini digunakan metode pemodelan desain yaitu UML (Unified Modeling language) yang diimplementasikan menjadi aplikasi berbasis web dengan Database MySQL. Dengan dibangunnya sistem ini diharapkan dapat menjadi solusi yang terbaik khususnya dalam mempermudah pengelolaan data transaksi penjualan secara tunai.
Implementasi Metode Forward Chaining, Certainty Factor dan Dempster Shafer pada Sistem Pakar Diagnosis Penyakit Gigi dan Mulut Nurajizah, Siti; Yulianti, Ita; Saputra, Elin Panca; Dewi, Rani Kurnia
Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 2 (2021)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v5i2.5995

Abstract

Dental and oral disease is one of the diseases that has been felt by most of the people. Insufficient information and the limited level of public awareness of the prevention of dental and oral diseases make the impact quite dangerous if not handled properly. An appropriate information system is needed in overcoming and providing solutions for handling a disease as early as possible. Expert systems can be used as a means of information on the treatment of dental and oral diseases. The manufacture of the expert system in this study initially used the forward chaining method, which is a method that searches based on information that is made into a set of rules so as to get a conclusion. However, after re-analysis, two other methods, namely certainty factor and dempster shafer, were also applied in this study with the aim of overcoming the shortcomings of the forward chaining method, one of which is uncertainty in producing a conclusion or diagnosis of disease. Determining the type of dental and oral disease can be known by looking at the symptoms experienced by the patient. The use of an expert system for diagnosing dental and oral diseases can be used as an initial solution in helping someone to treat the disease. The existence of this expert system can be used as consideration in making decisions to determine the type of dental and oral disease quickly, precisely and accurately.
Pendekatan Hibrida Statistik dan Machine Learning untuk Peramalan Jumlah Kunjungan Turis Leidiyana, Henny; Nurajizah, Siti
Jurnal Komtika (Komputasi dan Informatika) Vol 9 No 2 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v9i2.14909

Abstract

Tourist arrival forecasting is a crucial aspect of planning and decision-making in the tourism sector. Accurate predictions are essential to anticipate surges or declines in visitor numbers, design effective marketing strategies, and manage resources efficiently. This study proposes a hybrid forecasting approach that integrates traditional statistical methods with machine learning algorithms to improve the accuracy of tourist arrival forecasts. Five forecasting models are implemented: ARIMA as a representative of traditional statistical models; Random Forest and Extreme Gradient Boosting (XGBoost) as machine learning models; a simple hybrid model, which combines ARIMA and XGBoost predictions through simple averaging; a weighted hybrid model, which merges the two models using performance-based weights; and a stacking hybrid model, which utilizes a meta-model to optimize prediction combinations. Given that the dataset exhibits significant pattern changes, or structural breaks, particularly during the COVID-19 pandemic, this study employs a rolling window backtesting approach for model evaluation. This method allows the models to be tested progressively across normal, crisis, and recovery periods, providing a realistic assessment of their performance under dynamic conditions. Model performance is evaluated using three key metrics: RMSE, MAE, dan MAPE. The results demonstrate that the stacking hybrid model consistently achieves the lowest RMSE across all test periods, highlighting its ability to capture complex trends and extreme fluctuations caused by COVID-19 Keywords: Rolling Window Backtesting, Weighted Hybrid, Weighted Hybrid.
ENHANCING SLEEP QUALITY PREDICTION THROUGH SMOTE-BASED DATA BALANCING AND HYBRID MACHINE LEARNING MODELS Ami Rahmawati; Ita Yulianti; Ani Oktarini Sari; Siti Nurajizah; Hikmatulloh
Jurnal Riset Informatika Vol. 8 No. 1 (2025): Desember 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i1.456

Abstract

Sleep is a vital aspect in maintaining a person's physical and psychological balance. Poor sleep quality can reduce physical and cognitive performance, increasing the risk of various health problems. This study aims to develop a predictive model for sleep quality based on factors such as lifestyle, stress, daily activities, and caffeine consumption, using XGBoost combined with Recursive Feature Elimination (RFE). XGBoost was chosen for its ability to handle imbalanced datasets and heterogeneous features, while RFE helps simplify the model without losing important information. In the data pre-processing stage, a class imbalance was found, so the Synthetic Minority Over-sampling Technique (SMOTE) process was carried out to balance the proportion of the minority class. The dataset in this study was divided into two parts, namely 80% as training data and 20% as testing data, and validated using cross-validation to ensure generalization. The results show very high model performance with an accuracy of 99.79% on training data, 99.63% on cross-validation, and 99.10% on testing data. This model was then developed into a web application for practical use in analyzing sleep quality prediction. This study emphasizes the methodological contribution of a SMOTE-based hybrid machine learning model and its ready-to-use application implementation, while also opening opportunities for further testing on more diverse datasets and evaluating biases caused by synthetic data.
Application of Apriori Algorithm to Determine Sales of Traditional Foods Nurajizah, Siti; Normah, Normah; Nurfitriani, Nurfitriani
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1840

Abstract

Competition in the food sales industry is growing, making business owners have to be creative to increase sales turnover. Sales activities that occur every day make sales data increase. Researchers intend to make data on Traditional Restaurant as the basis for data mining processing on food sales using the apriori algorithm. The application of the Apriori Algorithm aims to find the most item combinations based on transaction data and then form association patterns from combinations of items. Association patterns are formed with a minimum support value of 10% and a minimum confidence value of 40% which results in 3 association rules and the most sold food products are Krupuk Bangka and Karedok with a support value of 0.105% and a confidence value of 0.583%
Qualitative Study of Morals in Students' Daily Lives Nurfauzia, Siti; Narada, Zaqiya; Khodijah, Siti; Nurajizah, Siti; Auliya Suty Gunawan, Dhinda
AT-TAJDID: Journal of Islamic Education Vol 2 No 1 (2025): January 2025
Publisher : Institut Studi Islam Muhammadiyah Pacitan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52640/attajdid.238

Abstract

This study aims to identify and understand moral issues among students and find effective solutions to improve their moral and ethical quality. The method used is descriptive qualitative, combining literature research. Data were collected through questionnaires and direct observation of students. The research findings show that morals significantly influence students' social and academic relationships on campus. The majority of respondents stated that good morals, such as respecting others' opinions, being honest, and being helpful, help build harmonious relationships with friends and lecturers. However, there are differences in the application of morals based on cultural or religious backgrounds. Challenges faced include situations where kindness is not reciprocated or emotions must be controlled. Nevertheless, respondents showed a commitment to consistently implementing positive moral values with support from peers and self-reflection. The role of family and the surrounding environment is recognized as important in shaping student morals. Programs and activities on campus, such as ethics seminars, social activities, and student organizations, help increase moral awareness. To enhance the application of morals, it is suggested to integrate moral education into the curriculum, organize seminars and workshops, and provide positive examples through lecturers and campus staff. Efforts to strengthen morals on campus can be increased with more programs that support the practical learning of moral and ethical values for students.
Penerapan Arsitektur U-Net pada Segmentasi Cacat Biji Kopi untuk Optimalisasi Inspeksi Kualitas Ami Rahmawati; Ita Yulianti; Ani Oktarini Sari; Siti Nurajizah
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.365

Abstract

Manual visual inspection of coffee bean defects remains prone to subjectivity and inconsistency, necessitating a more accurate and efficient approach. This study proposes a deep learning-based coffee bean image segmentation method using the U-Net architecture to detect the presence of defects in coffee beans using a binary segmentation approach. The dataset consists of 300 coffee bean images evenly divided into 150 images of black coffee and 150 images of insect damage. Annotation was performed using a semi-automatic pseudo-labeling method based on Gaussian filtering, absolute difference, and thresholding to generate ground truth in binary mask format. Training data was enriched through augmentation techniques including horizontal flip, vertical flip, rotation, and brightness-contrast adjustment. The model was trained using a combined loss function of Dice Loss and Binary Cross-Entropy with the Adam optimizer over 15 epochs with an early stopping mechanism. Evaluation results demonstrate excellent performance with a Mean IoU of 0.9240, Precision of 0.9707, Recall of 0.9495, and F1 Score of 0.9600, with an overall correct prediction rate of 97.45% based on pixel-level confusion matrix analysis. These results indicate that the U-Net architecture is capable of segmenting defective coffee bean areas accurately and consistently, making it a promising foundation for the development of an automated coffee quality inspection system.
Analysis of Grab Online Motorcycle Taxi Application Usability in Jakarta Using PLS-SEM Approach Model Elin Panca Saputra; Adila Faisal; Siti Nurajizah; Aryo Tunjung Kusumo; Tino Dwiantoro
Jurnal Infortech Vol. 8 No. 1 (2026): June 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v8i1.12766

Abstract

Founded in Singapore in 2012, Grab is one of the biggest online transportation companies in Southeast Asia. In Jakarta, GrabBike is part of this service. Even while technology advancements are driving the rise of these apps, issues including poor map accuracy, ugly UI, and frequently missed advertising still exist. Thus, the purpose of this study is to use the Technology Acceptance Model (TAM) to examine the variables that affect how simple it is to use the GrabBike service in Jakarta. Ease of use (Perceived Ease of Use), advantages (Perceived Usefulness), user attitude (Attitude Toward Using), user intention (Behavioral Intention to Use), and actual users (real System Usage) are the five study variables used in this method. Likert scale questionnaires were utilized to gather data from 106 individuals using a descriptive quantitative technique. The partial least squares (PLS)-based structural equation modeling (SEM) technique is used to assess the relationship between variables. The study's findings demonstrate that advantages (perceived usefulness) and usability (perceived ease of use) have a major impact on users' attitudes (attitude toward using). The intention to use (Behavioral Intention to Use) and Actual System Usage are subsequently impacted by this attitude.
Co-Authors Adila Faisal Adli, Idham Abdi Al Alifia Ramadhanti Ami Rahmawati Ami Rahmawati Ani Oktarini Sari ANI OKTARINI SARI, ANI OKTARINI Arinda Salbinda Aryo Tunjung Kusumo Auliya Suty Gunawan, Dhinda Bambang Rizki Wicaksono Dewi, Rani Kurnia Divika Namastute Duwik Sudarsono Ervan Aziz Fani Roziqi Fajri Fitria Dara Kurnia Fitrika, Sonia Hari Sugiarto - UBSI Henny Leidiyana Hikmatulloh Hikmatulloh, Hikmatulloh Irlia Oktavianisa Ita Yulianti Ita Yulianti Jestin Anttares Lis Saumi Ramdhani Maria, Vivi Marijan Marijan Maulana Saputra Mawadatul Maulidah Nadiyah Hidayati Narada, Zaqiya Nila Alis Ambarwati Normah Normah Normah Normah Normah Normah Normah Normah, Normah Nurfauzia, Siti Nurfitriani Nurfitriani Nurfitriani Nurfitriani, Nurfitriani Panca Saputra, Elin Rahmawati Maulida, Nurul Rahmawati, Ami Ramdiani Azzahra, Dinda Rifa Nurafifah Syabaniah Rizqitha Maula Safitri Linawati Sahrul, Nizar Saputra, Maulana Saumi Ramdhani, Lis Siti Khodijah Sri Muryani Supriatiningsih Supriatiningsih Susilawati, Susilawati Taufik Hidayatulloh Taufik Rahman Tino Dwiantoro Titik Misriati Wahyuni, Ayu Dewi Sri Wahyuni Yusti Farlina