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All Journal JURNAL SISTEM INFORMASI BISNIS Riau Journal of Computer Science Jurnal CoreIT Jurnal Penelitian Pendidikan IPA (JPPIPA) JSFK (Jurnal Sains Farmasi & Klinis) Buletin Ilmiah Nagari Membangun Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Bulletin of Computer Science Research Pharmaceutical Sciences and Research (PSR)
Rahmad Abdillah
Teknik Informatika Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau
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Result Based Manajemen Sistem untuk Monitoring dan Evaluasi Kegiatan Bimbingan Dasar Keislaman Okfalisa, Okfalisa; Simaremare, Harris; Abdillah, Rahmad; Najwa, Nina Fadilah
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 1 (2019): Volume 9 Nomor 1 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.452 KB) | DOI: 10.21456/vol9iss1pp77-85

Abstract

The Islamic values in the integrated curriculum should be reflected in governance, teaching lifestyle, and society dedication. The Islamic basic mentoring activity was the routine activity in UIN SUSKA Riau. That activity had been going on since 2010 and had unoptimization through stakeholder dissatisfaction with performance output. This research has developed a model by Result based for monitoring and evaluating the activity implementation. The results of the modeling mechanism were implemented in the construction of a Result Based Management Information System prototype. This research conducted by 7 constructs with 32 indicators that had been statistically tested by Confirmatory Factor Analysis to know the significance and the relation between indicators and constructs. This model was tested descriptive statistic to measure the activity implementation performance in accordance with the expected output. The results of performance activity at the Faculty of Science Technology were at the middle level. The construction of a prototype using Object Oriented Analysis had been successfully carried out with very good results in testing the UAT and Black Box. The system had 6 actors based on the stakeholder requirements and the system was successfully monitoring and evaluating problem and activity as long as the implementation. Performance information in graphically was to help the leader and top management for making decision and policy fixing. The discussion forum was developed as sharing information platform between the leader, the manager and the lecturer, the fellow lecturer, the lecturer and the participants. Thus, the transformation and transparency in implementation activity were formed.
EVALUASI AWARENESS POP-UP WEBSITE BERDASARKAN DESAIN, KONTEN DAN NOTIFIKASI Abdillah, Rahmad; Mai Candra, Reski
Riau Journal Of Computer Science Vol. 6 No. 2 (2020): Riau Journal of Computer Science
Publisher : Riau Journal Of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (496.029 KB)

Abstract

Pop-Up is one of the tools that can increase an organization's revenue because one of its functions is to direct. However, many are abusing this pop-up function. Many pop-ups point users to gambling, data theft, and so on. Therefore users who do not care about this threat will be targeted. This study evaluates pop-up models that appear in terms of design, content, and notification aspects. A total of 163 respondents who had an Information Technology (IT) background were evaluated. The evaluation has passed the tests of normality, reliability, and homogeneity. Respondents feel disturbed by the presence of pop-ups, especially how to close the pop-ups that appear. At the end of the sub-discussion, there are implications of this study
Security Testing Sistem Penerimaan Mahasiswa Baru Universitas XYZ Menggunakan Open Source Security Testing Methodology Manual (OSSTMM) Fernando, Yendri Ikhlas; Abdillah, Rahmad
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 2, No 1 (2016): Juni 2016
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.817 KB) | DOI: 10.24014/coreit.v2i1.2354

Abstract

Teknologi aplikasi web berkembang pesat sehingga digunakan untuk berbagai tujuan seperti keperluan akademik pada suatu universitas. Namun teknologi ini tidak bisa lepas dari tingginya ancaman kemanan yang tinggi sehingga bisa merugikan pihak-pihak tertentu. Pada dunia keamanan informasi dikenal security testing yakni suatu proses yang menguji seberapa tinggi tingkat kemanan suatu aplikasi yakni aplikasi web sehingga dapat diketahui nilai dan tingkat keamanan dan rekomendasi yang berguna. Salahsatu metode security testing yang efektif adalah Open Source Security Testing Methodology Manual (OSSTMM). OSSTMM adalah metode tertentu untuk melakukan security testing dan menyajikan hasil berupa RAV dan STAR. Aplikasi web yang diteliti adalah Sistem Penerimaan Mahasiswa Baru Universitas XYZ sehingga didapatkan hasil dan rekomendasi yang berguna dalam pengembangan lebih lanjut dimasa yang akan datang. Hasil penilaian yang didapatkan yakni dengan nilai Actual Security 74,5877.
Performance Analysis of LVQ 1 Using Feature Selection Gain Ratio for Sex Classification in Forensic Anthropology Harni, Yulia; Afrianty, Iis; Sanjaya, Suwanto; Abdillah, Rahmad; Yanto, Febi; Syafria, Fadhilah
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3625

Abstract

One approach to handling large of data dimensions is feature selection. Effective feature selection techniques produce the essential features and can improve classification algorithms. The accuracy performance results can measure the accuracy of the method used in the classification process. This research uses the Learning Vector Quantization (LVQ) 1 method combined with Gain Ratio feature selection. The data used is male and female skull bone measurement data totaling 2524. The highest accuracy results are obtained by LVQ 1, which uses a Gain Ratio with a threshold of 0.01 with a learning rate = 0.1, which is 92.01%, and the default threshold weka(-1.7976931348623157E308) with a learning rate = 0.1, which is 92.19%. In comparison, previous research that did not use gain ratio or that did not use GR only had the best results of 91.39% with a learning rate = 0.1, 0.4, 0.7, 0.9. This shows that LVQ 1 using the Gain Ratio can be recommended to improve the performance of the Skull dataset compared to LVQ 1 without Gain Ratio.
Interaction between Fluoxetine and Risperidone and Its Association with Clinical Outcomes in Schizophrenic Patients Rachmaini, Fitri; Ayu Juwita, Dian; Abdillah, Rahmad; Dwi Afrianti, Rezy; Sri Wahyuni, Fatma
Pharmaceutical Sciences and Research Vol. 10, No. 1
Publisher : UI Scholars Hub

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

Abstract

The concurrent use of fluoxetine and risperidone to treat schizophrenia may result in drug interactions. This study aims to analyse the clinical outcomes of fluoxetine-risperidone therapy and the possibility of their interaction in schizophrenic patients. The clinical outcomes are patient status at the time of hospital discharge, the length of hospitalisation and the Positive and Negative Syndrome Scale- Excitement Component (PANSS-EC). This study was conducted prospectively in psychiatric ward of HB Saanin Mental Hospital from May to October 2021 and study subjects were selected using consecutive sampling technique with inclusion criteria. Forty-three patients were eligible for this study. Research data were collected from direct observation and notes from medical records. To provide an overview of the frequency distribution and percentage of the variables evaluated, the data were analysed through descriptive statistics and a chi-square test using SPSS v.22. Symptoms due to risperidone-fluoxetine interaction were found in four patients (10%). The symptoms experienced are categorised as extrapyramidal syndrome (EPS). The results of the clinical outcomes showed that 38 patients (88%) having recovered and five patients (12%) were in remission. The PANSS-EC in male patient (6.24±1.12) was higher than female (5.88±1.12). The length of hospitalization was higher in patient with age 36-45 years (23.72). This study showed no significant relationship between fluoxetine-risperidone interaction on the outcome of therapy (p>0.05). It can be concluded that EPS was found in 10% of schizophrenic patients. However, there was no significant association between EPS due to fluoxetine-risperidone interaction with clinical outcomes.
Pengaruh Penggunaan Obat Antihipertensi Terhadap Tekanan Darah Dan Proteinuria Pada Pasien Preeklampsia Berat Di RSUP Dr. M. Djamil Rachmaini, Fitri; Juwita, Dian Ayu; Abdillah, Rahmad; Rifqi, Melvi Auliya
JSFK (Jurnal Sains Farmasi & Klinis) Vol 9 (2022): J Sains Farm Klin 9(suplemen), Desember 2022
Publisher : Fakultas Farmasi Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jsfk.9.sup.175-183.2022

Abstract

Kondisi preeklampsia dapat berkembang menjadi eklampsia yang beresiko meningkatkan angka kematian bagi ibu dan janin. Obat antihipertensi dapat digunakan untuk pengobatan preeklampsia. Penelitian ini bertujuan mengetahui pengaruh penggunaan obat antihipertensi terhadap nilai tekanan darah dan proteinuria pasien didiagnosis preeklampsia berat. Metode yang digunakan adalah retrospektif cross-sectional. Pengumpulan data dilakukan melalui rekam medis dari Januari sampai Desember 2021. Data disajikan dalam 76 pasien memenuhi kriteria inklusi. Hasil penelitian menunjukkan terdapat 19 pasien (23%) menggunakan monoterapi antihipertensi metildopa atau nifedipin, 30 pasien (39,47%) menggunakan kombinasi metildopa dan nifedipin, dan empat pasien (5,26%) menggunakan kombinasi metildopa, nifedipin dan furosemide. Rata-rata penurunan tekanan darah sistolik dan diastolik (TDS/TDD) paling besar yaitu 85,25 mmHg dan 29,5 mmHg. Sedangkan rata-rata penurunan nilai proteinuria paling besar yaitu 2. Berdasarkan hasil tersebut diketahui bahwa terdapat pengaruh signifikan penggunaan obat antihipertensi terhadap TDS (p=0,000), TDD (p=0,000), dan nilai proteinuria (p=0,002). Penurunan nilai tekanan darah dan proteinuria lebih efektif terjadi pada terapi kombinasi dibandingkan dengan monoterapi.
Drugs Related Problems (DRPs) Pada Pasien Penyakit Ginjal Kronik (PGK) Di RSUP Dr. M. Djamil Juwita, Dian Ayu; Rachmaini, Fitri; Abdillah, Rahmad; Meliani, Meliani
JSFK (Jurnal Sains Farmasi & Klinis) Vol 9 (2022): J Sains Farm Klin 9(suplemen), Desember 2022
Publisher : Fakultas Farmasi Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jsfk.9.sup.184-189.2022

Abstract

Penyakit Ginjal Kronis (PGK) ditandai dengan penurunan fungsi ginjal secara ireversibel yang dapat mempengaruhi proses eliminasi obat dari dalam tubuh. Drugs Related Problems (DRPs) merupakan suatu peristiwa terkait pengobatan bersifat aktual ataupun potensial yang dapat mempengaruhi hasil terapi pasien. Penelitian ini bertujuan untuk mengetahui persentase kejadian DRPs dan hubungan antara kejadian DRPs dengan kondisi pulang pasien didiagnosis PGK. Penelitian ini dilakukan secara retrospektif. Pengumpulan data dilakukan melalui rekam medis pasien pada tahun 2021. Analisis data dilakukan secara deskriptif dan uji korelasi Spearman Rank. Sebanyak 74 pasien memenuhi kriteria inklusi, terdiri dari 44 pasien laki-laki (59,46%) dan 30 pasien perempuan (40,54%). Rentang usia pasien PGK terbanyak adalah 46-55 tahun, yakni 22 pasien (29,73%). Ditemukan kejadian DRPs yakni indikasi tanpa terapi pada 7 pasien (35%), dosis obat kurang pada 1 pasien (5%), dan dosis obat berlebih pada 12 pasien (60%). Pada penelitian ini 67 orang pasien (90,54%) pulang dengan kondisi perbaikan, 5 orang pasien (6,76%) pulang dengan kondisi belum sembuh, dan 2 orang pasien (2,74%) meninggal. Dapat disimpulkan bahwa pada terdapat kejadian DRPs meliputi indikasi tanpa terapi, dosis obat kurang, dan dosis obat berlebih yang ditemukan pada pasien dengan Penyakit Ginjal Kronis (PGK) dalam penelitian ini. Tidak ada hubungan bermakna antara kejadian DRPs dengan kondisi pulang pasien (p>0,05).
SMS Phishing Detection Model with Hyperparameter Optimization in Machine Learning Abdillah, Rahmad; Insani, Fitri
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.35547

Abstract

Phishing is one of the growing cybersecurity threats, including through SMS, known as smishing. This research aims to build a model for SMS phishing detection using a machine learning approach optimized through hyperparameter tuning techniques. The data used is obtained from personal SMS messages collected through questionnaires, which are then labeled by information security experts. The SMS text is cleaned using Natural Language Processing (NLP) techniques and represented using the TF-IDF method. Ten classification algorithms are tested in this study: K-NN, Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost, Bagging, ExtraTree, Gradient Boosting, and XGBoost. Hyperparameter optimization is performed using Grid Search and Optuna, and performance is evaluated using accuracy, F1-score, and ROC-AUC metrics. The results show that the SVM and Logistic Regression models performed the best, achieving accuracy up to 98.5%. Hyperparameter optimization techniques have proven effective in improving the performance of SMS phishing classification models. This research is expected to contribute to the development of accurate and efficient SMS phishing detection systems.
Perbandingan Akurasi Arsitektur EfficientNet-B0, VGG16, dan Inception V3 Dalam Deteksi Tumor Ginjal Pada Citra CT-Scan Muhammad Fahri; Yanto, Febi; Syafria, Fadhilah; Abdillah, Rahmad
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.670

Abstract

Kidney dysfunction can trigger the development of various diseases, including kidney tumors. Early detection of kidney tumors is very important to increase the effectiveness of treatment and the chances of patient recovery. The use of deep learning technology in medical image classification has become a promising approach, especially in detecting abnormalities in the kidney organ through CT-Scan images. This study compares the performance of three Convolutional Neural Network (CNN) architectures, namely EfficientNet-B0, Inception-V3, and VGG16, in detecting kidney tumors. The dataset used was obtained from the kaggle website, namely CT-scan images with normal and tumor classes and divided by a ratio of training  data and test data of 80:20. The hyperparameter used is Stochastic Gradient Descent (SGD) with a learning rate of 0.001 and 0.0001. The evaluation was carried out using a confusion matrix with metrics of accuracy, precision, recall, and F1-score . According to the test outcomes, the VGG16 model configured with a 0.001 learning rate achieved the highest classification performance, recording 99.46% accuracy, precision, recall, and F1-score.
PENERAPAN TEKNIK SMOTE PADA KLASIFIKASI PENYAKIT STROKE DENGAN ALGORITMA SUPPORT VECTOR MACHINE Pasiolo, Lugas; Afrianty, Iis; Budianita, Elvia; Abdillah, Rahmad
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 1 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Januari 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v7i1.24731

Abstract

Stroke adalah kondisi darurat medis yang dapat menyebabkan kerusakan otak atau kematian. Deteksi dini dan klasifikasi risiko stroke sangat penting untuk pencegahan dan penanganannya. Penelitian ini menggunakan dataset sebanyak 5110 data untuk meningkatkan akurasi klasifikasi stroke dengan algoritma Support Vector Machine (SVM) pada data tidak seimbang. Teknik Synthetic Minority Over-sampling Technique (SMOTE) diterapkan untuk menyeimbangkan data stroke dan non-stroke, yang dapat meningkatkan performa model. SVM diuji dengan berbagai kernel, yaitu Linear, RBF, Polynomial, dan Sigmoid, serta variasi parameter pada masing-masing kernel untuk mencari konfigurasi optimal. Hasil pengujian menunjukkan penerapan SMOTE meningkatkan akurasi, presisi, dan recall, dengan kernel RBF mencapai akurasi tertinggi 92% pada parameter Cost 100 dan Gamma 1. Temuan ini menunjukkan bahwa penggunaan SMOTE dan optimasi parameter SVM dapat menghasilkan model klasifikasi yang lebih efektif dalam mendeteksi risiko stroke pada data tidak seimbang.
Co-Authors Agustian, Surya Amni, Hudiyah Ardiansyah, Aan Benardo, Benardo Dian Ayu Juwita Dwi Afrianti, Rezy Dwisari Dillasamola Elvia Budianita Fadhilah Syafria Fatma Sri Wahyuni Febi Yanto Fernando, Yendri Ikhlas Fitri Insani Harni, Yulia Iis Afrianty Julmiza, Adinny Meliani, Meliani Muhammad Fahri Najwa, Nina Fadilah Okfalisa Okfalisa Pasiolo, Lugas Pizaini Pizaini Putri, Adilah Atikah Rachmaini, Fitri Rahmi Yosmar Reski Mai Candra Rifqi, Melvi Auliya Simaremare, Harris Simaremare Srangenge, Yoneta Suwanto Sanjaya Yufri Aldi