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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Technologia: Jurnal Ilmiah Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Computing Theories and Applications Mekongga: Jurnal Pengabdian Masyarakat
Ramadhan, As'ary
Lambung Mangkurat University
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Estimasi Pada Effort Perangkat Lunak dengan Pendekatan Feed Forward Neural Network Backpropagation (FFNN-BP) As'ary Ramadhan
Technologia : Jurnal Ilmiah Vol 12, No 2 (2021): Technologia (April)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.07 KB) | DOI: 10.31602/tji.v12i2.4576

Abstract

Estimasi biaya pengembangan proyek perangkat lunak merupakan salah satu masalah yang kritis dalam rekayasa perangkat lunak. Kegagalan dari proyek perangkat lunak diakibatkan ketidak akuratannya estimasi sumber daya yang dibutuhkan. Beberapa model telah dikembangkan dalam beberapa puluh tahun belakangan ini. Untuk meberikan keakuratan dalam estimasi biaya proyek perangkat lunak masih menjadi tantangan hingga saat ini. Tujuan dilakukannya penelitian ini meningkatkan akurasi estimasi biaya proyek perangkat lunak dengan menerapkan algoritma genetika sebagai proses pelatihan pada Feed Forward Neural Network Backpropagation (FFNN-BP) yang mengakomodasi formula dari Post Architecture Model (COCOMO II). Magnitude of Relative Error (MRE) dan Mean Magnitude of Relative-Error (MMRE) digunakan sebagai pengkuran indikasi kinerja. Hasil percobaan menunjukkan bahwa model yang diusulkan memberikan hasil estimasi biaya proyek perangkat lunak menjadi lebih akurat dari COCOMO II dan FFNN-BP. Dalam kasus ini MMRE untuk COCOMO II adalah 74.68%, FFNN-BP adalah 39.90% .  Kata kunci: COCOMO II, Machine Learning, Proyek Manajemen IT, Backpropagation
PENGEMBANGAN WEBSITE UNTUK MENINGKATKAN MANAJEMEN BIMBINGAN PELATIHAN OLAHRAGA DAN ADMINISTRASI PADA BORNEO SPORTS SCIENCE Hegen Dadang Prayoga; Ari Tri Fitrianto; As`ary Ramadhan
RESWARA: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 1 (2023)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v4i1.2307

Abstract

Borneo sports science merupakan sebuah yayasan berfokus pada kegiatan olahraga physical training dan tutoring dengan dua agenda kegiatan yang ditangani oleh staff pengurus yayasan dan pelatih olaharga. Agenda kegiatan pertama adalah manajemen bimbingan pelatihan olahraga. Kedua adalah manajemen administrasi yang meliputi pendataan perserta baru, pembuatan jadwal pelatihan, absensi peserta pelatihan dan pembagian kelas pelatihan. Dalam menjalankan kegiatan tersebut masih menggunakan manajemen tradisional seperti bimbingan tertulis dan pencatatan kehadiran peserta latihan dengan cara manual yang dilakukan oleh pelatih olahraga yaitu berupa catatan pada kertas. Cara tersebut memiliki kekurangan seperti catatan mudah hilang, begitu juga pada manajemen administrasi yang dikerjakan oleh staff pengurus yayasan masih memiliki kekurangan seperti tidak dapat diakses dari mana saja dan tidak dapat digunakan pada sistem operasi yang berbeda karena masih menggunakan luring spreadsheet. Oleh karena itu manajemen bimbingan pelatihan olahraga dan administrasi pada borneo sports science perlu ditingkatkan. Tujuan dari pengabdian masyarakat ini adalah mengembangkan sistem berbasis website dengan metode protoype yang dapat diakses dari mana saja dan karena terhubung dengan internet artinya dapat digunakan pada sistem operasi apapun dan catatan bimbingan maupun kehadiran tersimpan pada sistem. Hasil dari pengabdian masyarakat ini terlihat adanya peningkatan manajemen yang dilihat dari kemudahan staff pengurus yayasan dan pelatih olahraga dalam memanajemen agenda kegiatan bimbingan pelatihan olahraga dan administrasi berbasiskan sistem website menjadi cepat, tepat dan efisien
Validation of the Haar Cascade Classification Method in Face Detection Muhammad Bahit; Nadia Putri Utami; Heru Kartika Candra; Yonal Supit; As’ary Ramadhan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.10040

Abstract

As technology develops, faces are used as a tool for human interaction with computers for security systems. Face detection technology can also provide convenience to users in various fields, especially security systems. However, there are problems regarding accuracy, complexity in the face recognition process so that many methods have been developed to increase the accuracy and complexity of the face detection process. This study aims to validate the haar cascade classification method in detecting faces from various shooting angles, with a distance of one meter from the camera and the respondent is free to make movements as well as various facial expressions and various lighting conditions that are different for each respondent. The results of this study found that the haar cascade classification method showed that the higher the epoch value, the lower the mean square error (MSE). This study also found that the haar cascade classification method has good accuracy for detecting faces from various angles, different lighting and different facial expressions with a maximum distance of one meter from the camera. This study provides recommendations for making face recognition applications using the haar cascade classification method because it can be used well for lighting effects, facial expressions and a maximum shooting distance of one meter.
PEMBUATAN DAN PELATIHAN APLIKASI BRACKET PERTANDINGAN MUAYTHAI DI PENGURUS PROVINSI MUAYTHAI KALIMANTAN SELATAN Hegen Dadang Prayoga; As`ary Ramadhan; Andi Kasandrawali; Kholik Setiawan
RESWARA: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 1 (2024)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v5i1.3515

Abstract

Pengurus Provinsi MuayThai Indonesia Kalimantan Selatan yang menjadi mitra kami mengalami kesulitan dalam membuat rancangan skema pertandingan atau disebut juga bracket pertandingan secara efektif dan efisien yang dapat digunakan dalam pertandingan olahraga muaythai berbasis aplikasi. Rancangan yang tidak efektif dan efisien berpengaruh secara signifikan terhadap keuangan penyelenggara pertandingan, individu dan tim yang berpatisipasi dan juga masalah yang menyangkut kepentingan pribadi bagi para penggemar pertandingan. Oleh karena itu di dalam kegiatan PKM ini yang menjadi perioritas solusi dari permasalahan mitra adalah membangun sebuah aplikasi yang dapat digunakan dalam membuat bracket pertandingan muaythai disertai dengan pelatihan penggunaan aplikasi tersebut. Cara yang digunakan untuk mengembangkan aplikasi adalah dengan menggunakan model prototipe dengan metode Software Development Life Cycle (SDLC) dan pengukuran untuk menguji aplikasi menggunakan instrument kuesioner System Usability Scale (SUS). Hasil pengabdian berdasarkan pengujian usability dengan nilai score avrg 82.5 termasuk dalam Grade A yang menandakan penerimaan responden terhadap efektifitas, efisiensi dan kepuasan yang dirasakan dalam menggunakan aplikasi sudah dapat diterima dengan baik (Acceptable)
Deep CNN for Wetland Mapping from Satellite Imagery Ramadhan, As`'ary; Herteno, Rudy; Farmadi, Andi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5280

Abstract

Wetland loss endangers the ecosystem through loss of biodiversity, carbon sequestration and flood regulation potential. A precise determination of wetlands status is necessary to safeguard for their conservation and ensure sustainable management. Implementation This study aims to assess the performance of deep CNNs in wetland detection using high-resolution Google Earth image data in South Kalimantan province, Indonesia. The work adopts the Chopped Picture Method (CPM) and the use of sliding windows for data augmentation to improve the diversity of the dataset and reduce the computational cost. Two CNN models, VGG-16Net, and LeNet-5, were trained using a dataset comprising 220 satellite images, which we converted into 89,100 patches of 56×56 pixels. Performance was compared using accuracy, precision, recall, and F1-score. Experimental results show good levels of accuracy for the two architectures, but LeNet-5 provided more stable results between test locations, having a F1-score closer to 100% and spending less computational time (≈10s per epoch) than VGG-16Net (≈40s per epoch). These results validate that CPM significantly increases the variety of training data, making it possible for a CNN to correctly identify the vague and irregular shapes of wetlands with high accuracy. In addition to advancing environmental conservation strategies, the study highlights the contribution of informatics to large-scale, automated environmental monitoring, particularly in supporting wetland conservation, sustainable land-use planning, and climate adaptation efforts.
BIMTEK FTI: Digital Village Governance Muhammad Nur Hidayat, Andi; Ramadhan, As'ary; Na’im Al Jum’ah, Muhammad
MEKONGGA: Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2024): April 2024
Publisher : Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mekongga.v1i1.173

Abstract

Currently, with the allocation of village funds from the government, village development has become an interesting topic of discussion. Both from an economic perspective and better village governance. As with most villages in general, the majority of village funds are used for physical development, such as building construction, repairing the village hall, and village infrastructure such as repairing roads and bridges. Considering the importance of digital village governance, the Faculty of Information Technology, Sembilanbelas November Kolaka University will hold FTI 2022 Technical Guidance: Digital Village Governance. The expected impact after this activity is the creation of good village governance based on information/electronic technology. Based on the results of the activities that have been carried out, it can be concluded that the community service program (PKM) activities, collaboration between Sembilanbelas November Kolaka University and village heads within Kolaka Regency have gone well and are able to provide understanding to village officials regarding good village governance. information/electronic technology based.
Improving Community Competence in Web Development through Company Profile Website Training Richard, Chlyfen; Ningrum, Via; Ramadhan, As'ary
MEKONGGA: Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2025): November 2025
Publisher : Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mekongga.v2i2.253

Abstract

The development of information technology requires society to acquire skills in web development, particularly in creating company profile websites that serve as essential media for information and company promotion. The partners of this program still face limitations in understanding website design, including database, backend, and frontend aspects. The solution provided was intensive online training aimed at improving participants’ knowledge and practical skills. The methods applied consisted of interactive lectures, hands-on practice, and discussion sessions. The results showed an improvement in participants’ abilities to design and implement company profile websites in line with current digital needs. The outcomes of this program include learning modules, e-certificates, and online documentation, which are expected to contribute to enhancing community competence in information technology, especially in web development.
Automated University Lecture Schedule Generator based on Evolutionary Algorithm yusri ikhwani; Khairan Marzuki; As’ary Ramadhan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2215

Abstract

university is a complicated work so in the implementation it have violation of the constraints and it also takes a lot of time since it is created manually. In this paper evolutionary algorithm (EA) is used to create an effective and feasible schedules based on the real data input that is obtained from each department. The objective functions in EA contribute in gaining the fitness function to solve the constraints problem in the schedule by applying weighting for each hard constraints. The objective function is gained from the total of infringement in each soft constraints addition by score weighting. The genetic operator used in EA is stochastic variation Operator. As far as the reproduction operator is concerned, the tournament selection was used with size 3. Crossover operator is conducted after selection process with crossover probability equal to 0.05 and mutation rate is 0.1. The size of population was set to 9 and stopping criteria algorithm was left run for fitness value = 1. The simulation result shows that EA can create lecture schedules efficiently and feasibly. Moreover, it is also faster with the execution time of the proposed EA is less than 30 and easier than creating manually.
Single elimination tournament design using dynamic programming algorithm yusri ikhwani; As`ary Ramadhan; Muhammad Bahit; Taufik Hidayat Faesal
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3290

Abstract

Finding the best single-elimination tournament design is important in scientific inquiry because it can have major financial implications for event organizers and participants. This research aims to create an optimal single-elimination tournament design using binary tree modeling with dummy techniques. Dynamic programming algorithms have been used to compute optimal single-elimination designs to overcome this effectively. This research method uses various implementations of sub-optimal algorithms and then compares their performance in terms of runtime and optimality as a solution to measure the comparison of sub-algorithms. This research shows that the difference in relative costs produced by various sub-algorithms with the same input is quite low. This is expected because quotes are generated as integer values from a small interval 1, ≤ 9, whereas costs tend to reach much higher values. From the comparison of these sub-algorithms, the best results among the sub-optimal algorithms were obtained in the Sub Optimal algorithm 3. We present the experimental findings achieved using the Python implementation of the suggested algorithm, with a focus on the best single-elimination tournament design solution.
Enhancing Software Defect Prediction through Hybrid Multi-Filter Feature Selection and Imbalance Handling Muhammad Khalid Maulana; Setyo Wahyu Saputro; Mohammad Reza Faisal; Radityo Adi Nugroho; As’ary Ramadhan
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.15943

Abstract

Software Defect Prediction (SDP) aims to identify defective modules early in the software development lifecycle to improve software quality and reduce maintenance costs. However, SDP datasets commonly suffer from high dimensionality, feature redundancy, and class imbalance, which can degrade model performance and stability. This study proposes a hybrid feature selection framework to address these challenges and enhance prediction performance. The proposed approach integrates Combined Correlation and Mutual Information (CONMI), which combines the Pearson Correlation Coefficient (PCC) and Mutual Information (MI) to capture both linear and nonlinear feature relevance. The selected features are further refined through Top-K selection, correlation-based filtering to reduce multicollinearity, and Backward Elimination (BE) to obtain an optimal feature subset. To address class imbalance, SMOTE-Tomek is applied by combining over-sampling and data cleaning techniques. Experiments are conducted on twelve NASA MDP datasets using Logistic Regression (LR) and Naïve Bayes (NB) classifiers. The results show that the proposed framework consistently achieves the best performance, with Logistic Regression combined with SMOTE-Tomek obtaining the highest average AUC of 0.7923 ± 0.0714, while NB achieves 0.7554 ± 0.0580. Statistical analysis using a paired t-test indicates that the proposed method significantly outperforms MI+SMOTE-Tomek and BE+SMOTE-Tomek for Logistic Regression, whereas no significant differences are observed for NB. In addition to improving overall classification performance (AUC), the proposed approach also enhances minority class detection, as reflected in improved Recall and F1-score. Overall, the proposed hybrid framework provides an effective and reliable solution for software defect prediction, particularly for high-dimensional and imbalanced datasets.
Co-Authors Andi Farmadi Andi Kasandrawali Ari Tri Fitrianto Hegen Dadang Prayoga Heru Kartika Candra Jeriko, Fadli Khairan marzuki Kholik Setiawan Muhammad Bahit Muhammad Bahit Muhammad Khalid Maulana Muhammad Nur Hidayat, Andi Muhammad Reza Faisal, Muhammad Reza Nadia Putri Utami Na’im Al Jum’ah, Muhammad Ningrum, Via Radityo Adi Nugroho Richard, Chlyfen Rudy Herteno Setyo Wahyu Saputro Taufik Hidayat Faesal Yonal Supit Yusri Ikhwani