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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Pseudocode Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUSIFO : Jurnal Sistem Informasi Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA Machine : Jurnal Teknik Mesin JURNAL REKAYASA TEKNOLOGI INFORMASI Justek : Jurnal Sains Dan Teknologi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) NUSANTARA : Jurnal Ilmu Pengetahuan Sosial CYBERNETICS BULETIN AL-RIBAATH Global Health Management Journal Jurnal Tekno Insentif JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer bit-Tech Jurnal Teknika Jurnal Sains Komputer dan Teknologi Informasi Jurnal Computer Science and Information Technology (CoSciTech) JUTECH : Journal Education and Technology Journal of Artificial Intelligence and Engineering Applications (JAIEA) Journal of Comprehensive Science J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) International Journal of Health, Engineering and Technology The Indonesian Journal of Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Digital Business and Data Science JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Publikasi Teknik Informatika TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Asrul Abdullah
Universitas Muhammadiyah Pontianak
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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PERBANDINGAN FUNGSI OPTIMIZER PADA IDENTIFIKASI DIABETES MENGGUNAKAN METODE FEED FORWARD Setyawan, Rizki Fajar; Abdullah, Asrul; Octariadi, Barry Ceasar
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7757

Abstract

Identifikasi dini diabetes merupakan kebutuhan mendesak untuk mencegah komplikasi serius dan mengurangi beban kesehatan global. Penelitian ini bertujuan untuk membandingkan kinerja fungsi optimizer pada model Feed Forward Neural Network (FFNN) dalam mengklasifi-kasikan data diabetes. Optimizer yang diuji meliputi RMSprop, Adam, Adagrad, dan Stochastic Gradient Descent (SGD). Dataset diabetes dari platform Kaggle, yang terdiri dari 768 sampel dengan 9 fitur, dibagi men-jadi data latih dan uji dengan rasio 80:20. Evaluasi model dilakukan menggunakan metrik Accuracy, Precision, Recall, dan F1-Score ber-dasarkan Confusion Matrix. Hasil penelitian menunjukkan bahwa RMSprop memberikan performa terbaik dengan akurasi sebesar 0,759740, Precision 0,660377, Recall 0,648148, dan F1-Score 0,654206, diikuti oleh Adam dengan akurasi 0,746753. RMSprop menunjukkan generalisasi yang lebih baik pada data uji berkat mekanisme pembaruan bobot adaptifnya. Penelitian ini merekomendasikan RMSprop sebagai optimizer optimal untuk model FFNN dalam identifikasi diabetes, memberikan kontribusi bagi pengembangan alat diagnosis yang lebih akurat dan efisien.
Optimasi Rute Pengambilan Bantuan Sosial Lazismu Menggunakan Algoritma Genetika Travelling Salesman Problem Iskandar Hadiatma; Rachmat Wahid Saleh Insani; Asrul Abdullah
Techno.Com Vol. 25 No. 2 (2026): May 2026
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v25i2.16016

Abstract

Lembaga Amil Zakat, Infaq, dan Sadaqah Muhammadiyah (Lazismu) di Pontianak Tenggara menghadapi kendala operasional dalam pengambilan donasi dari kotak infaq yang tersebar di berbagai lokasi. Proses penentuan rute yang belum optimal menyebabkan inefisiensi dari segi waktu dan biaya bahan bakar. Penelitian ini bertujuan untuk mengatasi masalah tersebut dengan menerapkan Algoritma Genetika untuk menyelesaikan Travelling Salesman Problem (TSP), guna menemukan rute terpendek untuk mengunjungi seluruh titik donasi. Sistem optimasi ini dibangun dalam bentuk aplikasi berbasis website menggunakan kerangka kerja Laravel untuk proses backend dan pustaka LeafletJS untuk visualisasi peta interaktif. Metode pengembangan sistem yang digunakan adalah model Waterfall, yang mencakup tahapan analisis kebutuhan, perancangan, implementasi, dan pengujian. Pengujian sistem dilakukan dengan metode Black Box Testing dan User Acceptance Testing (UAT). Hasil penelitian menunjukkan bahwa Algoritma Genetika berhasil mengoptimalkan rute pengambilan donasi. Pada studi kasus dengan 18 titik lokasi, rute yang dihasilkan sistem adalah 19.79 km, lebih efisien 7.57 km dibandingkan rute manual sebelumnya (27.36 km). Hasil pengujian UAT oleh staf Lazismu mencapai persentase penerimaan 94%, yang menunjukkan bahwa aplikasi yang dikembangkan sangat bermanfaat, mudah digunakan, dan sesuai dengan kebutuhan operasional.   Kata kunci – Algoritma Genetika, Lazismu, Optimasi Rute, Travelling Salesman Problem.
Implementation of a Web-Based Decision Support System for New Employee Recruitment Using the VIKOR Method Arochman; Sucipto; Asrul Abdullah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2298

Abstract

An effective and objective employee selection process is essential to obtain high-quality human resources. This study aims to develop a web-based decision support system to assist in the recruitment of new employees using the VIKOR method. The VIKOR method is chosen because it can rank alternatives based on their closeness to the ideal solution while considering compromise among criteria. The criteria used in the system include education, work experience, skills, interview results, and work personality. This research adopts the waterfall approach for system development and implements PHP programming language with a MySQL database. The testing results indicate that the system is capable of providing accurate and consistent rankings of job candidates, as well as facilitating the HR team in conducting evaluations more efficiently.
Recommendation System for Selecting Maternity Hospitals in Pontianak using Weighted Product Method Ervayana Sari; Asrul Abdullah; Istikoma
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2309

Abstract

In this research, a decision support system for recommending the selection of maternity hospitals in Pontianak was developed using the Weighted Product (WP) method, with the constructed system in the form of a web-based application. The aim of this study is to facilitate pregnant women in choosing maternity hospitals in Pontianak based on criteria obtained from a survey of pregnant women, including distance, facilities, cost, and reputation. The WP method was applied through three main stages: weight normalization, vector S calculation, and vector V computation for final ranking. Testing in this research involves five alternative maternity hospitals, and each criterion is assessed on indicators ranging from 1 to 5. The results obtained indicate that Anugerah Bunda Khatulistiwa Maternity Hospital achieved the highest final ranking score among all evaluated alternatives. This system is expected to assist expectant mothers in making more informed decisions when selecting a maternity hospital that best suits their needs.
Network Device Performance Monitoring Using the Simple Network Management Protocol (SNMP) Method Aldi Mulia Rismanto; Asrul Abdullah; Sucipto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2346

Abstract

Network problems frequently occur at Politeknik Negeri Pontianak due to the increasing number and scale of network devices. These issues require continuous monitoring to ensure service availability across all network devices. To address this problem, the author conducted network monitoring using the SNMP (Simple Network Management Protocol) method and network performance measurement using the Wireshark application. SNMP is a standard protocol used to monitor and manage network devices such as routers, switches, servers, and other networking equipment. The research stages began with data collection, followed by monitoring and performance testing of the network. After testing the network in the Informatics Engineering Building, both satisfactory and unsatisfactory results were obtained. The results of SNMP measurements on MRTG showed the lowest throughput values on the second day of testing, with 485.6 kbps for daily traffic, 236.8 kbps for weekly traffic, 232 kbps for monthly traffic, and 121.6 kbps for yearly traffic. Meanwhile, the Quality of Service measurement produced the lowest throughput value of 0.225 kbps, packet loss of 0.354%, delay of 3.331 ms, and jitter of 8.763 ms.
Diagnostic Expert System Website-Based Stroke Disease Using Forward Chaining and Certainty Factor Methods Muhammad Fikri Bagus Pratama; Asrul Abdullah; Istikoma Istikoma
Journal of Digital Business and Data Science Vol. 3 No. 1 (2026): Journal of Digital Business And Data Science
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jdbs.v3i1.34

Abstract

Background: Stroke is a neurological condition characterized by the sudden loss of brain function resulting from disruption of blood supply to the brain. It ranks as the second leading cause of death globally, with a mortality rate ranging from 18% to 37%, and constitutes a major cause of neurological disability in Indonesia as well as the third leading cause of death worldwide.Objective: This study aimed to develop a web-based expert system enabling patients and their families to perform early detection of stroke symptoms.Method: This study employed a prototype-based development methodology. The knowledge base was constructed through structured interviews with a neurologist and validated through cross-checking with clinical records. The Forward Chaining method served as the inference engine, deriving diagnostic conclusions from symptom-based facts, while the Certainty Factor method quantified diagnostic uncertainty. System testing was conducted using six patient case samples provided by the expert.Findings and Implications: The system achieved a diagnostic accuracy of 86.68% based on cross-validation with expert knowledge using six clinical case samples. Black-box functional testing confirmed that all system features performed as expected.Conclusion: These results indicate that the system is capable of supporting preliminary stroke symptom assessment, thereby facilitating early decision-making prior to professional medical consultation. However, given the limited number of test cases, the system’s generalizability warrants further validation using a larger clinical dataset.
Metode Analytical Hierarchy Process (AHP) untuk Pemilihan Media Sosial Pemasaran Songket Sambas Wawan Setiawan; Alda Cendekia Siregar; Asrul Abdullah
JUSIFO : Jurnal Sistem Informasi Vol 7 No 1 (2021): June
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v7i1.7717

Abstract

Songket Sambas (Kain Lunggi) is a gold thread cloth typical of the culture of the Sambas people. The Sambas songket craftsmen have used social media a lot in marketing their products. The selection of the right social media in product marketing can help increase sales of Sambas songket. It can be the key to success in expanding Sambas songket sales to various regions. This study aims to apply the Analytical Hierarchy Process (AHP) method in the selection of social media that is widely used as the right Sambas songket marketing media. In this study, the AHP method was used as a method for decision making. In determining the pairwise comparison matrix, Sambas songket craftsmen were involved. The criteria used are age range (C1), gender (C2), number of users (C3), level of popularity (C4). From this study, we have the value of Facebook is 0.82, Instagram is 0.60, Youtube is 0.06, Twitter is 0.04. The final priority result of the right social media to use with the first order is Facebook.
Prediction of the level of crime cases using multiple linear regression in the city of Pontianak Fadillah Bergas; Sucipto; Asrul Abdullah
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 2 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i2.1025

Abstract

This study aims to develop a predictive model for the crime rate in the Police Resort Area of Kota (POLRESTA) Pontianak using the Multiple Linear Regression method based on secondary data obtained from the Criminal Investigation Unit of POLRESTA Pontianak. The utilization of descriptive statistical techniques and data visualization aids in identifying relevant features that enrich the information within the model. The evaluation results indicate that this model performs well in both modeling and predicting crime rates in Kota Pontianak. Despite the variations in error rates between training and testing data, the model still demonstrates its proficiency in predicting known data. The testing results also reveal that the Mean Absolute Percentage Error (MAPE) values for each crime category exhibit variations in the testing dataset, with MAPE for "Berat" increasing to 12.91%, MAPE for "Sedang" increasing to 30.11%, and MAPE for "Ringan" increasing to 26.59%. Consequently, this study concludes that the Multiple Linear Regression method holds potential as an effective tool for decision-making and the development of strategies to combat criminal activities in Kota Pontianak
Klasifikasi Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Convolutional Neural Network Nur Rali Rahma Wati; Asrul Abdullah; Sucipto Sucipto
Jurnal Publikasi Teknik Informatika Vol. 4 No. 3 (2025): September : Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v4i3.5841

Abstract

Classifying the ripeness level of oil palm fruits represents a critical aspect of the oil palm industry that dominates Indonesia's economy. This research aims to develop and evaluate a Convolutional Neural Network (CNN) model to automatically, objectively, and accurately classify the ripeness level of oil palm fruits based on digital image analysis. The underlying problem of this research is the manual harvesting practice that relies on subjective assessment by harvesters, resulting in inconsistency and substantial economic losses. The research approach employs a quantitative experimental methodology with a dataset of 1,840 digital images of oil palm fruits balanced across four ripeness categories (unripe, semi-ripe, ripe, overripe). Image preprocessing was performed to standardize input with a data split of 80% training and 20% testing. The implemented CNN model achieved an average accuracy of 76.52% with optimal accuracy of 82.61%, precision of 0.77, recall of 0.77, and F1-score of 0.76 from five independent test runs. RGB profile analysis revealed a significant correlation between color pigment values and ripeness level, with extreme categories (unripe and ripe) achieving accuracy >95%, while transitional categories (semi-ripe) demonstrated higher challenges. Per-category results showed excellent F1-scores (0.946–0.983) for all classes, indicating that the model learned meaningful ripeness indicators based on biological pigment physiology. System implementation was complemented with a user-friendly Graphical User Interface (GUI) based on MATLAB, enabling non-technical operators to use the model directly. Functional black-box testing demonstrated a 100% pass rate, validating the system's readiness for operational deployment. In conclusion, CNN can be implemented as a practical solution for harvest automation that enhances objectivity, consistency, and efficiency in harvest timing determination, with positive implications for product quality, industry sustainability, and economic value added for Indonesian oil palm farmers. Keywords: Ripeness classification, oil palm fruit, Convolutional Neural Network, digital image processing, harvest automation, machine learning, RGB analysis
Development of an IoT-based Soil Nutrient Monitoring and GIS Mapping System for Precision Agriculture Asrul Abdullah; Eka Indah Raharjo; Muhammad Iwan; Rizki Faizal; Maryogi
Advance Sustainable Science Engineering and Technology Vol. 7 No. 4 (2025): August-October
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i4.2191

Abstract

Agriculture is a field that contributes to Indonesia's economic development.  Unpredictable weather, temperature fluctuations, and the difficulty in assessing soil quality hinder farmers in enhancing crop productivity. The IoT in signifies a beneficial progression that will assist farmers in their endeavors. Precision agriculture is an innovative approach that employs information technology for sustainable agricultural management. This research aims to assess soil nutrients and provide mapping data based on the evaluated agrarian sites. The testing sites are situated in three sub-districts within Kubu Raya Regency: Sungai Kakap, Ambawang, and Rasau Jaya. The soil study indicated a temperature range of 29.40 °C to 36.80 °C. Soil moisture varied from 4 % to 89.10 %. The soil pH varied between 6.90-8.07 PH. The soil salinity was rather modest. Nutrient levels, particularly nitrogen, were slightly lower than those of phosphate and potassium, necessitating fertilizer use to enhance plant vegetative development. Incorporating the Internet of Things onto agricultural land delivers data as real-time monitoring, which will be essential for improving agricultural output. This scalable method mitigates contemporary agricultural difficulties by diminishing environmental impact and enhancing crop resilience. This study facilitates sustainable, intelligent agricultural techniques to address the escalating needs of a swiftly expanding global population. 
Co-Authors Abrar, Ihya' Nashirudin Adi, Pranowo Aditya Wicaksono Alda Cendekia Siregar Aldi Mulia Rismanto Alkhairi, Muhammad Ghozy Anita Apriliasari, Betty Arni - Yanti Arochman Barry Ceasar Octariadi Dedy Susanto Doddy Irawan Dwika, Arya Sukma Putra Egy Andryan Eka Indah Raharjo Ema Utami Ervayana Sari Ewa Oktaviaghi Prasetya Fadillah Bergas Fakhruzi, Izhan Fenni Supriadi G. Gunawan Gunarto Gunarto Gusti Ardhasna Fauzan Hermansyah, Hermansyah Indah Budiastutik Iskandar Hadiatma Isra Pebrianti Istikoma Istikoma Istikoma Istikoma Istikoma Istiqoma Iwan, Muhammad Juliana Panemaan, Anita Karisma, Nova Khairah, Della Udya Khairul Khorlis Jainudin Khusnul Karomah Lea Candra Lidia Lidia, Lidia Linda Suwarni Marlenywati Marlenywati Maryogi Menur Wahyu Pangestika, Menur Wahyu Mifthahul Fitrah Muhamad Reynaldi Rendi Muhammad Agus Muljanto Muhammad Fikri Bagus Pratama Muhammad Iwan Nur Rali Rahma Wati Octariadi, Barry Ceasar Pedi Irawan Putri Utami, Putri Putri Yuli Utami Rachmat Wahid Saleh Insani Rachmat Wahid Saleh Insani Ramadhan, Dwi Rohmat Rizki Faizal Rizki Faizal Rizky Wahyu Prasetyo Roni, Roni Sahid Agustian Hudjimartsu Salim, Vilvilia Selviana Selviana Setyawan, Rizki Fajar Siregar, Alda Cendekia Siti Aminah SITI AMINAH Sri Wahyuni Sucipto Sucipto Sucipto Sucipto Sucipto Syafaat Agung Prakoso Syarifah Putri Agustini Alkadri Taruk, Medi Try Kardina Unitama Utami, Nur Sri Utami, Putri Yuli Vidyastuti, Vidyastuti Viona, Tiara Aurilia Virgilius Dalta Suprias Nandigna Wawan Setiawan Yanto, Maryogi Zulfan Ahmadi