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Asrul Abdullah
Universitas Muhammadiyah Pontianak
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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions 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 Other

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Pelatihan PMBA bagi Kader Kampung Keluarga Berkualitas Desa Membangun dalam Rangka Pencegahan Stunting Indah Budiastutik; Marlenywati; Abdullah, Asrul; Karisma, Nova; Juliana Panemaan, Anita
J-Dinamika : Jurnal Pengabdian Masyarakat Vol 9 No 3 (2024): Desember
Publisher : Politeknik Negeri Jember

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

Abstract

Stunting is a disorder that attacks the growth and development of children and babies caused by chronic malnutrition which is characterized by a body length or height that is below standard. Many factors underlie the high incidence of stunting, one of which is improper Infant and Child Feeding. The growth and development of toddlers is closely related to food intake which can have a major influence on optimizing the development and growth of infants and toddlers in 1000 HPK. The Kampung KB Membangun Desa is located in the Rasau Jaya Umum Village, Kubu Raya Regency, which is the focus of accelerating stunting reduction. The stunting rate in the district reached 27.8% in 2022. The stages of community service activities begin with coordination of activities with the coordinator, then continued with counseling and training. Community service is carried out using lecture, demonstration and question and answer methods supported by PMBA module media and equipment. Evaluation of counseling activities is carried out by providing a questionnaire sheet containing 10 questions. From the results of the SPSS analysis test, the respondents knowledge during the pre-test was 66.67%. After being educated, there was an increase in respondents knowledge during the post-test of 83.3%.
Perancangan Presensi Menggunakan Radio Frequency Identification (RFID) Dan Fingerprint Ramadhan, Dwi Rohmat; Abdullah, Asrul; Fakhruzi, Izhan
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 3: Desember 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i3.2443

Abstract

Attendance is the process of recording attendance as a form of employee discipline and professionalism. Manual attendance is very time-consuming and errors often occur in making attendance recaps because you have to count attendance one by one and attendance data can still be manipulated. Therefore, designing attendance using RFID and fingerprints can help to improve employee discipline and make the attendance process easier. Apart from that, attendance using RFID and fingerprints has advantages compared to manual attendance, such as making the attendance process easier, recording and storing attendance data in a database. Fingerprints also have quite high security because human fingers have unique fingerprints. By using the NodeMCU ESP8266 as a microcontroller that can connect to the internet, the attendance process is only done by scanning the attendance tool, and then processing the data using the website, which will produce more accurate attendance information compared to manual attendance.Keywords: Attendance; RFID; Fingerprint; NodeMCU ESP8266 microcontroller.    AbstrakPresensi merupakan proses pencatatan kehadiran sebagai bentuk kedisiplinan dan profesionalisme karyawan. Presensi manual sangat menyita waktu dan sering terjadinya kesalahan dalam melakukan pembuatan rekap presensi dikarenakan harus menghitung presensi satu per satu dan data presensi masih dapat dimanipulasi. Oleh karena itu, perancangan presensi menggunakan RFID dan fingerprint ini dapat membantu untuk meningkatkan kedisiplinan karyawan dan mempermudah dalam proses presensi, selain itu presensi menggunakan RFID dan fingerprint memiliki kelebihan dibandingkan presensi manual seperti dapat mempermudah proses presensi, perekapan serta data presensi tersimpan didalam database. Fingerprint atau sidik jari juga memiliki keamanan yang cukup tinggi dikarenakan jari manusia memiliki sidik jari yang unik. Dengan menggunakan NodeMCU ESP8266 sebagai mikrokontroler yang dapat terhubung ke internet proses presensi hanya dengan scanning pada alat presensi, kemudian dilakukan pengolahan data dengan website maka akan menghasilkan informasi kehadiran yang lebih akurat dibandingkan dengan presensi manual. 
Identifikasi Unsur Hara pada Lahan Pertanian Padi menggunakan Soil Integrated Sensor dan Sistem Informasi Geografis Abdullah, Asrul; Iwan, Muhammad; Alkhairi, Muhammad Ghozy
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 3 (2024): Volume 10 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i3.83329

Abstract

Pemenuhan SDG"™s di Indonesia salah satunya ditunjang oleh sektor pertanian. Produk pertanian dengan yang menjadi perhatian adalah padi. Pertumbuhan padi di Indonesia dapat tumbuh dengan subur karena di dalam tanah memiliki kandungan unsur hara. Kandungan unsur hara penting yang dibutuhkan oleh padi agar tumbuh dengan cepat adalah nitrogen, phosporus dan kalium / potassium (NPK). Kandungan unsur NPK yang terkandung di pupuk atau tanah melalui analisis laboratorium dengan biaya yang relatif mahal dan waktu yang lama. Untuk itu perlu cara lain yakni menggunakan soil integrated sensor. Penelitian ini memiliki tujuan untuk mendapatkan informasi terkait kandungan unsur hara pada lahan pertanian padi menggunakan soil integrated sensor serta lokasi menggunakan sistem informasi geografis. Parameter yang digunakan antara lain suhu tanah, kelembapan tanah, electrical conductivity, pH tanah, nitrogen, phosporus, potassium dan salinitas tanah. Parameter lain yang di dapatkan dari GPS adalah longitude, latitude, velocity, altitude serta tanggal pengukuran. Tahapan yang ada di dalam penelitian antara lain studi pustaka, pengumpulan data, analisis kebutuhan, rancangan, implementasi dan pengujian prototipe. Hasil dari penelitian ini adalah prototipe berhasil mengidentifikasi kandungan unsur hara tanah, membaca semua parameter dan mengirimkan hasilnya ke Node-RED menggunakan MQTT dan menyimpan data ke MySQL. Parameter lain yang juga ikut disimpan adalah titik lokasi dari pengambilan data menggunakan GPS. Kesimpulan dari penelitian ini protipe berhasil diuji coba pada lahan pertanian padi dan mengidentifikasi kandungan unsur hara. Titik-titik lokasi yang dikirimkan ke database berhasil dipetakan menggunakan Leaflet JS.    
Classification of Fetal Health Using the K-Nearest Neighbor Method and the Relieff Feature Selection Method Anita; Asrul Abdullah; Syarifah Putri Agustini Alkadri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.794

Abstract

Understanding fetal health early can reduce risks to the pregnancy and the womb. Identifying correlations among factors influencing fetal well-being helps medical professionals clarify key impacts. Quantified relationships between features and labels also guide future research. This study focuses on three aspects: evaluating KNN model performance with and without ReliefF feature selection, analyzing the impact of feature removal, and assessing ReliefF's ability to identify critical features for fetal health classification.The research begins by framing fetal health classification as a supervised machine learning task using labeled datasets. A cardiotocographic dataset from the UCI Machine Learning Repository supports data collection. Initial analysis identifies data types and detects outliers, followed by preprocessing, feature selection, and KNN model training. Model testing uses metrics such as accuracy and recall. Results show the KNN model with ReliefF features achieves an accuracy of 0.896. Testing a pruned model by removing high-importance features slightly reduces accuracy to 0.866. These findings confirm ReliefF's effectiveness in identifying essential features and optimizing model efficiency without compromising quality. This study underscores ReliefF's role in improving KNN performance for fetal health classification.
Decision Support System for Selection of Achieving Students Using MetDecision Support System for Selection of Achieving Students Using Method Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Web Based Isra Pebrianti; Syarifah Putri Agustini Alkadri; Asrul Abdullah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.829

Abstract

The selection of outstanding students identifies the best students based on grades and achievements to recommend them for college entrance. This process often encounters challenges due to numerous determining factors, leading to potential biases in decision-making. A Decision Support System (DSS) helps address this by utilizing data and decision models to resolve structured and unstructured problems. This study applies the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method, using criteria such as attendance, attitude scores, knowledge and skills component values, extracurricular/organizational involvement, and achievements. The DSS identified 40 outstanding students at SMA Negeri 1 Tayan Hulu, with the highest preference score of 0.0819 achieved by Indah Prasetyaning Tias. Functional testing was conducted using the black-box method with Equivalence Partitioning, and accuracy testing through MAPE showed a calculation accuracy rate of 2.79%.
Prediksi Banjir Di Kota Pontianak Menggunakan Metode Decision Tree C4.5 Fitrah, Mifthahul; Abdullah, Asrul; Istikoma, Istikoma
Justek : Jurnal Sains dan Teknologi Vol 8, No 1 (2025): Maret
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i1.29343

Abstract

Abstract:  – The city of Pontianak is prone to flooding during the rainy season due to its low land surface elevation of 0.1–1.5 meters above sea level and its location along the Kapuas River. Flood prediction in Pontianak needs to be conducted using predictive techniques from data mining. One of the predictive analysis methods is the C4.5 decision tree. This study aims to design a flood prediction model for Pontianak using the C4.5 decision tree method and to determine the obtained accuracy results. The research methodology follows several stages, including problem identification, literature review, data collection, data processing, testing, and conclusion. In this study, three experiments were conducted with different treatments. The model performance evaluation for these three experiments was carried out using a confusion matrix. Based on the evaluation results, the best model for flood prediction was obtained from the second experiment, achieving an accuracy, precision, recall, and F1-score of 98%, 72%, 76%, and 74%, respectively, on the test dataAbstrak: Kota Pontianak merupakan daerah rentan terjadinya bencana banjir saat musim hujan tiba karena memiliki ketinggian permukaan tanah 0,1-1,5 meter diatas permukaan laut dan dilalui oleh aliran Sungai Kapuas. Prediksi banjir di Kota Pontianak perlu dilakukan dengan memanfaatkan teknik prediksi dari data mining. Salah satu metode analisis prediktif adalah decision tree C4.5. Tujuan Penelitian ini adalah merancang model prediksi banjir di Kota Pontianak menggunakan metode decision tree C4.5 serta mengetahui hasil akurasi yang diperoleh. Metode penelitian pada penelitian ini melalui beberapa tahapan yaitu identifikasi masalah, studi Pustaka, pengumpulan data, pengolahan data, pengujian, dan Kesimpulan. Pada penelitian ini dilakukan tiga percobaan dengan perlakuan yang berbeda. Pengecekan kinerja model dari tiga percobaan tersebut mengunakan confusion matrix. Dari pengecekan tiga percobaan tersebut didapatkan model terbaik untuk memprediksi banjir yaitu pada percobaan kedua dengan hasil akurasi, presisi, recall, dan F1-score sebesar 98%, 72%, 76% dan 74% pada data uji.
Penggunaan Information Retrieval untuk Mendeteksi Kesamaan Judul Skripsi dengan Modified Cosine Similarity Wahyuni, Sri; Abdullah, Asrul; Sucipto, Sucipto
Justek : Jurnal Sains dan Teknologi Vol 8, No 2 (2025): Juni
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i2.30146

Abstract

Abstract:  This research develops a web-based system to detect the similarity of thesis titles using the Modified Cosine Similarity method and TF-IDF weighting. This system helps students in evaluating the similarity of titles automatically, so as to avoid plagiarism and increase the originality of research. The process used includes text preprocessing (case folding, tokenizing, stopword removal, stemming), TF-IDF calculation for word weighting, and the use of Modified Cosine Similarity to measure the level of similarity between titles. The test results show that the system is able to identify the similarity of titles with a 100% recall rate, where titles with >70% similarity need to be revised, 31%-70% similarity can be clarified by adding words, and ≤30% similarity is potentially accepted as an original title. With this implementation, it is expected that students can more easily determine a thesis title that is unique and in accordance with academic standards.Abstrak: Penelitian ini mengembangkan sistem berbasis web untuk mendeteksi kemiripan judul skripsi menggunakan metode Modified Cosine Similarity dan pembobotan TF-IDF. Sistem ini membantu mahasiswa dalam mengevaluasi kemiripan judul secara otomatis, sehingga dapat menghindari plagiarisme dan meningkatkan orisinalitas penelitian. Proses yang digunakan meliputi text preprocessing (case folding, tokenizing, stopword removal, stemming), perhitungan TF-IDF untuk pembobotan kata, dan penggunaan Modified Cosine Similarity untuk mengukur tingkat kemiripan antar judul. Hasil pengujian menunjukkan bahwa sistem mampu mengidentifikasi kemiripan judul dengan tingkat recall 100%, di mana judul dengan kemiripan >70% perlu direvisi, kemiripan 31%-70% dapat diperjelas dengan penambahan kata, dan kemiripan ≤30% berpotensi diterima sebagai judul orisinil. Dengan implementasi ini, diharapkan mahasiswa dapat lebih mudah menentukan judul skripsi yang unik dan sesuai dengan standar akademik.
AKSI UNIASIAH (Blood Transfusion Unit) Based on Android With Waterfall Apriliasari, Betty; Utami, Nur Sri; lidia, Lidia; Abdullah, Asrul
Jurnal Transformatika Vol. 17 No. 1 (2019): July 2019
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v17i1.1410

Abstract

Teknologi informasi merupakan salah satu teknologi yang sedang berkembang dengan pesat pada saat ini, sehingga informasi yang tersedia dapat berlangsung dengan cepat, efisien serta akurat. Pada Unit Transfusi Darah PMI ini sangat minim pelayanan informasi mengenai ketersediaan darah melalui mobile device sehingga banyak masyarakat yang kurang informasi mengenai persedian darah. Maka perlu ditemukan cara memecahkan masalah yang ada dengan menyediakan sebuah aplikasi berbasis android yang dapat diakses oleh masyarakat. Metode yang digunakan untuk membangun sistem ini menggunakan metode waterfall dan divisualisasikan dengan use case diagram. Hasil dari penelitian ini adalah aplikasi donor darah yang mampu menyediakan data stok darah, jadwal kegiatan donor dan lokasi, serta informasi donor darah.
Sistem Pendukung Keputusan Untuk Rekomendasi Topik Skripsi Dengan Metode Fuzzy AHP Abdullah, Asrul; Sucipto, Sucipto
Jurnal Transformatika Vol. 18 No. 2 (2021): January, 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v18i2.2708

Abstract

The ability to produce a scientific work both journals, scientific articles and thesis is needed to support the competence of undergraduate students in a university. The existence of a thesis course in a number of universities is one of the efforts to train students in producing a scientific work. To arrive at the stage of making a thesis, a student must first study various kinds of courses in each study program. Choosing a thesis topic is one of the most difficult stages in the preparation of a thesis. This is because there are still many students who do not understand and know their interest and ability in one of the courses which will later be used as a topic in thesis preparation. The focus of this research is a decision support system that is able to answer student problems in determining thesis topics according to their abilities. The method used is a waterfall within the SDLC (system development life cycle) framework starting from system requirement, data collection, design, implementation, testing, and maintenance. The result of this research is the ability of the decision support system to provide recommendations for thesis topics according to the abilities of students. The greatest weight is for A5 students for Computer Networking interest of 1,410 while the smallest weight is for A4 students for Multimedia interest of 0.080.
Klasifikasi Penyakit Kanker Paru-Paru Menggunakan Metode Decision Tree C4.5 Jainudin, Khorlis; Abdullah, Asrul; Sucipto, Sucipto
Justek : Jurnal Sains dan Teknologi Vol 8, No 3 (2025): September
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v8i3.31981

Abstract

The incidence of lung cancer in Indonesia has shown a significant increase, positioning the country as the eighth highest in Southeast Asia, with a growth rate of 10.85% over the past five years. A considerable number of lung cancer cases remain undiagnosed at earlier stages due to difficulties in detection, which contributes to the high mortality rate associated with this disease. Consequently, there is a need for a relatively efficient and straightforward technique to uncover knowledge, patterns, and interrelationships among data. The objective of this study is to develop a classification model for lung cancer using the C4.5 decision tree method and to evaluate its predictive performance. The methodology comprises several stages, including data preprocessing, exploratory data analysis (EDA), handling of missing values, identification of duplicate records, assessment of feature correlations, separation of features and target variables, partitioning of data into training and testing sets, model implementation, and performance evaluation through a confusion matrix. The experimental results demonstrate that the proposed model achieves a recall of 90%, a precision of 86%, an F1-score of 88%, and an overall accuracy of 89%. These findings indicate that the C4.5 decision tree method is effective in classifying lung cancer cases and holds potential as a reliable approach in medical data analysis for early detection and diagnosis.
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 Chatarina Umbul Wahyuni Dedy Susanto Doddy Irawan Dwika, Arya Sukma Putra Egy Andryan Eka Indah Raharjo Ema Utami Ervayana Sari Fadillah Bergas Fakhruzi, Izhan Fenni Supriadi Fitrah, Mifthahul G. Gunawan Gunarto Gunarto Gusti Ardhasna Fauzan Hermansyah, Hermansyah Indah Budiastutik Iskandar Hadiatma Isra Pebrianti Istikoma Istikoma Istikoma Istikoma Istikoma Istiqoma Iwan, Muhammad Jainudin, Khorlis Juliana Panemaan, Anita Karisma, Nova Khairah, Della Udya Khairul Lea Candra Lidia Lidia, Lidia Linda Suwarni Marlenywati Marlenywati Maryogi Menur Wahyu Pangestika, Menur Wahyu Muhammad Agus Muljanto Muhammad Fikri Bagus Pratama Muhammad Iwan Octariadi, Barry Ceasar Pedi Irawan Putri Utami, Putri Putri Yuli Utami Rachmat Wahid Saleh Insani Rachmat Wahid Saleh Insani Ramadhan, Dwi Rohmat 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 Syafaat Agung Prakoso Syarifah Putri Agustini Alkadri Taruk, Medi Try Kardina Unitama Utami, Nur Sri Utami, Putri Yuli Vidyastuti, Vidyastuti Viona, Tiara Aurilia Wawan Setiawan Yanto, Maryogi Zulfan Ahmadi