Abstract:Study This to study draft fence sea and ownership of sea areas through ecological interpretation perspective based on interpretation of the Qur'an, with referring to the interpretations of Al-Munir and Al- Maraghi . Approach…
oach interdisciplinary between knowledge ecology and religious studies are applied For evaluate role sharia principles in marine biota conservation endemic in Indonesian waters . Methodology analysis content with thematic coding techniques structured used For processing primary and secondary data collected from 2018 to 2023. Case studies that become focus is implementation draft fence sea in several coastal areas of Indonesia, accompanied by analysis legal aspects of ownership sea based on UNCLOS regulations and laws maritime international . Research results show that the ecological interpretation capable give framework philosophical and normative support effort conservation , at the same time offer recommendation policy strategic use support marine area management in a way sustainable . Implications results study This expected can encourage constructive dialogue between practitioner law , scholars, and researchers ecology in frame optimization management source Power marine .
Abstract:Dyslexia is a neurodevelopmental disorder that specifically affects an individual's ability to process phonological and orthographic information, thereby hindering the development of basic literacy skills. In inclusive education…
ducation systems at the elementary level, these limitations are often not addressed through pedagogical approaches that align with the neurocognitive needs of learners. The problem addressed in this study is the effectiveness of the multisensory learning approach in improving the reading skills of children with dyslexia in inclusive elementary education settings. This research was conducted through a systematic literature review using a descriptive qualitative approach, drawing upon scholarly sources published in nationally and internationally accredited journals over the past decade. Thematic analysis was employed to identify consistent empirical findings related to multisensory interventions. The results show that the multisensory approach (which simultaneously engages visual, auditory, kinesthetic, and tactile modalities) has been proven to enhance phonological decoding, word recognition accuracy, reading fluency, and learning affectivity in children with dyslexia. Its effectiveness is highly influenced by the duration and intensity of the intervention, educators' competence in designing multisensory activities, and the suitability of materials to individual sensory profiles. The conclusion of this review asserts that the multisensory approach is not merely a remedial strategy, but a neuroeducation-based pedagogical framework that is inclusive and transformative. The novelty of this research lies in its integrative emphasis on the multisensory approach and principles of educational neuropsychology as the foundation for developing learning models that are responsive to the needs of neurodivergent learners in the context of inclusive elementary education in Indonesia.
Abstract:Abstract: Inventory of goods is an important thing in a company, because inventory can support the operational needs of the company so that it runs smoothly. A good goods management process will produce accurate transaction…
ion and inventory reports. The process of managing goods at BPRS Artha Madani is currently still being carried out manually using Microsoft Excel, this results in difficulties in making reports on incoming and outgoing goods transactions and frequent discrepancies between the data in Microsoft Excel and the actual goods in the warehouse during stock taking. In addition, the process of picking up goods at the warehouse is still not structured, so it is necessary to apply a method of stock management. Therefore, in this study, the design and manufacture of web-based applications was carried out by applying the FIFO method. The FIFO method is a problem-solving method that can be applied in a way that goods that come in first are assumed to be sold or out first [1]. In building this application the author uses the extreme programming (XP) method for system development, this method consists of 4 stages, namely planning, design, coding, testing. With the development of this application, it is hoped that it can overcome problems in managing goods at BPRS Artha Madani.
Keywords: extreme programming; FIFO; inventory of goods
Abstrak: Persediaan barang merupakan hal yang penting pada sebuah perusahaan, karena persediaan barang dapat menunjang kebutuhan operasional pada perusahaan tersebut agar berjalan dengan lancar. Proses pengelolaan barang yang baik akan menghasilkan laporan transaksi dan stok barang yang akurat. Proses pengelolaan barang pada BPRS Artha Madani saat ini masih dilakukan secara manual dengan menggunakan Microsoft excel, hal ini mengakibatkan sulitnya membuat laporan transaksi barang masuk dan keluar serta seringnya terjadi selisih antara data pada Microsoft excel dan aktual barang di gudang saat melakukan stock opname. Selain itu proses pengambilan barang di gudang masih belum terstruktur sehingga perlu diterapkan metode pengelolaan stok barang. Oleh karena itu pada penelitian ini dilakukan perancangan dan pembuatan aplikasi berbasis web dengan menerapkan metode FIFO. Metode FIFO adalah sebuah metode pemecahan masalah yang dapat diterapkan dengan cara barang yang pertama kali masuk diasumsikan terjual atau keluar pertama kali [1]. Dalam membangun aplikasi ini penulis menggunakan metode extreme programming (XP) untuk pengembangan sistem, metode ini terdiri dari 4 tahapan, yaitu planning, design, coding, testing. Dengan dibangunnya aplikasi ini diharapkan dapat mengatasi masalah dalam pengelolaan barang pada BPRS Artha Madani.
Kata kunci: extreme programming; FIFO; pengelolaan barang
Abstract:Abstract: The community service activity entitled "Training on Making Android Applications with Android Studio at junior high school 1 Tinggi Raja" aims to train existing students at junior high school 1 Tinggi Raja to create…
reate an Android application. Moreover, most students must have already had an Android phone, it would be more interesting and fun to be able to make an application on their own cellphone. The method used in this activity is a description and practice. The speaker performs explanations about Android and Android Studio itself, their functions and uses, after that the practice directly uses the Android Studio and how to build it so that it becomes an android file that can be installed on each student's cellphone. Some important points are explained and practiced in this activity, namely the introduction of the Android operating system, the introduction of Android Studio, how to design displays in Android Studio, and how to learn java coding in Android Studio so as to produce an android application.
Keywords: android application, android studio, android
Abstrak: Kegiatan pengabdian kepada masyarakat yang diberi judul “Pelatihan Membuat Aplikasi Android dengan Android Studio pada SMPN 1 Tinggi Raja†bertujuan untuk melatih siswa-siswi yang ada pada SMPN 1 Tinggi Raja untuk membuat aplikasi Android. Terlebih lagi para siswa juga pasti sebagian besar sudah memiliki ponsel Android, hal ini akan lebih menarik dan menyenangkan jika dapat membuat aplikasi di ponsel sendiri. Metode yang digunakan dalam kegiatan ini adalah deskripsi dan praktek. Pemateri melakukan penjelasan-penjelasan tentang Android dan Android Studio itu sendiri, fungsi dan kegunaannya, setelah itu praktek langsung menggunakan Android Studio tersebut dan bagaimana cara build nya sehingga menjadi sebuah file android yang dapat dipasang di ponsel masing-masing siswa. Beberapa point penting yang dijelaskan serta dipraktekkan dalam kegiatan ini, yaitu pengenalan sistem operasi Android, pengenalan Android Studio, cara mendesain tampilan di Android Studio, dan bagaimana belajar koding java di Android Studio sehingga menghasilkan sebuah aplikasi android.
Kata kunci: aplikasi android, android studio, android
Abstract:Abstract: Stunting is a chronic nutritional condition in toddlers characterized by a Height-for-Age (HFA) measurement below the standard growth threshold, necessitating early detection to prevent long-term consequences.…
This study aims to classify toddler stunting status by comparing three machine learning methods: Random Forest (RF), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The dataset comprises 345 toddler records from Puskesmas Indramayu (2025), including weight, height, and nutritional status based on WFA, HFA, and WFH indicators. Preprocessing steps include data cleaning, StandardScaler normalization, One-Hot Encoding for categorical features, and splitting the training and testing data with a ratio of 80:20. The comparison results are that KNN achieved the best performance with an accuracy of 71.01%, a precision of 0.69, a recall of 0.69, and an F1 score of 0.67, while RF and SVM both had an accuracy of 69.57% with F1 scores of 0.67 and 0.68, respectively. Thus, KNN demonstrated superior effectiveness in classifying the stunting status of toddlers compared to RF and SVM on this dataset.
Keywords: KNN; Random Forest; SVM; Stunting; toddlers
Abstract: Stunting adalah kondisi gizi kronis pada balita yang ditandai dengan pengukuran Tinggi Badan menurut Usia (HFA) di bawah ambang batas pertumbuhan standar, sehingga memerlukan deteksi dini untuk mencegah konsekuensi jangka panjang. Penelitian ini bertujuan untuk mengklasfikasikan status stunting pada balita dengan membandingkan tiga metode pembelajaran mesin: Random Forest (RF), K-Nearest Neighbor (KNN), dan Support Vector Machine (SVM). Kumpulan data terdiri dari 345 catatan balita dari puskesmas indramayu (2025), termaksut brat badan, tinggi badan, dan status gizi berdasarkan indicator WFA, HFA, dan WFH. Langkah-langkah prapemrosesan meliputi pembersian data, normalisasi Stand-ardScaler, One-Hot Encoding untuk fitur kategirikal, serta pembagian data pelatihan dan pengujian dengan rasio 80:20. Hasil perbadingan adalah KNN mencapai kinerja terbaik dengan akurasi 71,01%, presisi 0,69, recall 0,69, dan skor F1 sebesar 0,67, RF dan SVM keduanya memiliki akurasi 69,57% dengan skor F1 masing-masing sebesar 0,67 dan 0,68. Dengan demikian, KNN menunjukkan keefektifan yang lebih unggul dalam mengklasifikasikan status stunting balita dibandingkan dengan RF dan SVM pada da-taset ini.
Kata kunci: KNN; random forest; SVM; Stunting; Balita
Abstract:Abstract: Stroke is one of the leading causes of death and disability in various parts of the world, including in Indonesia. Along with the development of digital technology, the use of Machine Learning in the health sector…
tor is growing, one of which is in an effort to predict the occurrence of stroke. This study aims to implement the Logistic Regression algorithm in predicting the likelihood of a person having a stroke based on data from the Brain Stroke dataset. The research process includes data preprocessing (missing value handling, normalization, and label encoding), dividing the data into 80% training data and 20% test data, as well as model training. The model was then evaluated using several measures such as accuracy, precision, recall, F1-score, and ROC-AUC, as well as a confusion matrix. The results of the study showed that Logistic Regression was able to provide stroke classification results with an accuracy of 82.4%, precision of 80.1%, recall of 78.6%, F1-score of 79.3%, and a ROC-AUC value of 0.87. Then, the model is integrated into applications that use Streamlit, so it can be used interactively to predict stroke risk in new data. The results of this study show that the combination of Machine Learning and web-based applications has the potential to support efforts to detect early stroke risk.
Keywords: logistic regression; machine learning; prediction; streamlit; stroke.
Abstrak: Stroke adalah salah satu penyebab utama kematian dan kecacatan di berbagai belahan dunia, termasuk di Indonesia. Seiring perkembangan teknologi digital, penggunaan Machine Learning dalam bidang kesehatan semakin berkembang, salah satunya dalam upaya memprediksi terjadinya penyakit stroke. Penelitian ini bertujuan untuk mengimplementasikan algoritma Logistic Regression dalam memprediksi kemungkinan seseorang mengalami stroke berdasarkan data dari dataset Brain Stroke. Proses penelitian meliputi preprocessing data (penanganan missing value, normalisasi, dan label encoding), membagi data menjadi 80% data latih dan 20% data uji, serta pelatihan model. Model kemudian dievaluasi menggunakan beberapa ukuran seperti akurasi, precision, recall, F1-score, dan ROC-AUC, serta confusion matrix. Hasil penelitian menunjukkan bahwa Logistic Regression mampu memberikan hasil klasifikasi penyakit stroke dengan akurasi sebesar 82,4%, precision 80,1%, recall 78,6%, F1-score 79,3%, dan nilai ROC-AUC sebesar 0,87. Kemudian, model tersebut diintegrasikan ke dalam aplikasi yang menggunakan Streamlit, sehingga dapat digunakan secara interaktif untuk memprediksi risiko stroke pada data baru. Hasil penelitian ini menunjukkan bahwa kombinasi Machine Learning dan aplikasi berbasis web berpotensi mendukung upaya deteksi dini risiko stroke.
Kata kunci: logistic regression; machine learning; prediksi; streamlit; stroke.
Abstract:Abstract: This study applies an integrated approach to optimize heart failure classification. The main objective is to address the challenge of class imbalance in medical datasets and to improve the accuracy, sensitivity,…
, and generalization of the classification model. The urgency of this issue is emphasized by statistics showing that cardiovascular diseases cause approximately 17.9 million deaths worldwide each year. Using a quantitative experimental approach, this study analyzes the "Heart Failure Prediction Dataset" from Kaggle, which consists of 918 records. The data were processed through normalization and encoding, followed by the application of SMOTE on the training set to balance class distribution. This step successfully increased model accuracy from 88.41% to 90.22% and minority class recall from 0.82 to 0.88. Furthermore, Bayesian Optimization was employed to refine the hyperparameters of SVM, resulting in a final model with an accuracy of 89.13% that demonstrated better generalization. This integrated approach significantly enhances the stability, sensitivity, and generalization of the model, making it a reliable tool for clinical decision support systems in predicting heart failure.
Keywords: bayesian optimization; heart failure; machine learning; SMOTE; SVM.
Abstrak: Penelitian ini menerapkan pendekatan terintegrasi untuk mengoptimalkan klasifikasi gagal jantung. Tujuan utama studi ini adalah untuk mengatasi tantangan ketidakseimbangan kelas dalam dataset medis dan meningkatkan akurasi, sensitivitas, serta generalisasi model klasifikasi. Urgensi ini ditegaskan oleh statistik yang menunjukkan bahwa penyakit kardiovaskular menyebabkan sekitar 17,9 juta kematian setiap tahun secara global. Menggunakan pendekatan eksperimental kuantitatif, penelitian ini menganalisis "Heart Failure Prediction Dataset" dari Kaggle, yang terdiri dari 918 catatan. Data diproses dengan normalisasi dan encoding, lalu SMOTE diterapkan pada data pelatihan untuk menyeimbangkan distribusi kelas. Langkah ini berhasil meningkatkan akurasi dari 88,41% menjadi 90,22% dan recall kelas minoritas dari 0,82 menjadi 0,88. Selanjutnya, Bayesian Optimization menyempurnakan hyperparameter SVM, menghasilkan model akhir dengan akurasi 89,13% yang menunjukkan generalisasi lebih baik. Pendekatan terintegrasi ini secara signifikan meningkatkan stabilitas, sensitivitas, dan generalisasi model. Hasil penelitian ini menjadikannya alat yang andal untuk sistem pendukung keputusan klinis dalam prediksi gagal jantung.
Kata kunci: bayesian optimization; gagal jantung; machine learning; SMOTE; SVM
Abstract:Abstract: Breast cancer is the leading cause of death for women globally, exacerbated by late detection. This study proposes a breast cancer risk prediction framework using XGBoost with SelectKBest feature selection. It…
aims to improve the accuracy and efficiency of early detection through exploratory data analysis, coding, SMOTE to address class imbalance, and feature selection (k=29). As a result, the XGBoost model achieved 98.1% accuracy, 98.1% recall, 98.1% f1-score, and 98.2% precision on test data, highlighting the importance of feature selection. These results are promising in patient prioritization (triage) for further examination, helping medical personnel identify high-risk patients, thus improving resource allocation efficiency. These findings validate SelectKBest and pave the way for the development of a machine learning-based clinical decision support system for breast cancer early detection workflows. This research contributes significantly to the application of machine learning to support early breast cancer detection.
Keywords: breast cancer; feature selection; machine learning; risk prediction; XGBOOST.
Abstrak: Kanker payudara menjadi penyebab utama kematian wanita global, diperparah deteksi yang terlambat. Penelitian ini mengusulkan kerangka prediksi risiko kanker payudara menggunakan XGBoost dengan seleksi fitur SelectKBest. Tujuannya meningkatkan akurasi dan efisiensi deteksi dini melalui analisis data eksploratif, pengkodean, SMOTE untuk mengatasi ketidakseimbangan kelas, dan seleksi fitur (k=29). Hasilnya, model XGBoost mencapai akurasi 98.1%, recall 98.1%, f1-score 98.1%, dan presisi 98.2% pada data uji, menyoroti pentingnya seleksi fitur. Hasil ini menjanjikan dalam penentuan prioritas pasien (triage) untuk pemeriksaan lebih lanjut, membantu tenaga medis mengidentifikasi pasien berisiko tinggi, sehingga meningkatkan efisiensi alokasi sumber daya. Temuan ini memvalidasi SelectKBest dan membuka jalan bagi pengembangan sistem pendukung keputusan klinis berbasis machine learning untuk alur kerja deteksi dini kanker payudara. Penelitian ini berkontribusi signifikan dalam penerapan machine learning untuk mendukung deteksi dini kanker payudara.
Kata kunci: kanker payudara; pembelajaran mesin; prediksi risiko ; seleksi fitur; XGBOOST.
Abstract:Abstract: Micro, small and medium enterprises (MSMEs), which are the main supporting of the Indonesian economy, need attention, because they can absorb labor and reduce the cost of unemployment by competing for jobs in the…
he formal sector. This research aims is to assist MSMEs Dechefdefinzs in marketing their products to prospective customers. The landing page method uses the waterfall methodology, by collecting data, analyzing data, making designs from an analyzed data, making coding, and testing the landing page and website. Developing this web-based application uses the HTML and PHP programming language with the Laravel framework which easy to apply at this time and in the long run. Creating a Dechefdefinzs landing page and website hopefuly can expand and spread widely its products in the society, such as traditional cakes, cake pans, bakery, rice menus and cookies. This website also makes it easier for customers to orders and get product information just by looking at the website without having to come to the location.
Keywords: landing page, MSMEs, waterfall, website.
Abstrak: Usaha mikro, kecil dan menengah (UMKM) yang merupakan penopang utama perekonomian Indonesia perlu mendapat perhatian, karena mereka dapat menyerap tenaga kerja dan mengurangi biaya pengangguran dengan bersaing mendapatkan pekerjaan di sektor formal. Penelitian ini bertujuan untuk membantu UMKM Dechefdefinzs dalam memasarkan produknya kepada calon konsumen. Metode yang digunaakan dalam pembuatan landing page dan website adalah metode waterall, dengan cara pengumpulan data, analisis data, pembuatan desain dari data yang dianalisis, pembuatan program, dan pengujian terhadap landing page dan website. Pengembangan aplikasi berbasis web ini menggunakan bahasa pemrograman HTML dan PHP dengan framework Laravel yang mudah diterapkan saat ini dan jangka panjang. Dengan dibuatnya landing page dan website Dechefdefinzs diharapkan dapat memperluas dan menyebarkan produk-produknya secara luas di masyarakat, seperti kue tradisional, kue loyang, roti, menu nasi dan kue kering. Website ini juga memudahkan pelanggan dalam memesan dan mendapatkan informasi produk hanya dengan melihat website tanpa harus datang ke lokasi.
Kata kunci: landing page, UMKM, waterfall, website.
Abstract:Abstract: crime mapping, namely by examining various spatial data factors that can be integrated to be able to produce a variety of information for security officers and the government in an effort to realize security in…
an area by utilizing geographic information systems by mapping, visualizing and analyzing crime incidents so that Various patterns and trends of spatial and temporal crime are generated using the main concept of cryptography, namely the encryption or encryption process where the plaintext encoding process becomes ciphertext and the decryption or description process, which is the process of returning the ciphertext to the original plaintext using the Electronic Code Book (ECB) algorithm and the ECB algorithm vigenere
Keywords: criminal patterns, geographic information systems, network system
Abstrak: pemetaan kriminalitas yaitu dengan mengkaji berbagai macam faktor data spasial yang dapat terintegrasi untuk dapat menghasilkan keanekaragaman informasi bagi aparat keamanan dan pemerintah dalam upaya mewujudkan kemanan di suatu area dengan memanfaatkan sistem informasi geografis dengan cara dilakukan memetakan, memvisualkan dan menganalisis insiden kriminalitas sehingga dihasilkan beragam pola maupun trend kriminalitas secara spasial temporal dengan menggunakan konsep utama dari kriptografi yaitu proses enkripsi atau enkription dimana proses penyandian plainteks menjadi cipherteks dan proses dekripsi atau description yaitu proses mengembalikan cipherteks menjadi plainteks semula menggunakan algoritma Elektronic Code Book (ECB) dan algoritma Vigenere.
Kata kunci: pola kriminalitas, sistem informasi geografis, sistem keamanan