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All Journal SAMUDERA Infotech Journal ITEj (Information Technology Engineering Journals) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL PENDIDIKAN TAMBUSAI JURIKOM (Jurnal Riset Komputer) Jurnal Sosial Humaniora Sigli Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Teknik Informatika (JUTIF) International Journal of Engineering, Science and Information Technology ARRUS Journal of Engineering and Technology Instal : Jurnal Komputer Jurnal Ilmu Komputer dan Informatika Journal of Renewable Energy, Electrical, and Computer Engineering TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Asrianda Asrianda
Teknik Informatika Universitas Malikussaleh
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Klasterisasi Data Stunting Pada Balita Di Puskesmas Xyz Dengan Menggunakan Metode Mixture Modelling Delianda, Anggun; Asrianda, Asrianda; Fitri, Zahratul
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8580

Abstract

This research is motivated by the high prevalence of stunting in Indonesia, reflecting nutritional imbalances in early childhood. To address this issue, an information technology approach is employed to identify at-risk infant groups. The analyzed data consists of anthropometric information, including height, weight, and age of infants, collected from the Peusangan Health Center. The applied method is the Gaussian Mixture Model (GMM) with the Expectation-Maximization algorithm to cluster the data into two groups: "Potential Stunting" and "Not Stunting." The research results indicate that several Posyandu and villages have notably high potential stunting rates, such as Posyandu Bungong Seulanga (141 infants) and Pante Gajah village (116 infants), with a higher prevalence among male infants (34.67%) and those aged 52–60 months (24.18%). Model evaluation using a confusion matrix on 1,465 data points showed a True Positive of 958 (65.36%), False Negative of 4 (0.27%), False Positive of 503 (34.33%), and True Negative of 0 (0%), with an accuracy of 65.36% and an error rate of 34.64%. However, a previous accuracy test on 1,665 data points only achieved 34.55%, indicating unsatisfactory individual prediction performance. In conclusion, Mixture Modelling is effective for clustering and identifying at-risk groups but lacks accuracy in individual predictions, with a bias toward the "Potential Stunting" class that requires improvement in future research.
Forecasting of Palm Oil CPO Production Results at PTPN III Batang Toru Plantation Using The Autoregressive Integrated Moving Average Method Utari, Sylva Putri; Asrianda, Asrianda; Retno, Sujacka
ITEJ (Information Technology Engineering Journals) Vol 10 No 2 (2025): December (In Progress)
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v10i2.254

Abstract

The increasing demand for palm oil as a raw material for food and energy industries has driven the need for accurate forecasting methods to optimize palm oil production management. This study aims to forecast Crude Palm Oil (CPO) production at PTPN III Batang Toru Plantation using the Autoregressive Integrated Moving Average (ARIMA) method. Monthly time series data from January 2020 to January 2024, including Fresh Fruit Bunches (FFB), loose fruit, and CPO yields, were analyzed to build the forecasting model. The Augmented Dickey-Fuller (ADF) test confirmed that the data is stationary without differencing. Based on the ACF, PACF, and white noise tests, the ARIMA(1,0,1) model was identified as the best fit. The forecasting results indicated a potential increase in CPO production from January 2025 to December 2026. However, alternative models like CPOF showed poor accuracy, with a high MAPE of 442.12%, suggesting the need for further model refinement. Despite limitations, the ARIMA method remains effective for short-term forecasting and supports data-driven decision-making in the plantation sector.
Stunting Risk Detection and Food Recommendation via Maternal Diagnosis Using the CF Method Kautsar, Al; Asrianda, Asrianda; Afrillia, Yesy
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9949

Abstract

Stunting in children often stems from maternal health conditions during pregnancy. This study aims to develop an intelligent rule-based IF–THEN system using the Certainty Factor method as a decision-support tool for the early detection of stunting risk factors. The detection is performed indirectly by diagnosing maternal health conditions during pregnancy. The knowledge base was constructed through interviews with obstetricians and nutritionists, encompassing 20 symptoms categorized into three primary conditions namely Chronic Energy Deficiency (CED), anemia, and preeclampsia. A total of 119 pregnant women from 11 villages in Muara Satu District participated as respondents. Implementation results revealed that among the respondents, 20 were identified with CED, 96 had anemia, and 3 exhibited signs of preeclampsia. Based on Certainty Factor (CF) calculations, the confidence distribution for CED included 2 respondents with CF <50%, 5 respondents within the 50–80% range, and 13 respondents with CF >80%. For anemia, 1 respondent had a CF value <50%, 4 fell within the 50–80% range, and 91 respondents had CF values above 80%. Meanwhile, for preeclampsia, all respondents exceeded the 50% CF threshold, with 1 respondent in the 50–80% range and 2 respondents >80%. In addition to diagnosis, the system provides tailored meal recommendations (breakfast, lunch, and dinner) based on the identified health conditions. Expert validation indicated a 90% agreement rate. However, results still require confirmation through clinical examinations and consultations to ensure medical accuracy.
Comparative Analysis of the C5.0 Algorithm and Other Machine Learning Models for Early Detection of Multi-Class Heart Disease Mardhatillah, Mardhatillah; Aidilof, Hafizh Al-Kautsar; Aidilof, Asrianda
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9753

Abstract

Cardiovascular diseases represent the leading cause of mortality worldwide, making accurate and early detection a critical factor for effective medical intervention and improved patient prognosis. While machine learning (ML) offers promising tools for predictive diagnostics, many existing studies rely on single-algorithm approaches or less-than-robust validation methods, thereby limiting the generalizability and real-world applicability of their findings.This study aims to conduct a rigorous, head-to-head comparative evaluation of multiple machine learning algorithms for the multi-class classification of heart disease, with the goal of identifying the most effective and reliable model for this complex clinical task.We utilized a private dataset comprising 300 patient medical records, each described by 11 clinically relevant features. To ensure a robust and unbiased evaluation, a stratified 5-fold cross-validation methodology was employed. Five widely-used classification algorithms were evaluated: Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), a C5.0-analog Decision Tree (DT), and Support Vector Machine (SVM). Model performance was assessed using standard metrics, including accuracy, precision, recall, and F1-score.The comparative analysis revealed that the Naïve Bayes algorithm delivered superior performance, achieving the highest mean accuracy of 43.33% (±4.22%). It also led in other key metrics with a mean precision of 43.40%, recall of 43.64%, and an F1-score of 41.26%. Other algorithms, such as Logistic Regression (40.67% accuracy) and Random Forest (39.33% accuracy), demonstrated competitive performance but were ultimately surpassed by the Naïve Bayes model in this specific multi-class classification context.This research underscores the critical importance of employing robust validation techniques and comprehensive comparative analyses to identify optimal models for clinical applications. The Naïve Bayes algorithm emerges as a strong candidate for developing a reliable clinical decision support system for the early differentiation of various heart conditions, providing a foundation for future data-driven diagnostic tools.
Perbandingan Multifaktor Evaluation dan Fuzzy Analytic Hierarchy Process pada Kualitas Biji Kopi Meiyanti, Rini; Asrianda, Asrianda; Azmi, Win
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 2 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i2.9741

Abstract

The development of information technology in the agricultural sector is crucial, including in determining coffee bean quality. This research implements a comparison of decision support systems (DSS) using the Multifactor Evaluation Process (MFEP) and Fuzzy Analytic Hierarchy Process (FAHP) methods to assess coffee bean quality based on moisture content, Trase, defects, color, aroma, and bean size. The results show that FAHP has an accuracy of 77%, higher than MFEP with an accuracy of 71%. Thus, FAHP is more effective in determining the farmers with the best coffee beans, thereby helping to improve the economic well-being of farmers and cooperatives.
Silat Perisai Diri sebagai Upaya Penguatan Karakter dan Kesehatan Masyarakat Asrianda, Asrianda; Wibowo, Patmono; Zulfadli, Zulfadli; ZA , Nasrul
Jurnal Malikussaleh Mengabdi Vol. 4 No. 1 (2025): Jurnal Malikussaleh Mengabdi, April 2025
Publisher : LPPM Universitas Malikussaleh

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Abstract

Silat Perisai Diri sebagai aliran Pencak Silat berfungsi sebagai seni bela diri, tetapi menjadi warisan budaya sarat nilai filosofis, spiritual, dan edukatif. Pengabdian masyarakat melalui pelatihan silat Perisai Diri dilaksanakan sebagai upaya pelestarian budaya sekaligus pembinaan generasi muda. Metode kegiatan dilakukan melalui pelatihan terstruktur dengan pendekatan integratif antara aspek fisik, mental, dan karakter. Hasil pelatihan menunjukkan peningkatan signifikan pada kebugaran fisik, ketangguhan mental, disiplin, rasa hormat, dan kemampuan teknis peserta. Kegiatan dilakukan berkontribusi pada penguatan identitas budaya, kohesi sosial, dan peningkatan motivasi remaja untuk terlibat dalam aktivitas positif, termasuk kompetisi bela diri. Dukungan masyarakat sekitar serta respons positif dari peserta menegaskan program dilakukan relevan dan berpotensi berkelanjutan. Silat Perisai Diri terbukti sebagai sarana bela diri, instrumen pendidikan karakter, kesehatan, dan pelestarian budaya dapat diintegrasikan dalam strategi pengembangan masyarakat berkelanjutan. Kkegiatan pengabdian dapat diperluas melalui sinergi dengan lembaga pendidikan formal maupun nonformal, silat Perisai Diri dapat terintegrasi ke dalam kurikulum ekstrakurikuler sekolah maupun program pembinaan pemuda di tingkat komunitas. Pendekatan dilakukan diharapkan tidak hanya memperkuat aspek fisik dan keterampilan bela diri, tetapi membentuk generasi yang memiliki ketangguhan karakter, kepedulian sosial, serta kecintaan terhadap budaya bangsa. Dukungan berkelanjutan pemerintah daerah, organisasi budaya, dan pihak swasta dapat memperkuat ekosistem pelatihan lebih luas, baik dalam bentuk fasilitas, pendanaan, maupun promosi kegiatan. Dengan adanya jejaring kolaborasi yang solid, pengembangan silat Perisai Diri sebagai warisan budaya sekaligus media pembentukan karakter semakin kokoh, memberi dampak nyata bagi ketahanan budaya nasional dan kualitas sumber daya manusia di era globalisasi.
Pandai Silat Tanpa Cedera: Kenaikan Tingkat Menuju Pengembangan Kelatnas Perisai Diri di Aceh Muhammad, Asrianda; Zulfadli, Zulfadli; Wibowo, Patmono
Jurnal Malikussaleh Mengabdi Vol. 1 No. 1 (2022): Jurnal Malikussaleh Mengabdi, April 2022
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v1i1.8394

Abstract

Berlatih silat sangatlah baik sekali, karena semua materi yang di ajarkan bersifat mengolah badan, keringat mengeluarkan kotoran-kotoran tubuh melalui liang pori-pori, mengeluarkan energi negatif dan memasukan energi positif. Energi positif ini yang membuat tubuh tetap fit, ringan, bertenaga, sehat, kuat dan energi cadangan yang terkumpul di dalam tubuh menjadikan daya tahan tetap kuat serta memiliki kekebalan terhadap penyakit.  Keberhasilan dari kegiatan ini dapat dilihat dari aspek pengetahuan dan ketrampilan pesilat Kelatnas Perisai Diri. Aspek pengetahuan dilihat dari hasil tes uji gerak yang diberikan sebelum dan sesudah pelaksanaan kegiatan. Sementara aspek ketrampilan dilihat dari kemampuan pesilat dalam mengulangi Kembali gerakan Teknik yang telah diberikan dan dapat Menyusun program latihan. Kelatnas Perissai Diri yang disusun secara sistematis berdasarkan pada pendekatan pola dan kemampuan pesilat dalam menguasai gerakan silat Perisai Diri. Pembelajaran gerakan teknik Perisai Diri diberikan secara urut dan terinci mulai dari pembukaan dan penutup, sehingga adanya keterkaitan antara latihan fisik dan rohani dengan prilaku pesilat Perisai Diri. 
Interaksi dalam Komunikasi Pelatih dan Anggota UKM Perisai Diri Universitas Malikussaleh Asrianda, Asrianda; Wibowo, Patmono; ZA, Nasrul; Zulfadli, Zulfadli
Jurnal Malikussaleh Mengabdi Vol. 2 No. 1 (2023): Jurnal Malikussaleh Mengabdi, April 2023
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v2i1.12624

Abstract

Saat latihan mnggunakan bahasa komunikasi seperti perintah, aba-aba, gerak teknik atau jurus yang disertai contoh gerakan oleh pelatih, kadangkala kritikan, larangan atau saran dalam evaluasi gerakan jurus. Perintah aba-aba yang disampaikan pelatih terasa hambar atau tidak bermakna kalua tidak diserta dengan contoh gerakan yang dipraktekkan pelatih. Jika, anggota salah dalam bergerak, pelatih harus segera mengkoreksi gerakan anggota didiknya sehingga kesalahan anggota didik dalam mengimplikasikan gerak semakin lama akan menjadi benar. Pelatih berkomunikasi dengan anggota UKM Perisai Diri untuk mencari tahu seberapa jauh ilmu yang telah diajarkan sesuai kurikulum dan materi standard Perisai Diri. Pelatih mengetahui kendali yang terjadi serta kesulitan yang dialami oleh anggota UKM silat Perisai Diri. Penyampaian dilakukan saat latihan sedang berlangsung, maupun saat latihan telah usai.
Arah Strategi Baru Komunikasi Internasional Diplomasi Pemerintah Baru Indonesia 2024 Hasan, Kamaruddin; Zulfadli, Zulfadli; Asrianda, Asrianda; Husna, Asmaul
Jurnal Pendidikan Tambusai Vol. 8 No. 3 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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Abstract

Transformasi digital mengubah paradigma hubungan internasional, mempengaruhi diplomasi, dan membuka peluang baru bagi diplomasi ekonomi. Pemerintah Indonesia di bawah kepemimpinan Presiden Prabowo Subianto dan Wakil Presiden Gibran Rakabuming menghadapi tantangan besar. Dalam memanfaatkan kemajuan teknologi untuk memperkuat posisi Indonesia di pasar global. Penelitian bertujuan untuk menganalisis hubungan antara diplomasi ekonomi dan diplomasi digital dalam konteks kebijakan luar negeri Indonesia. Dengan pendekatan kualitatif dan analisis deskriptif, penelitian ini menggali bagaimana diplomasi digital. Dapat memperkuat kerja sama ekonomi internasional, mendorong pertumbuhan ekonomi domestik, memperluas akses pasar global melalui teknologi digital. Hasil penelitian menunjukkan bahwa diplomasi digital memainkan peran krusial dalam meningkatkan daya saing Indonesia di dunia internasional. Untuk mencapainya, pemerintah harus memperkuat infrastruktur digital. Meningkatkan keamanan siber, serta mengembangkan kebijakan yang mendukung inovasi teknologi. Memberikan rekomendasi bagi pemerintah Indonesia untuk mengoptimalkan kebijakan diplomasi ekonomi berbasis digital guna menciptakan peluang ekonomi baru yang berkelanjutan.
Evaluating the Impact of Model Complexity on the Accuracy of ID3 and Modified ID3: A Case Study of the Max_Depth Parameter Asrianda, Asrianda; Mawengkang, Herman; Sihombing, Poltak; K. M. Nasution , Mahyuddin
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.2025.6.5.4864

Abstract

The complexity of decision tree structures has a direct impact on the generalization capability of classification algorithms. This study investigates and evaluates the performance of the classical ID3 algorithm and its modified version in the context of tree depth. The primary objective is to identify the optimal accuracy point and assess the algorithms' robustness against overfitting. Experiments were conducted across tree depths ranging from 1 to 20, with accuracy used as the main evaluation metric. The results indicate that both algorithms achieved peak performance at depth 3, followed by a notable decline. While the classical ID3 algorithm exhibited a gradual decrease in accuracy, the modified ID3 showed a sharp drop and performance stagnation between depths 11 and 20. These findings suggest that the modified ID3 algorithm enhances sensitivity in selecting informative attributes but also increases the risk of overfitting in the absence of structural regularization mechanisms. Therefore, the study recommends the implementation of regularization strategies such as pruning and cross-validation to mitigate performance degradation caused by model complexity. This research not only contributes to the theoretical understanding of how tree depth influences classification performance but also offers practical insights for developing adaptive, stable, and accurate decision tree-based classification systems.
Co-Authors Aidilof, Hafizh Al Kautsar Aidilof, Hafizh Al-Kausar Aidilof, Hafizh Al-Kautsar Alvesaldy, Alvin Amalia, Wildi Ar Razi Armaya, Devira Yuda Asmaul Husna Azmi, Win Damayanti, Ita Delianda, Anggun Dewi, Tursina Eva Darnila Fajriana, Fajriana Fyanda, Dwi Auji Gunarwan, Gunarwan Herman Fithra Herman Mawengkang Jange, Beno Jannah, Rauzatul K. M. Nasution , Mahyuddin Kamaruddin Hasan Kautsar, Al Lidya Rosnita Mardhatillah, Mardhatillah Maryana Muhammad Azhari Mutammimul Ula Nasrul ZA Nasrul ZA, Nasrul Panggabean, Pitra Rahmadani Poltak Sihombing Pratiwi, Dinda Putri, Sri Raihan Rachman, Aulia Rachmat Triandi Tjahjanto Rahayu, Lolia Lusiana Rahmat Hidayat Rahmat Hidayat Rahmat Triandi Rauzatul Jannah Razi, Ar Rini Meiyanti Risawandi, Risawandi Rozzi Kesuma Dinata Saputri, Rifa Andriani Siti Wahyuni Sujacka Retno Utari, Sylva Putri Wibowo, Patmono Yesy Afrillia ZA , Nasrul Zahratul Fitri, Zahratul Zulfadl, Zulfadl Zulfadli Zulfadli Zulfadli Zulfadli Zulfadli