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All Journal Ihsan: Jurnal Pengabdian Masyarakat Airlangga Journal of Innovation Management Instal : Jurnal Komputer Jurnal ICT : Information and Communication Technologies Portal Riset dan Inovasi Sistem Perangkat Lunak
Hutagalung, Fatma Sari
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Library & Information Science Mechanical Engineering Social Sciences

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Implementasi Metode Weight Product untuk Menentukan Jurusan IPA atau IPS di Sekolah Muhammadiyah 18 Sunggal Hutagalung, Fatma Sari; Ramadhani, Fanny; Sari, Indah Purnama
IHSAN : JURNAL PENGABDIAN MASYARAKAT Vol 3, No 2 (2021): Ihsan: Jurnal Pengabdian Masyarakat (Oktober)
Publisher : University of Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ihsan.v3i2.7650

Abstract

Ada beberapa metode yang dapat digunakan untuk membantu dalam menentukan jurusan. Salah satunya adalah metode Weight Product. Metode Weighted Product adalah salah satu penyelesaian pada sistem pendukung keputusan. Metode ini mengevaluasi beberapa alternatif terhadap sekumpulan atribut/kriteria, dimana setiap atribut tidak bergantung antara satu dengan lainnya. Dalam buku kusumadewi yang diterbitkan pada tahun 2006 disebutkan bahwa metode WP menggunakan teknik perkalian untuk rating atribut. dimana rating atribut harus dipangkatkan dengan bobot atribut yang bersangkutan.
Implementasi E-Monitoring Aktivitas Siswa Pada SMKN 5 dan SMKS 2 Medan Putri Berbasis Web Ramadhani, Fanny; Al-Khowarizmi, Al-Khowarizmi; Hutagalung, Fatma Sari
IHSAN : JURNAL PENGABDIAN MASYARAKAT Vol 3, No 2 (2021): Ihsan: Jurnal Pengabdian Masyarakat (Oktober)
Publisher : University of Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ihsan.v3i2.7571

Abstract

SMK Negeri 5 Medan is one of the vocational high schools in the city of Medan. One of the visions and missions of this school is to increase discipline in complying with existing regulations. One of the things that must be disciplined is attendance, timely collection of assignments and payment of tuition fees that must be on time. But in reality there are still some students who do not attend school because the student withdraws so that parents feel worried about the condition of their children at school, whether they actually go to school or not and parents also cannot know the progress of how many grades their children have earned in general directly because of busy work, there are even students who cannot maintain the mandate to pay tuition fees that have been deposited by their parents. Therefore, a system is needed to monitor student activities at school. Monitoring activities are the main activities in the world of education. However, these activities cannot be carried out optimally. Parents still find it difficult to monitor their children's learning activities at school. Notification of student achievement (grades) is only made at the time of receipt of the final report. Therefore we need a system that facilitates the process of monitoring and assessing students, both for teachers and parents to overcome these problems. The purpose of this research is to develop a student monitoring system (E-Monitoring). The method used to develop this system is data collection, hardware and software analysis, system design and analysis as well as system implementation and testing. The result of this study is a system that can assist teachers in managing grades, recap student errors, and facilitate parents to monitor and obtain information about their children's learning activities clearly and in real time.
Implementation Of The Weighted Product (Wp) Method In Selecting The Best Pesticide (Case Study: Kud Subur Makmur Village Teluk Panji Iv) Sulistiani, Nur; Hutagalung, Fatma Sari
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.214

Abstract

Pesticides are materials that are widely used in various sectors, especially in agriculture, plantations, forestry, fisheries, and food agriculture. The use of pesticides in the agricultural sector aims to eliminate nuisance plants, fungi, insects, rodents, and other organisms so that it has an impact on increasing agricultural production. This study aims to apply the Weighted Product (WP) method in determining the best pesticide in KUD Subur Makmur, Teluk Panji IV Village. The Weighted Product method is used because of its ability to handle many criteria relevant to the selection of pesticides, such as price, package size, type of pest eradicated and durability. Data was collected through an interview with one of the employees as well as through literature study and document analysis related to available pesticides. Each criterion is then given a weight according to its level of importance based on the results of the interview. The results show that the Weighted Product method is effective in providing optimal pesticide selection according to local needs and conditions. The implementation of this method can help in making better decisions regarding the use of pesticides, so as to increase agricultural productivity and sustainability. The impact obtained from this research is that it can increase crop yields in a sustainable manner and reduce losses due to ineffective or harmful pesticide use.
Implementasi Algoritma Analytic Hierarchy Process (AHP) Pada Mesin Penetasan Telur Ayam Berbasis Internet of Things (IoT) Ismana, Suci Indah; Hutagalung, Fatma Sari
Portal Riset dan Inovasi Sistem Perangkat Lunak Vol. 3 No. 2 (2025): Artikel Penelitian
Publisher : SoraTekno Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59696/prinsip.v3i2.111

Abstract

Penetasan telur ayam merupakan proses yang membutuhkan pengaturan suhu, kelembapan, rotasi telur, dan waktu secara presisi agar menghasilkan tingkat keberhasilan yang tinggi. Penelitian ini bertujuan untuk mengimplementasikan algoritma Analytic Hierarchy Process (AHP) dalam sistem mesin penetasan telur ayam berbasis Internet of Things (IoT). AHP digunakan untuk menentukan prioritas optimal dalam pengaturan parameter berdasarkan kriteria utama seperti suhu, kelembapan, dan rotasi telur. Sistem terdiri atas perangkat keras berupa sensor suhu dan kelembapan yang terhubung dengan modul IoT untuk memonitor dan mengontrol kondisi mesin secara real-time. Data dari sensor dikirim ke platform web, di mana algoritma AHP diterapkan untuk menghasilkan rekomendasi pengaturan optimal. Pengujian dilakukan pada lima butir telur ayam dengan berbagai skenario lingkungan, seperti kondisi suhu rendah, kelembapan tinggi, dan rotasi telur tidak merata. Sistem secara adaptif menyesuaikan pengaturan untuk menjaga kestabilan lingkungan penetasan. Sebagai perbandingan, metode penetasan konvensional menggunakan induk ayam cenderung tidak stabil karena suhu dan kelembapan bergantung pada kondisi alam, serta proses penetasan memakan waktu hingga ±21 hari. Selain itu, induk ayam sering meninggalkan sarang untuk mencari makan dan minum, yang menyebabkan turunnya peluang menetas. Dengan mesin tetas berbasis AHP-IoT, telur tetap berada dalam kondisi optimal secara terus-menerus sehingga waktu penetasan dapat dipercepat menjadi ±19 hari. Hasil implementasi menunjukkan tingkat keberhasilan penetasan mencapai 80%–90%, jauh lebih tinggi dibandingkan metode konvensional yang hanya 50%–60%. Integrasi teknologi IoT dan algoritma AHP memungkinkan pengguna untuk memantau dan mengendalikan proses penetasan secara jarak jauh melalui web. Penelitian ini memberikan kontribusi sebagai solusi inovatif yang dapat meningkatkan efisiensi dan produktivitas dalam industri peternakan.
Probabilistic Markov Chain Modeling for Predicting User Behavior Patterns in Digital Systems Using Data Mining Nazry, Hevlie Winda; Antoro, Budi; Hutagalung, Fatma Sari
Airlangga Journal of Innovation Management Vol. 7 No. 1 (2026): Airlangga Journal of Innovation Management
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/ajim.v7i1.87129

Abstract

This study addresses the challenge of transforming sequential clickstream data into accurate yet interpretable behavioral predictions for operational decision-making in digital systems. While complex machine learning models often achieve high accuracy, their limited transparency hinders practical adoption. Therefore, this research aims to develop and evaluate a probabilistic Markov-based framework for predicting users’ next actions while maintaining interpretability. A quantitative data mining approach is applied to e-commerce clickstream data collected in January 2026. User interactions are sessionized and mapped into eight discrete behavioral states. The study compares a frequency-based baseline with first-order, second-order, and variable-order Markov models using back-off and Laplace/Dirichlet smoothing. Model evaluation employs a time-based train–test split with Accuracy@1, Mean Reciprocal Rank (MRR), and log-loss as performance metrics. Results indicate that the variable-order Markov model achieves the best performance, improving Accuracy@1 from 0.231 to 0.331, increasing MRR from 0.318 to 0.437, and reducing log-loss from 1.74 to 1.39. The findings demonstrate that Markov-based models offer an effective balance between predictive accuracy and interpretability, enabling the identification of dominant transitions, drop-off points, and conversion bottlenecks. Future research may extend this framework with time-aware or hidden-state models to capture latent user intent, while managerial implications include data-driven system optimization, recommendation enhancement, and user retention strategies.
Classification of Oil Palm Fruit Ripeness Levels Based on Digital Image Feature Extraction Using the Catboost Algorithm Ardhini, Setya Eka; Hutagalung, Fatma Sari
Jurnal ICT : Information and Communication Technologies Vol. 17 No. 1 (2026): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v17i1.327

Abstract

Determining the ripeness level of oil palm fruit is essential for improving palm oil production quality. Manual assessment methods are often subjective and inconsistent because they rely on workers’ experience and environmental conditions. Therefore, this study proposes an automatic image-based classification system using the CatBoost algorithm. The novelty of this research lies in the integration of CatBoost with RGB color and Gray Level Co-occurrence Matrix (GLCM) texture feature extraction for multiclass oil palm fruit ripeness classification. The dataset consisted of 1000 images categorized into four classes: unripe, under-ripe, ripe, and overripe. The research stages included image preprocessing, feature extraction, classification, and web-based implementation using the Flask framework. Experimental results showed that the proposed system achieved high performance based on accuracy, precision, recall, and F1-score metrics, demonstrating the effectiveness of CatBoost in classifying oil palm fruit ripeness while reducing overfitting. The developed web-based system can assist plantation workers in determining fruit ripeness automatically, objectively, and efficiently, thereb
Co-Authors Al Khowarizmi Antoro, Budi Ardhini, Setya Eka Hapzi Ali Hevlie Winda Nazry S Ismana, Suci Indah Ramadhani, Fanny Sulistiani, Nur