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Ratu Mutiara Siregar
Institut Teknologi Sawit Indonesia
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Pemberdayaan Masyarakat Melalui Pelatihan Pembuatan Sabun Pada Ikatan Keluarga Besar Istri (IKBI) Pabrik Kelapa Sawit Rambutan PTPN IV Regional 1 Maisarah, Maisarah; Sri Wahyuna Saragih; Ratu Mutiara Siregar; Friska Anggraini Barus; Rahmad Dian; Budi Mulyara; Busrizal Faisal; Muhammad Akbar Syahbana Pane
SERVIRE: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2025): SERVIRE: Jurnal Pengabdian Kepada Masyarakat (April 2025)
Publisher : Indonesia Christian Religion Theologians Association and Widya Agape School of Theology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46362/servire.v5i1.285

Abstract

One of the products that are widely found and in demand in the community is soap. This product can be made as an added value from people's palm oil activities. Community service activities were carried out in the Desa Paya Bagas, Kecamatan Tebing Tinggi Kabupaten Serdang Bedagai, provinsi Sumatera Utara pada Ikatan Keluarga Besar Istri (IKBI) PT. Perkebunan Nusantara IV Regional 1 Rambutan Palm Oil Factory. The purpose of this activity is to provide knowledge, insight and technical skills in order to utilize palm oil to become a soap product that can be used for household needs or as a micro and small business effort. Community service initiatives that involve counseling, socialization, and education on empowering strategies through training in soap making demonstrations can be the answer. This community service activity is carried out consisting of a preparation stage consisting of a survey of completeness and preparation, socialization and education and implementation of community service activities by ITSI lecturers and students. The results of this community service activity are able to educate the community in soap making training. Salah satu produk yang banyak dijumpai dan diminati di masyarakat adalah sabun. Produk ini dapat dibuat sebagai addedd value dari kegiatan sawit rakyat. Kegiatan pengabdian masyarakat dilaksanakan di daerah Desa Paya Bagas, Kecamatan Tebing Tinggi, Kabupaten Serdang Bedagai, Provinsi Sumatera Utara pada Ikatan Keluarga Besar Istri (IKBI) PT. Perkebunan Nusantara IV Regional 1 Pabrik Kelapa Sawit Rambutan. Kegiatan ini bertujuan untuk memberikan pengetahuan, wawasan, serta keterampilan teknis kepada masyarakat agar mampu mengolah kelapa sawit menjadi produk sabun yang layak digunakan untuk keperluan rumah tangga maupun sebagai modal usaha mikro dan kecil. Solusi yang dapat diberikan yaitu kegiatan pengabdian masyarakat berupa metode penyuluhan, sosialisasi dan edukasi terkait teknis pemberdayaan melalui pelatihan demonstrasi pembuatan sabun. Kegiatan pengabdian masyarakat dilaksanakan terdiri dari tahap persiapan yang terdiri atas survei kelengkapan dan preparasi, sosialisasi serta edukasi dan kegiatan pengabdian kepada masyarakat yang dilakukan oleh civitas akademik Institut Teknologi Sawit Indonesia (ITSI) yaitu dosen dan mahasiswa ITSI. Hasil dari kegiatan pengabdian masyarakat mampu mengedukasi masyarakat dalam pelatihan pembuatan sabun.
IoT Oxymeter Starter Prototype As An Employee Health Monitoring Tool In The Blynk Integrated Palm Industry Muhammad Akbar Syahbana Pane; Rahmad Dian; Ratu Mutiara Siregar; Balqis Nurmauli Damanik; Asnita Yani; Alisarjuni Padang; Khairul Saleh
Journal of Technology Informatics and Engineering Vol. 3 No. 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.158

Abstract

One of the main challenges faced by workers in the palm oil industry is routine health monitoring. Therefore, innovation is needed in the form of health monitoring tools that can facilitate and increase the efficiency of employee health monitoring. The Internet of Things (IoT) has become an increasingly popular solution to overcome these challenges. The use of this technology is expected to increase employee health resilience, detect potential health problems early, and provide a quick response to health conditions that require medical attention.
ENHANCING NETWORK PERFORMANCE LOAD BALANCING IN CYBER CAFE NETWORKS WITH DIJKSTRA ALGORITHM ON MIKROTIK Prayogi, Andi; Kan, Phak Len Al Eh; Pane, Muhammad Akbar Syahbana; Dian, Rahmad; Siregar, Ratu Mutiara; Simbolon, Hasanal Fachri Satia
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1644

Abstract

The internet has become a fundamental necessity in various activities today. Stream Cyber Cafe, as an internet service provider, faces the challenge of maintaining network quality so that users can comfortably engage in activities such as gaming, streaming services, and social media. Load balancing, utilizing multiple internet sources from various ISPs, becomes a solution to enhance network efficiency and responsiveness. This research focuses on implementing the Dijkstra algorithm on MikroTik devices to determine the shortest path based on DNS server latency from various internet service providers (ISP). The main steps include configuring MikroTik devices, analyzing latency connections to DNS servers, and employing the Dijkstra algorithm. The Dijkstra algorithm, utilizing a Greedy approach, considers the minimum weight from the starting node to other nodes. Testing using the "PING" command provides information on the number of hops or steps required to reach each DNS server. Dijkstra adapts the shortest path based on latency, yielding optimal load balancing efficiency. Configuring MikroTik features, such as Firewall Mangle, Routing Table, and Routing Gateway, supports the functionality of the Dijkstra algorithm. Test results show that each ISP has a different shortest path to DNS servers, and the Dijkstra algorithm can determine the shortest path by considering time or latency factors. Although the author acknowledges some technical challenges during implementation, the proposed solution successfully overcomes these challenges. Thus, the use of the Dijkstra algorithm on MikroTik proves its effectiveness in enhancing the performance and reliability of the network in the Stream Cyber Cafe environment.
INOVASI PENGERING MEKANIS KOPI BERBASIS ARDUINO UNO PADA WILAYAH PETANI KOPI KECAMATAN PEMATANG SIDAMANIK KABUPATEN SIMALUNGUN Dian, Rahmad; Mulyara, Budi; Siregar, Ratu Mutiara; Maisarah, Maisarah; Dibisono, Muhammad Yusuf; Guntoro, Guntoro
Jurnal Pengabdian Masyarakat: Pemberdayaan, Inovasi dan Perubahan Vol 4, No 6 (2024): JPM: Pemberdayaan, Inovasi dan Perubahan
Publisher : Penerbit Widina, Widina Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59818/jpm.v4i6.929

Abstract

Coffee as one of Indonesia's plantation commodities that has very good development potential, considering that coffee consumption in Indonesia is still very high. Currently, the problem that occurs in Simalungun Regency is the conventional drying technology which is at risk of inconsistency in quality and taste so it needs to be fixed and given a solution. The partner team is the Mitra Sejati Jaya Cooperative, where community service activities are carried out in the Sait Buttu area, Pematang Sidamanik District, Simalungun Regency, North Sumatra which is one of the locations for planting Arabica coffee. The purpose of this activity is to create intelligent IT-based appropriate tools and technologies, namely the ARDUINO UNO Smart Sweetener as a solution to the problems of partners and coffee processing community groups, then improve coffee farmers in supporting improvements in the quality of Arabica coffee taste through efficient, portable, and environmentally friendly smart drying technology. The solution that can be provided is in the form of community service activities carried out by a team of lecturers and students from the Institut Teknologi Sawit Indonesia (ITSI) in the form of extension methods, socialization and education related to the technical innovation of the tool called the ARDUINO UNO Smart Sweetener. This community service activity was carried out for ±60 days consisting of the preparation stage consisting of a survey of completeness and preparation, assembly and finishing and pre-test, socialization and education and implementation of community service activities by ITSI lecturers and students. The activity was attended by people who are members of the Coffee Farmers, the Mitra Sejati Jaya cooperative partner team, local residents, lecturers from ITSI and supported by ITSI students. The results of this community service activity were able to educate the community in the Innovation of Mechanical Coffee Dryers.ABSTRAKKopi sebagai salah satu komoditas Perkebunan Indonesia yang memiliki potensi pengembangan masih sangat baik, mengingat konsumsi kopi di Indonesia masih sangat tinggi. Saat ini, permasalahan yang terjadi di Kabupaten Simalungun ialah teknologi pengeringan yang masih konvensional yang beresiko terhadap inkonsistensi mutu dan cita rasa sehingga perlu dibenahi dan diberi solusi. Tim mitra adalah Koperasi Mitra Sejati Jaya, dimana kegiatan pengabdian masyarakat dilaksanakan di daerah Sait Buttu, Kecamatan Pematang Sidamanik, Kabupaten Simalungun, Sumatera Utara yang merupakan salah satu lokasi penanaman kopi arabika. Tujuan dari kegiatan ini dapat menciptakan alat dan teknologi tepat guna yang cerdas berbasis IT yaitu Pemanis Pintar ARDUINO UNO sebagai solusi atas permasalahan mitra dan kelompok masyarakat pengolah kopi, kemudian meningkatkan petani kopi dalam mendukung perbaikan mutu cita rasa kopi arabika melalui teknologi pengeringan pintar yang efisien, portable, dan ramah lingkungan. Solusi yang dapat diberikan yaitu berupa kegiatan pengabdian masyarakat yang dilakukan oleh tim dosen dan mahasiswa Institut Teknologi Sawit Indonesia (ITSI) berupa metode penyuluhan, sosialisasi dan edukasi terkait teknis inovasi alat yang disebut Pemanis Pintar ARDUINO UNO. Kegiatan pengabdian masyarakat ini dilaksanakan selama ±60 hari yang terdiri dari tahap persiapan yang terdiri atas survei kelengkapan dan preparasi, perakitan dan finishing serta pra uji, sosialisasi dan edukasi serta pelaksanaan kegiatan pengabdian kepada masyarakat oleh dosen serta mahasiswa ITSI. Kegiatan dihadiri oleh orang yang tergabung dalam Petani Kopi, Tim mitra koperasi Mitra Sejati Jaya, warga setempat, dosen dari ITSI serta didukung oleh mahasiswa ITSI. Hasil dari kegiatan pengabdian masyarakat ini mampu mengedukasi masyarakat dalam Inovasi Alat Pengering Mekanis Kopi.
PERSEPSI MASYARAKAT MENGENAI ISU PENGHAPUSAN KELAS BPJS MENGGUNAKAN K-NEAREST NEIGHBOR Rahmamnsyah, Eka Patma; Siregar, Ratu Mutiara
Jurnal Edukasi Citra Olahraga Vol. 6 No. 1 (2026): Jurnal Edukasi Citra Olahraga
Publisher : STKIP Citra Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38048/jor.v6i1.6588

Abstract

Penelitian ini dilatarbelakangi oleh perubahan kebijakan BPJS Kesehatan terkait penghapusan kelas layanan dan penerapan KRIS yang menimbulkan beragam respons publik di media sosial, khususnya YouTube. Penelitian bertujuan menganalisis persepsi masyarakat terhadap kebijakan tersebut serta mengevaluasi efektivitas algoritma K-Nearest Neighbor (KNN) dalam klasifikasi sentimen. Metode penelitian dilakukan melalui studi literatur, pengumpulan data komentar YouTube dari kanal Liputan6 dan CNN menggunakan Netlytic, serta praolahan data yang meliputi cleansing, case folding, tokenisasi, stopword removal, dan stemming. Dataset yang dianalisis berjumlah 2.200 komentar, kemudian diklasifikasikan ke dalam sentimen positif, negatif, dan netral menggunakan KNN. Hasil penelitian menunjukkan bahwa komentar masyarakat didominasi sentimen negatif, terutama terkait kekhawatiran kenaikan iuran, ketidakadilan layanan, dan ketidakjelasan prosedur transisi BPJS ke KRIS. Evaluasi model KNN menunjukkan precision kelas negatif sebesar 1,00, tetapi recall kelas negatif rendah, yaitu 0,07, dengan F1-score keseluruhan 0,19, sehingga performa model belum optimal. Kesimpulannya, analisis sentimen berbasis KNN dapat memberikan gambaran awal persepsi publik terhadap kebijakan BPJS, tetapi masih memerlukan penyempurnaan pada representasi fitur dan parameter model agar hasil klasifikasi lebih akurat.
FROM ONTOLOGY TO INFERENCE: A COMPUTATIONAL PHILOSOPHICAL FRAMEWORK OF IoT-ML FOR READING THE MATURITY AND VOLUME OF PALM OIL Siregar, Ratu Mutiara; Prayogi, Andi; Nasution, Mahyuddin KM
Jurnal Agro Fabrica Vol. 7 No. 2 (2025): Desember 2025
Publisher : Institut Teknologi Sawit Indonesia (ITSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47199/jaf.v7i2.403

Abstract

The timing of harvesting in oil palm plantations necessitates objective and rapid ripeness assessment, coupled with an estimation of extractable oil volume. This paper presents a philosophical-computational framework with an end-to-end architecture integrating Internet of Things (IoT) sensors and machine learning (ML) for the classification of fresh fruit bunch (FFB) ripeness levels and oil volume regression. The approach rests on explicit ontological and epistemological foundations, operationalizes latent targets through standardized field protocols, and implements reproducible ML practices. We delineate a multimodal pipeline (RGB imagery + environmental sensors + weight), a late fusion modeling strategy (CNN embeddings + tabular features), and an evaluation design that emphasizes cross-block generalization, model explainability, and drift monitoring. Performance targets include an F1-macro ≥ 0.88 for ripeness classification and a Mean Absolute Error (MAE) ≤ 4 ml/kg for oil volume regression on out-of-block data. Discussions also encompass the ethics and axiology of transparency, data governance, and economic impacts, along with future directions such as federated learning and portable hyperspectral integration.
Implementasi Sistem Pendukung Keputusan Menggunakan Algoritma MOORA untuk Pemilihan Jenis Bibit Cabai Unggul Al Akbar, Abdussalam; Yasin, Alimuddin; Alex Rizky Saputra; Sepriano; Siregar, Ratu Mutiara; Budy Satria; Elfitra
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3464

Abstract

Cultivating chili plants is a business opportunity that has quite a large income. However, many farmers still use traditional concepts in determining which seeds to plant, such as trying out chili seeds without carrying out in-depth analysis or observation. A decision support system (DSS) is a system that is capable of providing decision recommendations using several criteria determined through method processes in the decision making system, namely ARAS, SAW, MOORA, AHP and others. The MOORA method is useful for separating the subjective part of an evaluation process into a decision weight criterion with several decision making attributes. And also the level of selectivity of this method is very good because it can determine objectives from conflicting criteria. Where the criteria can be profitable (benefit) or unprofitable (cost). Based on the results obtained after using the MOORA calculation method, there are 4 types of superior seed varieties that can be recommended for farmers, namely Taro Chili Seeds = 0.2875; Indrapura Chili Seeds = 0.2595 ; Lado Chili Seeds = 0.2490 ; Chili Seeds TM = 0.2154. By creating this decision support system, it is hoped that farmers will be able to use it as a reference in selecting superior chili seeds and be able to get maximum harvest results and increase commodity income for chili farmers.
IMPLEMENTASI METODE DEMPSTER SHAFER PADA SISTEM PAKAR UNTUK MENDIAGNOSIS PENYAKIT TROPIS Siregar, Ratu Mutiara
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4071

Abstract

Tropical diseases are various infectious diseases that occur frequently in tropical and subtropical regions. These diseases can be caused by infections from viruses, bacteria, fungi, and parasites, and are usually transmitted through vectors or direct contact. In Indonesia, some common tropical diseases include dengue fever, malaria, elephantiasis, tuberculosis, worm infections, and fungal infections. Understanding tropical diseases is crucial to finding ways to diagnose and treat them. Therefore, one method that can be used in this research is the expert system based on the Dempster-Shafer method. This method can be used to diagnose tropical diseases with high accuracy, thus enabling more effective treatment and prevention. The expert system using the Dempster-Shafer method is designed using symptom data of tropical diseases collected from an expert. The result obtained from this research is a system that functions to solve problems and provide information about diseases along with symptoms experienced by the user. By using a web-based system as access for the public, it becomes easier for them to obtain accurate results and information.
Association of single nucleotide polymorphism and phenotype in type 2 of diabetes mellitus using Support Vector Regression and Genetic Algorithm Siregar, Ratu Mutiara; Kusuma, Wisnu Ananta; Annisa, Annisa
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1283.194-202

Abstract

Precision Medicine is used to improve proper health care and patients' quality of life, one of which is diabetes. Diabetes Mellitus (DM) is a multifactorial and heterogeneous group of disorders characterized by deficiency or failure to maintain normal glucose homeostasis. About 90% of all DM patients are Type 2 Diabetes Mellitus (T2DM). Biological characteristics and genetic information of T2DM disease were obtained by looking for associations in Single Nucleotide Polymorphism (SNP) which allows for determining the relationship between phenotypic and genotypic information and identifying genes associated with T2DM disease. This research focuses on the Support Vector Regression method and Genetic Algorithm to obtain SNPs that have previously calculated the correlation value using Spearman's rank correlation. Then do association mapping on the SNP results from the SVR-GA selection and check pastasis interaction. The results produced 14 SNP importance. Evaluation of the model using the mean absolute error (MAE) obtained is 0.02807. If the value of MAE is close to zero, then a model can be accepted. The genes generated from the association can be used to assist other researchers in finding the right treatment for T2DM patients according to their genetic profile.
SMOTE-Based Comparative Analysis of Machine Learning Models for Stroke Risk Prediction Using Imbalanced Healthcare Data Siregar, Ratu Mutiara; Satria, Budy; Fadilah, Sandi; Mayola, Liga; Safira, Silky
ILKOM Jurnal Ilmiah Vol 18, No 1 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i1.3161.180-194

Abstract

Stroke remains one of the leading causes of mortality and long-term disability worldwide, with a significant burden in Indonesia. Early detection is crucial, as up to 90% of stroke cases are potentially preventable through timely intervention. However, predictive modeling for stroke risk is often challenged by imbalanced datasets, where non-stroke cases significantly outnumber stroke cases, potentially biasing classification models. This study aims to perform a systematic comparative evaluation of six machine learning algorithms Logistic Regression, Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) for stroke risk prediction under imbalanced data conditions. The dataset consists of 5,110 patient records with 11 health-related features obtained from a publicly available healthcare dataset. Data preprocessing included anomaly removal, categorical encoding, feature scaling, and class balancing using the Synthetic Minority Oversampling Technique (SMOTE). Model evaluation was conducted using 5-fold cross-validation and assessed through accuracy, precision, recall, and F1-score metrics. The experimental results demonstrate that ensemble-based models outperform single classifiers. Random Forest achieved the highest mean accuracy of 97.12% (±0.42) with an F1-score of 0.96, followed closely by XGBoost with 96.85% (±0.51). Both models also exhibited superior recall performance, indicating improved minority class detection. The novelty of this study lies in the systematic evaluation of multiple machine learning models using SMOTE-based balancing and cross-validation on publicly available healthcare data, providing robust comparative insights for imbalanced medical classification problems.
Co-Authors Abdussalam Al Akbar Alex Rizky Saputra Ali Ikhwan Alimuddin Yasin Alisarjuni Padang Aly, Moustafa H. Andi Prayogi Andi Prayogi Annisa Annisa Ardila Asnita Yani Awal, Elsa Elvira Balqis Nurmauli Damanik Busrizal Faisal Elfitra Erin Triani Sipayung Fadilah, Sandi Fajar Maulana . Ferdy Hardiansyah Friska Anggraini Barus Guntoro, Guntoro Kan, Phak Len Al Eh Khairul Saleh Liga Mayola Mahyuddin K. M Nasution Maisarah Maisarah Maisarah, Maisarah Makhrani Sari Ginting Maudy Hellena Harlyn Muhammad Akbar Syahbana Pane Muhammad Yusuf Dibisono Mulyara, Budi Navea, Roy Francis Nurliana Phaklen Ehkan Prayogi, Andi Rahmad Dian Rahmad Dian Rahmad Dian Rahmamnsyah, Eka Patma Ritna Wahyuni Ritna Wahyuni Rizky Delianngi safira, silky Sari, Yessi Ratna Sepriano Sepriano Simbolon, Hasanal Fachri Satia Sri Wahyuna Saragih Tuty Ningsih Wisnu Ananta Kusuma Yasir, Amru