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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH International Journal Software Engineering and Computer Science (IJSECS) International Journal of Management Science and Information Technology (IJMSIT)
Muhammad Iqbal
Universitas Royal
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Analysis of Decision Support System to Determine Toddlers Eligible for Additional Food at Posyandu in Perkebunan Tanah Datar Village Using Profile Matching Method Revina Salsabila; Nurul Rahmadani; Muhammad Iqbal
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6738

Abstract

The determination of toddlers eligible for the Supplementary Feeding Program (PMT) at the Integrated Health Post in Perkebunan Tanah Datar Village is still conducted manually, which can lead to subjectivity and inaccurate targeting of assistance. This study aims to develop a Decision Support System using the Profile Matching method to determine priority PMT recipients in a more objective and systematic manner. The assessment compares the actual condition of toddlers with an ideal profile by calculating GAP values across several criteria, including stunting status, nutritional status, parents’ income, and mother’s education level. These criteria are processed using Core Factor (60%) and Secondary Factor (40%) weighting to generate priority rankings. The system evaluation was conducted using seven toddler data samples, producing ranking results in which toddler B6 obtained the highest priority score of 4.5. The results indicate that the proposed method is able to generate consistent eligibility rankings and support a more transparent and measurable decision-making process compared to manual selection. By automating the calculation of GAP values and weighting factors, the system reduces subjectivity and improves the efficiency and accuracy of PMT recipient determination. However, this study is limited by the relatively small dataset and its implementation in a single Posyandu location. Future research may involve larger datasets and additional evaluation criteria to improve the robustness and applicability of the model in broader community health service settings.
SCM Prototype Design Using Economic Order Quantity (EOQ) Method to Improve Decor Material Inventory Performance Dina Triana; Muhammad Iqbal; Rohminatin Rohminatin
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.7349

Abstract

The decoration industry is experiencing rapid growth along with the increasing public demand for decoration services for homes, cafes, commercial spaces, and various other aesthetic needs. This growth requires companies to have an effective inventory management system to ensure the availability of decorative materials and ensure optimal operational processes. However, actual conditions at Rahani Homedecor show that inventory management is still carried out manually, resulting in various problems, such as delays in stock recording, difficulties in monitoring stock availability, suboptimal procurement processes, and a high risk of excess or shortage of inventory. This study aims to design a Supply Chain Management (SCM) prototype using the Economic Order Quantity (EOQ) method to improve the performance of decorative material inventory management. The research method used is a descriptive qualitative approach through observation, interviews, and analysis of ongoing business processes. The EOQ method is applied to determine the optimal order quantity so that the procurement process can be carried out in a more planned and economical manner, while the SCM concept is used to integrate the flow of information between inventory, suppliers, and the purchasing process. The results show that the EOQ-based SCM prototype can help inventory management become more structured, organized, and easily controlled. The system developed facilitates user management of product data, supplier data, and purchasing transactions in a computerized manner, resulting in faster and more efficient work. Furthermore, the application of the EOQ method helps companies determine optimal order quantities based on inventory needs. Based on these results, it can be concluded that the application of SCM with the EOQ method can improve the effectiveness and efficiency of decorative material inventory management and support the smooth operation of the company.
SENTIMENT ANALYSIS OF PUBLIC COMMENTS ON THE FREE NUTRITIOUS MEAL PROGRAM USING A RULE-BASED APPROACH Muhammad Iqbal; Mustika Fitri Larasati Sibuea; Indra Ramadona Harahap
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3994

Abstract

Abstract: The Free Nutritious Meal Program (MBG) is a government initiative aimed at improving children’s nutrition and reducing stunting in Indonesia. This study applies a rule-based sentiment analysis approach to evaluate public opinion on the program by analyzing YouTube comments. The dataset was processed through standard text preprocessing techniques, including case folding, stopword removal, and emoji filtering. Sentiment classification was performed using a keyword-based labeling system that categorized comments into positive, negative, and neutral classes. The classification results, visualized using a bar chart, revealed that neutral sentiment dominated the overall public discourse. This suggests that most users expressed uncertainty, factual observations, or non-judgmental questions about the program. Positive sentiment followed, reflecting public support and appreciation for the initiative’s goals. In contrast, negative sentiment accounted for the smallest portion, mainly expressing concerns about food safety and implementation. This study demonstrates that a simple and interpretable rule-based model, when combined with effective preprocessing, can serve as a practical and efficient tool for large-scale public sentiment monitoring. The visualization results provide initial insights for policymakers to improve communication strategies and address public concerns regarding the MBG program. Keywords: Sentiment Analysis; Public Opinion; Free Nutritious Meal Program (MBG); Stunting Reduction; Policy Evaluation. Abstrak: Program Makan Bergizi Gratis (MBG) merupakan inisiatif pemerintah untuk meningkatkan gizi anak dan menurunkan angka stunting di Indonesia. Penelitian ini bertujuan mengevaluasi opini publik terhadap program tersebut melalui analisis komentar di platform YouTube dengan pendekatan analisis sentimen berbasis aturan (rule-based). Data dianalisis melalui tahapan preprocessing teks, seperti case folding, penghapusan stopword, dan penyaringan emoji. Klasifikasi sentimen dilakukan menggunakan sistem pelabelan berbasis kata kunci yang membagi komentar ke dalam tiga kategori: positif, negatif, dan netral. Hasil klasifikasi yang divisualisasikan dalam grafik batang menunjukkan bahwa sentimen netral mendominasi komentar publik, mencerminkan ketidakpastian, pertanyaan, atau tanggapan informatif tanpa opini eksplisit. Sentimen positif berada di urutan kedua dan menunjukkan dukungan terhadap program, sementara sentimen negatif paling sedikit, umumnya berisi kekhawatiran terkait pelaksanaan dan keamanan pangan. Temuan ini menunjukkan bahwa pendekatan klasifikasi sederhana yang dipadukan dengan preprocessing yang efektif dapat menjadi alat yang efisien untuk memantau opini publik secara luas. Visualisasi hasil dapat menjadi dasar bagi pengambil kebijakan untuk menyusun strategi komunikasi yang lebih responsif terhadap persepsi masyarakat. Kata kunci: Analisis Sentimen; Opini Publik; Program Makanan Bergizi Gratis (MBG); Pengurangan Stunting; Evaluasi Kebijakan
SEGMENTASI JAMAAH UMRAH MENGGUNAKAN K-MEANS DENGAN METODE ELBOW GUNA STRATEGI PENINGKATANMANAJEMEN SUMBER DAYA MANUSIA Muhammad Iqbal; Nirda Julianda
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6757

Abstract

Abstract: The increasing number of Umrah pilgrims requires travel agencies to implement data-driven approaches to improve service quality and support Human Resource Management (HRM). This study aims to segment Umrah pilgrims using the K-Means clustering algorithm as a basis for HRM strategies. The research follows the Knowledge Discovery in Databases (KDD) process, including data preprocessing, clustering in RapidMiner, and cluster evaluation using the Elbow Method based on performance distance (average within centroid distance). Euclidean Distance was used to measure similarity among data objects. Seven clustering experiments were conducted with k = 2–8, producing performance distance values of 3418.971, 1416.677, 865.316, 479.795, 344.203, 258.804, and 214.562, respectively. The Elbow curve indicates that k = 3 is the optimal number of clusters because it represents the most significant decrease before the curve stabilizes. The resulting clusters provide objective information for supporting staff placement, service task allocation, pilgrim assistance planning, and employee competency development. Therefore, the integration of K-Means and the Elbow Method offers an effective data-driven approach for supporting HRM decision-making in Umrah travel agencies. Keyword: Elbow Method; Human Resource Management; K-Means Clustering; performance distance; Umrah pilgrims.   Abstrak: Peningkatan jumlah jamaah umrah mendorong biro perjalanan memanfaatkan analisis data untuk meningkatkan kualitas pelayanan dan mendukung pengambilan keputusan pada Manajemen Sumber Daya Manusia (MSDM). Penelitian ini bertujuan melakukan segmentasi jamaah umrah menggunakan algoritma K-Means Clustering sebagai dasar penyusunan strategi MSDM. Metode penelitian mengikuti tahapan Knowledge Discovery in Databases (KDD), meliputi data preprocessing, proses klasterisasi pada RapidMiner, serta evaluasi menggunakan Metode Elbow berdasarkan performance distance (average within centroid distance). Pengukuran kemiripan data dilakukan menggunakan Euclidean Distance. Pengujian dilakukan sebanyak tujuh kali dengan variasi k = 2–8, menghasilkan nilai performance distance berturut-turut 3418,971; 1416,677; 865,316; 479,795; 344,203; 258,804; dan 214,562. Hasil evaluasi menunjukkan bahwa k = 3 merupakan jumlah klaster optimal karena membentuk titik siku (elbow point) dengan penurunan nilai paling signifikan sebelum kurva melandai. Hasil segmentasi dapat dimanfaatkan sebagai dasar penempatan pegawai, pembagian tugas pelayanan, penyusunan tim pendamping jamaah, dan pengembangan kompetensi pegawai secara lebih tepat sasaran.  Kata kunci: jamaah umrah; K-Means Clustering; Manajemen Sumber Daya Manusia; Metode Elbow; performance distance.
Prioritizing Regional Research and Innovation Program Proposals Using a MOORA-Based Decision Support System: A Case Study of Asahan Regency Riski Ramadhan; Riki Andri Yusda; Muhammad Iqbal
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 2 (2026): AUGUST 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i2.7531

Abstract

The evaluation of regional research and innovation program proposals at the Regional Planning, Research, and Development Agency (BAPPERIDA) of Asahan Regency is still conducted manually, which may lead to subjectivity and inefficiency in the decision-making process. This study aims to develop a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support the prioritization of regional research and innovation proposals. The study evaluates ten proposal alternatives based on five criteria: program relevance, innovation level, implementation potential, resource readiness, and budget feasibility. The criterion weights were determined through expert judgment involving five evaluators from BAPPERIDA. The MOORA method was applied to normalize the evaluation data, incorporate the criterion weights, and calculate the optimization value for each alternative. The results show that alternative A8, Gunting Saga (Gerakan Cegah Stunting Siap Siaga), obtained the highest optimization score of 0.2340, followed by A7 with 0.2097 and A3 with 0.2082. The results indicate that the proposed DSS can provide a structured ranking of regional research and innovation proposals based on predetermined criteria and weights. The system can support BAPPERIDA in evaluating proposals and determining priority programs in a more systematic and measurable manner.
Co-Authors Dina Triana Indra Ramadona Harahap Mustika Fitri Larasati Sibuea Nirda Julianda Nurul Rahmadani Revina Salsabila Riki Andri Yusda Riski Ramadhan Rohminatin Rohminatin