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Nasution, Alvi Sahrin
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Penerapan Rantai Markov dalam Menentukan Jumlah Tingkat Pengangguran di Provinsi Sumatera Utara Abdurrahman, Abdurrahman; Wibowo, Anastasya Putri; Adiva, Cut Tasya; Kanaya, Niquita Sepha; Hutabarat, Reinaldo Fernandes Matheus; Simorangkir, Tri Gustini; Manullang, Sudianto; Nasution, Alvi Sahrin
Innovative: Journal Of Social Science Research Vol. 5 No. 3 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i3.19437

Abstract

Tingkat pengangguran yang fluktuatif di Sumatera Utara mencerminkan tantangan besar dalam pengelolaan ketenagakerjaan. Penelitian ini bertujuan untuk menganalisis pola transisi tingkat pengangguran menggunakan pendekatan Rantai Markov sebagai metode probabilistik. Data historis dari tahun 2005 hingga 2025 diklasifikasikan ke dalam kategori naik dan turun, lalu dihitung matriks probabilitas transisi dan steady-state untuk memperkirakan tren jangka panjang. Hasilnya menunjukkan bahwa sistem cenderung menuju keadaan stabil dengan probabilitas lebih tinggi berada dalam kondisi penurunan pengangguran. Temuan ini memberikan kontribusi dalam menyediakan informasi prediktif yang dapat digunakan oleh pembuat kebijakan untuk merumuskan strategi penanggulangan pengangguran yang lebih tepat sasaran dan berbasis data.
Analisis Model Stokastik Birth-Death pada Populasi Bakteri Esherichia coli dengan Kematian di Bawah Tekanan Antibiotik Anshari, Farhan; Ginting, Puspa Arinda; Aritonang, Anggi Pasha; Hutasoit, Elizabeth; Manihuruk, Oliver Juan Gery; Manullang, Sudianto; Nasution, Alvi Sahrin
Innovative: Journal Of Social Science Research Vol. 5 No. 3 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i3.19442

Abstract

Penelitian membahas model stokastik dinamika populasi bakteri Escherichia coli pada kondisi tekanan antibiotik, khususnya pada konsentrasi Minimum Inhibitory Concentration (MIC), menggunakan proses birth-death linier sebagai kerangka dasar. Dinamika sistem dianalisis melalui master equation untuk memperoleh distribusi probabilitas waktu-ke-waktu, distribusi stasioner, serta waktu rata-rata kepunahan (Mean Time to Extinction) dan probabilitas first-passage time. Pendekatan stokastik mengintegrasikan model berbasis widget pada tingkat sel individu, di mana setiap sel direpresentasikan sebagai unit molekuler minimum. Ketika jumlah widget mencapai ambang batas, sistem mengalami kematian atau pembelahan, masing-masing dengan distribusi binomial simetris. Analisis dilakukan secara teoritis melalui simulasi Monte Carlo berbasis Python. Hasil menunjukkan bahwa meskipun rata-rata populasi tampak stasioner pada kondisi, sistem mengalami fluktuasi stokastik signifikan yang memicu aktivitas mikroskopik intens. Varians populasi meningkat terhadap waktu, menandakan instabilitas tersembunyi. Simulasi menunjukkan bahwa waktu rata-rata kepunahan meningkat subeksponensial terhadap ukuran populasi awal.
Implementasi Metode Markov Chain Untuk Prediksi Laju Inflasi Di Sumatera Utara Muthiah, Ade Naila; Nurjannah, Annisa; Aulia, Ilmi; Kanaya, Nayla Yasyra; Nasution, Tri Annisya Aini; Manullang, Sudianto; Nasution, Alvi Sahrin
Innovative: Journal Of Social Science Research Vol. 5 No. 3 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i3.19461

Abstract

Inflasi merupakan indikator penting dalam menilai kestabilan ekonomi suatu daerah. Di Sumatera Utara, fluktuasi laju inflasi dari tahun ke tahun menuntut adanya metode prediktif yang andal untuk mendukung pengambilan kebijakan. Penelitian ini bertujuan untuk memprediksi laju inflasi di Sumatera Utara dengan menggunakan metode Markov Chain, yang mengandalkan sifat transisi antar kondisi inflasi dari waktu ke waktu. Data historis inflasi dari tahun 2001 hingga 2020 diklasifikasikan ke dalam tiga kategori: rendah, sedang, dan tinggi. Berdasarkan data tersebut, dibentuk matriks transisi probabilitas yang kemudian digunakan untuk menghitung distribusi stasioner. Hasil analisis menunjukkan bahwa kondisi inflasi rendah memiliki peluang jangka panjang tertinggi, yaitu sebesar 84,2%. Tidak ditemukan transisi menuju inflasi tinggi, yang mengindikasikan kestabilan ekonomi regional. Temuan ini menunjukkan bahwa metode Markov Chain dapat memberikan gambaran prediktif yang kuat dan dapat dijadikan alat bantu dalam perencanaan kebijakan ekonomi daerah
DIVERSIFIKASI PRODUK OLAHAN IKAN LELE UNTUK PEMBERDAYAAN EKONOMI MASYARAKAT DESA SIGUMURU Rambe, Muhammad Rahman; Nasution, Alvi Sahrin; Pohan, Rizky Febriani
Jurnal Abdi Insani Vol 12 No 10 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i10.2913

Abstract

Catfish is a type of freshwater fish with high economic value, both in terms of sales value and nutritional value. Furthermore, this fish is easy to grow, with a high protein content, soft, white meat, and affordable prices. However, suboptimal cultivation results in low yields, which reduces the income of catfish farmers. One effort to increase the income of catfish farmers is through diversification of processed catfish products (catered fish paste, catfish meatballs, and catfish satay). This activity aims to improve the knowledge and skills of the Sigumuru Village community in processing catfish into a variety of processed products. Furthermore, this activity can also increase the income of the Sigumuru Village community. The methods used in this activity were location surveys, socialization, demonstrations, marketing, and monitoring. The participants of this activity were the Fish Cultivation Group (FCG) "Sigumuru Jaya" which consisted of 12 people. This activity was carried out for 8 months. The activity evaluation method was carried out using a pre-test, post-test, preference questionnaire, and monitoring questionnaire. The results of this activity showed an average increase in community empowerment outcomes of 83.89% which consisted of increased skills, knowledge, business sustainability, and partner income. However, the overall activities carried out showed an increase in community empowerment outcomes of 91.11%. The results of the preference questionnaire showed that the majority of the community (50%) chose pecal lele as the most popular processed catfish product because it tastes good (37.5%). The results of the monitoring questionnaire showed an assessment score of 75. Pecal lele is the most popular food among the community. Thus, the PKM team recommends that target partners further increase pecal lele production to increase their income and business sustainability.
Optimasi Produksi Perusahaan Semen dengan Pendekatan Fungsi Turunan: Studi pada PT Semen Indonesia Tbk Prajogo Tambunan, Combest; Hasibuan, Febriyanti; Nasution, Alvi Sahrin
QISTINA: Jurnal Multidisiplin Indonesia Vol 4, No 2 (2025): December 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v4i2.7309

Abstract

This study aims to analyze the application of derivative functions in optimizing production at PT Semen Indonesia Tbk. Using a differential calculus approach, the research examines the relationship between revenue, cost, and profit through the concepts of Marginal Revenue (MR) and Marginal Cost (MC). The financial report shows total sales of 33.8 million tons, revenue of IDR 34.95 trillion, and cost of goods sold of IDR 24.54 trillion. The results indicate an average price of IDR 1,033,000 per ton and a variable cost of IDR 726,000 per ton. With a demand elasticity of ε = −2, the analysis yields MR = IDR 516,500 and MC = IDR 726,000 per ton. The optimal production level is calculated at approximately 26.9 million tons, which is lower than the actual production. The condition MR MC implies that additional production does not increase marginal profit. Therefore, production optimization strategies should focus on cost efficiency, distribution improvements, and pricing adjustments to achieve the equilibrium condition MR = MC as the optimal production point.
SELIMUT ANTI API INOVASI PENCEGAHAN DAN MITIGASI KEBAKARAN TAHAP AWAL BERSAMA MITRA PBKM KESUMA MARELAN MEDAN Suyanti, Retno Dwi; Pardosi, Sri Masnita; Nasution, Alvi Sahrin; Prima, Heppy Setya
Jurnal Abdi Insani Vol 12 No 11 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i11.2838

Abstract

Fires are sudden disasters that can cause significant losses, both material and non-material. Prompt early response is crucial to prevent the spread of fire, but many communities lack simple and easy-to-use fire extinguishers. A five-member community service team, in collaboration with the Kesuma Community Learning Center (PKBM), led by Ms. Siti Nurhayati, located in Lk 2 Pasar 2 Barat Terjun, Medan Marelan, and involving 40 community members as partners, conducted training and developed an innovation called a "Fulerene Patterned Fire Blanket." This blanket is made from heat-resistant fullerene-patterned fiberglass and coated with sodium bicarbonate (NaHCO₃), which accelerates fire extinguishing by lowering the temperature and inhibiting oxidation. This combination of materials results in a device that is high-temperature resistant, lightweight, and reusable after washing. This activity included outreach, demonstrations, hands-on training, and involved the local community in simple production of the device. The results demonstrated an increase in community knowledge and skills in dealing with small fires. Enthusiasm for this safe and economical design has also increased disaster awareness and preparedness at the community level. The positive response has opened up opportunities for broader program development. Scientific studies have shown that fullerene-patterned fire blankets are effective as a preventative solution, enhancing community preparedness for early fire risks.
An optimized kernel SVM framework for game review sentiment analysis using particle swarm optimization Karo Karo, Ichwanul Muslim; Dewi, Sri; Nasution, Alvi Sahrin
Joutica Vol 11 No 1 (2026): MARET
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jti.v11i1.1633

Abstract

The digital game industry’s rapid growth has increased interaction between developers and players through online review platforms. These reviews contain vital information about gaming experiences and satisfaction, serving as guides for future game versioning. Sentiment analysis provides a strategic approach to automatically classify reviews, offering data-driven insights for developers. This study focuses on enhancing sentiment analysis performance for Player Unknown's Battlegrounds (PUBG) reviews by integrating Kernel Support Vector Machine (SVM) with Particle Swarm Optimization (PSO). A dataset of 1,205 reviews from the Google Play Store was analyzed using TF-IDF feature extraction and 5-fold cross-validation. While default Kernel SVM achieved 76.78% accuracy, it suffered from low precision (56.9%). Implementing PSO for parameter optimization significantly improved performance, reaching 86.42% accuracy, 70.98% precision, and an 83.03% F1-score. Comparisons with Naïve Bayes, basic SVM, BERT, and Lexicon + SVM confirm that the Kernel SVM + PSO model provides superior and more stable performance. These findings highlight PSO’s effectiveness in SVM parameter tuning. Future research should investigate combining metaheuristic optimization with deep learning models to improve model generalization.
PEMODELAN DAN PERBANDINGAN ALGORITMA MACHINE LEARNING UNTUK PREDIKSI BANJIR: STUDI KASUS KOTA MEDAN Putri Maulidina Fadilah; Putri Harliana; Br Rambe, Imelda Wardani; Nasution, Alvi Sahrin
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 1 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n1.p235 - 242

Abstract

Banjir merupakan salah satu bencana hidrometeorologis yang sering terjadi di Indonesia, termasuk di Kota Medan, dan menimbulkan kerugian sosial ekonomi yang signifikan. Penelitian ini bertujuan untuk mengembangkan dan membandingkan model prediksi kejadian banjir menggunakan tiga algoritma machine learning, yaitu Random Forest (RF), Support Vector Machine (SVM), dan Decision Tree (CART). Data yang digunakan merupakan data hidrometeorologis Kota Medan periode 2021–2024 yang diperoleh dari BMKG dan Geoportal BNPB, meliputi variabel curah hujan (RR), suhu (TN, TX, TAVG), kelembapan (RH_AVG), kecepatan angin (FF_X), arah angin (DDD_X), serta jumlah kecamatan dan rumah terdampak. Tahapan penelitian meliputi pra-pemrosesan data, pemodelan, serta evaluasi menggunakan metrik akurasi, presisi, recall, F1-score, dan AUC. Hasil penelitian menunjukkan bahwa Random Forest memiliki kinerja terbaik dengan akurasi sebesar 86,24% dan AUC sebesar 0,851, yang menunjukkan kemampuan prediksi yang sangat baik. Analisis feature importance menunjukkan bahwa curah hujan (RR) merupakan faktor paling berpengaruh terhadap kejadian banjir, diikuti oleh temperatur minimum (TN) dan temperatur rata-rata (TAVG). Metode ROSE terbukti efektif dalam mengatasi ketidakseimbangan kelas dengan meningkatkan recall tanpa mengorbankan akurasi. Secara keseluruhan, hasil penelitian ini menunjukkan bahwa algoritma Random Forest lebih andal dan stabil dibandingkan SVM dan Decision Tree dalam konteks analisis data hidrometeorologis, serta berpotensi menjadi dasar pengembangan sistem peringatan dini banjir berbasis kecerdasan buatan di masa depan. Kata Kunci: Prediksi Banjir, Random Forest, Support Vector Machine, Decision Tree, ROSE.
Co-Authors Abdurahman Abdurrahman Adiva, Cut Tasya Afniria, Afniria Ameliya, Ameliya Angelyca Annisa Hidayah Anshari, Farhan Aritonang, Anggi Pasha Aulia, Ilmi Br Rambe, Imelda Wardani Dani, Danu Rama Erwina Azizah Hasibuan, Erwina Azizah Felicia Eldora Fithriyah Patriotika Ginting, Puspa Arinda Gultom, Ledy Meva Tiurma Gultom, Rahmad H Handre Gabriel Pinem Harahap, Sahrul Hasibuan, Eka Sri Hartini Hasibuan, Febriyanti Heppy Setya Prima Hutabarat, Reinaldo Fernandes Matheus Hutasoit, Elizabeth Ichwanul Muslim Karo Karo Kanaya, Nayla Yasyra Kanaya, Niquita Sepha Karin Aulia Putri Khoiriyati Azmi Lubis, Raja Harly Anugrah Lubis, Rhamanda Ardiyansyah Manihuruk, Oliver Juan Gery Manulang, Sudianto Manullang, Maria Ayuni Isabella Manullang, Sudianto Muhammad Rahman Rambe Muthiah, Ade Naila N Simanjuntak, Christina Nainggolan, Dina Olivia Nasution, Tri Annisya Aini Noni Paisah, Noni Nurjannah, Annisa Pardosi, Sri Masnita Piliang, Yumna Khairi Amani Pohan, rizky febriani Prajogo Tambunan, Combest Purba, Mutia Agustin Purba, Rut Omega Putri Maulidina Fadilah Rambe, Muhammad Rahman Retno Dwi Suyanti Rizky Febriani Pohan Shofia Lubis, Shofia Siboro, Alio Hutaperi Simanjuntak, Natalia Anggriani Simbolon, Taing Pebrieni Simorangkir, Tri Gustini Sinaga, Roberto Karlos Siregar, Usnul Marisa Sitanggang, Santa Falare Sri Dewi Tobing, Rizky Saputra Wibowo, Anastasya Putri