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All Journal JISI UMJ (Jurnal Integrasi Sistem Industri UMJ) Jurnal Ilmu Komputer dan Informatika Journal of Green Engineering for Sustainability Jurnal Pengabdian Cendikia Nusantara
Nensi, Sri Wahyu
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Medicine & Pharmacology

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Analisis Prediksi Stroke dengan Membandingkan Tiga Metode Klasifikasi Decision Tree, Naïve Bayes, dan Random Forest Aulia, Yunita; Andriyansyah, Andriyansyah; Suharjito, Suharjito; Nensi, Sri Wahyu
Jurnal Ilmu Komputer dan Informatika Vol 3 No 2 (2023): JIKI - Desember 2023
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jiki.90

Abstract

Prediksi stroke telah muncul sebagai bidang penelitian dan intervensi kesehatan yang penting karena dampaknya yang signifikan terhadap kesehatan masyarakat dan kesejahteraan individu. Pemeriksaan rinci mengenai usia, hipertensi, penyakit jantung, status perkawinan, jenis pekerjaan, jenis tempat tinggal, rata-rata kadar glukosa, BMI, status merokok, dan jenis kelamin sebagai factor terjadinya stroke. Dengan melakukan sintesis penelitian dan menganalisis kumpulan data yang luas, penelitian ini bertujuan untuk menjelaskan hubungan rumit antara faktor-faktor tersebut dan dampak kumulatifnya terhadap risiko stroke. Metode penelitian ini diawali dengan perbandingan algoritma Decision Tree, Naïve Bayes dan Random Forest dengan menggunakan software RapidMiner. Dari dataset prediksi stroke yang diberikan, terdapat 5110 responden dengan kondisi beragam. Di antara 5110 responden tersebut terdapat 12 atribut. Berdasarkan uraian yang telah dibahas maka dapat diambil kesimpulan bahwa metode Decision Tree merupakan metode terbaik dengan nilai akurasi tertinggi sebesar 95,13% dibandingkan dengan metode Random Forest dan Naïve Bayes dan nilai TF (True False) yang dipilih adalah 4861, TT (True True) adalah 0, FF (False False) adalah 249, dan FT (False True) adalah 0.
The Best Time Series Model For Elotex Demand Forecasting Fitra, Zhakia Irsalina; Gunawan, Fergyanto E.; Nensi, Sri Wahyu
Greeners: Journal of Green Engineering for Sustainability Vol 2 No 2 (2025): Journal of Green Engineering for Sustainability
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jges.v2i2.275

Abstract

Inventory management is carried out to ensure the accuracy of raw material stock in the warehouse. In a chemical raw material distribution company, stockpiling or shortages of raw materials often occur due to fluctuating customer demand. The company is at risk of indirect losses if the product is not sold immediately or if it becomes unavailable. When products are not sold promptly, there is a potential loss due to the limited shelf life of the goods. On the other hand, when products are not available, the company risks losing its customers. The objective of this study is to design a time series model to predict the quantity of chemical raw materials by comparing the accuracy of the Moving Average, ARIMA, and ARMA models. The comparison results will be based on historical demand data for one of the company's products. The product selected in this study is the chemical raw material Elotex, which has the highest demand. The sample data used spans from 2015 to 2023 in daily units. The selection of the best method in this study is determined by considering the model with the lowest RMSE (Root Mean Square Error) value. The research results show that the RMSE value for the Moving Average (MA) model is 3052.7560, the ARIMA model is 4247.9554, and the ARMA model is 4241.8059. Thus, the Moving Average (MA) model, having the lowest RMSE value, is the most accurate model for forecasting the purchase of Elotex chemical raw materials.
Konservasi Mangrove : Edukasi, Aksi, dan Kolaborasi untuk Ekosistem Pesisir yang Berkelanjutan Nugroho, Adi; Nensi, Sri Wahyu; Azharman, Zefri
Jurnal Pengabdian Cendikia Nusantara Vol 3 No 1 (2025): Jurnal Pengabdian Cendikia Nusantara
Publisher : Lembaga Riset Cendekia, Yayasan Berkah Putera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70104/pcn.v3i1.117

Abstract

The mangrove ecosystem plays a vital role in maintaining environmental balance, making it one of the most productive ecosystems. In addition to functioning as a natural barrier against coastal abrasion, mangroves also serve as habitats for marine organisms and provide economic resources for local communities. Batam City, as an archipelagic region with approximately 13,000 hectares of mangrove potential, is facing a significant reduction in mangrove forest areas due to development and land-use conversion. In response to this condition, a community service activity was carried out in the form of mangrove tree planting as part of efforts to conserve the mangrove ecosystem. The activity took place in Kampung Terih, Batam, involving students and lecturers, and was supported by the local community. The implementation method consisted of three stages: pre-activity (location survey, stakeholder coordination, and logistical preparation), core activity (environmental education and seedling planting), and post-activity (monitoring and scientific publication). The activity resulted in the planting of approximately 200 mangrove seedlings of the Rhizophora stylosa and Bruguiera gymnorrhiza species. In addition to contributing to environmental rehabilitation, this activity had a positive impact in raising participants’ environmental awareness and providing experiential learning for students. Evaluation indicated challenges in reaching the target number of seedlings and limited information on alternative planting locations. This activity is expected to serve as a sustainable initiative for mangrove conservation in Batam’s coastal areas and to strengthen the role of educational institutions in environmental preservation through community collaboration.
Optimasi Pemilihan Rute Terpendek Distribusi Gas LPG 3 Kg Menggunakan Algoritma Sweep Berbasis Python Setiawan, Andry; Nensi, Sri Wahyu; Rizani, Nataya Charoonsri; Bryan Matutina, Tarcisius Yodris; Hamidi, Kurniawan
JISI: Jurnal Integrasi Sistem Industri Vol. 12 No. 2 (2025): JISI UMJ
Publisher : Fakultas teknik Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jisi.12.2.235-248

Abstract

Distribusi gas LPG 3 Kg memerlukan perencanaan rute yang efisien untuk menekan biaya operasional, menghemat waktu, dan meningkatkan keamanan pengiriman. Penelitian ini bertujuan untuk mengoptimalkan pemilihan rute terpendek distribusi gas LPG 3 Kg dengan menerapkan Algoritma Sweep berbasis Python pada kasus Capacitated Vehicle Routing Problem (CVRP). Data yang digunakan meliputi lokasi pelanggan, jarak antar titik, dan kapasitas angkut truk. Algoritma Sweep digunakan untuk mengelompokkan pelanggan berdasarkan sudut polar relatif terhadap depot, dilanjutkan dengan penentuan urutan kunjungan yang meminimalkan jarak tempuh sambil memenuhi batas kapasitas kendaraan. Hasil optimasi menunjukkan bahwa metode ini mampu menghasilkan tiga rute distribusi dengan total jarak tempuh 98,7 km, mengalami pengurangan sebesar 26,18 km atau sekitar 21% dibandingkan kondisi awal yang mencapai 124,88 km. Selain itu, jumlah armada dapat ditekan menjadi tiga truk tanpa melanggar batas kapasitas angkut. Implementasi berbasis Python memungkinkan proses penghitungan dan pemodelan rute dilakukan secara cepat, akurat, dan dapat diulang untuk berbagai skenario distribusi.
Analysis Quality for Kernel Production with Seven Tools Method Nensi, Sri Wahyu
Greeners: Journal of Green Engineering for Sustainability Vol 3 No 01 (2025): Journal of Green Engineering for Sustainability
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jges.v3i1.309

Abstract

In today’s era of rapid industrial advancement, the palm oil industry in Indonesia has experienced significant growth, intensified competition and prompting companies to enhance production quality to remain competitive. Predominantly acting as raw material suppliers, many palm oil companies, including those in Southeast Sulawesi, are required to meet stringent quality standards set by their domestic and international partners. One such company processes oil palm into crude palm oil (CPO), palm kernel, fibre, and kernel shell, with CPO and kernel being distributed to partner companies under strict quality agreements. A breach of these agreements, particularly in kernel quality, has led to penalties and potential termination of partnerships. Palm kernel oil (PKO), a high-value derivative, must meet quality criteria such as free fatty acid content, moisture, dirt content, and kernel integrity. Observations revealed recurring deviations from these standards, notably in excessive dirt content. This study aims to identify root causes of quality issues using the Seven Quality Control Tools method, supported by primary data including production outputs and interviews with workers. The analysis identified key contributing factors: inadequate adherence to machine efficiency guidelines by operators, sorting errors in raw materials, and mismatched or poorly maintained machinery. Corrective actions were proposed using 5W+1H analysis, emphasizing the need for operator compliance with efficiency protocols, improved raw material handling, and appropriate machine usage and maintenance to ensure consistent kernel quality aligned with agreed standards.
Co-Authors Adi Nugroho Andriyansyah, Andriyansyah Andry Setiawan, Andry Aulia, Yunita Azharman, Zefri Bryan Matutina, Tarcisius Yodris Fergyanto E. Gunawan Fitra, Zhakia Irsalina Hamidi, Kurniawan Nataya Charoonsri Rizani Suharjito Suharjito, Suharjito