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KESIAPAN MAHASISWA UNIVERSITAS NEGERI MEDAN DALAM MENGHADAPI TANTANGAN JUDI ONLINE: TINJAUAN PSIKOLOGIS DAN AGAMA Siregar, Hapni Laila; Lubis, Ardilla Syahfitri; Sulistiyani, Fani; Assiddiq, Rahmad Susilo; Siregar, Sutan Surya Darpan; Putri, Taqiyyah Nabila
JURNAL LENTERA [PENDIDIKAN PUSAT PENELITIAN LPPM UM METRO] Vol 9, No 1 (2024): Jurnal Lentera Pendidikan LPPM UM Metro
Publisher : Lembaga Penelitian UM Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jlpp.v9i1.3448

Abstract

KESIAPAN MAHASISWA UNIVERSITAS NEGERI MEDAN DALAM MENGHADAPI TANTANGAN JUDI ONLINE: TINJAUAN PSIKOLOGIS DAN AGAMA Siregar, Hapni Laila; Lubis, Ardilla Syahfitri; Sulistiyani, Fani; Assiddiq, Rahmad Susilo; Siregar, Sutan Surya Darpan; Putri, Taqiyyah Nabila
JURNAL LENTERA [PENDIDIKAN PUSAT PENELITIAN LPPM UM METRO] Vol 9, No 1 (2024): Jurnal Lentera Pendidikan Pusat Penelitian LPPM UM Metro
Publisher : Lembaga Penelitian UM Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jlpp.v9i1.3448

Abstract

Identifikasi Variasi Paprika Berdasarkan Jenis Warna Paprika Berbasis Analisis Citra Digital Menggunakan Algoritma Support Vector Machine (SVM) Nasution, Adzkia; Lubis, Ardilla Syahfitri; Kiswanto, Dedy
Jurnal Informasi, Sains dan Teknologi Vol. 7 No. 2 (2024): Desember: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v7i2.282

Abstract

Penelitian ini bertujuan untuk merancang sistem klasifikasi warna paprika (merah, kuning, hijau, orange) dengan memanfaatkan analisis citra digital yang didukung oleh algoritma Support Vector Machine (SVM). Pendekatan yang digunakan meliputi pengumpulan data berupa gambar paprika, pengolahan awal data melalui langkah-langkah seperti penyesuaian ukuran gambar, pengaburan untuk mengurangi noise, serta peningkatan kontras menggunakan metode CLAHE. Selain itu, fitur warna diekstraksi menggunakan momen warna, dan fitur tekstur diperoleh melalui matriks co-occurrence skala abu-abu (GLCM). Model SVM diuji dengan berbagai jenis kernel, yaitu linier, polinomial, RBF, dan sigmoid, guna menentukan kernel dengan kinerja terbaik. Hasil pengujian menunjukkan bahwa kernel linier dan RBF mengalami overfitting karena menghasilkan akurasi sempurna sebesar 100%, sementara kernel poly dan sigmoid mencapai akurasi sebesar 97,56% dan 39%. Secara keseluruhan, model SVM mampu mengklasifikasikan warna paprika dengan tingkat akurasi yang tinggi, dengan rata-rata presisi, recall, dan skor F1 mencapai 97,56%. Sistem ini diharapkan mampu meningkatkan efisiensi dan ketepatan dalam identifikasi warna paprika serta mendukung inovasi dan modernisasi dalam sektor pertanian.
Model Simulasi Dinamis Pengelolaan Sampah di Kabupaten Jepara Berbasis Stella Nur Nasution, Adzkia; Lubis, Ardilla Syahfitri; Harliana, Putri
Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.335

Abstract

Waste management has become increasingly complex due to population growth and limited infrastructure, especially in densely populated areas such as Jepara Regency. To better understand this issue, this study employs a system dynamics approach to simulate waste generation projections up to the year 2030. The model was developed using 2023 baseline data and incorporates variables such as population growth, waste sorting effectiveness, and land area. The simulation was conducted using Stella, a specialized modeling software designed to visualize dynamic systems through flow diagrams and causal relationships. Stella enables users to explore how variables interact over time, making it a valuable tool for analyzing potential policy outcomes through scenario testing. The simulation results indicate that waste volume can be reduced if waste sorting policies are consistently implemented at the household level. This model provides a comprehensive overview of policy impacts and serves as a decision-support tool for strategic waste management planning at the regional level. The findings highlight the importance of data-driven planning to establish a sustainable and responsive waste management system in the face of changing demographic conditions.
Decision Support System for Selecting BPS Central Tapanuli Partners Using the SMART Method Nur, Adzkia; Lubis, Ardilla Syahfitri; Sambora, Dicky; Niska, Debi Yandra
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1857

Abstract

The selection of partners at the Central Statistics Agency (BPS) of Central Tapanuli is a very important process because it determines the quality of supporting staff in census and survey activities. One of the core stages in the selection process is the interview, which functions to directly evaluate the abilities and character of prospective partners. The assessment in the interview covers several main aspects, namely analytical skills, communication, appearance, and politeness. This study aims to design a decision support system based on the SMART (Simple Multi Attribute Rating Technique) method that can help process interview results systematically and objectively. Each criterion in the interview is given a weight based on the level of importance, then the value of each candidate is processed through mathematical calculations that produce a final score. This score is used to determine the candidate's ranking and provide recommendations to the selection committee. The system is developed in the form of a web-based application with a user-friendly interface, and supports data input, value processing, and automatic presentation of results. The implementation results show that the SMART method is able to improve assessment accuracy, reduce subjectivity, and accelerate the decision-making process in partner selection. With this system, the interview process is not only a fairer and more transparent means of assessment, but also supports work efficiency and consistency of selection results in the BPS environment.