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Determining the Appropriate use of 3 Phase 150 kV Transformer Oil Using the Fuzzy Method Dina Maizana, MT; Moulando Tampubolon; Muhathir Muhathir; Muhammad Fadlan Siregar; Yanawati Yahya
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 4 No. 2 (2024): September 2024
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v4i2.17914

Abstract

Transformer is electrical power equipment that functions to convert electrical energy from one voltage value to another through the action of a magnetic field. Transformers are important electrical equipment because they are directly connected to electricity transmission and distribution lines. The aim of this research is to analyze transformer oil and its suitability standards. The type of research used is quantitative research using the Dissolved Gas Analysis (DGA) method. The data obtained for this method will be calculated by applying Fuzzy Logic to map the problem or determine variables. The mapping results will then be calculated using Matlab as the result of mathematical data analysis in graph form.
Sistem Informasi Manajemen Data Surat Dengan Algoritma Blowfish Essay Puspita Sitopu; Nurul Khairina; Rizki Muliono; Muhathir Muhathir
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 6 No. 1 (2022): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2022
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v6i1.7964

Abstract

Perkembangan teknologi informasi yang semakin pesat saat ini menuntut kita untuk mampu mengikuti perkembangannya. Komunikasi secara digital di era modern dapat menjadi salah satu ancaman akan adanya penyadapan, penyalahgunaan informasi, dan pencurian data penting yang tidak diinginkan oleh pihak yang tidak berwenang. Apalagi jika informasi tersebut bersifat rahasia dan memliki ruang lingkup yang luas dalam kenegaraan. Oleh karena itu, keamanan penyimpanan data menjadi sangat penting. Data yang terdapat pada surat masuk ataupun surat keluar dalam satu sekolah juga memliki kerahasiaan yang harus dijaga, kemana surat dikirimkan dan dari mana surat berasal juga menjadi salah satu hal yang perlu dijaga kerahasiannya. Atas dasar inilah peneliti ingin membangun sistem informasi manajemen surat yang berfokus pada penyimpanan data surat atau database surat. Dari berbagai metode penyandian yang ada hingga saat ini, salah satunya adalah metode Kriptografi Blowfish yang menggunakan blok cipher 64-bit dengan panjang kunci variabel. Proses enkripsi pada penelitian ini merupakan proses memberikan kunci rahasia pada surat tersebut agar surat tersebut berubah menjadi tulisan sandi yang tidak dapat dipahami oleh pihak yang tidak berwenang. Proses deskripsi merupakan proses menterjemahkan kembali surat yang telah terahasia agar pihak sekolah dapat membaca surat yang dimaksud. Dari hasil pengujian sistem informasi, sistem informasi manajemen surat dapat menerapkan Algoritma Blowfish dengan baik, hal ini ditandai dengan adanya perubahan nomor surat, tanggal pengiriman surat serta tujuan pengiriman surat pada saat proses enkripsi maupun pada saat proses dekripsi.
Peningkatan Profit Melalui Strategi Diskon Dinamis Menggunakan Reinforcement Learning pada Data Transaksi Ritel Daring Andre Hasudungan Lubis; Rizki Muliono; Nanda Novita; Susilawati Susilawati; Muhathir Muhathir; Sayuti Rahman
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 2 (2026): Edisi Oktober
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Discount strategies play a critical role in e-commerce profitability, yet most platforms continue to rely on fixed discount rates that fail to account for heterogeneous customer behavior. This study proposes a dynamic discount optimization framework based on the Q-Learning algorithm, in which discount decisions are modeled as a Markov Decision Process (MDP) with a state space constructed from two customer behavioral indicators: transaction revenue and purchase frequency. Each customer transaction is mapped to one of six discrete states formed by combining three revenue categories (Low, Medium, High) and two frequency categories (Low, High), and the agent selects from five discount levels (0%, 5%, 10%, 15%, 20%) to maximize cumulative profit. A price elasticity mechanism is incorporated into the reward function to simulate demand responsiveness to price reductions, enabling the agent to learn non-trivial discount preferences. The framework is evaluated on the Online Retail II dataset comprising 397,885 cleaned transactions. Experimental results show that the proposed method achieves a total profit of 10,586,828.77, outperforming four of five fixed discount baselines with profit improvements of +18.80%, +11.16%, +5.60%, and +1.65% over the 0%, 5%, 10%, and 15% uniform discount scenarios, respectively. The learned policy consistently assigns 15% discounts to Low-frequency customers and 20% discounts to High-frequency customers, demonstrating that purchase frequency is the primary driver of optimal discount differentiation. These findings confirm that RL offers a more targeted and profit-competitive alternative to static promotional strategies
Co-Authors Al Khowarizmi Albar, Rizka Amri Ismail Tumanggor Andre Hasudungan Lubis Andre Hasudungan Lubis Arief Goeritno Aripin Rambe Ayu Pariyandani Azmi, Fadhillah Cahyo Hasanudin Cut Lika Mestika Sandy Cut Try Utari Deti Indah Kiranti Diah Ayu Larasati Dian Ifantiska Dina Maizana Dinur Syahputra Dwipayana, Mahendar Effiati Juliana Hasibuan Eka Pirdia Wanti Ellis Susmawati Esrayanti Simanjuntak Essay Puspita Sitopu FADHILLAH AZMI Fadli, MHD. Fajar Alry Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fauzi FAUZI . Fawwaz, Insidini Fitra , Akbario Gultom, William Habib Satria Hashina Qiamu Mumtaziah Hayani Wulandari Idrus, Syed Zulkarnain Syed Indra Muda Ira Safira Ira Safira Juliansyah Putra Tanjung Karynda Natalie Theofilus Leonardi Paris Hasugian M. Hamdani Santoso Maghfirah Maghfirah Mahardika Abdi Prawira Tanjung Mahmudah Salwa Gianti Marpaung, Febriady Melisah Melisah Merri Hafni Moulando Tampubolon Muchammad Takdir Sholehati Muhammad Fadlan Siregar Muhammad Fauzy Mungkin, Moranaim N P Dharshinni Nadzifah Nadzifah Nanda Novita Napisah, Napisah Nasution, Annisa Neneng Yulia Barky Noor, Fredy Nugraha Rahmadan Diyanto Nurul Khairina Pariyandani, Ayu Purba, Sentia Ovania Rahman, Sayuti Rambe, Yunita Syafitri Reydo Trisno Pangestu Reyhan Achmad Rizal Rifa Alia Syahidah Rizki Muliono Saufa Yardha Moerni Sibarani, Theofil Tri Saputra Simangunsong, Roy Candra Simanjuntak, Juan Siregar, Erlina Sri Juwita Sri Wahyuni Subairi Subairi Susilawati Susilawati Syahputra, Dinur Syahputra, Dinur Syifaul Fuada Syuhada, Rahmad Taufik Ismail Simanjuntak Taufik Ismail Simanjuntak Theofil Tri Saputra Sibarani Tika Ermita Wulandari Wahyu Hidayah Wanti, Eka Pirdia Wibawa, M. Bayu Yahya, Yanawati Binti Yanawati Yahya Yopan Rahmad Aldori Yuhefizar Yuhefizar Zebua, Meniati Zuhar Musliyana, Zuhar Zulfikar Sembiring Zulfikar Sembirirng