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All Journal Teknika CESS (Journal of Computer Engineering, System and Science) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) INFOKUM International Journal of Engineering, Science and Information Technology Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Journal of Renewable Energy, Electrical, and Computer Engineering TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Journal of Advanced Computer Knowledge and Algorithms Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Safwandi Safwandi
Fakultas Teknik Universitas Malikussaleh
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Implementation of Simple Exponential Smoothing and Weighted Moving Average in Predicting Netflix Stock Prices Sadewa, Bima; Safwandi, Safwandi; Fajriana, Fajriana
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.708

Abstract

This study aims to develop a stock price prediction system for Netflix using the Simple Exponential Smoothing and Weighted Moving Average methods and evaluate the accuracy of both methods. The system provides future stock price estimates based on historical data and includes evaluation metrics such as Mean Absolute Error and Mean Absolute Percentage Error. The implementation results show that SES achieved an MAE of 4.40 and a MAPE of 1.08%, while WMA resulted in an MAE of 8.65 and a MAPE of 2.11%. These findings indicate that SES is more effective in predicting stock prices with lower error rates, particularly for stable historical data. In contrast, WMA is more responsive to short-term trends but less accurate overall. Based on the results, SES is recommended as the developed system's primary method for stock price prediction.
Supporting Application Fast Learning of Kitab Kuning for Santri' Ula Using Natural Language Processing Methods Zaman, Qamaruz; Safwandi, Safwandi; Fajriana, Fajriana
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.713

Abstract

Education in Islamic boarding schools is one of Indonesia's traditional forms of education that teaches Islamic religious teachings, including studying the yellow classic books as the primary source of spiritual learning. However, learning the Yellow classic book is often complicated by 'ula students (early level students) because Arabic is without harakat or lines, and the material studied is very complex. To overcome these challenges, this research aims to develop a yellow Islamic classic book learning support application for 'ula students using the Natural Language Processing (NLP) method. This application has an interactive chatbot feature that helps students understand the contents of the yellow book more effectively and enjoyably. The research method includes literature study, data collection, data processing, and system development using the Sparse Categorical Cross Entropy algorithm in Natural Language Processing to improve the accuracy of chatbot responses. This application provides an innovative solution by presenting an interactive learning experience that can be accessed anytime and anywhere, thus facilitating Santri learning outside the boarding school environment. The results show that learning for 'ula students with the Natural Language Processing method is very good and easy to understand. The test shows that the accuracy of the application reaches 100% with a low error value (loss), which is 0%. It can be recognized that the effectiveness of Natural Language Processing in supporting yellow book learning, maintaining the tradition of Islamic education in the digital era, and helping teachers and parents monitor the development of students.
SISTEM PENGENALAN POLA MAD IWAD PADA CITRA AL-QUR`AN DENGAN MENGGUNAKAN METODE COSINE Munauwarah, Munauwarah; Safwandi, Safwandi; Agusniar, Cut
Jurnal Teknologi Terapan and Sains 4.0 Vol 5 No 3 (2024): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v5i3.19680

Abstract

Mempelajari ilmu Al-Qur'an sesuai dengan hukum dan kaidah tajwid yang benar adalah kewajiban, karena kesalahan dalam pengucapan huruf Al-Qur'an dapat mengubah maknanya. Dalam Al-Qur'an, terdapat berbagai tanda khusus seperti hukum tajwid dan hukum mad, yang umumnya dipelajari dengan bimbingan guru ahli Al-Qu`an. Namun, metode belajar langsung dari guru menjadi kurang efisien di era modern ini, yang menuntut cara lebih praktis karena keterbatasan waktu dan akses. Seiring perkembangan teknologi, dibutuhkan sistem yang mampu mengenali hukum tajwid, khususnya mad iwad, melalui citra yang diinputkan secara digital. Program ini dirancang untuk memudahkan pengenalan pola mad iwad yang terdapat di dalam Al-Qur'an. Penelitian ini menjelaskan bahwa pola dideteksi melalui beberapa tahap, yaitu resize gambar, konversi ke citra grayscale, dan dilanjutkan dengan konvolusi. Proses pendeteksian pola mad iwad, khususnya pada surah Abasa, menggunakan metode Cosine yang menghitung nilai citra berdasarkan koordinasi dan piksel citra tersebut. Hasil penelitian menunjukkan bahwa sistem pengenalan pola mad iwad pada surah Abasa ini mencapai detection rate sebesar 85%. Ini membuktikan bahwa metode Cosine efektif dan dapat diterapkan sebagai salah satu pendekatan untuk mendeteksi pola mad iwad dalam citra Al-Qur'an. Namun, efektivitas sistem ini bergantung pada kualitas citra, semakin jelas citra yang diinput, semakin mudah sistem dalam mendeteksinya.Kata kunci: Sistem pengenalan pola, Mad Iwad, Metode Cosine, Surah Abasa
Implementation of Complex Proportional Assessment Method in Determining Prioritization of Beneficiary Groups Fish Seeds in Lhokseumawe City Ramadhani, Putri Yesi; Safwandi, Safwandi; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.754

Abstract

The fisheries sector in Lhokseumawe City has an essential role in the regional economy, but the limited allocation of fish seed assistance requires an efficient and objective decision-making system (SPK). This research applies the Complex Proportional Assessment (COPRAS) method to prioritize groups of fish seed aid recipients. COPRAS was chosen because it can handle quantitative and qualitative criteria and produce a clear ranking of alternatives. The system evaluates criteria such as pond area, number of members, pond condition, and group age. The results showed that the Tani Mandiri group had the highest utility value = 1, while Tani Maju Berkah obtained the lowest value = 0.655. The COPRAS method effectively provided accurate and transparent recommendations in determining beneficiaries. Implementing this system is expected to help the Lhokseumawe City Marine, Fisheries, Agriculture, and Food Service Office allocate fairer and more targeted assistance, as well as increase the fisheries sector's productivity in the area. This research also contributes to developing technology-based decision-making systems to support government policies.
Optimalisasi Lokasi Pembangunan Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) Menggunakan Sistem Informasi Geografis Di Kota Medan Dengan Metode Analisis Buffer Veirrel, Dwi Harsya Ramadhan; Safwandi, Safwandi; Fajriana, Fajriana
TEKNIKA Vol. 19 No. 2 (2025): Teknika Mei 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14936546

Abstract

Perubahan iklim global dan kebutuhan yang sangat mendesak untuk mengurangi emisi karbon membuat kendaraan listrik semakin menarik untuk dijadikan sebagai solusi transportasi ramah lingkungan. Namun, salah satu tantangan dalam mendukung penggunaannya ialah kurangnya infrastruktur pengisian daya yang memadai, seperti Stasiun Pengisian Kendaraan Listrik Umum (SPKLU). Penelitian ini bertujuan untuk menentukan lokasi terbaik untuk pembangunan SPKLU di Kota Medan dengan memanfaatkan teknologi Sistem Informasi Geografis (SIG) dan metode analisis buffer. Data geografis dan deimografis Kota Meidan digunakan seibagai dasar analisis, deingan meimpeirtimbangkan faktor-faktor seipeirti keipadatan peinduduk, akseisibilitas, dan keibeiradaan fasilitas umum. Meilalui analisis buffeir, zona strateigis diteintukan beirdasarkan radius peingaruh 100 meiteir, 300 meiteir, dan 500 meiteir dari titik poteinsial. Hasil peineilitian meinunjukkan bahwa peindeikatan ini eifeiktif untuk meineintukan lokasi yang ideial, meimudahkan akseis, dan meindukung eifisieinsi opeirasional. Peineilitian ini beirhasil meingideintifikasi beibeirapa lokasi strateigis untuk peimbangunan SPKLU di Kota Medan, yang diharapkan dapat meningkatkan kenyamanan pengguna kendaraan listrik dan mempercepat pengurangan emisi karbon. Sebagai rekomendasi, pemerintah daerah dan pengembang infrastruktur disarankan untuk memprioritaskan pembangunan SPKLU di zona-zona strategis yang telah ditentukan.
DECISION SUPPORT SYSTEM USING WEIGHTED PRODUCT METHOD IN CHIPS MATERIAL SELECTION (CASE STUDY: HASTI FAMILY CHIPS BUSINESS) Luqman Nul Hakim; Safwandi; Risawandi
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 4 No. 4 (2024): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v4i4.2406

Abstract

This study designs a decision support system to help the owner of the Hasti Family chips business choose the optimal raw materials in making cassava, banana, and breadfruit chips. The Weighted Product (WP) method is used as a multi-criteria decision-making method by considering criteria such as chip color, chip texture, chip taste, chip durability and fruit price. Criteria data and alternative raw materials are processed using WP calculations to produce the best alternative ranking. The result is a web-based decision support system that implements the WP method, presents an interface for entering data and displays the best alternative ranking. This system improves the efficiency of decision-making, minimizes the risk of selecting inappropriate raw materials, improves product quality, and supports business growth. The results of the research on the decision support system for selecting chips ingredients show that this system determines the best ingredients by finding the final value of the V vector search from 3 cassava data, 3 banana data and 3 breadfruit data that will be entered into the system and get results from butter cassava, which has the highest V value of 0.38311467, followed by wak banana with an impressive V value of 0.398763354, and Bali breadfruit, which has a prominent V value of 0.350015233. The conclusion of this study is that the designed application is able to optimize the process of selecting raw materials for chip production more efficiently, quickly, and this system not only accelerates decision making but also ensures more structured and reliable data recording.
Implementation Of Agglomerative Clustering Method On Mapping Crime-Prone Areas Of Webgis-Based Lhokseumawe City Case Study Of Lhokseumawe Prosecutor's Office Teuku Ibrar Faturrahman Ibrar; Safwandi Safwandi; Zahratul Fitri Zahratul Fitri
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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

Abstract

The application of the Agglomerative Hierarchical Clustering method was carried out for mapping the Lhokseumawe City area, with a focus on sub-districts grouped by village and their crime rates. The types of crimes analyzed include drugs, oharda (violations of public order and security), and kamtibum (public order and security). The data used came from the Prosecutor's Office and was taken through the Department of Law, covering various crimes that are very detrimental to society. By utilizing Geographic Information System (GIS) technology, this system can provide clear visual information about the location of criminal incidents and the types of crimes that occur in each village. This clustering process allows for the grouping of villages that tend to have high crime rates, thus helping to identify areas that require more attention in law enforcement. The application of this clustering is not new, because previously many researchers and scientists have applied similar methods, but with different case studies. In this context, clustering helps provide more detailed insights into the distribution of crime at the village level, allowing for more focused and targeted prevention efforts.
Implementation Of The Support Vector Machine Method In Determining The Best Quality Of Sap Azhari Putra Sayani; Safwandi; Fajriana
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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

Abstract

Rubber trees (Hevea brasiliensis) are the main source of natural rubber and play an important role in Indonesia's industry. Determining the quality of rubber sap is a challenge for companies, as traditional manual processes are time-consuming and prone to human error. PT Poly Kencana Raya, a company in Besitang, North Sumatra, currently still uses conventional methods in determining the quality of rubber latex it produces. This research aims to design a web-based system with the application of the Support Vector Machine (SVM) method to facilitate the determination of rubber latex quality. SVM was chosen as a classification method because of its ability to determine the optimal hyperplane that can separate data from two different classes, namely feasible and unfit. The built system utilizes the main criteria such as tree age, tapping time, moisture content, color, and texture in determining the quality of the sap. Implementation. This study used 120 samples of test data, with accurate prediction results on 111 data, resulting in an accuracy rate of 92.5%. This decision support system is expected to increase efficiency and accuracy in rubber sap selection and support the development of rubber production quality in Indonesia. This research also opens up opportunities for further development by adding other classification methods for accuracy comparison or adding training data to optimize prediction results. Keywords: Rubber Trees, Support Vector Machine, Data Mining
Implementasi Data Mining Penentuan Daya Pelanggan Baru untuk Klasifikasi Subsidi dan Non Subsidi di Wilayah PLN Kota Lhokseumawe Andik Bintoro; Safwandi Safwandi
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 2 No. 2 (2018): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2018
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v2i2.1011

Abstract

Penerapan model data mining dalam klasifiaksi K-Nearest Neighbor (KNN) dalampenentuan Daya Pelanggan Baru untuk Klasifikasi Subsidi dan Non Subsidi diWilayah PLN Kota Lhokseumawe sangatlah perlu untuk dilakukan. Hal ini untukmengetahui pelanggan PLN dalam klasifikasi pengelompokkan berdasarkandengan variable yang digunakan. Pelanggan baru PLN yang ingin mengetahuiberapa klasifikasi pengelompokkan listrik untuk pasang baru dapat menggunakan aplikasi ini dalam penentuan besaran daya yang digunakan untuk pasang baru. Variable yang digunakan adalah untuk K1 adalah pendapatan keluarga secara keseluruhan, K2 adalah pekerjaan orang tua, K3 adalah pekerjaan orang tua, K4 adalah luas rumah. Dari variable ini akan dimasukkan kedalam sistem dengan sub kriteria yang akan dimasukkan. Adapun Golongan tarif daya listrik subsidi terbagi menjadi dua yaitu Tarif R-1/450 VA untuk penggolongan K1 dan golongan R-1/900 VA Subsidi Tarif R-1/586 kWh untuk penggolongan K2, sedangkan Golongan K3 non subsidi Tarif R-1/1352 VA untuk rumah tangga mampu. Tujuan dari penelitian ini adalah memudahkan pelanggan baru dalam penentuan golongan yang diberikan oleh pihak PLN kota lhokseumawe dan pelanggan mengetahui besaran yang akan digunakan. Sehingga pelanggan kota lhokseumawe dapat melihat besaran jumlah daya yang diberikan. Model klasifikasi KNN menggunakan data training untuk di uji coba dengan data pengujian untuk pelanggan baru dan hasilnya dari nilai terdekat dari data training yang telah diujikan. Dalam penelitian ini data training yang digunakan adalah 30 data training, hal ini berguna untuk nilai pengujian lebih akurat dan hasil yang diharapkan menjadi lebih baik. Untuk pengujian V1 adalah dengan nilai 3, untuk kriteria V2 adalah 3, dan nilai variabel V=3 adalah 2 dan nilai variabel terakhir V4 adalah 1. Selanjutnya untuk hasil pengujian dari pelanggan baru adalah termasuk kedalam golongan subsidi R-1/900 VA Subsidi Tarif R-1/586 kWh yang telah dilihat dari hasil training. Hasil dari aplikasi ini dapat menampilkan besaran daya yang digunakan untuk pelanggan baru berdasarkan nilai pengujian yang dilakukan.Kata kunci : Klasifikasi, Daya Listrik ,KNN
Co-Authors Andik Bintoro Annisa raihan asmaul husna Asri Anda Azhari Putra Sayani Cut Agusniar Dahlan Abdullah Diana Diana Eva Darnila Fadisar, Nanda Fadlisyah Fadlisyah Fajriana Fajriana, Fajriana Hamdi Akmal Lubis, Hamdi Akmal Luqman Nul Hakim Maryana Maryana Mirza Farhan Misbahul Jannah Mochamad Ari Saptari Muhammad Aldonny Altharizka Muhammad Fikry Muhammad Muhammad Muhammad Sadli, Muhammad Mukti Qamal Munauwarah, Munauwarah Muthmainnah Muthmainnah Novia Hasdyna Nurwijayanti Putri, Riska Yolanda Rahmad Wahyudi Ramadhani, Putri Yesi Rini Meiyanti Risawandi, Risawandi Rizky Putra Fhonna Rozzi Kesuma Dinata Sadewa, Bima Teuku Ibrar Faturrahman Ibrar Tri Wulandari Veirrel, Dwi Harsya Ramadhan Veri Ilhadi Yenni Maulida Yulidayanti, Yulidayanti - Zahratul Fitri Zahratul Fitri Zaman, Qamaruz Zara Yunizar Zuraida Zuraida