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All Journal Elkom: Jurnal Elektronika dan Komputer CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika JISTech (Journal of Islamic Science and Technology) IJISTECH (International Journal Of Information System & Technology) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Riset Informatika Technologia: Jurnal Ilmiah TIN: TERAPAN INFORMATIKA NUSANTARA Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Teknologi Informasi dan Komunikasi IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Sistem Pendukung Keputusan dengan Aplikasi DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Internet of Things and Artificial Intelligence Journal Jurnal Ekonomi, Teknologi dan Bisnis Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas
Aidil Halim Lubis
Universitas Islam Negeri Sumatera Utara
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PERANCANGAN APLIKASI PENCARIAN LOKASI VAKSIN MENGGUNAKAN METODE HAVERSINE BERBASIS ANDROID Adjie Prakasa Viragupty; Yusuf Ramadhan Nasution; Aidil Halim Lubis
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 1 (2024): February 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i1.1673

Abstract

Abstract: Searching for the location of Health Facilities that are still serving the Covid 19 vaccination with the closest distance to the user's position using the Haversine Formula and Google Maps as a support. Haversine Formula is an equation that gives the great circle distance (radius) between two points on the surface of the ball (earth) based on longitude and latitude From the results of this study, the Design Of A Vaccine Location Search Application Was Created Using The Android-Base Haversine Method to determine the closest distance of the location of health facilities that still serve the Covid 19 vaccination to the user's location. In searching forthe location of Health Facilities that are still serving the Covid 19 vaccination, the data used comes from the database server. The device used must have a GPS and an internet connection. Based on speed trials in providing location recommendations based on the closest mileage, the environment and weather can affect the speed in providing healthfacility location recommendation. Keywords: Vaccin; Covid-19; Haversine Abstrak: Pencarian lokasi faskes yang masih melayani vaksinasi covid 19 dengan jarak terdekat dengan posisi pengguna menggunakan Haversine Formula serta Google Maps sebagai pendukung. Haversine Formula merupakan sebuah persamaan yang memberikan jarak lingkaran besar (radius) antara dua titik pada permukaan bola (bumi) berdasarkan garis bujur dan lintang. Dari hasil penelitian ini, tercipta Perancangan Aplikasi Pencarian Lokasi Vaksin Menggunakan Metode Haversine Berbasis Android untuk menetukan jarak terdekat lokasi Faskes yang masih melayani vaksinasi covid 19 dengan lokasi pengguna. Dalam pencarian lokasi fasilitas kesehatan yang masih melayani vaksinasi covid 19, data yang digunakan berasal dari database server. Device yang digunakan harus memiliki GPS dan koneksi internet. Berdasarkan uji coba kecepatan dalam memberikan rekomendasi lokasi berdasarkan jarak tempuh terdekat, lingkungan dan cuaca dapat mempengaruhi kecepatan dalam memberikan rekomendasi lokasi fasilitas kesehatan yang masih melayani vaksinasi covid 19 terdekat dengan lokasi user. Kata kunci: Vaksin; Covid 19; Haversine
Analisis Sentimen Masyarakat Terhadap Resesi Ekonomi Global 2023 Menggunakan Algoritma Naïve Bayes Classifier Sriani; Aidil Halim Lubis; Yunus Fadillah Harahap
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 2 (2023): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i2.1673

Abstract

The global economic recession is a global economic downturn that affects the domestic economies of countries in the world. The stronger the economic dependence of one country on the global economy, the faster a recession will occur in that country. In 2020 the country of Indonesia and even the world are exposed to the COVID-19 virus which has an impact on the country's economic growth, even the world economy. This is the trigger for an economic recession. This has led to many different public perspectives on the occurrence of a global economic recession whose opinions or reactions are expressed on social media Youtube. The data was obtained by crawling techniques from social media Youtube with a total of 500 comments used. The data is then labeled (class) with a lexicon-based method with an Indonesian language dictionary. From the labeling results, it was obtained 185 positive labeled data (37%) and 315 negative opinions (63%). The data preprocessing stage is carried out in preparation for the data to be processed for sentiment analysis. Of the many opinions obtained, an analysis of public sentiment regarding the 2023 global economic recession will be carried out using the Naïve Bayes classification algorithm. This study also applied the TF-IDF word weighting method with the n-gram feature used, namely bigram (n=1). The system will be evaluated using a confusion matrix. The implementation results show a prediction model with a total of 500 opinion data with a comparison of training data and test data of 9:1, producing an accuracy value of 84.00%, a precision value of 75.00%, a recall of 30.00%, and an f1-score of 42.86%. The performance of the system model built in this study can be said to be good.
IMPLEMENTASI SISTEM INFORMASI PENGELOLAAN BARANG INVENTARIS MILIK NEGARA STUDI KASUS BALAI DIKLAT KEAGAMAAN MEDAN Monica Situmeang; M Alif Fahrezy; Shella Fahdilla Sari; Aidil Halim Lubis
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 5 No 4 (2023): EDISI 18
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v5i4.3504

Abstract

Dalam era ini Teknologi memegang peranan sangat penting dalam meningkatkan efisiensi kegiatan pemerintahan. Barang Milik Negara (BMN) merupakan aset yang wajib dipertanggungjawabkan oleh penguasa yang memilikinya. Kajian BMN Medan mengangkat persoalan barang milik negara yang diangkut dari ruangan ke ruangan tanpa sepengetahuan pengelola, sehingga berdampak pada pengelolaan barang tanpa memperhatikan data sebenarnya di lapangan. Tujuan dari penelitian ini adalah mengimplementasikan sistem informasi SIMA agar pendataan angkutan barang  lebih efektif. Metode deskriptif kualitatif  digunakan untuk membantu pengguna sistem informasi SIMAN Pusdiklat Keagamaan Medan agar lebih memahami sistem informasi tersebut. Penelusuran menemukan bahwa sistem informasi tidak efektif dalam pengelolaan barang milik negara di Pusdiklat Keagamaan Medan  karena kurangnya pelatihan ulang dalam penggunaan sistem informasi dan kurangnya kewenangan sebelumnya dalam mengelola barang tersebut. Oleh karena itu, pemahaman penggunaan sistem informasi SIMA berdampak signifikan terhadap efektivitas pengelolaan properti nasional.
Sentiment analysis on twitter about the death penalty using the support vector machine method Sriani; Aidil Halim Lubis; Lia Putri Ashari Lubis
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 11 No 2 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK-Sekolah Tinggi Teknologi Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v11i2.1096

Abstract

It is estimated that 175 million people in Indonesia utilize the Internet, according to the most recent We Are Social survey. 160 million of them are internet users who utilize social media, according to this data. It is estimated that 19.5 million Indonesians use Twitter. This is consistent with the numerous tweets that users have posted on Twitter about a variety of topics, including politics, music, health, and education. The death penalty is still one of the most popular subjects that is addressed on Twitter. When a judge rules that someone will be executed as retribution for a crime they have committed, this is referred to as the death penalty. As a result, sentiment analysis utilizing the Support Vector Machine technique with linear kernel features and Python programming was used to study public opinions on the death sentence. To improve the accuracy of the results obtained, data labeling on 848 data that were received through the scraping process was done manually in this study. Positive data is categorized as belonging to the class that supports the death sentence, while negative data is categorized as belonging to the class that opposes it. The study that was done shows an 8:2 difference between the training and test data. After preprocessing a dataset containing 758 data points, of which 606 will be utilized for training and 152 for testing, we obtain 91% accuracy, 91% precision, 100% recall, and 95% f1-score
Islamophobia Sentiment Classification Using Support Vector Machine Lubis, Aidil Halim
Journal of Intelligent Computing & Health Informatics Vol 3, No 2 (2022): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v3i2.11179

Abstract

Sentiment analysis is the process of understanding and classifying words into several categories. It is also known as opinion mining, which involves exploring opinions and emotions from text data. Sentiments can be classified into positive, negative, and neutral categories. Islam is a religion that has been in existence for centuries. Its teachings aim to foster peace and surrender to its creator, namely Allah SWT. The constructivist view of Islam has given rise to Islamophobia, which is the result of a long-standing construct that presents a negative image of Islam. Currently, Islamophobia is a growing issue that generates diverse views, especially on social media platforms. The analysis was conducted using the SVM algorithm and a dataset comprising 1000 tweets sourced from Twitter. The algorithm achieved an accuracy rate of 99.99% after testing, indicating its suitability for sentiment analysis. The error rate generated using MSE was 0.010, while the RMSE was 0.099.
Penerapan Metode Simple Multi Attribute Rating Technique pada Pemilihan Cafe Terfavorit Suhardi; Lubis, Aidil Halim; Aprilia, Annisa; Ningrum, Indri Ayu
Sistem Pendukung Keputusan dengan Aplikasi Vol 2 No 1 (2023)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v2i1.114

Abstract

Banyaknya jumlah kafe yang ada di kota Medan khususnya di kawasan pemancingan membuat sebagian orang kesulitan untuk memilih kafe dengan kenyamanan yang baik untuk menghabiskan waktu bersama teman dan keluarga, baik itu untuk mengerjakan tugas maupun menghabiskan waktu bersama orang tersayang. Tujuan dari penelitian ini adalah untuk membantu pengunjung khususnya di area pemancingan yang kesulitan menemukan kafe terfavorit dengan kriteria dan bobot tertentu dengan melakukan observasi langsung di lapangan. Pada penelitian ini mengembangkan sistem pendukung keputusan yang menerapkan metode Simple Multi-Attribute Rating Technique (SMART) untuk menentukan kafe favorit di area pemancingan, dari hasil wawancara dengan beberapa pengunjung dan pihak terkait, dengan ini peneliti memperoleh beberapa dari data yang akan dibutuhkan seperti, kriteria dan bobot serta alternatif apa yang digunakan melalui penilaian dalam penelitian, sedangkan kriteria dan bobot yang digunakan sudah ditentukan sesuai dengan selera pengunjung, seperti kualitas pelayanan, harga, fasilitas, suasana, dan kepuasan pelanggan serta 25 alternatif yang akan dipertimbangkan dalam pemilihan kafe favorit di area pemancingan. Hasil pemeringkatan yang diperoleh dari penelitian ini adalah kafe Labasta dengan skor tertinggi yaitu 16.00 dipilih dan juga direkomendasikan sebagai kafe terfavorit di kawasan pemancingan. Sehingga penelitian ini dapat membantu menyelesaikan permasalahan di daerah pemancingan dengan menghasilkan keputusan penentuan kafe favorit melalui sistem pendukung keputusan dengan metode SMART.
Decision Support System For Chicken Animal Feed Selection Using The Fuzzy Tsukamoto Method Wahyuni, Sri; Furqan, Mhd.; Lubis, Aidil Halim
IJISTECH (International Journal of Information System and Technology) Vol 7, No 5 (2024): The February edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i5.330

Abstract

Selection of chicken feed is a fairly important decision support process. This decision support system was developed to assist breeders in choosing chicken feed based on predetermined criteria and alternatives. In this study using the Tsukamoto fuzzy method which produces a model of a system that can provide recommendations for choosing chicken feed that is applied in a decision support system. The Tsukamoto fuzzy method in determining the selection of chicken feed is based on 3 variables, namely price, quality and stock. Each variable consists of 3 sets which are combined in order to obtain 4 fuzzy rules, which are then used in the inference stage. The choice of chicken feed to be recommended (z) is searched by the centralized average defuzzification method. Testing will be carried out objectively where the decision support system is tested directly for capacity and filling out a questionnaire regarding satisfaction with the content of the point requirements and distributed to the owner of the animal feed shop. With this test, it can be seen that the features provided are easy to learn and easy to understand.
Literasi Digital : Pemanfaatan dan Penggunaan E-Library Menggunakan Software SLiMS" di Desa Denai Lama, Pantai Labu-Deli Serdang Zufria, Ilka; Hasugian, Abdul Halim; Suhardi; Hasibuan, Muhammad Siddik; Lubis, Aidil Halim; Armansyah
Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2022): Juni 2022
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v1i1.7

Abstract

Information technology has developed very rapidly and covers various fields. The field of education is one area that is influenced by information technology. Both in the formal learning process at school and non-formal in the form of training outside of school. The form of participation from universities, especially the Computer Science study program, FST UIN North Sumatra Medan, in this community service activity is to provide skills training in the field of information technology in the form of digital literacy and the use of SLiMS software to the Circle Community Reading Park (TBM), Denai Lama Village, Labu Beach. Deli Serdang, North Sumatra which was held with the theme "Digital Literacy: Utilization and Use of E-Library Using SLiMS Software".
Decision Support System For Chicken Animal Feed Selection Using The Fuzzy Tsukamoto Method Wahyuni, Sri; Furqan, Mhd.; Lubis, Aidil Halim
IJISTECH (International Journal of Information System and Technology) Vol 7, No 5 (2024): The February edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i5.330

Abstract

Selection of chicken feed is a fairly important decision support process. This decision support system was developed to assist breeders in choosing chicken feed based on predetermined criteria and alternatives. In this study using the Tsukamoto fuzzy method which produces a model of a system that can provide recommendations for choosing chicken feed that is applied in a decision support system. The Tsukamoto fuzzy method in determining the selection of chicken feed is based on 3 variables, namely price, quality and stock. Each variable consists of 3 sets which are combined in order to obtain 4 fuzzy rules, which are then used in the inference stage. The choice of chicken feed to be recommended (z) is searched by the centralized average defuzzification method. Testing will be carried out objectively where the decision support system is tested directly for capacity and filling out a questionnaire regarding satisfaction with the content of the point requirements and distributed to the owner of the animal feed shop. With this test, it can be seen that the features provided are easy to learn and easy to understand.
PENERAPAN DATA MINING UNTUK PREDIKSI PENJUALAN PRODUK ELEKTRONIK TERLARIS MENGGUNAKAN METODE K-NEAREST NEIGHBOR Sriani Sriani; Aidil Halim Lubis; Ridho Rizky Nasution
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2153

Abstract

Penjualan produk elektronik merupakan bagian integral dari pasar yang terus berkembang dengan cepat. Dalam konteks ini, penerapan teknik Data Mining menjadi penting untuk mengungkap pola dan wawasan yang tersembunyi dalam data penjualan, dengan tujuan utama memprediksi produk elektronik terlaris. Penelitian ini fokus pada penerapan metode K-Nearest Neighbor (KNN) sebagai alat untuk mencapai prediksi yang akurat. Metode KNN adalah algoritma yang berdasarkan pada konsep bahwa entitas cenderung memiliki kinerja serupa jika mereka berdekatan dalam ruang fitur. Dalam konteks penjualan produk elektronik, KNN digunakan untuk mengidentifikasi pola dari sejumlah besar data penjualan, yang mencakup variabel-variabel seperti harga dan jumlah terjual. Dengan menganalisis pola ini, algoritma KNN dapat memprediksi produk elektronik yang kemungkinan besar menjadi produk terlaris di masa depan. Penelitian ini melibatkan langkah-langkah penting seperti pra-pemrosesan data, pemilihan parameter K dalam KNN, validasi model, dan pengukuran akurasi. Hasil penelitian ini berupa akurasi dalam melakukan prediksi dengan nilai 92% Dari total keseluruhan jumlah produk yang terjual adalah 491 produk. Secara keseluruhan penelitian ini menunjukkan bahwa penerapan Data Mining dengan metode KNN memiliki potensi untuk meningkatkan pemahaman tentang tren penjualan produk elektronik dan memberikan informasi berharga untuk prediksi produk terlaris di masa mendatang. Keakuratan prediksi dapat ditingkatkan dengan mempertimbangkan variabel tambahan dan menggabungkan metode analisis lainnya.
Co-Authors Abdul Halim Hasugian Adjie Prakasa Viragupty Algifahri, Muhammad Dzar Annisa Aprilia Armansyah As’Ary Sahlul Irsyad Darisma Daulay Desmi Roma Putra Lubis Dimas, Dimas Erma Julita, Erma Faris Jihad Galang Desdwiansyah Hazizah Ulfa Nasution Husein Nur Ansyari Ilka Zufria istiqomah istiqomah Jihan Ulfa Deski Kiki Widya Pratiwi Lia Putri Ashari Lubis M Alif Fahrezy Mhd Furqan Monica Situmeang Muhammad Alwi Baihaqi Muhammad Fadiga Muhammad Ihsan Nugraha Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad Zarlis, Muhammad Ningrum, Indri Ayu Nurmaiyah, Nurmaiyah Pandu Wicaksono Putra, Donny Dwi Qori Siagian Rahman, Anisa Rahman, Elsa Azila Rakhmat Kurniawan R Ridho Rizky Nasution Rizky Pulungan, Miftahul Santoso, Heri Shella Fahdilla Sari Siregar, Muhaimi Rizki Siregar, Romadon Goring Sofiah Sri Wahyuni Sriani Sriani Suhardi Suhardi Suhardi Supiyandi Supiyandi Tasya, Yulianda Yunus Fadillah Harahap Yusuf Ramadhan Nasution Zulfi, Tio Fahreza Zulfi