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Aidilof, Hafizh Al Kautsar
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Review AHP dalam Fenomena Gelumbung Ekonomi Asrianda, Asrianda; Aidilof, Hafizh Al Kautsar; Rosnita, Lidya; Zulfadli, Zulfadli
TECHSI - Jurnal Teknik Informatika Vol 14, No 1 (2023)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v14i1.12588

Abstract

Keinginan memperoleh keuntungan didasarkan pada sifat kerakusan pada diri seseorang sehingga harga komoditas tidak akan turun dan semakin naik, kosekuensinya masyarakat berusaha untuk memiliki barang sebanyak mungkin sehingga harga naik dan mendapat keuntungan yang banyak. Mencari penyebab alasan menurun minat masyarakat terhadap barang akibat gembung ekonomi yang ada dipasaran. AHP menggabungkan pertimbangan dan penilaian pribadi dengan cara yang logis dan dipengaruhi imajinasi, pengalaman, dan pengetahuan untuk menyusun hierarki dari suatu masalah yang berdasarkan logika, intuisi dan juga pengalaman untuk memberikan pertimbangan. Dari hasil perhitungan menggunakan metode AHP dapat diambil kesimpulan bahwa minat tren gelumbung ekonimi dimasyarakat Aceh khususnya Lhokseumawe disebakan oleh nilai seni dari barang yang menjadi minat dimasyarakat. Dengan perhitungan yang tersebut sesuai dengan hasil penilaian responden yang telah peneliti lakukan menggunakan metode AHP.
Pelatihan dan Pendampingan Teknologi Informasi Pengembangan Gampong Digital Gampong Uteunkot Berbasis Web di Kota Lhokseumawe Ilhadi, Veri; Aidilof, Hafizh Al Kautsar; Fakhrurrazi; Sahputra, Ilham; Zohra, Siti Fatimah A; Angelina, Difa
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 5 No. 3 (2024): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v5i3.1064

Abstract

This program aims to enhance information technology capabilities in Uteunkot Village, Lhokseumawe City, focusing on developing web-based digital villages. The initiative includes training and assistance for village residents to support the village apparatus in public services, archiving, and marketing for MSMEs. The training aims to facilitate archiving at the Geuchik office through digital public service and archiving socialization, accompanied by website development training for the village. The web application is designed to present relevant and beneficial information for village residents with an efficient interface. The results of the digital web training and assistance indicate that villages in Indonesia are now more connected and can access broader information, contributing to increased community knowledge. The digitalization of public services has accelerated administrative processes, enhanced transparency, and facilitated interactions between village governments and their residents. Additionally, the training enhances the digital skills of village officials, increasing their capacity to utilize web-based technology. The implications of this training suggest that villages can transform to be smarter and more competitive in the digital era
Water Quality Monitoring and Control System for Tilapia Cultivation Based on Internet of Things Rosnita, Lidya; Ikhwani, Muhammad; Aidilof, Hafizh Al Kautsar; Salamah, Salamah; Hamsi, Widia; Rangkuti, Haris Yunanda
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.566

Abstract

This research analyzes the quality of water for tilapia habitat which is a type of brackish water fish that is currently widely cultivated by pond farmers. This fish is the choice because of its flexibility regarding habitat. However, despite having flexibility in terms of habitat, each harvest of tilapia that lives in a different habitat will produce tilapia with different quantity and quality. Currently, many tilapia farmers still carry out the cultivation process using traditional methods using ponds. Kuala Kerto Village, Lapang District, North Aceh is one of the locations where many tilapia fish farmers use ponds as a habitat for this fish. Not infrequently, changes in natural conditions such as rain and floods have an impact on tilapia fish ponds in this village. Thus, crop yields are very varied, often even resulting in losses. One of the reasons for this is that there is still minimal use of technology in tilapia cultivation in this village. The design of a water quality monitoring and control system for IoT-based tilapia cultivation in this research was carried out to help the problems of tilapia pond farmers. Through this research, a tool was produced in the form of a prototype IoT device that can be used to monitor and control water quality in tilapia fish ponds. This device utilizes several sensors such as turbidity sensors, ammonia sensors, salinity sensors, pH sensors, and several other sensors as data takers which will later be transmitted and displayed via a web application. Research and development of this device uses the RD method, namely research and development.
Classification of Heart Disease Using Modified K-Nearest Neighbor (MKNN) Method Lubis, Aulia Azzahra Ma'aruf; Dinata, Rozzi Kesuma; Aidilof, Hafizh Al Kautsar
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15702

Abstract

Penyakit jantung memiliki banyak jenis dan gejala yang dialami. Penyakit jantung adalah sebuah kondisi ketika organ jantung tidak dapat bekerja sebagaimana fungsinya dengan baik. Jantung adalah organ penting dalam tubuh manusia yang dimana fungsinya adalah memompa darah ke seluruh tubuh. Karena itu dibutuhkannya diagnosa awal untuk pencegahan penyakit jantung dengan memanfaatkan system yang dapat dibuat untuk diagnosa awal pada gejala yang dialami. Yang pada penelitian ini akan menggunakan metode Modified K-Nearest Neighbor (MKNN) dalam mengklasifikasikan penyakit jantung berdasarkan kriteria atau gejala yang ada. Penelitian ini menggunakan 6 kriteria penyakit dan 3 kelas diagnosa penyakit jantung. Dengan melewati beberapa langkah pengerjaan yaitu menghitung jarak Euclidean, menghitung nilai validitas dan terakhir menghitung weight voting dengan mengandalkan nilai K yang telah ditentukan sejak awal perhitungan. Pada penelitian ini telah ditentukan nilai K=5 dan didapat hasil pengujian akurasi sebesar 85%, dengan recall 90% dan precision 85%.
Implementasi Algoritma K-Medoid pada Clustering Sayuran Unggulan di Kabupaten Aceh Utara Meiyanti, Rini; Munauwar, Muhammad Muaz; Fitria, Rahma; Aidilof, Hafizh Al Kautsar
TEKNIKA Vol. 19 No. 1 (2025): Teknika Januari 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14378546

Abstract

Klasterisasi tanaman pada kelompok tani adalah proses pengelompokan tanaman berdasarkan karakteristik tertentu, seperti jenis tanaman, musim tanam, atau lokasi geografis, dengan tujuan meningkatkan efisiensi produksi. Kelompok Tani KWT Meugah Raya masih belum mampu melebihi hasil produksi pertanian sayuran di Aceh Utara. Metode data mining dapat mengidentifikasi pola-pola menarik dalam kumpulan data, salah satunya adalah algoritma K-Medoids clustering yang mengelompokkan data berdasarkan kesamaan karakteristik. Cluster terbentuk dengan menghitung sejauh mana kedekatan antara medoid dan objek non-medoids. Data yang digunakan adalah data dari Badan Pusat Statistik (BPS) pada tahun 2021-2023 di Kabupaten Aceh Utara mengumpulkan data dari 5 kategori sayuran dan 4 variabel, meliputi luas panen, produksi, luas tanaman, dan luas penanaman baru. Melalui algoritma K-Medoids, hasil klastering sayuran unggulan menghasilkan pengelompokan potensi ke dalam 3 klaster, yaitu klaster rendah (C1), sedang (C2), dan tinggi (C3) dengan mengumpulkan macam-macam data sayuran yang ditanam oleh masyarakat setempat berupa cabai besar, kacang panjang, kangkung, terong dan tomat. Langkah berikutnya adalah Menentukan nilai titik pusat awal dengan menyusun data berdasarkan urutan dari yang terendah hingga tertinggi pada setiap data variabel, berdasarkan keseluruhan data yang tersedia. Berdasarkan hasil penelitian ini, metode K-Medoids terbukti sangat efektif dalam melakukan clustering pada data hasil panen tanaman hortikultura. Evaluasi kinerja algoritma dilakukan dengan memanfaatkan Davies-Bouldin Index (DBI) sebagai metode evaluasi, dilakukan pengukuran untuk menilai kualitas pengelompokan yang dihasilkan. Setelah proses evaluasi menggunakan DBI selesai, algoritma K-Medoids memperoleh nilai 0,5537744324187953.
Sentiment Analysis of User Reviews on BSI Mobile and Action Mobile Applications on the Google Play Store Using Multinomial Naive Bayes Algorithm Samudera, Brucel Duta; Nurdin, Nurdin; Aidilof, Hafizh Al Kautsar
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.581

Abstract

Mobile banking services are designed to facilitate customer transactions. Bank Syariah Indonesia (BSI) and Bank Aceh also provide these online services through their respective applications, BSI Mobile and Action Mobile. The mobile banking apps aim to simplify customer transactions, which can be conducted remotely via several features, from transfers, payments, and purchases to zakat payments, by simply connecting to the internet. Therefore, this research aims to classify the sentiment of user reviews for BSI Mobile and Action Mobile applications on Google Play Store to understand the users' experiences. The Multinomial Naïve Bayes algorithm is used in this study, where the algorithm analyzes and classifies the user reviews into positive and negative sentiment categories. The study involves several stages, such as text preprocessing, sentiment visualization, splitting the data into an 80:20 ratio for training and testing datasets, and training the model using the Multinomial Naïve Bayes algorithm. The results of this study show that the Multinomial Naïve Bayes algorithm performs well in analyzing user sentiment for BSI Mobile and Action Mobile, achieving an accuracy of 78.7%, precision of 76.5%, recall of 86.2%, and an F1-score of 80.6% for BSI Mobile, and an accuracy of 85.6%, precision of 75%, recall of 75%, and an F1-score of 75% for Action Mobile. Additionally, the sentiment classification results reveal that 52.8% of BSI Mobile user reviews are positive and 47.2% are negative, while for Action Mobile, 35.1% are positive and 64.9% are negative. For BSI Mobile, 21,497 reviews express a positive sentiment with dominant keywords such as "updated," "good," "balance," "transaction," and "thank." Meanwhile, for Action Mobile, 274 reviews express a negative sentiment with dominant keywords such as "transaction," "application," "network," "register," "please," and "update."
Comparison of Triple Exponential Smoothing and ARIMA in Predicting Cryptocurrency Prices Prasetyo, Adi; Nurdin, Nurdin; Aidilof, Hafizh Al Kautsar
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.577

Abstract

Cryptocurrency has emerged as a prominent digital asset over the past decade, but its high price volatility presents significant challenges for investors. This study evaluates and compares the effectiveness of the Triple Exponential Smoothing (TES) and Autoregressive Integrated Moving Average (ARIMA) methods in forecasting the prices of five major cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Solana (SOL), and Ripple (XRP). TES models trends and seasonality in time series data, while ARIMA captures autoregressive patterns and moving averages. The dataset is split into 80% for training and 20% for testing, with performance evaluated using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). TES outperforms ARIMA in predicting Bitcoin and Binance Coin, achieving MAPE values of 10.38% and 13.81%, and RMSE values of 3,985.55 and 41.28, respectively. However, ARIMA shows better performance for Ethereum, Solana, and Ripple, with MAPE ranging from 8.78% to 32.84% and RMSE between 0.08 and 204.59. Notably, Ethereum has the lowest MAPE at 8.78%, while Ripple exhibits the smallest RMSE at 0.08. These findings suggest that TES is more suitable for cryptocurrencies with relatively stable price patterns, while ARIMA is better adapted to forecasting highly volatile assets. This research underscores the importance of selecting forecasting models based on the specific characteristics of each cryptocurrency
ANALISIS FUNDAMENTAL DALAM MEMILIH ALTCOIN PADA CRYPTOCURRENCY DENGAN PREFERENCE SELECTION INDEX (PSI) METHOD Ritonga, Huan Margana; Yunizar, Zara; Aidilof, Hafizh Al Kautsar
TECHSI - Jurnal Teknik Informatika Vol. 15 No. 2 (2024)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v15i2.19000

Abstract

Cryptocurrency telah menjadi salah satu topik yang menarik perhatian di dunia keuangan dan teknologi dalam beberapa tahun terakhir. Seiring dengan popularitas Bitcoin, munculnya altcoin (alternative coins) juga menunjukkan potensi besar dalam pasar cryptocurrency. Skripsi ini bertujuan untuk menentukan opsi altcoin dengan investasi paling bagus dan memiliki potensi kenaikan paling tinggi. Metode Preference Selection Index adalah metode yang paling tepat dan di pilih untuk kasus ini karena didasari dengan beberapa preferensi aalternatif dan juga kriteria yang mendukung.Web yang dikembangkan memungkinkan pengguna untuk jauh lebih mudah memilih altcoin paling berpotensi dari beberapa opsi yang telah di pilih.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN JURUSAN SEKOLAH PADA MAN MENGGUNAKAN METODE WASPAS Marpaung, Rifky Firzani; Fuadi, Wahyu; Aidilof, Hafizh Al Kautsar
TECHSI - Jurnal Teknik Informatika Vol. 15 No. 1 (2024)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v15i1.19471

Abstract

Penentuan jurusan sekolah pada Madrasah Aliyah Negeri (MAN) merupakan proses penting yang harus mempertimbangkan berbagai faktor seperti nilai akademik, minat, dan bakat siswa. Namun, penentuan jurusan sering kali masih dilakukan secara manual, sehingga kurang efisien dan memerlukan waktu yang lama. Penelitian ini bertujuan untuk merancang dan membangun Sistem Pendukung Keputusan (SPK) berbasis web yang menggunakan metode Weighted Aggregated Sum Product Assessment (WASPAS) guna membantu pihak sekolah dalam menentukan jurusan yang sesuai dengan kemampuan siswa. SPK ini menggabungkan berbagai kriteria seperti nilai raport, hasil tes akademik, serta kemampuan praktek untuk memberikan rekomendasi penjurusan yang optimal. Metode WASPAS dipilih karena kemampuannya dalam mengkombinasikan metode Weighted Sum Model (WSM) dan Weighted Product Model (WPM), yang menghasilkan perhitungan yang lebih akurat. Hasil pengujian menunjukkan bahwa sistem yang dibangun mampu memberikan rekomendasi jurusan dengan lebih cepat dan efektif dibandingkan dengan metode manual. Sistem ini diharapkan dapat membantu sekolah dalam mengelola penjurusan siswa dengan lebih efisien dan objektif.
Developing Prototype Model Based on Analysis of The People at The Center of Mobile App Development (PACMAD) on The Panel Harga Pangan Application Fitria, Rahma; Meiyanti, Rini; Aidilof, Hafizh Al Kautsar; Ruzanna, Arina; Hamsi, Widia; Na'syakban, Irvan
JINAV: Journal of Information and Visualization Vol. 5 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav3115

Abstract

The increasing demand on mobile applications to monitor and analyze market trends in the food industry necessitates a focus on usability to ensure that these tools are functional and user-friendly. The Panel Harga Pangan app, which is widely utilized by traders, consumers, and policymakers, provides essential information on food prices across many marketplaces. However, as its user base grows, correcting usability concerns becomes increasingly important to its sustained effectiveness and customer happiness. This article looks into the implementation of the People At The Center Of Mobile Application Development (PACMAD) usability concept on the panel harga pangan app and finally proposed the prototype to similar application. The PACMAD model, designed specifically for mobile applications, evaluates usability based on seven key criteria: effectiveness, efficiency, satisfaction, learnability, memorability, mistakes, and cognitive load. The application's effectiveness is approximately (62.5%), including efficiency (73.27%), satisfaction (64%), learnability (65.78%), memorability (70.93%), errors (68.59%), and cognitive load (72.72%). The study's findings show that the application has an average score of 68%, indicating that the program is neither particularly successful or satisfying. Issues such as less efficiency and higher error frequency diminish the overall user experience. The research includes specific recommendations for improving the app's usability, such as redesigning the user interface and optimizing onboarding processes. These findings aim to improve the user experience, ensuring that the panel harga pangan remains a reliable and user-friendly tool for its varied audience. The findings have significant consequences for applying the PACMAD model to other mobile agriculture applications.
Co-Authors A, Hendra Adi Prasetyo Al-Shahzam , Mohd. Hafez Angelina, Difa Asrianda Asrianda Eri Saputra Fachruzi, Faza Reihan Fahrizal, Effan Fakhrurrazi Fuadi, Wahyu Hamsi, Widia Hassan, Soraya Masthura Hisyam, Mochammad Iswari, Syahyana Kurniawati Kurniawati Lidya Rosnita Lubis, Aulia Azzahra Ma'aruf Marpaung, Rifky Firzani Mirsa, Rinaldi Muhammad Ikhwani Muhammad Muaz Munauwar Munawarah Munawarah, Munawarah Na'syakban, Irvan Nurdin Nurdin Qardawi, M Yusuf Qardawi, Muhammad Yusuf Rahma Fitria, Rahma Rangkuti, Haris Yunanda Rini Meiyanti Ritonga, Huan Margana Rizal S.Si., M.IT, Rizal Rozzi Kesuma Dinata Ruzanna, Arina Sahputra, Ilham salamah salamah Samudera, Brucel Duta Veri Ilhadi Zahratul Fitri, Zahratul Zara Yunizar Zohra, Siti Fatimah A Zulfadli Zulfadli