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Web-Based Expert System Application for Early Diagnosis of HIV/AIDS Using the Naive Bayes Method Aisah, Sri Purwani; Adek, Rizal Tjut; Yunizar, Zara
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17809

Abstract

AIDS is a progressive decrease in the immune system so that opportunistic infections can appear and end in death, therefore the author created an early diagnosis system for HIV/AIDS using the website-based Naïve Bayes algorithm. Naïve Bayes is a simple probability classification that can calculate all possibilities by combining a number of combinations and frequencies of a value from the database obtained.the results of the research obtainedThe naïve Bayes algorithm can be implemented for early diagnosis of HIV/AIDS by means that the existing HIV/AIDS symptom data is adjusted to the patient's symptom data processed using the naïve Bayes algorithm and then it is concluded what the symptoms are and What is the solution.
Comparison of the Results of the K-Nearest Neighbor (KNN) and Naïve Bayes Methods in the Classification of ISPA Diseases (Case Study: RSUD Fauziah Bireuen) Putri, Riska Yolanda; Yunizar, Zara; Safwandi, Safwandi
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 1 (2024): Journal of Advanced Computer Knowledge and Algorithms - January 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i1.14535

Abstract

Acute Respiratory Infection or commonly called (ARI) is a disease caused by bacteria or viruses. (ARI) can attack all ages, especially children. This study aims to compare the accuracy of classification in (ARI) disease. The data used is data from patients affected by (ARI) disease at Fauziah Bireuen Hospital. K-Nearest Neighbors and Naïve Bayes can be used in the classification of (ARI) diseases. Measurement of accuracy using Confusion Matrix in the K-Nearest Neighbors method with the Eulidean Distance approach in the case of (ARI) disease classification obtained a percentage of precision of 91%, recall 84% and accuracy of 88%. While the Naïve Bayes method obtained a percentage of precision of 95%, recall 78% and accuracy of 86%. The results of the accuracy comparison of the two methods show that the K-Nearest Neighbors method has a higher accuracy rate than the Naïve Bayes method.
Comparison of Chen's Fuzzy Time Series and Triple Exponential Smoothing in Forecasting Medicine Stocks at the Blang Cut Kuala Community Health Center Devi, Salma; Yunizar, Zara; Retno, Sujacka
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16870

Abstract

Forecasting is estimating future conditions by examining conditions in the past. In social life, everything is uncertain and difficult to predict precisely, so forecasting is needed. Efforts are always made to make forecasts in order to minimize the influence of this uncertainty on a problem. In other words, forecasting aims to obtain forecasts that can minimize forecast errors, which are usually measured by the mean absolute percentage error. This method is usually used for time series-based forecasting and uses data or information from the past as a reference when predicting current data. This research will compare the application of the Fuzzy Time Series Chen method and the Triple Exponential Smoothing method in forecasting drug stock determination at the Kuala Community Health Center, Blang Mangat District, Lhokseumawe City Regency, Aceh. The research results showed that the Triple Exponential Smoothing method was better in forecasting drug stock inventories compared to Chen's Fuzzy Time Series method. Chen's Fuzzy Time Series method produces a MAPE value of 17.67%, which means it has an accuracy of 82.33%, while the Triple Exponential Smoothing method produces a MAPE value of 9.842%, which means it has an accuracy of 90.158%
Geographic Information System for Mapping Drug Abuse Areas in Lhokseumawe City Using the Average Linkage Method Syintia, Icut; Fuadi, Wahyu; Yunizar, Zara
Journal of Advanced Computer Knowledge and Algorithms Vol 2, No 1 (2025): Journal of Advanced Computer Knowledge and Algorithms - January 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i1.17804

Abstract

Aceh is one of the provinces in Indonesia where the development of drug abuse has increased. The system that runs at BNN Lhokseumawe City in recording data and information about drug abuse cases has not been integrated with the mapping of drug abuse areas. Therefore, BNN and Lhokseumawe City Police need a drug abuse area mapping system in the Lhokseumawe City area. This research aims to build a webgis-based geographic information system using the Google Maps API for map visualization. The data mining method used is Average Linkage, clustering is done based on the number of cases, number of suspects and population in each sub-district in Lhokseumawe City. Cluster 1 consists of 1 sub-district, namely Banda Sakti, which in cluster 1 has a relatively high average value compared to clusters 2 and 3 so that it is included in a very vulnerable level. In cluster 2 consists of 2 sub-districts, namely Muara Satu and Muara Dua, because this cluster has a medium average value compared to clusters 1 and 3 so that it is included in the vulnerable level. Whereas the cluster in cluster 3 consists of 1 sub-district, namely Blang Mangat, which in cluster 3 has a relatively lower average value than clusters 1 and 2 so that it is included in the moderately vulnerable level.
News Popularity Prediction in West Sumatera Using Autoregressive Integrated Moving Average Aminsyah, Ansharulhaq; Nurdin, Nurdin; Yunizar, Zara
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.v5i1.615

Abstract

The increasing public interest in reading online news is undoubtedly a challenge for news portals as online news providers. Therefore, this research was conducted to predict news popularity in West Sumatra through the FajarSumbar.com news portal using the Autoregressive Integrated Moving Average (ARIMA) model. This research aims to develop a forecasting model that can assist in estimating the popularity of each news category so that news portals can devise more effective content strategies. The data used in this study includes the number of monthly news impressions from March 2021 to June 2024, which are grouped into various categories such as Religion Culture, Industrial Economics, Criminal Law, etc. Using the ARIMA method, which can handle time series data and overcome data non-stationarity problems through differencing and the use of grid search in optimization to find the best parameters based on the lowest evaluation metric. The results show that the ARIMA model can provide reasonably accurate predictions, although the level of accuracy varies between categories. The Mean Absolute Percentage Error (MAPE) values obtained are as follows: Religion Culture 26%, Industrial Economy 29%, Criminal Law 29%, Health 40%, Sports 38%, Tourism Entertainment 26%, Education 27%, Government Politics 31%, Social Environment 27%, and Technology 51%. The Technology and Health news categories show higher error rates than others, while Religion Culture and Tourism Entertainment have better accuracy rates. Thus, the ARIMA model can be used to predict future trends in news popularity, helping editors plan content strategies that are more relevant and interesting to readers. However, improvements are needed for news categories that have high variability.
Pelatihan Pembuatan Media Pembelajaran Online dan Perakitan Komputer Pada Sekolah di Desa Paloh Lada Kecamatan Dewantara Bustami, Bustami; Muhammad, Muhammad; Yunizar, Zara; Rosnita, Lidya; Meiyanti, Rini; Afrillia, Yesy; Hafidh Rafif, Teuku Muhammad; Harahap, Ilham Taruna
MEUSEURAYA - Jurnal Pengabdian Masyarakat Vol.1 No.2 (Desember 2022)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat STAIN Teungku Dirundeng Meulaboh

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.218 KB) | DOI: 10.47498/meuseuraya.v1i2.1436

Abstract

Pesatnya perkembangan teknologi informasi saat ini secara tidak langsung juga “memaksa” kita untuk dapat mengikuti perkembangannya, bukan hanya bagi kita yang memang bergerak di bidang IT, namun juga bagi kita yang bergerak disemua bidang, salah satunya di bidang Pendidikan. Teknologi informasi menjadi kebutuhan primer bagi kita yang membutuhkan efisiensi dalam berkegiatan. Guru dan siswa juga merasakan langsung bagaimana teknologi berperan dalam kegiatan Pendidikan, pembelajaran secara daring di masa covid menjadi puncak dari pemanfaatan teknologi didunia Pendidikan. Salah satu point penting dari kegiatan pembelajaran daring adalah pemanfaatan media pembelajaran daring, misalnya google classroom. Kegiatan pengabdian ini bertujuan untuk membantu Guru dan juga siswa/I memanfaatkan teknologi dalam kegiatan pembelajaran. Kegiatan pengabdian ini terdiri dari dua kegiatan besar, yaitu Pelatihan pembuatan media pembelajaran online yang diberikan kepada para guru dan kegiatan pelatihan perakitan komputer dan instalasi komputer kepada para murid. Kegiatan ini dilakukan pada MTsS Jabal Nur dan MTsN 2 Aceh Utara, Kecamatan Dewantara, Kab. Aceh Utara. Output dari kegiatan ini adalah Jurnal yang di submit pada Jurnal Rambieden dan Publikasi media massa. Selain itu, kegiatan ini juga memberikan pemahaman pada para guru dalam pemanfaatan media pembelajaran online dan dapat diterapkan dalam kegiatan pembelajran, sedangkan bagi siswa, kegiatan pelatihan ini memberikan pengetahuan pada mereka tentang perkembangan teknologi informasi.
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.
Application of the Internet of Things in Monitoring and Controlling Water Quality of Goldfish in Aquariums Mahara, Sabda; Yunizar, Zara; Nunsina, Nunsina
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.763

Abstract

Caring for ornamental fish in aquariums often presents significant challenges, primarily when maintenance relies on manual methods. Owners may face difficulties when they are unavailable to feed the fish or clean the aquarium, potentially compromising the health and well-being of the ornamental fish. Consistent water quality monitoring is critical to maintaining a stable and healthy environment for these aquatic creatures. To address these issues, this study developed an Internet of Things (IoT)-based system to monitor water conditions in real-time via an internet connection. By leveraging IoT technology, the system allows owners to access real-time data and remotely control aquarium parameters through a user-friendly interface, providing convenience and improved management. The system monitors essential water parameters, including temperature and pH levels, to sustain the fish's health and ensure the aquarium ecosystem's stability. Testing was conducted over two days, with data recorded at fifteen-minute intervals each day, and the results demonstrated that the system effectively monitored these parameters with sufficient accuracy. The collected data is presented in an intuitive table interface, making it easy for users to analyze trends and respond promptly to any irregularities. Additionally, the system features automatic actuator controls that allow necessary adjustments without requiring constant user involvement, significantly simplifying aquarium maintenance. The accompanying monitoring website further enhances usability by enabling users to check and manage water quality anywhere and anytime, providing flexibility and control. These features collectively ensure a more effective, efficient, and sustainable approach to ornamental fish care, ultimately improving aquarium management and fish well-being.
INCREASING THE EFFECTIVENESS OF WEBGIS-BASED VILLAGE IRRIGATION NETWORK MANAGEMENT IN GAMPONG KEUTAPANG KEC. NISAM, DISTRICT NORTH ACEH Zara Yunizar; Muthmainnah; Nura Usrina; Mukhlis; Zalfie Ardian Zainal; Rizal Tjut Adek; Maizuar
RAMBIDEUN : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 1 (2025): Rambideun : Jurnal Pengabdian kepada Masyarakat
Publisher : LPPM Universitas Al Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/pkm.v8i1.3053

Abstract

Keutapang Village is located in Nisam District, North Aceh Regency, Aceh Province with a village area of 123.4 ha. This village has 120 ha of agricultural land and rice as the main commodity, but the productivity of the planting season and harvest cannot be maximized due to the lack of irrigation that has been built, thus it is necessary to increase the effectiveness of irrigation management by mapping irrigation as information for village irrigation development planning. The rural irrigation map contains information on the location, situation and condition of irrigation, and the priority scale for improving the WEBGIS-based network. The purpose of this community service activity was to produce a village irrigation network map and educate village officials in increasing the effectiveness of irrigation network management through WEBGIS-based mapping. The mapping stages included measurement surveys using GPS, digitizing the surface of the area through Google Earth, depicting the layout with the AutoCAD application and making maps with QGIS/ArcGIS software. This community service activity in Keutapang Village, Nisam District produced informative and attractive village irrigation geospatial maps. The result of this activity is a digital irrigation map whose printout is submitted to the village officials. It is hoped that this map can be published and used as a basis for future sustainable village development planning.
Fundamental Analysis in Choosing Altcoins in Cryptocurrency With Preference Selection Index Method Ritonga, Huan Margana; Yunizar, Zara; Aidilof, Hafizh Al Kautsar
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.848

Abstract

Cryptocurrency has become one of the most intriguing topics in finance and technology in recent years. With the growing prominence of Bitcoin, the rise of altcoins (alternative cryptocurrencies) also demonstrates significant potential within the cryptocurrency market. Altcoins, which include all cryptocurrencies other than Bitcoin, offer diverse functionalities and use cases, ranging from smart contracts to decentralized finance (DeFi) applications. This thesis identifies the altcoin options with the best investment opportunities and the highest growth potential. The study employs the Preference Selection Index (PSI) method, a multi-criteria decision-making approach that evaluates alternatives based on specific preferences and criteria. This method is particularly suitable for assessing complex investment decisions involving multiple variables, such as market capitalization, technological innovation, and utility. By applying PSI, investors can decide which altcoins will likely yield substantial returns. A web-based platform has been developed as part of this research to simplify selecting promising altcoins. This platform enables users to evaluate options based on predefined criteria, such as market trends, project objectives, and development team credibility. The accessibility of this tool empowers users—whether novice or experienced investors—to navigate the dynamic cryptocurrency market more effectively. Altcoins provide a unique opportunity for diversification in investment portfolios. Unlike Bitcoin, which is often viewed as a store of value, many altcoins are designed with specific purposes and innovative features. For instance, Ethereum introduced smart contracts that revolutionized decentralized applications, while other altcoins focus on scalability or niche markets like the Internet of Things (IoT). However, investing in altcoins also comes with challenges like high market volatility, security risks, and regulatory uncertainties. Therefore, thorough research and strategic planning are essential for minimizing risks while maximizing returns in this rapidly evolving sector.
Co-Authors ,, Iqbal ,, Maulidasari ,, Zulaifani ., Yulisma Aidilof, Hafizh Al Kautsar Aidilof, Hafizh Al-Kautsar Aisah, Sri Purwani Amelia, Ulva Aminsyah, Ansharulhaq Arief Fazillah Arif H., Nanda Nan Arnawan Hasibuan Asran Asran Bariah, Hairul Bustami Bustami Cindy Rahayu Dahlan Abdullah Devi, Salma Dhyra Gibran Alinda Dr M Rajeswari Elma Fitria Ananda ERNAWITA ERNAWITA Ersa, Nanda Savira Eva Darnila Fadlisyah Fadlisyah Fajri, Riyadhul Fajri, Ryadhul Fajriana, Fajriana Fardiansyah, T. Fasdarsyah Fasdarsyah Fatimah Zuhra Fatimah Zuhra Fatimah Zuhra Fuadi, Wahyu Hafidh Rafif, Teuku Muhammad Harahap, Ilham Taruna Hasan, Phadlin HENDRA ZULKIFLI Irshad Ahmad Reshi Johan, T. M. Kartika Kartika Kurnia Amanda, Destiara Lidya Rosnita M. Fauzan M.Cs, Iqbal, Maghfirah Maghfirah Maha, Dedi Torang P Mahara, Sabda Mahendra Febriliansyah Maizuar Maizuar Maryana Maryana, Maryana Maulana Helmi, Fathan Maulana, O.K.Muhammad Majid Melizar Meutia Rahmi Misbahul Jannah Muhammad Daud Muhammad Fikry Muhammad Ikhwani Muhammad Muhammad Muharni Muharni Mukhlis Mukhlis Mukhlis Mulaesyi, Syibbran Munar, Munar Munirul Ula Mursyidah Mursyidah MUTHMAINNAH Muthmainnah Muthmainnah NinaUlfauza NinaUlfauza Nunsina, Nunsina Nur Mauliza Nura Usrina Nurdin Nurdin Nuryawan, Nuryawan Putri, Riska Yolanda Ramadhana Juseva Ridha, Ridha Rini Meiyanti Ritonga, Huan Margana Rizal S.Si., M.IT, Rizal Rizki Suwanda Rizky Almunadiansyah Rizky Putra Fhonna Rizky, Rahmat Rizkya, Dini Dara Rozzi Kesuma Dinata Rusnani Rusnani Rusniati Rusniati Ruwaida Ruwaida Safwandi Safwandi Said Fadlan Anshari Savira Ersa, Nanda Siregar, Winda Ramadhani Sriana, Anis Suci Fitriani, Suci Sujacka Retno Syintia, Icut Taufiq Taufiq Tjut Adek, Rizal Wahyu Fuadi Yanti, Winda Yesy Afrillia Zalfie Ardian Zulsuhendra, Edi