Articles
<![CDATA[Komparasi Algoritma SAW, AHP, dan TOPSIS dalam Penentuan Uang Kuliah Tunggal (UKT) ]]>
<![CDATA[Wawan Firgiawan]]>;
<![CDATA[Sugiarto Cokrowibowo]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ Journal of Computer and Information System ( J-CIS ) Vol 3 No 1 (2020): J-CIS Volume 3 Issue 1 2020 ]]>
Publisher : <![CDATA[Universitas Sulawesi Barat ]]>
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DOI: 10.31605/jcis.v1i2.426
<![CDATA[Abstrak UKT mahasiswa mempunyai kelompok yang berbeda-beda, dimana tiap kelompok mempunyai persentase masing-masing yang sudah ditetapkan oleh pemerintah berdasarkan ekonomi mahasiswa. Tidak adanya standarisasi yang jelas dalam penentuan UKT menuai banyak problem. Pendekatan pengambil keputusan atau disebut Decision Support Systems (DSS) akan membantu dalam pengambilan keputusan terhadap UKT mahasiswa yang akurat. Tujuan dari makalah ini ingin membandingkan 3 metode Multicriteria Decision Analysis, yaitu menggunakan metode Simple Additive Weinghting (SAW), metode Technique for Order Preference by Similarity to Ideal Solustion (Topsis) serta metode Analitical Hierarcy Process (AHP) yang digunakan dalam pengambilan keputusan penentuan UKT mahasiswa sesuai dengan kriteria untuk menentukan metode yang relevan akan permasalahan tersebut. Penentuan skala dan pembobotan dalam setiap metode akan mempengaruhi hasil yang diperoleh oleh masing-masing kriteria. Dari hasil komparasi dari 3 metode yaitu SAW, TOPSIS, dan AHP diperoleh bahwa AHP mempunyai nilai rata-rata yang mendekati nol yaitu dengan nilai 0,10, sedangkan TOPSIS mempunyai rata-rata yaitu 0,44 dan AHP sendiri dengan nilai rata-rata 0,53 sehingga AHP merupakan metode yang terbaik digunakan dalam penentuan UKT. Kata Kunci:]]>
<![CDATA[Sistem Rekomendasi Berbasis-Konten Pada Pengembangan Web Smart Tourism ]]>
<![CDATA[Nuralamsah Zulkarnaim]]>;
<![CDATA[Musyrifah]]>;
<![CDATA[Sulfayanti]]>;
<![CDATA[Irfan]]>;
<![CDATA[Asmawati]]>
<![CDATA[ Jurnal Komputer Terapan Vol. 8 No. 1 (2022): Jurnal Komputer Terapan ]]>
Publisher : <![CDATA[Politeknik Caltex Riau ]]>
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DOI: 10.35143/jkt.v8i1.5214
<![CDATA[The utilization of the internet in the tourism is very helpful for tourists in planning trips, including in exploring local tourist areas. The existence of special media such as smart tourism web facilities to publish local tourist attractions and tourist facilities in the local area certainly help stakeholders and tourists. To facilitate the tourists as web users to access information about visited area, it is necessary to have a recommendation system that can provide a recommendation regarding the tourist needs such as tourist destinations, lodging, restaurants and even souvenir shops typical of the local area. Recommendation system development can be done through two basic methods, namely: Content Based Recommendation and Collaborative Filtering. This study aims to show how to implement content-based filtering in providing content-based recommendations on supporting the development of smart tourism webby utilizing cosine similarity and K-Nearest Neighbor. This study shows that Content Based Recommendation can provide recommendation according to the tourist needs based on the content that has been selected by other users.]]>
<![CDATA[IMPLEMENTATION OF BACKPROPAGATION ARTIFICIAL NEURAL NETWORK FOR FOOD PRICE PREDICTION IN MAJENE CENTRAL MARKET ]]>
<![CDATA[Arnita Irianti]]>;
<![CDATA[Parma Hadi Rantelinggi]]>;
<![CDATA[Alief Taufik]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>;
<![CDATA[Sugiarto Cokrowibowo]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.3.226
<![CDATA[Food has a fairly high price and the stability of food prices can affect entrepreneurs and the community in meeting their daily needs. This is often seen as a sudden increase in prices (extreme). Therefore, it is necessary to have precise and accurate forecasts or predictions to assist local governments in taking the initial steps in efforts to stabilize food prices. Artificial Neural Networks (ANN) can be used to predict future food prices using the Backpropagation Algorithm. Sental Market is one of the trading centers for daily necessities in Majene district, West Sulawesi. The study used data taken from the Office of Cooperatives, SMEs, Industrial Trade, Kab. Majene, in the form of food price data per week. The research aims to assist the Majene Regional Government (PEMDA) in taking initial steps / policies to stabilize food prices. The system is designed to predict food prices by applying a Backpropagation Neural Network, then reviewing the accuracy obtained in the food price prediction system for each commodity. The results of the study used a Backpropagation Neural Network pattern with a total data of ±156 for each commodity. The results of the study used N.Input of 2, N.Hidden of 3, and N.Output of 1. While the parameters used were Alpha of 0.3, an error tolerance of 0.001, and a maximum iteration of 100. The highest accuracy in the prediction of Commodity Rice Prices was 98.47 with the computation time for the training and testing process being 1.69 and 0.004 respectively.]]>
<![CDATA[Clustering Wilayah berdasarkan Data Kesehatan Lingkungan menggunakan Fuzzy C-Means ]]>
<![CDATA[Irfan A.P.]]>;
<![CDATA[Siti Aminah]]>;
<![CDATA[Sugiarto Cokrowibowo]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ Journal of Computer and Information System ( J-CIS ) Vol 3 No 1 (2020): J-CIS Volume 3 Issue 1 2020 ]]>
Publisher : <![CDATA[Universitas Sulawesi Barat ]]>
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DOI: 10.31605/jcis.v1i2.609
<![CDATA[Abstrak Kesehatan merupakan hal penting dalam kehidupan, karena dengan kesehatan kita dapat menjalankan kegiatan kita sehari - hari. Secara administratif, Kabupaten Majene terdiri dari 8 kecamatan, 82 desa/kelurahan dan 361 SLS (Satuan Lingkungan Setempat) yang terbagi dalam 257 dusun dan 104 lingkungan. Karena hal itu, kesehatan lingkungan pemukiman sangatlah penting. Tujuan utama dalam penelitian ini adalah mengelompokan tiap wilayah (kecamatan) menjadi beberapa kelompok dan mengetahui tingkat kesehatan lingkungan berdasarkan 5 parameter yang spesifik dengan menggunakan metode Fuzzy C – Means. Dengan adanya metode ini, keakurasian data dan tingkat kesehatan lingkungan menjadi lebih akurat. Hasil output dalam penelitian ini berupa informasi pengelompokan kesehatan lingkungan yang diharapkan mampu untuk menjadi bahan pertimbangan dalam menentukan tingkat kesehatan lingkungan berdasarkan 5 parameter yang menjadi indikator penyehatan lingkungan.]]>
<![CDATA[VISUALISASI DATA AKREDITASI PROGRAM STUDI BERBASIS WEB MENGGUNAKAN EXTREME PROGRAMMING ]]>
<![CDATA[Muh. Fahmi Rustan]]>;
<![CDATA[Hasriani]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ Jurnal Informatika Teknologi dan Sains Vol 4 No 4 (2022): EDISI 14 ]]>
Publisher : <![CDATA[Program Studi Informatika Universitas Teknologi Sumbawa ]]>
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DOI: 10.51401/jinteks.v4i4.2143
<![CDATA[The accreditation status of a study program is determined by a lot of data that can support the assessment criteria. The availability of data certainly supports the amount of information that can be obtained so that it will be easier if the data is collected in one accreditation system. Yet it is not easy to understand the information from unstructured data. Thus, a brief and interesting presentation of information on the accreditation system is needed. This can be realized through data visualization where information can be obtained by exploring, understanding, and communicating data. Data visualization is also a tool for conducting data analysis. Moreover, This research aims to develop a study program accreditation system that focuses on educational criteria and is equipped with data visualization that can assist the data analysis process so that users or policymakers are able to make the right decisions. By utilizing the Extreme Programming (XP) method, this research produces a study program accreditation system that is equipped with data visualization which enables to presentation of effective and attractive data displays. The results of this study will make the users be easier to make decisions regarding efforts to achieve study program accreditation.]]>
<![CDATA[Adopsi Metode Scrum Untuk Elisitasi Kebutuhan Smart Tourism ]]>
<![CDATA[Dian Niswati]]>;
<![CDATA[Asmawati S]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ J-ICON : Jurnal Komputer dan Informatika Vol 10 No 1 (2022): Maret 2022 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v10i1.6321
<![CDATA[The first step in software engineering is to get information about the scope and requirements of the system to be built. However, there are several problems that can hinder the process of designing the elicitation of smart tourism needs, such as a misunderstanding in the definition of system requirements that have been determined by one party, resulting in great potential for change. The purpose of designing the elicitation of smart tourism needs is to minimize the occurrence of change. The design of elicitation of smart tourism needs uses the scrum method which emphasizes team collaboration and is adaptive. The type of research used in this research is descriptive research with a qualitative approach. The results of the elicitation of smart tourism needs are a feature for designing smart tourism with a system design that focuses on use case diagrams using Unified Modeling Language (UML).]]>
<![CDATA[PENGEMBANGAN APLIKASI MOBILE LAYANAN PARIWISATA LOKAL SULAWESI BARAT MENGGUNAKAN FRAMEWORK FLUTTER ]]>
<![CDATA[Sultan Jorgi]]>;
<![CDATA[Asmawati S]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ J-ICON : Jurnal Komputer dan Informatika Vol 10 No 2 (2022): Oktober 2022 ]]>
Publisher : <![CDATA[Universitas Nusa Cendana ]]>
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DOI: 10.35508/jicon.v10i2.6623
<![CDATA[One of the provinces in eastern Indonesia, namely West Sulawesi, has many types of tourist attractions. Many of these tourism objects have not been managed optimally by the managers or the government. Currently, there is still no available information platform that can provide detailed information regarding local tourism services available in West Sulawesi Province. This study aims to create an application product that can make it easier for tourists who will visit to find information on local tourism in West Sulawesi. Waterfall is a systematic and sequential application development method at each stage starting from the analysis stage to the implementation stage. Flutter is used as a framework for mobile application development that makes it easy to create application user interfaces. This application has succeeded in providing information related to local tourism services in West Sulawesi Province according to actual data from tourism services. Based on Alpha and Betha testing using the BlackBox method, the results in the Alpha test were that there were no functionality errors in the application, while the Betha test which was carried out directly to the user obtained the results that the application had an attractive appearance, was easy to use, informative, quite easy to understand and useful for users.]]>
<![CDATA[Prediksi Produktivitas Kakao Kabupaten Mamuju Dengan Algoritma K-Nearest Neighbor ]]>
<![CDATA[Samsari .]]>;
<![CDATA[Irfan A. P]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Vol 19 No 2 (2020): In Search ]]>
Publisher : <![CDATA[LPPM UNIBI ]]>
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DOI: 10.37278/insearch.v19i2.346
<![CDATA[This study processes data using the Knowedge Discovery in Database (KDD) process flow. The test sample used was cocoa statistical data in Mamuju district from 2016-2019. The KDD process flow itself consists of data selection, preprocessing, transformation, data mining and evaluation. In the data mining process, determining the pattern of the selected data uses the K-Nearest Neighbor (K-NN) method, while the evaluation uses the Root Mean Square Error (RMSE) method. RMSE is used to measure the level of predictive accuracy of the error value obtained. If the resulting error value is low, it means that the prediction is close to its actual value. The results showed that using the K-NN method can be used to predict cocoa productivity, this is evidenced by the RMSE evaluation of the error value obtained in low districts, with an average error of 6,395.]]>
<![CDATA[Implementasi Sistem Pendukung Keputusan (SPK) Pada Seleksi Proposal Penelitian Dan Pengabdian Kepada Masyarakat Menggunakan Metode Mod SAW ]]>
<![CDATA[Padli, Muh]]>;
<![CDATA[Amirul Asnan Cirua, A]]>;
<![CDATA[Zulkarnaim, Nuralamsah]]>
<![CDATA[ Informatics and Digital Expert (INDEX) Vol. 6 No. 2 (2024): INDEX, November 2024 ]]>
Publisher : <![CDATA[LPPM Universitas Perjuangan Tasikmalaya ]]>
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DOI: 10.36423/index.v6i2.2010
<![CDATA[Kegiatan penelitian dan pengabdian masyarakat merupakan salah satu tugas dan kewajiban dosen yang telah tertuang dalam tridarma perguruan tinggi. Secara rutin tiap tahun setiap kampus melalui Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) menyeleksi dan menerima proposal kegiatan tersebut. Seleksi yang dilakukan oleh beberapa kampus masih dilakukan secara manual. Selain itu, banyaknya kriteria yang digunakan dengan bobot yang bebeda-beda akan memakan waktu proses yang lama. Sehingga, potensi terjadinya human error relatif besar dapat mengakibatkan hasil seleksi proposal yang tidak objektif. Oleh karena itu, diperlukan sebuah sistem yang dapat membantu menentukan proposal lolos seleksi dengan berbagai macam kriteria. Sistem ini dikembangkan menggunakan kombinasi metode Simple Additive Weighting (SAW) dan Weighted Product (WP). Metode yang SAW memungkinkan proses perangkingan lebih simple dan sederhana, serta tak jarang metode ini dilakukan pada kasus pengambilan keputusan dalam rekomendasi pemilihan proposal dengan multi atribut. Sedangkan pada metode WP, dapat melengkapi kekurangan pada metode SAW yaitu dengan adanya perbaikan bobot. Diharapkan melalui penelitian ini, hasil seleksi proposal dapat ditentukan dalam waktu yang singkat dan objektif.]]>
<![CDATA[Implementasi 3D Virtual Tour Sebagai Media Promosi Wisata Bahari Menggunakan Metode Extreme Programming ]]>
<![CDATA[Siti Zahra Salma]]>;
<![CDATA[Asmawati S]]>;
<![CDATA[Nuralamsah Zulkarnaim]]>
<![CDATA[ JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 4 No 2 (2023) ]]>
Publisher : <![CDATA[SOTVI - Society of Visual Informatics ]]>
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DOI: 10.62527/jitsi.4.2.130
<![CDATA[Berbagai lokasi wisata di Kabupaten Majene dan Kabupaten Polewali banyak diminati baik oleh pengunjung domestik maupun internasional, salah satunya adalah destinasi wisata bahari. Karena pengaruh kawasan pesisir, kedua kabupaten ini didominasi oleh destinasi wisata bahari yang menyuguhkan lanskap pemandangan laut. Jumlah wisatawan yang berkunjung ke Kabupaten Majene dan Polewali mengalami penurunan dalam beberapa tahun terakhir yang disebabkan oleh adanya pandemi COVID-19, sekitar 0.3 persen pada Kabupaten Majene dan 4.05 persen pada Kabupaten Polewali. Implementasi teknologi 3D virtual tour sebagai media promosi wisata bahari merupakan tujuan dari penelitian ini. Penelitian ini menggunakan metode extreme programming sebagai metode pengembangan sistem. Berdasarkan hasil pengujian uji kelayakan yang dilakukan menunjukkan bahwa hasil implementasi sistem 3D virtual tour diperoleh nilai tampilan sistem sebesar 83,5 % yang masuk kedalam kategori sangat setuju, kemudian 82% dari olah data layanan yang tergolong kategori sangat setuju, dan 83,63% untuk efisiensi sistem dengan kategori sangat setuju]]>
