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<![CDATA[Fuzzy Neural Network (FNN) Pada Proses Identifikasi Penyakit ISPA ]]>
<![CDATA[Saputra, Dhio]]>;
<![CDATA[Yanto, Musli]]>;
<![CDATA[Safitri, Wifra]]>;
<![CDATA[Mayola, Liga]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v5i3.3020
<![CDATA[ISPA is a disease that can affect anyone from children, adolescents, adults, and even the elderly. The causes experienced by sufferers of this disease are quite simple, such as fever, runny nose, and cough. The discussion in this paper describes the process of ISPA disease identification by developing a Fuzzy Neural Network (FNN) model. The process will be optimized using Fuzzy Logic to form rules for the diagnostic process, then proceed with an Artificial Neural Network (ANN). This model can maximize the performance of ANN in the identification process so that the output given is quite precise and accurate. The results provided by Fuzzy Logic can describe the clarity of the rules in diagnosis by presenting several rules (rules) that are presented from the Fuzzyfication process to the Defuzzyfication process. The output obtained from the ANN process also shows quite perfect results with an average error value based on MSE of 0.00912 and accuracy value of 91.96%. With these results, it can be stated that the FNN model can be used in the ISPA diagnosis process so that the presentation of this paper aims to provide an alternative in the identification process]]>
<![CDATA[Neural Network Backpropagation Identifikasi Pola Harga Saham Jakarta Islamic Index (JII) ]]>
<![CDATA[Musli Yanto]]>;
<![CDATA[Liga Mayola]]>;
<![CDATA[M. Hafizh]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i1.1266
<![CDATA[Jakarta Islamic Index (JII) is an organization engaged in the economy with the aim to pay attention to stock movements every day. With the JII, people who do not understand about shares and their movements, will be easy to know and understand the movement of shares that occur at certain times. The problem in this research is that many investors are unable to predict the rise and fall of stock prices. The prediction process can be done with a backpropagation algorithm. The algorithm is a concept of computer science which is widely used in the case of analysis, prediction and pattern determination. The process starts from the analysis of the variables used namely interest rates, exchange rates, inflation rates and stock prices that occurred in the previous period. The variables used are continued in the formation of network patterns and continued in the process of training and testing in order to produce the best network patterns so that they are used as a process of identifying JII stock price movements. The results obtained in the form of the value of stock price movements with an error rate based on the MSE value of 11.85% so that this study provides information in the form of knowledge for making a decision. The purpose of the research is used as input for investors in identifying share prices. In the end, the benefits felt from the results of this study, investors can make an initial estimate before investing in JII.]]>
<![CDATA[Analisis Hybrid Decision Support System dalam Penentuan Status Kelulusan Mahasiswa ]]>
<![CDATA[Dodi Guswandi]]>;
<![CDATA[Musli Yanto]]>;
<![CDATA[M. Hafizh]]>;
<![CDATA[Liga Mayola]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v5i6.3587
<![CDATA[Determination of graduation status is often faced by lecturers in every university. The facts show that many of the decisions still have a fairly high error rate in determining graduation status. This study aims to develop an analytical model in the process of determining student graduation using the Hybrid Decision Support System (DSS). The methods used in the analysis process are Analytical Hierarchy Process (AHP) and Technique for Others Preference by Similarity to Ideal Solution (TOPSIS). The performance of AHP can determine the value of the weight criteria and TOPSIS performs rankings to produce solutions in determining. The criteria indicators used to consist of Depth (C1), Material Breadth (C2), Answer Accuracy (C3), Fluency of Answers (C4), Scientific Attitude (C5), Logical Consistency of Content (C6), Authenticity (C7), Scientific Quality ( C8), Language (C9), and Writing (C10). The results of this study indicate that the Analytical Hierarchy Process (AHP) method provides a weighting value for each criterion with a fairly good accuracy rate of 85,86%. These results conclude that each criterion has a consistent level of relationship in determining student graduation. Based on the output of the TOPSIS analysis, the results presented can determine the student's graduation status correctly and accurately.]]>
<![CDATA[IDENTIFIKASI KARAKTERISTIK JAKARTA ISLAMIC INDEX DENGAN MENGGUNAKAN ALGORITMA K-MEANS ]]>
<![CDATA[Liga Mayola]]>;
<![CDATA[Sigit Sanjaya]]>;
<![CDATA[Wifra Safitri]]>
<![CDATA[ Sebatik Vol 22 No 2 (2018): DESEMBER 2018 ]]>
Publisher : <![CDATA[STMIK Widya Cipta Dharma ]]>
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<![CDATA[Investor memerlukan informasi pergerakan harga saham dan variabel ekonomi yang mempengaruhi naik-turunnya harga saham. Penelitian ini bertujuan mengidentifikasi karakteristik harga saham, bagaimana hubungan inflasi, kurs dan suku bunga terhadap harga saham JII. Pengetahuan yang ditemukan akan membantu investor untuk berinvestasi lebih cerdas. Jakarta Islamic Index (JII) adalah salah satu indeks saham yang menghitung indeks harga rata-rata saham untuk jenis saham yang memenuhi kriteria syariah. Pergerakan harga saham JII disajikan setiap hari berdasarkan harga penutupan di bursa efek pada hari tersebut. Data pergerakan saham terus bertambah dan menciptakan data yang besar atau gunungan data. Dalam gunungan data tersebut, tersembunyi pengetahuan dan informasi yang dapat ditemukan dengan menggunakan teknik data mining. Data mining merupakan sebuah teknologi baru yang powerful dengan potensi yang luar biasa untuk membantu institusi menemukan pengetahuan berharga di dalam database. Dalam penelitian ini data yang akan dianalisa adalah data pergerakan harga saham JII dan beberapa variabel ekonomi makro yang mempengaruhinya yang digunakan sebagai kriteria. Kemudian data tersebut akan dikelompokkan dengan menggunakan algoritma k-Means. Algoritma k-Means akan mengelompokkan objek-objek yang memiliki kemiripan ke dalam sebuah cluster. Cluster yang terbentuk merepresentasikan karakteristiknya masing-masing. Dalam penelitian ini ditemukan pengetahuan dari cluster yang terbentuk bahwa nilai suku bunga, kurs dan inflasi berbanding terbalik dengan harga saham.]]>
<![CDATA[PERAMALAN JUMLAH PRODUKSI AIR DENGAN ALGORITMA BACKPROPAGATION ]]>
<![CDATA[Musli Yanto]]>;
<![CDATA[Sitti Rizki Mulyani]]>;
<![CDATA[Liga Mayola]]>
<![CDATA[ Sebatik Vol 23 No 1 (2019): JUNI 2019 ]]>
Publisher : <![CDATA[STMIK Widya Cipta Dharma ]]>
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<![CDATA[Pada masa saat sekarang ini, peramalan sudah menjadi bentuk bahan pertimbangan dalam segala aspek bidang. Kajian dalam jumlah produksi sering kali banyak peneliti mencoba melakukan peramalan guna sebuah proses manajemen. Dalam penelitian ini, penulis menjadikan topik penelitian yang mengkaji peramalan jumlah produksi air. Hal ini sudah banyak para peneliti melakukan penelitian yang membahas kajian prediksi jumlah produksi air dengan menggunakan Jaringan Saraf Tiruan (JST). Pada penelitian ini, penulis juga akan membahas pembahasan mengenai (JST) dengan algoritma backpropagation guna melihat lagi hasil peramalan jumlah prediksi air yang terjadi pada PDAM yang ada di kota Padang. Algoritma ini berkerja untuk melatih dan menguji pola jaringan yang terbentuk dari beberapa variabel yang digunakan dilihat dari aspek penggunaan dan jumlah air yang terjual. Proses pelatihan dan pengujian dilakukan nantinya akan menghasilkan nilai seberapa besarnya akurasi dari sebuah peramalan. Pada peramalan jumlah produksi air dengan algoritma beckpropagation, penulis mendapati Nilai akurasi pada peramalan ini sebesar 99,78 % dan nilai rata-rata kesalahan (Mape) yang didapat sebesar 0.23%, sehingga hasil peramalan yang didapat bisa dijadikan landasan dalam melakukan manajemen jumlah produksi air.]]>
<![CDATA[Implementasi E-Commerce Untuk Memperluas Pangsa Pasar Hasil Kerajinan UMKM Komunitas Hobi Kayu Padang ]]>
<![CDATA[Febri Hadi]]>;
<![CDATA[Yuhandri Yuhandri]]>;
<![CDATA[Liga Mayola]]>
<![CDATA[ JDISTIRA Vol. 1 No. 1 (2021) ]]>
Publisher : <![CDATA[JDISTIRA ]]>
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<![CDATA[Setiap UMKM sebenarnya sudah mempunyai ciri khas dari masing-masing produknya, terlebih lagi cara pengolahan kerajinan kayu. Tetapi yang perlu dilakukan disini adalah bagaimana produk milik UMKM tersebut dapat dipasarkan secara nasional maupun internasional dengan memanfaatkan E-Commerce. Selain itu dengan sosialisasi strategi pemasaran produk ini, tentunya juga bisa membantu meningkatkan penjualan UMKM tersebut. Terlebih Kota Padang merupakan Ibukota Sumatera Barat yang mana banyak dikunjungi oleh para wisatawan dari berbagai daerah di Indonesia.]]>
<![CDATA[Clustering Tingkat Penjualan Menu (Food and Beverage) Menggunakan Algoritma K-Means ]]>
<![CDATA[Hadi Syahputra]]>;
<![CDATA[Liga Mayola]]>;
<![CDATA[Dodi Guswandi]]>
<![CDATA[ Jurnal KomtekInfo Vol. 9 No. 1 (2022): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v9i1.274
<![CDATA[Menu planning in a restaurant is part of the sales strategy. Each menu has a different level of sales. To determine the effectiveness of sales and raw materials, restaurants need knowledge of what menus need to be maintained and vice versa. An analysis that can determine the sales level menu is the analysis of the k-means algorithm data mining clustering method. The source of research data is from the history of menu sales transactions for 1 year, then analyzed by the k-means algorithm. The information found is in the form of popular F&B menus and sales level menus. The purpose of this study is to group the data menu on the level of sales (Food and Beverage). The method used is the Clustering method with the performance of the K-Means algorithm. The results showed that the clustering method with the K-Means algorithm gave a significant output in grouping sales data. The research contribution provides knowledge in the form of information in conducting sales data management]]>
<![CDATA[Medical Record Information System with Rapid Application Development (RAD) Method ]]>
<![CDATA[Mutiana Pratiwi]]>;
<![CDATA[Liga Mayola]]>;
<![CDATA[Vince Kris Hiburan Laoli]]>;
<![CDATA[Ulya Ilhami Arsyah]]>;
<![CDATA[Nila Pratiwi]]>
<![CDATA[ Journal of Information Systems and Technology Research Vol. 1 No. 2 (2022): May 2022 ]]>
Publisher : <![CDATA[AIRA ]]>
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DOI: 10.55537/jistr.v1i2.170
<![CDATA[Computer technology that is increasingly developing has created a situation that demands everything to be computerized. Science from technology has also changed the way of life of most Indonesians. The presence of information and communication technology affects the technology applied in information systems, especially the input and output mechanisms. One of them is at the Clinic which requires computer technology in its operations. The design of this website also uses 3 stages of Rapid Application Development (RAD) system design, the result of which is a website for a medical record information system. In order for clinical activities to run smoothly at the Clinic, an information system using the Rapid Application Development (RAD) method is needed because the software development process model is classified as an incremental technique and emphasizes short, short, and fast development cycles. Medical record system testing will be tested using Blackbox Testing and User Acceptance Test (UAT) testing.]]>
<![CDATA[Sistem Pakar Diagnosa Penyakit Hiperlipidemia Menggunakan Metode Certainty Factor Berbasis Web ]]>
<![CDATA[Muhammad Afdhal]]>;
<![CDATA[Rita]]>;
<![CDATA[Liga Mayola]]>
<![CDATA[ Jurnal KomtekInfo Vol. 9 No. 4 (2022): Komtekinfo ]]>
Publisher : <![CDATA[Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.35134/komtekinfo.v9i4.321
<![CDATA[Perkembangan siklus modrenisasi seiring meningkatnya kepentingan manusia berbagai segi kehidupan telah mengubah gaya dan pola hidup saat sekarang ini. Hal ini dapat terlihat dari gaya hidup masyarakat yang membiasakan diri dalam pola hidup tidak sehat dengan banyak mengkosumsi makanan yang tidak sehat. Akibat yang ditimbulkan dengan hal ini adalah penyakit yang dapat menyerang bahkan dapat merenggut nyawa seseorang. Salah satu penyakit yang berkembang dari pola makanan tidak sehat salah satunya adalah Hiperlipidemia. Penyakit ini merupakan kumpulan lemak yang terdapat di dalam aliran darah atau sel tubuh yang sebenarnya dibutuhkan untuk pembentukan dinding sel. Penyakit ini mampu membuat sesorang mengalami penurunan kesehatan hingga mampu menyebabkan gejala penyakit struk. Dengan ini maka tujuan penelitia ini adalah untuk membangun sistem pakar yang mampu melakukan diagnosa penyakit Hiperlipidemia. Metode Forward Chaining (FW) dan Certainty Factor (CF) digunakan untuk memberikan hasil diagnosa yang cukup tepat dan akurat. Dataset penelitian ini menggunakan data gejala dan jenis dari penyakit Hiperlipidemia. Hasil penelitian ini memberikan keluaran berupa hasil diagnosa dengan nilai CF berdasarkan jenis penyakit dan gejala yang dialami oleh user. Hasil ini mampu dijadikan sebuah solusi alternatif guna membantu pihak medis dalam melakukan pengawasan terhadap penyakit Hiperlipidemia yang dialami oleh masyarakat. dengan hal ini maka manfaat penelitian ini mampu dijadikan sebagai model analisis dalam penekanan laju pertumbuhan penyakit Hiperlipidemia.]]>
<![CDATA[KEPUASAN PELANGGAN TERHADAP JASA PENGIRIMAN BARANG MENGGUNAKAN METODE ALGORITMA C4.5 ]]>
<![CDATA[Nurul Azwanti]]>;
<![CDATA[Sri Tria Siska]]>;
<![CDATA[Liga Mayola]]>
<![CDATA[ Ensiklopedia of Journal Vol 5, No 2 (2023): Volume 5 No. 2 Edisi 2 Januari 2023 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia ]]>
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DOI: 10.33559/eoj.v5i2.1509
<![CDATA[Currently shipping services are needed by the community to make it easier to move between cities and transport products or trade goods. PT. Kerabat Jasa Antar is a provider of goods delivery services based in the Batam area and already has many customers. Quality of service is the most important factor to win the competition between shipping services. Goods delivery service providers must give the best to their customers in order to survive. Therefore, it is necessary to analyze customer satisfaction to see whether the customer is satisfied or not with the services provided. The research method uses interview techniques and distributes questionnaires and studies literature related to research. The C4.5 algorithm is a data mining method that is capable of producing rules to view the results of customer satisfaction data processing. The results of the rules that are formed are 4 rules with the attributes that affect are Security, Timeliness and Service. The first rule is if the security is not safe, then the customer is not satisfied, the next rule is if the security is safe, on time is not and the service is not good then the customer is not satisfied. Testing was carried out using the Weka application where the decision tree formed produced the same rules as the analysis that had been carried out. The results of this study are expected to be a consideration for companies to improve their performance in order to retain their customers.]]>
