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All Journal ILKOM Jurnal Ilmiah Jurnal Nasional Komputasi dan Teknologi Informasi Simtek : Jurnal Sistem Informasi dan Teknik Komputer
Annahl Riadi
Universitas Ichsan Sidenreng Rappang
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Neuroscience Transportation

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ANALISIS IMPLEMENTASI PREPROCESSING DENGAN OTSU-GAUSSIAN PADA PENGENALAN WAJAH Riadi, Annahl; Sulaehani, Ruhmi
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.457.200-205

Abstract

In this research, we will focus on facial expressions to detect customer satisfaction in mini markets where the service level is less than optimal. To find out the level of custome satisfaction can be seen through facial recognition tahen through CCTV in the mini market. The problems that occur are many customers who do not directly convey the impression that is felt when shopping, while minimarkets and shopping conters must know the level of customer satisfaction to improve sales strategies. Research to solve the problem is still rerely done, therefore one of the roles of intelligent computing is to solve the problem using Support Vector machine (SVM). The purpose of this study is to improve the accuracy of facial expressions of mini market customers through improved preprocessing. The results of the application of the otsu method and the gaussian function can be used for the preprocessing stage through a threshold image that has good image quality. The otsu-gaussian method is not effectively used for preprocessing data sourced from video or images with poor image quality, making it difficult to recognize faces.
PENERAPAN METODE FUZZY TSUKAMOTO UNTUK SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN PEMBANGUNAN RUMAH LAYAK HUNI PADA DESA SIPAYO Annahl Riadi
Simtek : jurnal sistem informasi dan teknik komputer Vol 4 No 1 (2019): April 2019
Publisher : STMIK Catur Sakti Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.756 KB) | DOI: 10.51876/simtek.v4i1.49

Abstract

Dengan adanya program bantuan pembangunan rumah layak huni dari desa diharapkan masyarakat Desa Sipayo dapat merasakan hidup layak dan nyaman. Namun terkadang proses seleksi yang tidak terkomputerisasi menimbulkan kecemburuan antara masyarakat penerima bantuan dan masyarakat miskin lainnya. Agar pemberian bantuan Rumah Layak huni menjadi tepat sasaran, maka dibutuhkan suatu Sistem yang mampu mendukung dalam proses pengambilan Keputusan Penerima Bantuan Pembangunan Rumah Layak Huni. Oleh karena itu pada penelitian ini akan dirancang sebuah sistem pendukung keputusan untuk mendukung pengambilan keputusan dalam menentukan Pemberian bantuan Rumah Layak huni, agar benar-benar tepat sasaran dan melalui proses seleksi dan perhitungan yang tepat. Untuk itu peneliti mencoba membantu permasalahan tersebut di atas dengan membuatkan suatu sistem pendukung keputusan menggunakan metode Fuzzy Tsukamoto dengan Bahasa Pemrograman PHP, Database MySQL, serta penggunaan Aplikasi Deamweaver dan Photoshop. Berdasarkan hasil pengujian white box disimpulkan bahwa sistem pendukung keputusan ini bebas dari kesalahan program dengan total Cyclomatic Complexity=6, Region= 6, dan Independent Path=6
PENERAPAN METODE CERTAINTY FACTOR UNTUK SISTEM PAKAR DIAGNOSA PENYAKIT DIABETES MELITUS PADA RSUD BUMI PANUA KABUPATEN POHUWATO Annahl Riadi
ILKOM Jurnal Ilmiah Vol 9, No 3 (2017)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i3.162.309-316

Abstract

Diabetes Melitus (DM) atau biasa disebut diabetes merupakan penyakit gangguan metabolik menahun akibat pankreas tidak memproduksi cukup insulin atau tubuh tidak dapat menggunakan insulin yang diproduksi secara efektif. Penderita Diabetes Melitus di Kabupaten Pohuwato mengalami peningkatan sebanyak 8,5% setiap Tahun. Sistem pakar adalah program komputer yang menirukan penalaran seorang pakar dengan keahlian  pada suatu wilayah pengetahuan tertentu. Sistem pakar mencoba mencari solusi, memberikan saran atau kesimpulan yang konsisten terhadap permasalahan yang ditemukannya. Penelitian ini akan dirancang menggunakan Aplikasi Dreamweaver dan bahasa pemrograman PHP, serta database MySQL. Harapan penulis, sistem ini dapat membantu masyarakat dalam mendiagnosa penyakit Diabetes Melitus. Melalui aplikasi ini, pengguna dapat melakukan konsultasi dengan sistem layaknya berkonsultasi dengan seorang pakar untuk mendiagnosa gejala yang terjadi pada pengguna serta menemukan solusi atas permasalahan yang dihadapi. Hasil pengujian sistem diperoleh nilai  Cylomatic complexity = 5 dengan jumlah Region (R)= 5, Node (N)= 10, Edge (E)=13  Predicate Node (P) = 4.
Neural Network Method Based on Particle Swarm Optimization for Predicting Satisfaction of Recipients of Internet Data Support from the Ministry of Education and Culture Annahl Riadi; Irvan Muzakkir; Marniyati H. Botutihe
ILKOM Jurnal Ilmiah Vol 14, No 1 (2022)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The free quota assistance program for students and lecturers is an assistance program carried out by the ministry of education and culture, this program has been implemented since the impact of the covid-19 pandemic in all regions of Indonesia, this assistance is expected to help students and lecturers in carrying out online learning caused by the pandemic covid-19, the purpose of this study is to measure the level of visitor satisfaction through predictions of satisfaction so that it can help the government in advancing the world of education., data processing is carried out using the rapid miner application and using the neural network method with particle swarm optimization, from the results of data processing the results obtained are Values the accuracy for the neural network algorithm model is 42.44% and the accuracy value for the PSO-based neural network algorithm model is 91.86%.
Visitor satisfaction prediction of the 'Pantai Pohon Cinta' beach tourism using the backpropagation algorithm with particle swarm optimization feature selection Annahl Riadi; Marniyati Husain Botutihe
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.791.117-124

Abstract

This study focuses on the visitors of Pohon Cinta beach tourist area. This beach is one of the potential tourism objects in Pohuwato Regency. The main problem that frequently occurs is that many visitors cannot directly convey their impression when visiting and enjoying the beauty of the Pohon Cinta beach. The government needs to know the level of visitor satisfaction to attempt to improve and develop the Pohon Cinta beach tourist attraction. Thus, to solve the problem above, a method that can help predict visitor satisfaction is needed. This study aims to measure visitor satisfaction through predictions using the Backpropagation algorithm and PSO feature selection to assist the government in developing tourism potential in Pohuwato Regency. The method used is the backpropagation algorithm for prediction and Particle Swarm Optimization which is considered effective in overcoming optimization problems. This algorithm is considered capable of solving problems in the backpropagation algorithm. The accuracy value of the backpropagation algorithm model is 84.67%, the accuracy value of the PSO-based backpropagation algorithm model is 85.00%, and the difference in accuracy is 0.33. The results of the application of the Backpropagation algorithm and Particle Swarm Optimization can increase the predictive accuracy value of visitor satisfaction at the Cinta Tree Beach tourist attraction.
Metode Composite Performance Indekx (CPI) Sistem Pendukung Keputusan Penilaian Desa Terbaik Annahl Riadi; Irvan Muzakkir
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 6 (2022): Desember 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i6.5153

Abstract

Abstrak - Kegiatan pelaksanaan penilaian desa terbaik harus dilakukan dengan terbuka dan kompetitif meskipun jumlah data yang dimasukan relatif banyak. Penilaian desa terbaik sering terkendala, karena setiap desa memiliki karakteristik yang berbeda sehingga menyebabkan nilai kriteria pada masing-masing desa berbeda. Perhitungan dari penilaian masih dilakukan dalam manual sehingga masih banyaknya kesalahan pelaksanaannya dan penilaian desa yang terbaik belum dilaksanakan secara terbuka dan transfaran. Berdasarkan permasalahan tersebut dibutuhkan sistem pendukung keputusan penilaian desa terbaik menggunakan metode Composite Performance Index (CPI) yag dapat diterapkan pada Kecamatan Patilanggio dalam pengambilan keputusan, sehingga dapat diimplementasikan. Sistem pendukung keputusan penilaian desa terbaik hasil dari perhitungan Metode Composite Performance Index (CPI) merupakan prioritas yang dibutuhkan sebagai bahan pertimbangan pada Kecamatan Patilanggio untuk menentukan Penilaian Desa Terbaik. Hasil yang diperoleh SPK Penilaian Desa Terbaik Berdasarkan Hasil Pengujian White Box Disimpulkan Bahwa Sistem Pendukung Keputusan Ini Bebas Dari Kesalahan Program Dengan Total Node(N)= 15, Edge(E)= 18, Predicate Node(P)= 7 Region(R)= 8Kata kunci: SPK, CPI, Penilaian, Desa Terbaik, Patilanggio Abstrack - The activity of implementing the best village assessment must be carried out openly and competitively even though the amount of data entered is relatively large. The assessment of the best village is often constrained, because each village has different characteristics, causing the criteria values for each village to be different. The calculation of the assessment is still done manually so there are still many implementation errors and the best village assessment has not been carried out openly and transparently. Based on these problems, a decision support system for the best village assessment is needed using the Composite Performance Index (CPI) method which can be applied to Patilanggio District in decision making, so that it can be implemented. The decision support system for the best village assessment resulting from the calculation of the Composite Performance Index (CPI) Method is a priority needed as material for consideration in Patilanggio District to determine the Best Village Assessment. The results obtained by the SPK for the Best Village Assessment Based on the White Box Test Results It was concluded that this Decision Support System was free from program errors with Total Node(N)= 15, Edge(E)= 18, Predicate Node(P)= 7 Region(R)= 8Keywords: SPK, CPI, Evaluation, Best Village, Patilanggio
Metode K-Nearest Neighbor (KNN) Untuk Sistem Pakar Diagnosa Penyakit Pneumonia Pada Balita Fatma Tolana; Irvan Muzakkir; Annahl Riadi
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 6, No 3 (2023): Juni 2023
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v6i3.6332

Abstract

Abstrak - Pneumonia yaitu radang paru-paru, penyebabnya adalah bakteri dengan gejala panas tinggi disertai batuk berdahak, napas cepat, sesak, dan gejala lainnya. Permasalahan yang dihadapi masyarakat saat ini adalah keterlambatan penanganan secara medis kepada penderita pneumonia karena beberapa alasan diantaranya masyarakat harus menunggu antrian sehingga balita yang di periksa kondisinya setelah penyakit pneumonia sudah parah. Dikarenakan permasalahan tersebut, sehingga mendorong peneliti untuk merancang sebuah system yang dapat dimanfaatkan oleh puskesmas paguat sehingga mampu mengurangi banyaknya antrian serta mampu mendeteksi adanya penyakit khususnya pada balita. Sistem pakar ini bisa memberikan informasi yang cepat tentang penyakit pneumonia beserta terapi pengobatan. Pada penelitian ini digunakan metode K-Nearest Neighbor sebagai metode untuk menghitung nilai data pembelajaran (neighbor) yang jaraknya paling dekat dengan objek tersebut. atas gejala-gejala yang dipilih. Bahasa pemrograman yang digunakan php dan database mysql.Kata kunci: expert system, PHP, Pneumonia , KNN Abstract - Pneumonia is inflammation of the lungs, the cause is bacteria with symptoms of high heat accompanied by cough with phlegm, rapid breathing, spasms, and other symptoms. The problem faced by the community at this time is the delay in medical treatment to patients with pneumonia due to several reasons including the community having to wait in a queue so that toddlers who are examined for their condition after pneumonia are already severe. Because of these problems, thus encouraging researchers to design a system that can be used by health centers paguat so as to reduce the number of queues and be able to detect the presence of disease, especially in infants. This expert system can provide fast information about pneumonia and treatment therapies. In this study the K-Nearest Neighbor method is used as a method to calculate the value of learning data (neighbor) which is the closest distance to the object. for the selected symptoms. The programming language used is php and the mysql database.Keywords: expert system, PHP, Pneumonia , KNN
Metode K-Nearest Neighbor (KNN) Untuk Sistem Pakar Diagnosa Penyakit Pneumonia Pada Balita Fatma Tolana; Irvan Muzakkir; Annahl Riadi
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 6, No 3 (2023): Juni 2023
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v6i3.6332

Abstract

Abstrak - Pneumonia yaitu radang paru-paru, penyebabnya adalah bakteri dengan gejala panas tinggi disertai batuk berdahak, napas cepat, sesak, dan gejala lainnya. Permasalahan yang dihadapi masyarakat saat ini adalah keterlambatan penanganan secara medis kepada penderita pneumonia karena beberapa alasan diantaranya masyarakat harus menunggu antrian sehingga balita yang di periksa kondisinya setelah penyakit pneumonia sudah parah. Dikarenakan permasalahan tersebut, sehingga mendorong peneliti untuk merancang sebuah system yang dapat dimanfaatkan oleh puskesmas paguat sehingga mampu mengurangi banyaknya antrian serta mampu mendeteksi adanya penyakit khususnya pada balita. Sistem pakar ini bisa memberikan informasi yang cepat tentang penyakit pneumonia beserta terapi pengobatan. Pada penelitian ini digunakan metode K-Nearest Neighbor sebagai metode untuk menghitung nilai data pembelajaran (neighbor) yang jaraknya paling dekat dengan objek tersebut. atas gejala-gejala yang dipilih. Bahasa pemrograman yang digunakan php dan database mysql.Kata kunci: expert system, PHP, Pneumonia , KNN Abstract - Pneumonia is inflammation of the lungs, the cause is bacteria with symptoms of high heat accompanied by cough with phlegm, rapid breathing, spasms, and other symptoms. The problem faced by the community at this time is the delay in medical treatment to patients with pneumonia due to several reasons including the community having to wait in a queue so that toddlers who are examined for their condition after pneumonia are already severe. Because of these problems, thus encouraging researchers to design a system that can be used by health centers paguat so as to reduce the number of queues and be able to detect the presence of disease, especially in infants. This expert system can provide fast information about pneumonia and treatment therapies. In this study the K-Nearest Neighbor method is used as a method to calculate the value of learning data (neighbor) which is the closest distance to the object. for the selected symptoms. The programming language used is php and the mysql database.Keywords: expert system, PHP, Pneumonia , KNN
Sistem Pendukung Keputusan Penerimaan Siswa Baru Pada SMA Negeri 1 Paguat Menggunakan Metode Weighted Product Bahrin Bin Dahlan; Betrisandi Betrisandi; Annahl Riadi
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 2 (2024): April 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i2.7200

Abstract

Abstrak—Siswa adalah komponen masukan dalam sistem pendidikan, yang selanjutnya diproses dalam proses pendidikan, sehingga menjadi manusia yang berkualitas sesuai dengan tujuan pendidikan nasional. Sebagai suatu komponen pendidikan siswa dapat ditinjau dari berbagai pendekatan, antara lain Proses Penerimaan Siswa Baru yang dilakukan selama ini masih memiliki beberapa kelemahan sehingga menimbulkan beberapa persoalan, diantaranya proses penentuan siswa baru yang diterima kurang transparan, semua itu dikarenakan hasil pengumuman hanya di umumkan nilai skor akhir, tetapi criteria yang lain tidak di umumkan. Dalam penerimaan siswa baru, ada 6 kriteria yang digunakan. Ada beberapa orang tua calon siswa baru mempertanyakan hasil penilaian atau penentuan kelulusan, mengapa anaknya tidak lulus, padahal menurut mereka anaknya bisa lulus Salah satu metode sistem pendukung keputusan adalah Metode Weighted Product. Metode ini merupakan salah satu metode penyelesaian yang ditawarkan untuk menyelesaikan masalah Multi Attribute Decision Making (MADM). Metode Weighted Product mirip dengan metode Weighted Sum (WS), hanya saja metode Weighted Product terdapat perkalian dalam perhitungan matematikanya. Dengan metode Weighted Product ini penulis membuat sebuah sistem pendukung keputusan Penerimaan Siswa Baru yang akan membantu para pembuat keputusan dalam menentukan pilihan siapa yang berhak dan layak diterima sebagai siswa baru pada Sekolah Menengah Atas Negeri 1 Paguat.Keyword : Penerimaan, Siswa Baru, Weighted Product, Multi Attribute Decision Making  Abstract — Students are input components in the education system, which are then processed in the education process, so that they become quality human beings in accordance with national education goals. As a component of student education, it can be viewed from various approaches, including the New Student Admissions Process that has been carried out so far still has several weaknesses, giving rise to several problems, including the process of determining which new students are accepted is less transparent, all of this is because the results of the announcement only announce the score. final, but other criteria are not announced. In accepting new students, there are 6 criteria used. There are several parents of prospective new students who question the results of the assessment or determination of graduation, why their child did not pass, even though they think their child can pass. One of the decision support system methods is the Weighted Product Method. This method is one of the solution methods offered to solve Multi Attribute Decision Making (MADM) problems. The Weighted Product method is similar to the Weighted Sum (WS) method, only the Weighted Product method contains multiplication in the mathematical calculations. Using the Weighted Product method, the author created a decision support system for New Student Admissions that will assist decision makers in determining who has the right and worth to be accepted as a new student at Paguat 1 State High School.Keywords: Admissions, New Students, Weighted Product, Multi Attribute Decision Making
Co-Authors Bahrin Bahrin Betrisandi, Betrisandi Fatma Tolana Irvan Muzakkir Ivo Colanus Rally Drajana Marniyati H. Botutihe Marniyati Husain Botutihe Novriyanti Polimengo Sulaehani, Ruhmi