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All Journal Pixel : Jurnal Ilmiah Komputer Grafis SITEKIN: Jurnal Sains, Teknologi dan Industri CESS (Journal of Computer Engineering, System and Science) Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komputer Terapan Indonesian Journal of Artificial Intelligence and Data Mining INOVTEK Polbeng - Seri Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) CSRID (Computer Science Research and Its Development Journal) JOISIE (Journal Of Information Systems And Informatics Engineering) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal J-PEMAS JAIA - Journal of Artificial Intelligence and Applications Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi Jurnal Indonesia : Manajemen Informatika dan Komunikasi

Rahmaddeni Rahmaddeni

STMIK Amik Riau

Author-ID : 355412

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Implementasi Metode Forward Chaining untuk Identifikasi Penyakit Kulit dan Alternatif Penanganannya Rohana Yola Parastika Hutasoit; Rahmaddeni Rahmaddeni; Erlin Erlin; Muhammad Khairul Anam
Jurnal Inovtek Polbeng Seri Informatika Vol 6, No 1 (2021)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v6i1.1851

Salah satu penyakit yang sangat sering menjangkiti manusia adalah penyakit kulit. Hal tersebut terjadi karena kulit adalah bagian terluar tubuh, sehingga kuman, bakteri dan kotoran sangat mudah menempel pada kulit dan menyebabkan penyakit. Namun, mengetahui jenis penyakit kulit dan bagaimana cara penanganannya bukanlah hal yang mudah, sementara untuk konsultasi atau berobat ke dokter pakar atau ahli kulit pastinya membutuhkan biaya yang besar. Selain itu, keterbatasan waktu dan tempat juga membuat penderita penyakit kulit sulit untuk berkonsultasi atau berobat. Oleh karena itu, aplikasi mobile dirancang untuk membantu mengidentifikasi penyakit yang diderita menggunakan forward chaining. Penyakit yang dapat diidentifikasi pada aplikasi ini adalah eksim, scabies, psoriasis dan tinea. Selain mengidentifikasi penyakit, aplikasi ini juga memberikan alternatif penanganan sehingga pengguna dapat melakukan alternatid tersebut untuk mengatasi penyakit yang diderita. Sebelum penelitian ini dilakukan, penulis telah berdiskusi dengan spesialis kulit yang merupakan seorang dokter poli kulit dan kelamin di Rumah Sakit Awal Bross Panam Pekanbaru. Hasil dari penelitian ini adalah sebuah aplikasi mobile untuk membantu penggunanya dalam mengidentifikasi penyakit kulit dan memberikan alternatif penanganan sehingga pengguna dapat menghemat biaya, waktu dan tempat. Nilai akurasi hasil penelitian ini adalah 90%, presisi 100% dan spesifikasi 100%.

Perbandingan Boolean Model Dan Vector Space Model Dalam Pencarian Dokumen Teks Susanti Susanti; Muhammad Azmi; Edwar Ali; Rahmaddeni Rahmaddeni; Yansyah Saputra Wijaya
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 11 No. 2 (2020): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v11i2.4168

Perkembangan teknologi informasi di era globalisasi saat ini, membuat semua aspek kehidupan kita berubah dan tidak dapat dihindarkan dari pengaruh kemajuan zaman. Untuk mendapatkan data dan informasi yang kita inginkan bukanlah perkara mudah, mengingat sedemikian banyaknya informasi yang tersedia untuk berbagai keperluan dengan berbagai gaya penyajian. Pencarian data di komputer, baik itu secara online ataupun offline berkembang banyak metode yang semakin menyempurnakan hasil pencarian. Hal ini juga meningkatkan kepuasan pengguna dalam mencari informasi. Metode yang umum digunakan dalam melakukan pencarian adalah Boolean Model. Metode lainnya adalah Vector Space Model (VSM). VSM yaitu model yang digunakan untuk mengukur kueri antara suatu dokumen dengan suatu kata kunci. Oleh karena itu, penulis bertujuan untuk membandingkan kedua metode tersebut dari kecepatan (waktu) pencarian dan jumlah temuan. Kecepatan tersebut dihitung berdasarkan lama waktu pencarian untuk kedua metode tersebut. Hasil yang didapati adalah perbandingan waktu pencarian antara boolean model dan vector space model didapati bahwa boolean model lebih cepat dengan selisih 30 sampai 50 detik. Perbandingan untuk hasil temuan didapati bahwa vector space model mempunyai hasil temuan yang sama dengan boolean model yang menggunakan operator or, sedangkan dengan operator and dan gabungan and serta or didapati bahwa jumlah hasil temuan tidak sama dengan vector space model. Kata kunci: Perbandingan, Boolean Model, Vector Space Model, Pencarian, Dokumen Teks Abstract The development of information technology in the current era of globalization, makes all aspects of our lives change and cannot be avoided from the influence of the times. To get the data and information that we want is not an easy matter, considering that so much information is available for various purposes with various styles of presentation. Searching data on a computer, be it online or offline, there are many methods that improve the search results. It also increases user satisfaction in finding information. The most commonly method of searching is the Boolean Model. Another method is the Vector Space Model (VSM). VSM is a model used to measure queries between a document and a keyword. Therefore, the authors aim to compare the two methods from the speed (time) of the search and the number of findings. The speed is calculated based on the search time for both methods. The result is that the comparison between boolean model and vector space model shows that the boolean model is faster by a difference of 30 - 50 seconds. The comparison for the foundings document text shows that vector space model has the same findings as the boolean model using the or operator, whereas with the and operator and the combination of operator and or it is found that the number of findings is not the same as vector space model. Keywords: Comparison, Boolean Model, Vector Space Model, Search, Text Documents

Virtual Tour Interaktif 360 Derajat Menggunakan Teknik Image Stitching Sebagai Media Informasi Kampus STMIK Amik Riau Mardainis Mardainis; M. Arifin; Rahmaddeni Rahmaddeni; Yoyon Efendi
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 11 No. 2 (2020): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v11i2.4265

Salah satu strategi untuk meningkatkan pertumbuhan jumlah mahasiswa baru untuk masuk ke STMIK Amik Riau dilakukannya kegiatan sosialisasi oleh bagian promosi dan penerimaan mahasiswa baru (PPMB). Media promosi yang digunakan berupa brosur, kalender, spanduk dan baliho serta melaksanakan sosialisasi ke sekolah. Promosi secara digital juga dilakukan dengan memanfaatkan website kampus dan media sosial seperti facebook, instagram, whatsapp serta youtube. Penelitian ini memberikan ide promosi dengan penggunaan Virtual Tour dengan memanfaatkan teknologi fotografi 360 derajat dengan teknik image stitching. Langkah pertama dilakukan pemilihan beberapa lokasi yang akan ditampilkan dalam Virtual Tour yang berada dalam lingkungan kampus STMIK Amik Riau. Pemilihan lokasi dengan mempertimbangkan kebutuhan informasi yang sering dibutuhkan oleh calon mahasiswa, seperti lokasi ruang pendaftaran, ruang akademik, ruang baak, ruang perkuliahan, laboratorium, aula dan mushala beserta fasilitas lainnya. Selanjutnya dilakukan kegiatan pemotretan diberbagai lokasi kampus yang sudah dipilih sebelumnya. Beberapa foto yang sudah diambil ditiap lokasi digabungkan menjadi bidang yang besar dengan teknik stitching. Selanjutnya dibuat narasi berupa teks dan audio untuk setiap lokasi foto tersebut. Penelitian dilakukan melalui beberapa langkah mulai dari Concept, Design, Material Collecting, Assembly, Testing sampai Distribution. Dari hasil pengujian Virtual Tour ini, calon mahasiswa baru bisa mengetahui informasi kampus tanpa datang ke kampus STMIK Amik Riau. Abstract One of the strategies to increase the growth of the number of new students to enter Amik Riau STMIK is to conduct socialization activities by the promotion and admission of new students (PPMB). Promotional media used in the form of brochures, calendars, banners and billboards as well as carrying out socialization to schools. Digital promotion is also carried out by utilizing campus websites and social media such as Facebook, Instagram, WhatsApp and YouTube. This research provides promotional ideas with the use of Virtual Tour by utilizing 360 degree photography technology with image stitching techniques. The first step is to choose several locations that will be displayed on the Virtual Tour within the Amik Riau STMIK campus environment. Site selection by considering the information needs that are often needed by prospective students, such as the location of the registration room, academic room, classroom, lecture room, laboratory, hall and prayer room along with other facilities. Next, there will be a photo shoot at various campus locations that have been previously selected. Some photos that have been taken at each location are combined into a large field with stitching techniques. Then a narration in the form of text and audio is made for each location of the photo. The study was conducted through several steps ranging from Concept, Design, Material Collecting, Assembly, Testing to Distribution. From the results of this Virtual Tour test, prospective new students can find out campus information without coming to the STMIK Amik Riau campus.

Penerapan Algoritma Naïve Bayes Untuk Pengelompokkan Predikat Peserta Uji Kemahiran Berbahasa Indonesia Michal Dennis; Rahmaddeni Rahmaddeni; Fransiskus Zoromi; M. Khairul Anam
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3956

Indonesian Language Proficiency Test is a proficiency test to measure a person's language proficiency in communicating using Indonesian, both Indonesian speakers and foreign speakers. The UKBI rating has 7 rating categories consisting of special, very excellent, excellent, intermediate, poor, marginal, and limited. The number of participants who take UKBI at the Riau Province Language Center has more than 1000 but no one has managed the data into new knowledge. One of the efforts that can be done with the data is classification. The Naïve Bayes Classification Algorithm is a classification algorithm that is very effective (getting the right results) and efficient (the reasoning process is carried out by utilizing existing inputs in a relatively fast way). In order to obtain good accuracy results, the Naive Bayes Algorithm is combined with the Adaboost feature selection with a 70:30 and 80:20 test scheme. The results of the research carried out resulted in the highest accuracy value, namely 89% which combined the Naive Bayes algorithm with the Adaboost feature selection with 70:30 data splitting

Prediksi Penambahan Piutang Iuran Jaminan Sosial Ketenagakerjaan menggunakan Algoritma K-Nearest Neighbor Devi Efriadi; Rahmaddeni Rahmaddeni; Agustin Agustin; Junadhi Junadhi
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 1 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i1.5255

There are several issues with Social Security Organizing Agency (BPJS) employment at the moment, one of which is contribution receivable. To reduce the BPJS contribution receivables, BPJS has done various ways. However, the resulting effort is not maximal enough to reduce the number of receivables in BPJS. This study aims to provide input by predicting the addition of receivables from social security contributions made by several companies or organizations. This study used the K-Nearest Neighbor (KNN) Algorithm with a cross-validation technique. KNN is a very simple classification method in classifying an image based on the closest distance to its neighbors. This study conducted data processing from BPJS use, which amounted to 1193 data. The data is then preprocessed so that the processed data is clean from missing and noise, this data uses 70:30 data splitting. After the preprocessing and splitting of data were carried out, the next step was to do modeling using KNN, so the cross-validation to improve the accuracy of results obtained from the KNN algorithm. The results obtained from this research get the highest accuracy of 92% with the Optimal K value being 6, then the ROC curve gets 94% accuracy. From these results, it can be said that the use of cross-validation can increase the accuracy of this study.

Pengujian ISO 25010 Pada Smart Chair Akupresure Berbasis Internet Of Things (IoT) Diki Daryanto; M. Khairul Anam; Yoyon Efendi; Rahmaddeni Rahmaddeni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4134

Smart chair acupressure is a technology that has been built using the application of the internet of things concept. The purpose of this study was to determine the quality level of the Acupressure Smart Chair, so that there are no errors in some features and the occurrence of errors in its functionality, which must be in accordance with the specified usability, the researchers conducted a test by utilizing the characteristics of ISO 25010. Related to the researcher's reasons taking ISO 25010 as one of the tests on the acupressure smart chair is because the smart chair acupressure technology cannot be said to be feasible because there has been no testing carried out in the measurement, the researchers used ISO 25010 which utilizes several characteristics that can be used such as functional suitability, usability and performance efficiency which focuses on measuring the electronic equipment used. Basically the concept used in this research is the internet of things which is a system that functions to control and simplify the workings of acupressure massage techniques for users. Whereas other problems that occur and arise often depend on customer satisfaction related to the quality provided on software and devices. This study uses the ISO 25010 method as the standard for the feasibility test on the device, where ISO 25010 basically also has 8 characteristics. In this study, to test the smart acupressure hair, the researchers used 7 characteristics that exist in ISO 25010, namely functional suitability, compatibility, usability, performance efficiency, reliability, maintability and portability. The instrument used is looking for an approach using the formula for reliability testing and processing on SPSS software. The results obtained from this study are that the acupressure smart chair has not been able to meet the ISO 25010 standard because the results obtained are 34.9% with an alpha cronbch value of 0.46 (unacceptable)

Sistem Marketplace Pencarian Lapangan Futsal Menggunakan Metode Haversine Berbasis Android Muhamad Jamaris; Hendra Saputra; M. Khairul Anam; Khusaeri Andesa; Rahmaddeni Rahmaddeni
Pixel :Jurnal Ilmiah Komputer Grafis Vol 15 No 1 (2022): Vol 15 No 1 (2022): Jurnal Ilmiah Komputer Grafis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v15i1.712

Futsal is a soccer game played indoors, this game itself is played by two teams, each team consisting of five people. At this time futsal is very much in demand from various groups ranging from children to adults, so there are many futsal field rental places, especially in the city of Pekanbaru. However, the problem that occurs is that it is still difficult for tenants to find out where there is a futsal field and the nearest futsal field from where the tenant is located, including price information and field facilities. Therefore, we need a system that can make it easier for tenants to find out where there is a futsal field and the nearest futsal field from the tenant's location. This system is made based on Android so that it can make it easier for users to use this system. The method used in making this system is the Haversine method. The results obtained are a marketplace system that can make it easier for users to find out where there is a futsal field, find the nearest field and it is also easy to find out all information related to the field and can make it easier to rent a futsal field through the marketplace system.

Chatbot Designing Information Service for New Student Registration Based on AIML and Machine Learning Yansyah Wijaya; Rahmaddeni; Fransiskus Zoromi
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 1 (2020): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

One of the efforts made by universities to serve prospective students is by providing consulting services and information that is usually carried out directly at the booth provided, through phone service or live chat support available on the college website. Increased visitors will result in waiting times due to limited availability of officers, which results in decreased satisfaction of prospective new students, moreover this service is only available during campus operating hours. One alternative solution to overcome this problem is to use Chatbot, able to answer questions raised by prospective new students which can be categorized as Frequently Asked Questions abbreviated as FAQ. Chatbot technology can be developed with a variety of AI (Artificial Intelligence) techniques. One of them is the AIML (Artificial Intelligence Markup Language) technique. One of the main drawbacks of AIML is that there is no reasoning ability so a learning system that is focused on supervised learning is needed. In the chatbot that will be built the learning process uses a selective neural conversational model or commonly called the Deep Semantic Similarity Model (DSSM) developed by Microsoft. Meanwhile, the measurement of chatbot performance will be done using Confusion Matrix which is a method of evaluating the performance of the algorithm from Machine Learning (ML). The results of the study stated that the chatbot system that was built was able to answer questions posed by prospective students properly and correctly while the questions were available in the chatbot knowledge base.

Data Mapping System Of Riau Province Fire Potential Using K-Means Clustering Method Rahmaddeni Deni; Andi Kurnianto
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 1 (2020): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

According to a report from the Riau Province BLHK states that hotspots in Riau Province are always present every year despite the number of hotspots that have been suppressed (http://dislhk.riau.go.id/). One of the causes is the frequent land clearing occurred as a trigger from a hotspot in Riau Province. There is a need for countermeasures as soon as possible to overcome the problem of hotspots that will cause forest fires. These problems need to be watched out quickly, one of which is to know in advance the hotspots that are likely to emerge based on existing data. Data mining processing is very suitable to be applied in order to produce relevant data to find out the possibility of hotspots. In this study the data grouping was done in the form of a visualization of hotspot mapping using the K-means Clustering method. The parameters used include 3 number of clusters (critical, alert, vigilant), 12 regencies / cities in Riau Province and 3 attributes (hotspots, number of fires, number of events). With the results of the visualization of the mapping using the K-means Clustering method, it is expected to be able to help the relevant parties, namely the Riau Provincial Forest Service in handling early the hotspots that are likely to emerge.

4 Star Complementary Food Menu Recommendation System Using the Mobile-Based Fuzzy Multiple Attribute Decision Making (FMADM) Method Rahmaddeni; Fransiskus Zoromi; Yansyah Saputra Wijaya; M. Khairul Anam
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 2 (2021): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Toddler in the age category of six to twenty-four months should be ready to be given complementary food. In order to fulfill the nutritional needs for the toddler's growth, complementary foods must be sufficient for the kid according to their age while still paying attention to the continuity of breastfeeding. One thing that must be considered in choosing complementary foods is the Recommended Dietary Allowances (RDA) which is categorized by age, weight, and food texture, which is adjusted to the toddler age category. In terms of fulfilling all aspects of choosing complementary foods, this study proposes the design of a 4-star daily menu recommendation system for toddlers which refers to the intake of daily calorie needs for toddlers, namely carbohydrates, animal protein, vegetable protein, and vitamins/minerals using the FMADM method (Fuzzy Multiple Attribute Decision Making). The FMADM method used is the Electre method. In this study, the authors succeeded in building the desired recommendation system using the Electre method which produces a daily menu based on the number of mealtimes, based on the age and weight of toddlers by observing the user's tendency to the texture and composition of food and its nutritional content in the recommendation system that is built, so that can be accessed via mobile devices owned by the user.

Co-Authors -, Dedek Ispandi Adhitya Karel Maulaya Agustin Agustin -, Agustin Agustin Agustin Aisyah Nurul Putri Aldino Evel Anam, M Khairul Andi Kurnianto Aprillian Kartino Aulia Putri Br.Situmorang, Elisabet Sinta Romaito Bunga Nanti Pikir Chandra, Deni Cindy Syaficha Hardiana Dea Safitri Dedek Ispandi - Deni Chandra Devi Efriadi Dhini Septhya Didik Sazali Diki Daryanto Edwar Ali Efrizoni, Lusiana Elma Novfuja Erlin Fahreza, Rino Farida Try Puspa Siregar Fazri Fazri Firman Akbar Fransiskus Zoromi Fransiskus Zoromi Habibah Br. Lumbantobing Hadi Asnal, Hadi Hamdani Hamdani - Hanif Wira Saputra Hasnor Khotimah Hayami, Regiolina Hendra Saputra Herianto - Herianto Herianto Jamaris, Muhamad Jasmarizal Junadhi Junadhi Kharisma Rahayu Khusaeri Andesa Koko Harianto Koko Harianto Koko Harianto, Koko Kurniawan, Bambang Lili Marlia M Fadhil Arfa M. Arifin Mahdiawan Nurkholifah Mardainis Mardainis Mardainis Michal Dennis Muhaimin, Abdi Muhammad Azmi Muhammad Bambang Firdaus Muhammad Fajri Jamil Muhammad Fikri Hidayat Muhammad Ihza Mahendra Muhammad Ridho Al Fathan Nova Indriyani Nurjayadi Nurjayadi Ratna Andini Husen Refni Wahyuni Renaldi, Reno Rini Yanti Rino Fahreza Rizki Astuti Rizky Rahman Salam Rohana Yola Parastika Hutasoit Rometdo Muzawi, Rometdo Salsabila Rabbani Saputra, Haris Tri Sazali, Didik Singgih - Widiantoro Soni Susandri -, Susandri Susandri, Susandri Susanti, Susanti Syahrul Imardi T. Sy. Eiva Fatdha Triyani Arita Fitri Ulfah, Aniq Noviciate Unang Rio Vindi Fitria Wirta Agustin Wirta Agustin Yansyah Saputra Wijaya Yesaya Twin Situmorang Yoyon Efendi Yuda Irawan Yulia Fatma Yusran Umar Yusril Ibrahim

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