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All Journal International Journal of Advances in Intelligent Informatics Science and Technology Indonesia JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Serambi Engineering JURSIMA (Jurnal Sistem Informasi dan Manajemen) Indonesian Journal of Electrical Engineering and Computer Science jeti Jurnal Teknologi JURSIMA Journal Of Artificial Intelligence And Software Engineering Bulletin of Engineering Science, Technology and Industry

Arhami, Muhammad

Politeknik Negeri Lhokseumawe

Author-ID : 2558016

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences

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Aceh's Historic Tourist Attractions: An Augmented Reality-Based Prototype of a Virtual Tour Application Anwar Anwar; Cut Adnin Nalisa; Hendrawati Hendrawati; Safriadi Safriadi; Muhammad Arhami
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.6460

Indonesia has attractive tourist destinations for tourism such as beautiful interior areas and historical places. The purpose of this research is to design and build a virtual tour application for Aceh tourism objects using augmented reality. One of the problems that occur in tourist objects is that foreign tourists do not have an idea about the tourist objects they want to visit. The technology used in this study and previous research is Augmented Reality, but previous research only displays 3D tourist objects, while in this study, augmented reality technology is incorporated into the design of the 4 Aceh tourist attractions by showing a 3-dimensional illustration of the object as a whole. for the outside of the building and displays a virtual tour image in the form of a video to illustrate the inside of the tourist attraction building on the Android mobile platform. Based on the results of distance and angle testing, the best (ideal) distance that produces clear and bright marker detection is found at a distance between 25 to 45 cm, while the best angle is between an angle with a slope of 0° to 60°. Measurements of distances and angles are carried out using threads, bows and measuring tapes. The 3D object is successfully displayed by pointing the camera at the marker to be detected.

Penggunaan Metode TOPSIS sebagai Pendukung Keputusan Bantuan Modal Usaha bagi Masyarakat Pedesaan di Kabupaten Pidie Muhammad Arhami
Jurnal Infomedia:Teknik Informatika, Multimedia & Jaringan Vol 5, No 2 (2020): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jim.v5i2.1966

Dinas Sosial Kabupaten Pidie memiliki beberapa program, salah satunya program pemberdayaan sosial yaitu memberikan bantuan modal usaha berupa barang bagi masyarakat miskin yang memiliki usaha kecil. Dinas Sosial Kabupaten Pidie memerlukan suatu sistem pendukung keputusan (SPPK) yang dapat memperhitungkan segala kriteria yang dimiliki oleh pemohon untuk mempermudah proses pengambilan keputusan. Metode yang digunakan untuk Sistem Pendukung Keputusan dalam pemberian modal usaha adalah dengan menggunakan metode TOPSIS. Salah satu alasan metode ini dipilih karena mampu memilih alternatif terbaik dari sejumlah alternatif. Alternatif yang dimaksud adalah nama pemohon terbaik berdasarkan kriteria-kriteria yang dari ditentukan. Kriteria yang dimaksud adalah status, tanggungan, jenis usaha, kepemilikan usaha. Hasil proses pengimplementasian metode TOPSIS dapat mengurutkan nama pemohon berdasarkan nilai preferensi yang terbesar ke nilai preferensi terkecil, sehingga dari 30 data yang diuji, 17 orang berhak menerima bantuan dikarenakan nilai preferensi yang dimiliki diatas 0,5.

Sistem Pendukung Keputusan Penerimaan Bantuan Renovasi Rumah Dhuafa Menggunakan Metode Multi Attribute Utility Theory Derry Fajirwan; Muhammad Arhami; Ismi Amalia
Jurnal Infomedia:Teknik Informatika, Multimedia & Jaringan Vol 3, No 2 (2018): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Abstrak— Baitul Mal merupakan lembaga yang mengelola zakat, wakaf, dan harta agama sebagai potensi ekonomi umat Islam. Salah satu program Baitul Mal Aceh Barat Daya adalah pemberian bantuan renovasi rumah dhuafa. Dalam menentukan pemberian bantuan tersebut pihak Baitul Mal Abdya menyeleksi dari data yang masuk. Pada tahap penyeleksian ada beberapa kriteria dalam memutuskan seseorang berhak menerima atau tidak. Akan tetapi pada pelaksanaan masih menggunakan cara yang lama yaitu dengan faktor kedekatan petugas. Pada tahun 2017 setelah pergantian ketua Baitul Mal Abdya cara lama tersebut diganti dengan cara turun kelapangan untuk mengecek status kelayakan penerimaan bantuan. Untuk mendukung keputusan tersebut penulis akan membuat suatu sistem pendukung keputusan untuk menentukan kepada siapa saja yang berhak menerima bantuan rumah dhuafa berdasarkan data yang masuk. Metode yang digunakan adalah Multi Attribute Utility Theory (MAUT). Pengolahan nilai metode MAUT yaitu akan menghasilkan hasil akhir dengan perangkingan. Jadi dari perangkingan tersebut akan dipilih berdasarkan jumlah nilai tertinggi dengan batas nilai ≥ 0.58. Nilai batas 0.58 didapatkan berdasarkan hasil diskusi dengan ketua Baitul Mal Aceh Barat Daya. Dari hasil perbandingan perangkingan antara data hasil seleksi manual sebanyak 75 dengan data hasil seleksi sistem, didapatkan 60 data hasil seleksi sistem sesuai dengan hasil seleksi manual, sementara 15 data tidak sesuai dengan hasil seleksi manual. Tingkat akurasi yang didapatkan dari hasil implementasi Metode Multi Attribute Utility Theory (MAUT) mencapai 80%.Kata kunci — Sistem Pendukung Keputusan, Baitul Mal, Zakat, MAUT. Abstract— Baitul Mal is an institution that manages charity, endowments and religious property as an economic potential of Muslims. One of the Baitul Mal Aceh Barat Daya programs is the provision of renovation assistance for dhuafa homes. In determining the provision of assistance, Baitul Mal Abdya selected from incoming data. At the selection stage there are several criteria in deciding whether or not someone has the right to accept. However, the implementation still uses the old method, namely the proximity factor of the officer. In 2017 after the change of chairman of Baitul Mal Abdya the old method was replaced by the way to go down to check the status of eligibility for receiving assistance. To support this decision the author will make a decision support system to determine who has the right to receive assistance from poor households based on the data entered. The method used is Multi Attribute Utility Theory (MAUT). Processing the value of the MAUT method is that it will produce the final result by ranking. So the ranking will be chosen based on the highest number of values with a limit of ≥ 0.58. The limit value of 0.58 was obtained based on the results of discussions with the head of the Baitul Mal Aceh Barat Daya. From the results of the comparison of the ranking between the manual selection data as much as 75 with the data of the system selection results, obtained 60 data from the system selection results in accordance with the results of manual selection, while 15 data were not in accordance with the results of manual selection. The level of accuracy obtained from the implementation of the Multi Attribute Utility Theory (MAUT) method reaches 80%.Keywords — Decision Support System, Baitul Mal, Zakat, MAUT

Sistem Antrian Pasien pada Praktek Dokter menggunakan Algoritma FCFS Dan Notifikasi SMS Berbasis Web Hendrawaty, Muhammad Arhami, Muhammad Iqbal
Jurnal Elektro dan Informatika Vol 2 No 1 (2021): Maret 2021
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v2i1.269

Queue is an important thing to discuss as part of testing one's patience, so it can be said that the queue has become a part of everyday life for everyone. From these problems, with a queuing system that implements FCFS and WEB-based methods. To make it easier for patients to queue, the FCFS algorithm is relatively easy to use because it is the simplest and more efficient scheduling algorithm when used for queuing at the doctor's practice so that the first patient to queue is to be served. Notification feature in the form of SMS provided by the system so that patients get a notification when the patient's queue number is near and the schedule update if there is a patient has already taken a card and cannot be present.

Penggunaan Metode Analytic Network Process (ANP) Untuk Pendukung Keputusan Pemberian Bonus Karyawan Nadia Ulfa; Muhammad Arhami; Muhammad Rizka
Jurnal Teknologi Vol 21, No 1 (2021): April 2021
Publisher : Politeknik Negeri Lhokseumawe

The decision support system is a system that can provide problem-solving abilities and communication skills for problems with semi-structured and unstructured conditions, such as determining which employees deserve a bonus. The decision-making process is a frequent occurrence and is at the core of activities at PT Perta Arun Gas, one of which is to determine bonuses for employees by calculating the average value of criteria for each employee, not counting the values of related criteria. The system designed is a decision-making system to determine employees who get bonuses using the Analytic Network Process (ANP) method, this ANP method can calculate the related criteria values. ANP is a method that accommodates the relationship between criteria and alternatives. The criteria used are, professional at work, politeness (behavior), presence, loyalty (a sense of ownership of employees towards the company), responsibility, cleanliness tidiness, and discipline. The test results indicate that this system can solve the problem of determining the distribution of bonuses to employees so that it can help in selecting employees who receive the bonus.

PENGUKURAN APTITUDE DENGAN UJI KRAEPELIN MENGGUNAKAN METODE LINEAR CONGRUENTIAL METHOD (LCM) Qatrun Nada; Muhammad Arhami; Zulfan Khairil Simbolon
Jurnal Teknologi Vol 22, No 1 (2022): April 2022
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v22i1.2418

Psychological tests are an important need in various spaces of human life. Not only related to matters of a clinical nature, psychological tests are also used in the workspace. Psychological tests are carried out as an effort to find out by knowing more about a person's personality. One of the methods used by psychologists is Kraepelin to get personality types. In practice, psychological tests in understanding an object, namely humans with all their attitudes and behavior, still use the old way. Psychological tests still use sheets or series of questions given to related objects and the calculation of results or assessments is still done manually. Errors in the assessment will affect the results so that it will lead to inappropriate perceptions. Making questions requires time and high accuracy, so the system is built using the Linear Congruential Method (LCM). LCM method is used to generate random numbers with better access time performance in terms of complexity and optimality. The 20 minute test application consists of 40 columns and 60 rows of questions with a time limit of 30 seconds for each column. The website-based Kraepelin test application can support all related parties, both the test organizers and test takers, to get real-time and accurate test results by applying the Kraepelin test using the LCM method. The implementation of the Kraepelin test is in accordance with the purpose of using the test, namely as a tool to measure aptitude (speed, accuracy, stability and work endurance). Based on the test results, the calculation of the score using the system will be faster with a calculation time of 2 seconds while the manual calculation is 5 minutes.

Perbaikan Algoritma Naive Bayes Classifier Menggunakan Teknik Laplacian Correction Muhammad Rizki; Muhammad Arhami; Huzeni Huzeni
Jurnal Teknologi Vol 21, No 1 (2021): April 2021
Publisher : Politeknik Negeri Lhokseumawe

Naïve Bayes Classifier is one of the classification algorithms in Data Mining with a good processing speed and a fairly high level of accuracy. In the classification process the Naïve Bayes Classifier adopts the Bayesian theorem to map a data against a class by taking into account the probability of the attribute data, but because the Naïve Bayes Classifier makes probability the basis for its calculations, it is certainly very risk if it is wrong. If one class that is contained in the attribute has a value of 0, this will reduce the level of accuracy of the classification process carried out by the Naïve Bayes Classifier algorithm itself, therefore in this study the Laplacian Correction technique is used as an alternative to fix the problems that are owned by the Naïve Bayes Classifier Algorithm. The result of this research is that the Laplace Correction technique has succeeded in improving the performance of the Naïve Bayes Classifier by fixing the 0 value for each attribute. The level of accuracy that is owned by the Naïve Bayes Classifier after experiencing improvements with the Laplacian correction technique is 94.44%.

Contrast Enhancement for Improved Blood Vessels Retinal Segmentation Using Top-Hat Transformation and Otsu Thresholding Muhammad Arhami; Anita Desiani; Sugandi Yahdin; Ajeng Islamia Putri; Rifkie Primartha; Husaini Husaini
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

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

Diabetic Retinopathy is a diabetes complication that usually results in abnormalities in the retinal blood vessels of the eye, resulting in blurry vision, including blurry vision and blindness. Automatic segmentation of blood vessels in retinal images can detect abnormalities in these blood vessels, actually resulting in faster and more accurate segmentation results. The paper proposed an automatic blood vessel segmentation method that combined Otsu Thresholding with image enhancement techniques, including Contrast Limited Adaptive Histogram Equalization (CLAHE) and Top-hat transformation for the retinal image. The retinal image data used in the study were the Digital Retinal Images for Vessel Extraction (DRIVE) dataset generated by the fundus camera. The CLAHE and Top-hat transformation methods were used to increase the contrast of the retinal image and reduce noise so that blood vessels could be highlighted appropriately and the segmentation process could be facilitated. Otsu Thresholding was used to distinguish between blood vessel pixels and background pixels. The performance evaluation measures of the methods used are accuracy, sensitivity, and specificity. The DRIVE dataset's study results showed that the average accuracy, sensitivity, and specificity values were 94.7%, 72.28%, and 96.87%, respectively, indicating that the proposed method was successful through blood vessels segmentation retinal images, especially for thick blood vessels.

PENGGUNAAN NAÏVE BAYES UNTUK PREDIKSI MINAT PASAR KEWIRAUSAHAAN BERDASARKAN DATA MICROBLOGGING Dwi Meilvinasvita; Nabila Mufida; Muhammad Arhami; Salahuddin Salahuddin
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3 (2022): Jursima Vol.10 No.3 Desember 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.516

Masalah awal dalam berwirausaha biasanya para pelaku wirausaha sulit untuk memahami permintaan serta kebutuhan calon konsumen. Ketidakpastian pasar dan perubahan permintaan membuat para wirausahawan tidak dapat memprediksi permintaan dan kebutuhan pasar. Tujuan penelitian ini melakukan evaluasi yang kuat pada kumpulan informasi yang didapat dari data microblogging untuk memperkirakan variabel pasar. Dengan membuat perancang sistem prediksi minat pasar wirausaha melalui pemanfaatan platform microblogging twitter menggunakan metode naïve bayes, sistem ini dapat menghasilkan model prediksi pasar secara otomatis melalui pemanfaatan data microbloging popular. Metode naïve bayes digunakan untuk mengklasifikasikan data untuk minat pasar tertentu hasil prediksi ini diperkirakan akan menjadi cara efektif untuk meningkatkan kinerja dan keunggulan bersaing dalam berwirausaha. Kumpulan dataset diambil dari salah satu platform microblogging yaitu aplikasi twitter dengan lima kata kunci dari cabang bisnis pakaian diantaranya celana, jaket, mukena, tunik dan kebaya. Dataset yang di ambil dibagi menjadi dua, data latih dan data uji. Data latih digunakan untuk membuat model prediksi sedangkan data uji dijadikan sebagai data evaluasi perancangan model. Setelah melakukan pengujian, akurasi sistem yang dihasilkan model sebesar 87%. Model yang dibuat menggunakan metode naïve bayes dikategorikan sangat baik dalam melakukan prediksi. Hasil akurasi prediksi dapat dilihat dalam bentuk berita popular sebagai acuan dalam menyediakan produk sesuai dengan permintaan dan kebutuhan calon konsumen

Handling Missing Data Using Combination of Deletion Technique, Mean, Mode and Artificial Neural Network Imputation for Heart Disease Dataset Anita Desiani; Novi Rustiana Dewi; Annisa Nur Fauza; Naufal Rachmatullah; Muhammad Arhami; Muhammad Nawawi
Science and Technology Indonesia Vol. 6 No. 4 (2021): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2021.6.4.303-312

The University of California Irvine Heart disease dataset had missing data on several attributes. The missing data can loss the important information of the attributes, but it cannot be deleted immediately on dataset. To handle missing data, there are several ways including deletion, imputation by mean, mode, or with prediction methods. In this study, the missing data were handled by deletion technique if the attribute had more than 70% missing data. Otherwise, it were handled by mean and mode method to impute missing data that had missing data less or equal 1%. The artificial neural network was used to handle the attribute that had missing data more than 1%. The results of the techniques and methods used to handle missing data were measured based on the performance results of the classification method on data that has been handled the problem of missing data. In this study the classification method used is Artificial Neural Network, Naïve Bayes, Support Vector Machine, and K-Nearest Neighbor. The performance results of classification methods without handling missing data were compared with the performance results of classification methods after imputation missing data on dataset for accuracy, sensitivity, specificity and ROC. In addition, the comparison of the Mean Squared Error results was also used to see how close the predicted label in the classification was to the original label. The lowest Mean Squared Error wasobtained by Artificial Neural Network, which means that the Artificial Neural Network worked very well on dataset that has been handled missing data compared to other methods. The result of accuracy, specificity, sensitivity in each classification method showed that imputation missing data could increase the performance of classification, especially for the Artificial Neural Network method.

Co-Authors Ajeng Islamia Putri Al Khaidar Amalia, Ismi Anita Desiani Annisa Nur Fauza Anwar Anwar Azhar Azhar Kholiq Affandi Cut Adnin Nalisa Derry Fajirwan Des Alwine Zayanti Dwi Meilvinasvita Endang Sri Kresnawati Endro Setyo Cahyono Guntur Syahputra Hendrawati Hendrawati Hendrawaty Husaini Husaini Husaini Husaini Huzaeni Huzaeni Huzeni Huzeni Indra Mawardi Indrawati Indrawati Irmeilyana Irmeilyana Irvan Andrian Khairul Azman Khairunnisa Atami Mahdi Mahdi Muhammad Irmansyah Muhammad Muhammad Muhammad Nawawi Muhammad Nawawi Muhammad Rizka Muhammad Rizki Mustainul Abdi Nabila Mufida Nadia Ulfa Naufal Rachmatullah Naziruddin Naziruddin Nelly Safitri Ning Eliyati Novi Rustiana Dewi Qatrun Nada Renol Herwinsyah Rifkie Primartha Rizaldo Setiawan Safriadi Safriadi Salahuddin Salahuddin Salma Sheila Maulina Putri Shania Putri Andhini Simbolon, Zulfan Khairil Sugandi Yahdin Sugandi Yahdin Sugandi Yahdin Titania Jeanni Charissa Yuli Andirani Yulia Resti Zamzami Zhenyu Cui

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