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All Journal Techno.Com: Jurnal Teknologi Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Indonesian Journal on Software Engineering (IJSE) Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika Systemic: Information System and Informatics Journal TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Indonesian Journal of Business Intelligence (IJUBI) Jurnal Infortech Jurnal Scientia Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Sistem Informasi RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Bulletin of Computer Science Research Computer Science (CO-SCIENCE) INSANtek – Jurnal Inovasi dan Sains Teknik Elektro JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Hexagon Jurnal Ticom: Technology of Information and Communication

Omar Pahlevi

Universitas Bina Sarana Informatika

Author-ID : 2546806

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences

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Application of Expert System for Diagnosing Diseases Cocoa Plants Using the Forward Chaining Algorithm Method Pahlevi, Omar; Atmojo, Muhamad Kusumo
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Cacao plants originated from South America, then spread to North America, Africa and Asia. In Indonesia, cocoa has been known since 1560, but has become an important commodity since 1951. Cacao commodity plays an important role in the national economy and is a national mainstay commodity. This shows that cocoa is one of the results of plantation commodities that have a high economic value and play an important role as a source of foreign exchange through exports, as well as encouraging the regional economy, especially in rural areas. But behind the high value of cocoa production, there are problems faced, including the low quality of cocoa in Indonesia because cocoa plantations in Indonesia are threatened by pests and plant diseases. Lack of information that is known by the plantation and cocoa farmers about the types of diseases that attack cocoa plants, causing many cocoa plants that are not handled properly. If this is allowed to continue it will impact on the declining quality and production of cocoa plants. Current advances in information technology, especially cellular phones, can be used as a means to improve public services, one of the results of the development of cellular technology is the birth of cellular phones with the android operating system. In this research produced if the symptoms data entered could not find the type of cocoa plant disease because the input data did not match any disease data in the database, the system would display the word "Can not find the disease you are looking for because it is not related to fruit rot disease, stem cancer, vascular antraknosem, streak dieback, upas fungus and root fungus ". From the data of symptoms, diseases and relations above, the algorithm is depicted using a decision tree. Decision tree is a picture of tracking symptoms, determining the disease and concluding results in the form of a solution. In this application, using the Forward Chaining method so that tracking begins with the selection of symptoms experienced then the results of the diagnosis in the form of cocoa plant diseases.

The RPTRA Geographic Information System Application in Central Jakarta City Using the Dijkstra Algorithm Based on Android Sugiharja, Danur; Pahlevi, Omar; Widyastuti, Reni
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Child Friendly Integrated Public Space or also known by the abbreviation RPTRA is the concept of public space in the form of green open spaces or parks that are equipped with various interesting games. Currently RPTRA is already widely available in all DKI Jakarta, especially in Central Jakarta, but there are still many people who do not know the location of the location of RPTRA. The dijkstra algorithm applied to this Android-based RPTRA geographic information system application in the City of Central Jakarta is to use google maps as a navigation map, where the Algorithm: {When users select the Map menu in the main menu, users will see maps and points of all RPTRA locations in Central Jakarta City, select one of the RPTRA location points, after the user selects one RPTRA location point, select the image on the right bottom route, then the user will go to google maps to get the route to the selected RPTRA. } The location of RPTRA directly takes coordinates at each RPTRA located in Central Jakarta City. The results achieved in testing the application went well able to provide accurate data on the location points of RPTRA in Central Jakarta.

Penerapan Algoritma Apriori Dalam Pengendalian Kualitas Produk Pahlevi, Omar; Sugandi, Anton; Sintawati, Ita Dewi
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.113 KB)

Penelitian ini dilakukan untuk mengetahui defect apa saja yang sering muncul pada proses injection dan kombinasi item defect apa saja yang sering terjadi, untuk melakukan pengendalian kualitas produk yang bersangkutan. Metode analisis yang digunakan adalah analisis kuantitatif dengan menggunakan metode algoritma apriori yang dapat mengelola nilai input yang sesuai dengan kriteria-kriteria pada item yang mempunyai nilai support dan confidence tertentu dengan perhitungan RapidMiner. Algoritma apriori merupakan salah satu algoritma dalam data mining yang dapat digunakan dalam association rule untuk menentukan frequent itemset yang berfungsi untuk membantu menemukan pola dalam sebuah data. Dengan menggunakan algoritma apriori, dapat menghasilkan pola kombinasi sebanyak 17(tujuh belas) rules dengan nilai support sebesar 70% dan nilai confidence tertinggi dari 17(tujuh belas) rules tersebut sebesar 93% yang terdapat dalam rule Lock Broken → Disscolour.

Disaster Information on Mobile Application in Indonesia Using Sequential Search Algorithms Based On Android Bachtiar, Dimas Agung; Pahlevi, Omar; Santoso, Tri
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Indonesia has 28 regions in the Republic of Indonesia Archipelago which are declared as areas prone to tectonic earthquakes, volcanoes and tsunamis. Among these are NAD, North Sumatra, West Sumatra, Bengkulu, Lampung, Banten, Central Java, and DIY in the south, East Java in the south, Bali, NTB, and NTT. Based on these facts, it can give an idea that the South East Java Province in particular has a high level of vulnerability when compared to other islands, when viewed from the total population density. Disasters can occur anytime and anywhere so people need to increase awareness, awareness, and preparedness, which is most at risk during the emergency response phase, where in that phase the situation is very conducive and the increasing hoaxes about data and information on disasters that spread in the community, along with the development of technological advancements, we need a mobile application that can provide the latest data and information routinely in the community. Referring to the design of mobile application designs that have been designed, in this study using the sequential algorithm method. With the sequential algorithm in this design, users can easily use this Android-based disaster information application, just by entering the keywords in the year of the disaster event, the location will be searched. The purpose of making this mobile application is to be able to provide data and information about disasters in Indonesia to all elements of society effectively and efficiently.

Data Mining Penentuan Aturan Asosiasi Penjualan Makanan di Amaria Hotel Jakarta Menggunakan Algoritma Apriori Pahlevi, Omar
Jurnal Sistem Informasi Vol 7 No 2 (2018): Vol VII No.2 Agustus 2018
Publisher : STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.01 KB)

Abstractâ€”In order to know what foods and drinks purchased by consumers, can be done with analytical techniques that is the analysis of consumer buying habits. Detection of food and beverages that are often purchased simultaneously is done using association rules. In this research will be used a priori algorithm for determination of association rules of sale of food and beverage. From the results of the discussion and data analysis conducted can be concluded that with the application of a priori algorithm in determining the combination between itemsets with a minimum of 20% support and minimum confidence 75% found 10 association rules, which has the highest value of support and confidence is if consumers make rice purchase transactions fried seafood and bottle aqua simultaneously with the value of 69% support and 100% confidence value. Thus, if there are consumers buying seafood fried rice, then the possibility of the consumer is buying a bottle aqua is 100%. Intisariâ€”Agar dapat mengetahui makanan dan minuman apa saja yang dibeli oleh para konsumen, dapat dilakukan dengan teknik analisis yaitu analisis dari kebiasaan membeli konsumen. Pendeteksian mengenai makanan dan minuman yang sering dibeli secara bersamaan dilakukan dengan menggunakan aturan asosiasi. Pada penelitian ini akan digunakan algoritma apriori untuk penentuan aturan asosiasi penjualan makanan dan minuman. Dari hasil pembahasan dan analisis data yang dilakukan dapat disimpulkan bahwa dengan penerapan algoritma apriori dalam menentukan kombinasi antar itemset dengan minimum support 20% dan minimum confidence 75% ditemukan 10 aturan asosiasi, dimana yang memiliki nilai support dan confidence tertinggi adalah jika konsumen melakukan transaksi pembelian nasi goreng seafood dan aqua botol secara bersamaan dengan nilai support 69% dan nilai confidence 100%. Dengan demikian, jika terdapat konsumen membeli nasi goreng seafood, maka kemungkinan konsumen tersebut membeli aqua botol adalah 100%. Kata kunci: data mining, algoritma apriori, aturan asosiasi, support, confidence

Data Mining Model For Designing Diagnostic Applications Inflammatory Liver Disease Pahlevi, Omar; Amrin, Amrin
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 1 (2020): Article Research, October 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i1.10589

Hepatitis is an infectious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of hepatitis is very important so that it can be treated and treated quickly. In this study, the authors will apply and compare several data mining classification methods, including the C4.5 algorithm, NaÃ¯ve Bayes, and k-Nearest Neighbor to diagnose hepatitis, then compare which of the three methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods, it is known that the C4.5 method is the best method with an accuracy of 70.99% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with accuracy of 67.19% and the value under the curve (AUC) 0.873, then the naÃ¯ve Bayes method with an accuracy rate of 66.14% and a value under the curve (AUC) of 0.742.

Analisa Dampak Penggunaan Sistem Conference Dalam Mendukung Pembelajaran Daring Omar Pahlevi; Danny Ong; Imelda Sari
Indonesian Journal on Software Engineering (IJSE) Vol 7, No 2 (2021): IJSE 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v7i2.11398

Abstrak Sistem Pembelajaran daring selama masa pandemi Covid-19 merupakan mekanisme pembelajaran pendidikan yang diterapkan oleh hampir seluruh negara di dunia dari tingkat pendidikan dasar hingga perguruan tinggi.Permasalahan yang dihadapai secara mayoritas adalah terkait effektivitas dan kualitas yang dapat diperoleh oleh anak didik selama mengikuti pembelajaran daring.Kesulitan, hambatan dan juga terkait masalah teknis seperti jaringan sering membuat pembalajaran menjadi tidak maksimal karena adanya perbedaan dari salah satu yang banyak dibahas yaitu daya tangkap setiap anak didik yang berbeda-beda dan juga antusiasme dalam pengawasan pembelajaran menjadi kendala yang harus diperhatikan. Dalam melaksanakan penelitian ini, peneliti menggunakan metode analisa Strength, Weakness, Opportunities, Threats (SWOT) dan juga metode penilaian balance scorecard. Analisa yang digunakan memiliki tujuan utama untuk mengetahui seberapa besar parameter dari penilaian yang dilakukan memberikan hasil terkait dengan apakah ada kelebihan, kelemahan, peluang dan gangguan dari dilakukannya pembelajaran daring terhadap anak didik yang sudah berjalan selama pandemi COVID-19 serta melakukan akumulasi dari nilai ukur yang dilakukan dari kumpulan pertanyaan kuesioner yang diberikan kepada sejumlah anak dan orang tua untuk mengetahui suara hati dari peserta didik yang terlibat. Hasil dari analisis dilihat dari perhitungan analisa teknikal dan juga response yang mayoritas menunjukan angka diatas 4 dengan nilai maksimal adalah 5 telah menunjukan sebagian besar mayoritas anak didik tidak terbiasa dengan mekanisme proses pembelajaran daring karena berbagai hambatan seperti daya tangkap khususnya pelajaran yang bersifat praktek, waktu yang tidak sesuai hingga kondisi jaringan yang terputus dan ketika tersambung kembali pembelajaran sudah tertinggal dan self learning yang tidak berjalan effektif karena faktor lingkungan. Kata kunci: Sistem Pembelajaran Daring,SWOT, Balance Scorecard Abstract Online Learning System in this era of Covid-19 pandemic is one of the learning mechanism adopted by majority education institute of all country in the world from the junior level until university. Much problem faced by majority is about effectivity and quality for the student who has faced this mechanism. Difficulty level, obstacle and also technical problem like network ofted make learning is not going to reach maximum level because every student have different comprehension and enthusiasm for learning monitoring become obstacle that must have attention to settle it. On this research, researcher is using Strenght, Weakness,Opportunities, Threats (SWOT) analyst method and also balance scorecard method for report calculation. This analyst have a main purpose to have knowledge about impact of parameter for assessment that have been done to give result if strength, weakness, opportunites and threat have a impact for student are going to this mechanism in the COVID-19 pandemic and do accumulation measuring value from the questioner that have been distributed to student and parents get involved in this research, this questioner will be mirroring sound from the heart inside of participants. The result of this analyst is to show majority of students is used to have learning offline and feel uncomfortable if have learning by online mechanism because many problem like comphrehension difference, frustation in the field like practice, time suitability until network lost problem and when back connected study is already going far and self learning doesn't run effective because of environment factorKeywords: Online Learning System, SWOT, Balance Scorecard

Data Mining Optimization Based on Particle Swarm Optimization For Diagnosis of Inflammatory Liver Disease Amrin Amrin; Omar Pahlevi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 1 (2021): EDISI JULY 2021
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i1.5312

Inflammation of the liver is a contagious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of this disease is very important so that it can be quickly treated and treated. In this study the researchers will apply and compare several data mining and optimization classification methods with particle swarm optimization (pso), including the C4.5 algorithm, k-Nearest Neighbor, C4.5 with PSO, and k-Nearest Neighbor with PSO to diagnose inflammatory diseases. carefully, then compare which of the several of these methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods. Based on the research results, it is known that the C4.5 method with PSO is the best method with an accuracy of 79.51% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with PSO has an accuracy of 75.59% and an AUC value of 0.909, then the C4.5 method with an accuracy rate of 70.99% and an AUC value of 0.950, then the k-Nearest Neighbor method with an accuracy rate of 67.19%, and an AUC value of 0.873. This proves that particle swarm optimization can improve the performance of the classification method used.

Implementation of Logistic Regression Classification Algorithm and Support Vector Machine for Credit Eligibility Prediction Amrin - Amrin; Omar - Pahlevi
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.v5i2.6220

Credit is a provision of money or bills that can be equated with it, the provision of loans or credit. A good credit analysis is very necessary, because it is one of the most important processes in the form of an investigation regarding the smooth or substandard credit repayments. The stages of identifying and predicting customers properly and correctly can be done before the loan process. This is done by examining the historical data of the customer's loan. At this time this activity is an effort made by the banking industry in dealing with credit risk problems. In this research, researchers will apply several data mining classification methods, including Logistic Regression algorithms and Support Vector Machines to predict creditworthiness. The dataset used 481 record motorized vehicle loan data, both problematic and non-problematic. The input variables in this study consisted of thirteen variables, including marital status, number of dependents, age, residence status, home ownership, occupation, employment status, company status, income, down payment, education, length of stay, and housing conditions. From the results of research and testing, the performance of the Logistic Regression model for predicting creditworthiness provided an accuracy rate of 94.81% with an area under the curve (AUC) value of 0.987. While the performance of the Support Vector Machine model provides an accuracy of 94.19% with an area under the curve (AUC) value of 0.978. Based on the T-Test test, the Logistic Regression method has the same performance compared to the Support Vector Machine.

Studi Dan Analisa Faktor-faktor Yang Mempengaruhi Kepuasan Pelanggan Pada Sistem Informasi Penjualan Online (e-Commerce) Pada CV Selaras Batik Himawan Wijaya; Omar Pahlevi; Harriansyah Harriansyah
Systemic: Information System and Informatics Journal Vol. 5 No. 2 (2019): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Online or e-commerce businesses in Indonesia continue to seek ideas and innovations to increase the number of customers and also retain old customers, so that it is expected to increase the volume of sales transactions and ultimately provide benefits for e-commerce companies. Research conducted by researchers is a continuation of research from previous research conducted in 2014, where research conducted on this occasion is one form of evaluation of services that have been carried out by CV. Selaras Batik to its customers, so as to provide data and information on satisfaction customers who have made a purchase transaction. Where in this study customer satisfaction factors that will be the focus of the study will be divided into 4 categories which is product factors, price factors, delivery time speed factors and also after sales service factors. Where the four factors are considered factors that can affect customer satisfaction to continue to make transactions in CV. Selaras Batik. The research method that will be used in this research is a combination of sampling data and descriptive analysis, so that this research can produce feedback from customers of CV. Selaras Batik and also can be an optimal marketing strategy for CV. Selaras Batik management to continue to exist amid world competition ecommerce is increasingly stringent and competitive.

Co-Authors Agni Isador Harsapranata Amrin Amrin Amrin Amrin Astriana Mulyani Atmojo, Muhamad Kusumo Bachtiar, Dimas Agung Cucu Ika Agustyaningrum Danny Ong Dewi Ayu Nur Wulandari Dony Ardiyansah Enok Tuti Alawiah Fahrizal Fahrizal Faiz Octa Reynaldi Fryda Fatmayati Harmen Harmen Harriansyah Harriansyah Harsih Rianto Henny Leidiyana Himawan Wijaya Imelda Sari Indah Suryani Ita Dewi Sintawati Ita Dewi Sintawati Luci Kanti Rahayu Miftahul Khoir Muhammad Syafrizal Rahmadian, Jefri Renal Verdiyan Erlangga Reni Widyastuti Riyanto, Umbar Rizka Dahlia Rony, Zahara Tussoleha Satriadi, Irawan Sismadi Sismadi Sriyadi Sriyadi, Sriyadi Sugandi, Anton Sugiharja, Danur Sunarti Tri Santoso Tri Santoso Yopi Handrianto, Yopi

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