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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic CESS (Journal of Computer Engineering, System and Science) IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri JIEET (Journal of Information Engineering and Educational Technology) Techno Nusa Mandiri : Journal of Computing and Information Technology IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal ULTIMA Computing Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Infotek : Jurnal Informatika dan Teknologi Computer Science (CO-SCIENCE) Jurnal Info Sains : Informatika dan Sains IMTechno: Journal of Industrial Management and Technology Profitabilitas Journal of Accounting Information System Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Achmad Baroqah Pohan
Universitas Bina Sarana Informatika
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

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Pengembangan Idle Game “Havok Runner” Berbasis Android Menggunakan Metode Agile Game Development Achmad Baroqah Pohan; Ibnu Alfarobi; Sofian Wira Hadi
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.v6i3.3994

Abstract

Video games are one of the industries that are growing very rapidly every year. And in a video game industry, there are many types/genres of games that have been widely circulated in the community. One of them is a type of game where players interact a little while the game is running, namely idle games. Even though gaming is one of the industries that is growing very rapidly, based on the report of Diana Paskarina (COO of game loka nutmeg) the contribution of the creative game industry is still very small to state revenue. However, regardless of the existing constraints, there are opportunities/opportunities that can be utilized to improve the country's economy through idle games. This refers to the results of the Sensor Tower survey which shows that the income of the idle game genre in Q3 2016 to Q2 2018 has increased very rapidly. Therefore, researchers try to make a positive contribution by developing game applications with the idle game genre using the Agile Game Development method.
Penerapan Metode Algoritma C5.0 Untuk Klasifikasi Pemberian Kredit KUR UMKM Pada PT Pegadaian Hilda Amalia; Moranta Timotius; Sriyadi Sriyadi; Yunita Yunita; Achmad Baroqah Pohan
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 10, No 2 (2024): Periode Juli 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v10i2.21588

Abstract

KUR or known as People's Business Credit is a government program which aims to provide business assistance to small people, namely those who own businesses (MSMEs). Providing Credit can also refer to a situation where one party provides money or services to another party. Every time you give credit to a customer, there is a possibility of default. Default conditions can be detrimental to those who provide credit. This default condition, apart from being detrimental to the credit provider company, also has an impact on the company's performance. To overcome the risk of default, it is important for credit companies to carry out careful credit analysis, provide financial education to customers, and have an effective strategy. In addition, monitoring and updating customers' financial conditions regularly are also an important step in preventing payment failures. Data mining is a method for finding knowledge from piles of data. In this research, data mining is used to overcome the problem of default risk on business credit worthiness by involving data to identify patterns and factors that can predict potential default. By using the natural 5.0 algorithm method, data processing can be used to automate most of the credit assessment process which can save time and costs. The application of data mining in pawnshops allows more precise decisions to be made based on historical data and in-depth analysis, thereby helping to reduce risk and increase operational efficiency at credit granting companies. The application of the C5.0 Algorithm method helps identify critical factors that influence the feasibility of MSME sharia currency, such as customer profiles, business characteristics and financial performance. The results of the feasibility evaluation show that the majority of MSMEs receive funding through sharia currency.
PENERAPAN FEATURE WEIGHTING OPTIMIZED PADA NAÏVE BAYES UNTUK PREDIKSI PROSES PERSALINAN Amalia, Hilda; Pohan, Achmad Baroqah; Masripah, Siti
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (918.778 KB) | DOI: 10.33480/pilar.v15i1.3

Abstract

Birth of a baby is something that is very desirable for every married couple. All parties expect safety for mothers and babies who have just been born. Medical personnel make various efforts to help the delivery process run smoothly and the mother and baby survive. But in the labor process not all the baby's birth process runs smoothly. Problems often occur during labor. There are several obstacles so that there is a risk of labor, namely maternal and infant mortality. Every mother wants to be able to give birth to a baby normally, but due to medical reasons the delivery process is done by cesarean. The act of choosing a type of delivery faster can affect the safety of the mother and baby. The selection of the cesarean method is carried out late so it will increase the risk of maternal and infant mortality. For this reason, it is necessary to conduct research by using labor delivery data so that they can choose the right type of labor. In this study the classification of maternity labor will be carried out with data mining methods, namely Naive Bayes, which are improved by using the Optimize Weight (PSO) method. Naive Bayes was able to produce a high accuracy value for processing labor data for mothers, namely 94%. The final results of this study obtained the value of naïve bayes performance that can be improved by the Optimize Weights (PSO) method to be better at 98%
PREDICTION OF SURVIVAL OF HEART FAILURE PATIENTS USING RANDOM FOREST Rahayu, Sri; Purnama, Jajang Jaya; Pohan, Achmad Baroqah; Nugraha, Fitra Septia; Nurdiani, Siti; Hadianti, Sri
Jurnal Pilar Nusa Mandiri Vol 16 No 2 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v16i2.1665

Abstract

Human survival, one of the roles that is controlled by the heart, makes the heart need to be guarded and be aware of its damage. Heart failure is the final stage of all heart disease. The medical record tool can measure symptoms, body features, and clinical laboratory test values, which can be used to perform biostatistical analyzes but to highlight patterns and correlations not detected by medical doctors. So technology assistance is needed to do this in order to predict the survival of heart failure patients. With data mining techniques used in the available history data, namely the Heart Failure Clinical Records dataset of 299 instances on 13 features used the Random Forest algorithm, Decision Tree, KNN, Support Vector Machine, Artificial Neural Network and Naïve Bayes with resample and SMOTE sampling techniques. The highest accuracy with the resample sampling technique in the random forest is 94.31% and the SMOTE technique used in the random forest produces an accuracy of 85.82% higher than other algorithms.
SENTIMENT ANALYSIS AGAINST THE DANA E-WALLET ON GOOGLE PLAY REVIEWS USING THE K-NEAREST NEIGHBOR ALGORITHM Masturoh, Siti; Pohan, Achmad Baroqah
Jurnal Pilar Nusa Mandiri Vol 17 No 1 (2021): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v17i1.2182

Abstract

DANA e-Wallet or digital wallet application can be downloaded on the Android platform via Google Play, and google play itself provides a review column. The public will usually see reviews on Google Play before they download an application because the information obtained through these reviews is considered effective in providing information, problems regarding reviews or sentiment analysis of the application must be processed using text mining. Text mining in this study uses k-nearest neighbor by testing 3 classes based on star rating, the first class consists of 1-5 stars, the second class consists of (1 & 5 stars, 3rd class consists of labeling stars (1 & 2) negative label, 3 neutral labels, as well as 4 & 5 stars positive labels) and testing the value of k 1-10 so that the highest accuracy value is obtained with class 2 (1 star and 5 stars) and the best test at k 1 value is obtained the accuracy result of 86.64%
Rancang Bangun Sistem Informasi Bersih Bersama yunita, yunita; Satya, Muhammad Taufik; Pratama, Muhammad Ngurah Arya; Amalia, Hilda; Pohan, Achmad Baroqah
IMTechno: Journal of Industrial Management and Technology Vol. 5 No. 1 (2024): Vol. 5 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/imtechno.v5i1.2409

Abstract

Sampah dan lingkungan salah satu isu yang semakin mendesak saat ini, meingkatnya jumlah penduduk berbanding lurus dengan meningkatnya jumlah sampah dan berbagai masalah lingkungan yang semakin kompleks. Meningkatnya jumlah penduduk tidak mempengaruhi kesadaran penduduk untuk menjaga lingkungannya. Hal ini menimbulkan berbagai masalah baru seperti bay tak sedap, penyakit, dan bencana banjir. Berbagai masalah Kesehatan lainnya. Oleh karena itu diperlukan kesadaran kolektif masyarakat unruk menjaga lingkungan terutama soal pembersihan sampah. Beberapa upaya telah dilakukan untuk menangani masalah sampah tetapi hanya sebatas menumbuhkan kesadaran masyarakat untuk menjaga kebersihan dan bagaimana mengelola sampah, sedangkan untuk membersihkan sampah atau lingkungan yang sudah tercemar oleh sampah belum ada upaya yang dilakukan hanya sebatas membersihkan wilayah sekitarnya saja. Berdasarkan latar belakang tersebut kami membuat sebuah aplikasi Bersih Bersama berbasis web dengan menggunakan metode waterfall untuk mengajak masyarakat dari seluruh wilayah untuk berpartisipasi membersihkan wilayah yang sudah tercemar maupun memberikan informasi mengenai wilayah yang tercemar agar ditindak lanjuti. Sehingga memberi manfaat dalam memfasilitasi kegiatan kebersihan lingkungan secara efektif dan efisien serta meningkatkan partisipasi masyarakat dalam menjaga kebersihan lingkungan.
An implementation of machine learning on loan default prediction based on customer behavior Robi Aziz Zuama; Nurul Ichsan; Achmad Baroqah Pohan; Mohammad Syamsul Azis; Mareanus Lase
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 01 (2024): Informatika dan Sains , Edition March 2024
Publisher : SEAN Institute

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

Abstract

In the banking sector, loans have become a key component that steers the economy, encourages company expansion, and directly impacts the growth of a nation's economy. Banks must evaluate borrowers' ability to repay loans given the inherent risks involved in order to reduce the likelihood of default. In particular, machine learning (ML) has shown promise as a revolutionary tool for loan default prediction using advanced methodologies to examine historical data relating to customer behavior, this study investigates the application of machine learning (ML) in forecasting loan outcomes. The results show that XGBoost performs better than other machine learning algorithms, with an accuracy rate of 89%. Random forest and logistic regression come in second and third, respectively, with 88% accuracy. KNN and decision trees come next, both with somewhat lower accuracy rates (87%). By incorporating consumer behavior domain variables, this study fills in the gaps in the literature and offers a more thorough understanding of loan projections. In order to improve model performance and strengthen the predictive power of machine learning algorithms in loan scenarios, further research incorporating trials to optimize algorithm parameters is necessary as financial institutions continue to experience difficulties.
IMPLEMENTASI METODE AGILE DEVELOPMENT DALAM PERANCANGAN SISTEM INFORMASI PEMESANAN MENU PADA RESTORAN M.Kom, Walim; Pohan, Achmad Baroqah; Safrudin, Azman
PROFITABILITAS Vol 2 No 2 (2022): JURNAL PROFITABILITAS
Publisher : Sistem Informasi Akuntansi Kampu Kabupaten Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/profitabilitas.v2i2.1661

Abstract

The development of businesses carried out by business people is not far from the development of internet technology to make these businesses superior and ready to compete in this era. The number of competitors makes business people have to innovate in creating ideas to be able to attract customers and make them more effective and efficient in running their business as well as in the restaurant business. Sentral Aljazeerah Epicentrum is a restaurant that serves Middle Eastern-style food or dishes located in Kuningan. Based on research on qraved, it shows that typical middle eastern restaurants in Jakarta have at least more than 40 restaurants, and to compete among these restaurants, they must have an effective and efficient ordering system. At the Aljazeerah Epicentrum restaurant, in carrying out services to customers to place orders, they still use book notes or just written on paper, so that the service becomes ineffective and seems long if the restaurant is receiving many visitors and an error is found in recording orders, not to mention if the customer asks for an explanation. about the menu you want to order. For that we need a system that helps the problems that have been described above, namely creating a web-based ordering system using an intranet network, in making the system, the software development process uses the agile method, where the agile method helps facilitate the process of developing information systems because the agile method prioritizes user satisfaction.
Implementasi Metode Prototype Dalam Rancang Bangun E-Marketplace Untuk Penyewaan Villa Imam, Prastiya; Pohan, Achmad Baroqah; Walim, Walim
JAIS - Journal of Accounting Information System Vol. 2 No. 2 (2022): Desember
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jais.v2i2.1549

Abstract

Penyewaan merupakan suatu perjanjian dimana pihak yang satu memberikan hak kepada pihak yang lainnya atas suatu barang, properti atau tempat selama satu waktu tertentu dan dengan pembayaran yang telah disepakati oleh kedua pihak. Villa Finidz merupakan sebuah usaha yang bergerak di bidang penginapan. Seiring perkembangan teknologi saat ini villa finidz juga membutuhkan suatu sistem informasi yang menunjang dalam segi pelayanan untuk memuaskan para customer. Untuk itulah penulis mencoba membuat rancangan program mengenai sistem penyewaan villa berbasis web, karena sistem yang ada pada saat ini masih dilakukan secara manual, mulai dari proses penyewaan, proses pembayaran sewa sampai proses pembuatan. Oleh karena itu, dibutuhkan sistem yang terkomputerisasi untuk memecahkan permasalahan yang ada. Adapun metode pengembangan system yang digunakan adalah model Prototype. Bahasa pemrograman yang digunakan yaitu PHP dan menggunakan framework Codeigniter, serta database sever-nya menggunakan MYSQL. Dengan dibangunnya sistem penyewaan villa berbasis web ini dapat membantu dalam proses penyewaan villa dan pengolahan data secara cepat, tepat dan akurat, serta sistem penyewaan villa menjadi lebih kondusif dibandingkan dengan sistem yang sebelumnya.
Penerapan Integrasi Algoritma K-Means Dan Naïve Bayes Untuk Klasifikasi Wilayah Rawan Banjir Di Jakarta Sinatrya, Irfan Maulana; Pohan, Achmad Baroqah; Yunita, Yunita; Amalia, Hilda; Lestari, Ade Fitria
Computer Science (CO-SCIENCE) Vol. 5 No. 2 (2025): Juli 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i2.6900

Abstract

Jakarta, as a metropolitan city in Indonesia, often experiences flooding caused by high rainfall, poor drainage systems, and rapid urbanization. This research aims to classify flood-prone areas in Jakarta using a combination of K-Means Clustering and Naïve Bayes Classifier algorithms. The research phase begins with data collection from the Satu Data Jakarta website, including attributes such as region, sub-district, village, average water level, number of affected RWs, number of affected families, number of affected people, and number of flood events. The collected data is then processed through cleaning and normalization stages before being analyzed using the K-Means algorithm to group areas based on their flooding characteristics. Furthermore, the Naïve Bayes algorithm was used to build a classification model that predicts flood-prone areas. The results showed that the combination of these two algorithms resulted in higher average accuracy compared to the use of conventional Naïve Bayes, having an accuracy of 98.18%% at training and testing data split ratios of 70:30, 80;20 and 90:10. The findings provide valuable insights for flood risk mitigation in Jakarta, assisting the government in taking more effective preventive measures.
Co-Authors A.A. Ketut Agung Cahyawan W Abdul Latif Achmad Rifai Ade Fitria Lestari Ade Suryadi Alfian , Deny Alfian, Deny Andre Gusti Hermawan Apriwiguna, Auliya AR, Syaifur Rahmatulah Aziz Zuama, Robi Azzahro , Fathimah Azzahro, Fathimah Besus Maula Sulthon Daniati Uki Eka Saputri Deni Gunawan Dessi Eka Satie Entin Sutinah, Entin Fitra Septia Nugraha Gunawan, Deni Herlin Widasiwi Setianingrum Hidayatullah, Hiroki Setiawan Hilda Amalia Ibnu Alfarobi Imam, Prastiya Istianto Wahyu Jajang Jaya Purnama M.Kom, Walim Mareanus Lase Mohammad Syamsul Azis Moranta Timotius Muhamad Abdul Ghani Nugraha, Fitra Septia Nur Rosit Jaelani Nurul Ichsan Pratama, Muhammad Ngurah Arya Razaq, Sultan Nur Hadi Robi Aziz Zuama Rusnandi Rusnandi Rusnandi, Rusnandi Safrudin, Azman Saputra, Yoga Satya, Muhammad Taufik Sinatrya, Irfan Maulana Siti Masripah, Siti Siti Masturoh Siti Nurdiani Sofian Wira Hadi Sri Hadianti SRI RAHAYU Sri Wasiyanti, Sri Sriyadi Sriyadi Sulthon, Besus Maulana Suparni Suparni Suparni Suparni Syaifur Rahmatullah Taopik Hidayat Walim, Walim YUNITA Yunita Yunita Yunita Yunita