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All Journal International Journal of Electrical and Computer Engineering Elektron Jurnal Ilmiah TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) SITEKIN: Jurnal Sains, Teknologi dan Industri Riau Journal of Computer Science JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan Jurnal Mantik Penusa Rang Teknik Journal Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Pendidikan Systematics Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Informatika Ekonomi Bisnis Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Jurnal Teknik Informatika C.I.T. Medicom Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Journal of Computer Scine and Information Technology Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Sistim Informasi dan Teknologi Innovative: Journal Of Social Science Research Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) Jurnal Elektronika dan Teknik Informatika Terapan Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Gunadi Widi Nurcahyo
Universitas Putra Indonesia YPTK Padang
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Other

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Tingkat Efisiensi Penggunaan Resep Dokter Spesialis Menggunakan Metode K-Means Clustering Sharon; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.118

Abstract

The National Formulary (Fornas) is a list of drugs stipulated in a Decree of the Minister of Health of the Republic of Indonesia, which is used as a guideline for hospitals in drug supply for participants of the National Health Insurance (JKN) program. Doctor's prescription is one indicator of the quality of hospital services. Prescribing drugs based on guidelines will provide efficiency in the supply of drugs. The purpose of this study was to facilitate controlling drug supplies, safe use of drugs and control costs and quality of treatment. K-Means Clustering is a method of grouping data into clusters using the K-Means algorithm. The data used in this study was a specialist doctor's prescription in December 2019 which was sourced from the Pharmacy department of the Meranti Islands District Hospital. The results of this research with the K-Means Clustering method consisted of 3 (three) clusters, namely cluster 0 obeying Fornas as many as 2 polyclinics, cluster 1 being less obedient to Fornas as many as 2 polyclinics and cluster 2 not obeying Fornas as many as 3 polyclinics. This research can be used as a reference and evaluation to hospital management on the efficiency level of using specialist doctor's prescriptions in improving the quality of hospital services.
Data Mining dalam Mengukur Tingkat Keaktifan Siswa dalam Mengikuti Proses Belajar pada SMP IT Andalas Cendekia dengan Menggunakan Metode K-Means Clustering Melissa Triandini; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.120

Abstract

The learning process is essentially to develop the activities and creativity of students through various interactions and learning experiences. The teacher is the most important factor in the process of improving the quality of education. In addition, student learning activeness is also an important basic element for the success of the learning process. The quality and activeness of students in learning at school has a lot of diversity which makes students have different levels of understanding, this needs to be a concern for the school, especially teachers as teachers and educators of students in schools. The purpose of this study is to measure the extent to which students' ability to undergo the learning process as well as a reference and evaluation material for the school in the success of educators when carrying out the teaching and learning process. In this study the data were sourced from the Integrated Islamic Junior High School Andalas Cendekia Dharmasraya which consisted of several variables, namely the presence of student data, Academic value (knowledge), Psychomotor value (skills), Affective value (spiritual and social). In grouping the data, the appropriate method in this study is the Clustering method with the K-Means Algorithm. The results of this study obtained 3 groupings of students, namely students who are very active, students who are active and students who are less active. This research is used as a guideline for teachers in the field of study in selecting students to participate in competitions and Olympics, and can be used as a benchmark for schools of the ability of educators in the teaching and learning process.
Akurasi Pemberian Insentif Menggunakan Algoritma K-Medoids Terhadap Tingkat Kedisiplinan Pegawai Wendi Robiansyah; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.125

Abstract

Assessment of a discipline is a performance evaluation stage that is important for the continuity of company activities. Monitoring and assessment of an employee's discipline must be carried out continuously in order to improve the quality of human resources. This research was conducted to make the accuracy of providing incentives based on the level of employee discipline. The data processed in this study is a recapitulation of the attendance of AMIK and STIKOM Tunas Bangsa Pematangsiantar employees as many as 25 employees as a sample. For grouping the employee data using the K-Medoids Algorithm. K-Medoids groups a set of n objects into a number of k clusters using the partition clustering method. Furthermore, the employee data is processed using Rapid Miner software. Research using this method obtained results in the form of grouping employees into 3 groups that have good discipline levels of 12 employees, sufficient discipline levels of 8 employees, and less disciplinary levels of 5 employees. Based on the grouping results that have been produced, it can be a consideration for the leadership to determine the amount of incentives for employees.
Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS Faisal Roza; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.140

Abstract

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.
Sistem Pakar Dalam Mengidentifikasi Kenaikan Pangkat Pegawai Negeri Sipil Menggunakan Metode Backward Chaining Yolla Rahmadi Helmi; Y Yuhandri; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.149

Abstract

Promotion can be interpreted as an element in enforcing the career of Civil Servants (PNS). The promotion to the rank of Civil Servants (PNS) is in the form of an award for work achievements that have been achieved and service to the country after fulfilling certain conditions. At this time there are still many Civil Servants (PNS) who do not understand employee governance such as this promotion and there are still many who do not know what are the completeness of promotions and do not know whether a Civil Servant (PNS) can be promoted. or not. This study aims to make Civil Servants (PNS) know whether it is proven or not to be able to be promoted based on certain conditions that must be met for promotion. The data processed in this study were directly directed by experts. The data is sourced from the staffing of the Regional Office of the Ministry of Religion of West Sumatra Province. The promotion data is processed and developed using an expert system built using PHP programming and MySQL database. In the Expert System in identifying the promotion of Civil Servants using the Backward Chaining method, the appropriate and suitable results are obtained between the expert data and the tracking results. 5 matches were obtained from the tracking results with 5 expert data whose percentage reached 100%, so whether or not a Civil Servant could be promoted to rank could be identified. It is hoped that the application that has been built in this research can be useful for Civil Servants (PNS) in identifying promotions, and to provide information about promotions.
Data Mining dalam Pengelompokan Penyakit Pasien dengan Metode K-Medoids Dwi Utari Iswavigra; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.150

Abstract

Disease is a condition in which the mind and body experience a kind of disturbance, discomfort for those who experience it. Day by day, the number of patients at the Kuok Health Center is increasing with various types of different diseases. The increase number of patients requires the Kuok Health Center staff always update the patient's medical record data. The patient's medical record data is the form of a report containing the number of patients and their illnesses. Based on these data, the Puskesmas needs to find out information about the diseases that are most vulnerable and suffered by many patients. This study aims to classify patient disease data to find out the most common diseases suffered by patients at the Kuok Health Center, Kampar Regency. The grouping of patient disease data is carried out with the Data Mining Clustering and followed by the K-Medoids method. Next, cluster testing is carried out using the Silhouette Coefficient. The results of this study indicate that in cluster 1 the most common disease suffered by patients is non-insulin dependent diabetes mellitus (type II) with a total of 435 cases. In cluster 2, the most common disease suffered by patients was Essential Hypertension (Primary) with a total of 2785 cases. For cluster 3, the most common disease suffered by patients was Vulnus Laseratum, Punctum, with a total of 328 cases. From the cluster results obtained, the results of the Silhouette Coeficient test are 0.900033674.
Machine Learning Rekomendasi Produk dalam Penjualan Menggunakan Metode Item-Based Collaborative Filtering Daniel Theodorus; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.151

Abstract

The shift towards Industry 4.0 has pushed many companies to adopt a digital system. With the sheer amount of data available today, companies start to face difficulties with providing product recommendation to their customers. As a result, data analysis has become increasingly important in the pursuit of providing the best service (user experience) to customers. The location appointed in this research is PT. Sentral Tukang Indonesia which is engaged in the sale of building materials and carpentry tools such as: paint, plywood, aluminum, ceramics, and hpl. Machine Learning has emerged as a possible solution in the field of data analysis. The recommendation system emerged as a solution in providing product recommendation based on interactions between customers in historical sales data. The purpose of this study is to assist companies in providing product recommendation to increase sales, to make it easier for customers to find the products they need, providing the best service (user experience) to customers. The data used is customer, item, and historical sales at PT. Sentral Tukang Indonesia over a time span of 1 period.data historical sales divide to dataset training 80% and dataset testing 20%. The Item-based Collaborative Filtering method used in this study uses Cosine Similarity algorithm to calculate the level of similarity between products. Score prediction uses Weighted Sum formula while computation of error rate uses the Root Mean Squared Error formula. The result of this study shows top 10 product recommendations per customer. The products displayed are products with the highest score from the individual customer. This research can be used as a reference by companies looking to provide product recommendations needed by their customers.
Identifikasi Tingkat Pemakaian Obat Menggunakan Metode Fuzzy C-Means Hidayati Rusnedy; Gunadi Widi Nurcahyo; S Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.152

Abstract

Medicine is one of the irreplaceable components in health services that can help in treating sick people. Planning for drug needs is one of the important aspects in drug management, because it affects the procurement, distribution and use of drugs in health care units. Planning the right drug needs will make procurement effective and efficient so that it is in accordance with the needs of health services with guaranteed quality and can be obtained when needed. Puskesmas is one of the health services that is managed under the District and City Health Offices. However, in reality there are still obstacles in the process of drug procurement at the Puskesmas so that it has not yet achieved excellent service related to the availability of drug services. Clustering in Data Mining can be used to analyze the use of drugs, planning and controlling drugs at the Puskesmas. The method that will be used in this research is the Fuzzy C-Means algorithm, which is the most widely used and relatively successful unsupervised machine learning method among many fuzzy clustering algorithms. The purpose of this study was to categorize drug data which can be used as a reference in making decisions in planning and controlling medical supplies at the puskesmas. Based on 501 Pharmacy Monthly LPLPO data records in October 2020-February 2021, the results obtained in cluster one are 179 types of drugs which are included in the low level of use, cluster 2 there are 18 types of drugs that are included in the moderate level of use and cluster 3 as many as 4 types. drugs that are included in the high level of use.
Sistem Pakar Dalam Mengidentifikasi Penanda Minat Karakteristik Ekstrakurikuler Berbasis Case Based Reasoning Sisi Hendriani; Gunadi Widi Nurcahyo; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.154

Abstract

Extracurricular is an additional activity at school whose purpose is to help develop students' talents, talent is defined as an innate ability which is a potential that needs to be developed and trained. Extracurricular selection is chosen by the students themselves without the intervention of teachers or parents so that students often only follow the majority of their friends' wishes. Knowing the extracurricular characteristics of students through the type of learning will make students' self-development more focused. This study uses the Case Based Reasoning method with similarity calculations which has 4 stages, namely retrieve (rediscover old similar cases), reuse (make old cases as solutions to new cases), revise (evaluate proposed solutions) and retain (store new cases). on a case basis) to determine the type of learning of students which will then be known to be suitable extracurricular activities due to the condition of the psychological development of children during the junior high school (SMP) level who tend to make the wrong choice or just participate in choosing something, especially in terms of selection. extracurricular at school. The learning styles are classified into six learning styles, namely Linguistic, Kinesthetic, Interpersonal, Musical, Naturalist and Logical Mathematics which are then adapted to the extracurricular fields at school. This study identifies the characteristics of student interest using student data at SMP Negeri 17 Padang, the results of similarity 66% for interpersonal learning style, 0% for kinesthetic learning style, 6% for musical learning style, 14% for natural learning style, 0% for logical mathematics learning style and 13% for linguistic learning style. The resulting expert system can help students quickly provide an appropriate extracurricular overview.
Prediksi Potensi Relawan Pendonor Darah Menjadi Pendonor Darah Tetap dengan Penerapan Metode Klasifikasi Decision Tree Afifah Cahayani Adha; Y Yuhandri; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.158

Abstract

Blood donation is an important activity to obtain blood as a raw material into the blood supply chain. If there is not enough blood in the human body, then human survival will be threatened, for some conditions blood transfusions are required, such as accidents, childbirth or certain grades of dengue fever. UTD PMI Pekanbaru City is the organizing body for blood donation activities in the process of helping and serving the blood needs for public. Based on data from the Ministry of Health in 2019, Pekanbaru City lacked in blood stock 32.4 percent, which the ideal supply of blood bags in Pekanbaru City was 130,019 blood stock. This causes some hospitals difficult to find the supply of blood stock. The cause of lacking in blood bags' availability in Pekanbaru City was the number of volunteer donors fluctuates and the public's low interest in becoming volunteer blood donors. So it becomes a problem when the number of requests for blood increases, while the supply at the blood bank is running low. The method used in this research was the Decision Tree method. The algorithm used in this study was the C.45 Algorithm. To solve the problems that occur, data analysis of blood donor volunteers was carried out. Based on the results of the testing data analysis as many as 50 records, 6 rules were produced which can be concluded that age over 19 years with an entrepreneur job has the potential to become a permanent blood donor
Co-Authors A Alfarisdon AA Sudharmawan, AA Abdi Rahim Damanik Afifah Cahayani Adha Afriosa Syawitri Agung Ramadhanu Ahmad Zamsuri, Ahmad Alexyusandria alexyusandria Alfarisdon, A Ali Djamhuri Andi, Muhammad Yusril Haffandi Anggraini, Siska Dwi Anita Sindar Apriade Voutama Ardia Ovidius ardialis Asyhari, Ahmad Aulia Mardhatilla Ayudia, Dina Ayunda, Afifah Trista Bayu Rianto Billy Hendrik Boy Sandy Dwi Nugraha.H Breinda, Engla Budayawan, Khairi Budiarti, Lela Bufra, Fanny Septiani Candra Putra Cyntia Lasmi Andesti Cyntia Trimulia Damanik, Abdi Rahim Daniel Theodorus Darma Yunita Darmawi Darnis, Rahmi Dedi Irawan Deri Marse Putra Dina Ayudia Dinda Permata Sukma DWI JULISA UTARI Dwi Utari Iswavigra Dyan Mardinata Putra Eka Putra, Dian Elfina Novalia Erizke Aulya Pasel Faisal Roza Fajri Karim Fanny Septiani Bufra Fauzan Azim Fauzi Erwis Febriani, Widya Febrina, Yerri Kurnia Fernando Ramadhan Fitriani, Yetti Fortia Magfira Gaja, Rizqi Nusabbih Hidayatullah Hafid Dwi Adha Handika, Yola Tri Hartati, Yuli Hasni, Salmi Hazlita, H Hendrik, Billy Honestya, Gabriela Humairoh, Putri Idir Fitriyanto Idir Ilham Effendi Indah Savitri Hidayat INTAN NUR FITRIYANI Ipri Adi Ira Nia Sanita Jefri Rahmad Mulia Johan Harlan Jufri, Fikri Ramadhan Jufriadif Na`am, Jufriadif Jufriadif Na’am Juliantho, Dwana Abdi Julius Santoni Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony Karim, Fajri Khelvin Ovela Putra Kholil, Muhammad Irvan Larissa Navia Rani Leony Lidya Lidia Sutra Lova Endriani Zen Lubis, Fitri Amelia Sari Lusi Kestina Luth Fimawahib M Mutia M, Mutia M. Almepal Wanda M. Ibnu Pati Mardayatmi, Suci Mardison Mardison Marfalino, Hari Meilinda Sari Meilinda Sari Melissa Triandini Miftahul Hasanah Miftahul Hasanah, Miftahul Miftahul Mardiyah Mike Zaimy Muhammad Irvan Kholil Nabila, Tuti Nadia, Nadia Aini Hafizhah Nadya Alinda Rahmi Nasution, Amir Salim Khairul Rijal Nia Nofia Mitra Nissa, Ika Ima Nst, Ely Nurhalizah Nur Azizah Nur, Rofil M Nurdini, Siti Pati, Muhammad Ibnu Pebriyanti, Defi Petti Indrayati Sijabat Puji Chairu Sabila Putra, Akmal Darman Putra, Deri Marse Putra, Dyan Mardinata Putri Humairoh Putri, Stefani Putut Wicaksono, Putut Radillah, Teuku Rafiska, Rian Rahmad Supriadi Rahman, Zumardi Ramadhanu, Agung Riati, Itin Rika Apriani Rika Apriani, Rika Ririn Violina Ritna Wahyuni Rizka Hafsari Rizki Mubarak Roby Nurbahri Roni Salambue Rovidatul Rozakh, Muhammad Rusnedy, Hidayati Rustam, Camila S Sumijan Sabil, Muhammad Sahari Sahari Sahri, Alfi Sajida, Mayang Sandi Alam Sandrawira Anggraini Sani, Rafikasani Santriawan, Aji Sari, Fitri P. Sarjon Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Sharon Sintia Sintia Siregar, Fajri Marindra Sisi Hendriani Siska Dwi Anggraini Siti Nurdini Sovia, Rini Sri Handayani Sri Layli Fajri Stefani Hardiyanti Putri Suci Mardayatmi Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Suri, Melati Rahma Sutra, Lidia Syafri Arlis Tesa Vausia Sandiva Ulfa, Ulia Ulfatun Hasanah Ulia Ulfa Verdian, Ihsan Vratiwi, Septiana W Wahyudi Wahyu, Fungki Wahyudi Wahid Wahyudi Wahyudi Wendi Robiansyah Weri Sirait Widya Febriani Yeng Primawati Yerri Kurnia Febrina Yetti Fitriani Yolla Rahmadi Helmi Yoni Aswan Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri Yunus Yuhandri, Y Yuli Hartati Yunita Cahaya Khairani Yunus, Yuhandri Yuyu, Yuhandri