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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Informatika Jurnal Informasi dan Teknologi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Majalah Ilmiah UPI YPTK Journal Of Human And Education (JAHE) Journal of Vocational Education and Information Technology (JVEIT) J-Icon : Jurnal Komputer dan Informatika JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) JCSE: Journal of Community Service and Empowerment Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat
Yofhanda Septi Eirlangga
Universitas Adzkia
Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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Prediksi Tingkat Kunjungan Pasien dengan Menggunakan Metode Monte Carlo Aldo Eko Syaputra; Yofhanda Septi Eirlangga
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i2.202

Abstract

The increase in the number of patient visits that often occur at community health centers / puskesmas has caused some activities in health services to be slightly hampered, disturbed and less than optimal, resulting in some patients not getting comprehensive services and some even waiting too long in queues. The purpose of this study was to provide information to the health center about the prediction of an increase in the number of patient visits that might occur in the future. The data used in this study were patient visit data at the IX Koto Sungai Lasi health center from 2019, 2020, and 2021 to extract the data that was obtained. The method used in this study was the Monte Carlo method. The results of the study can predict patient visit rates in the following years with an average accuracy rate of 91%, in 2020, and 85% in 2021, the results of these predictions can be a reference for the Puskesmas to take action and policies to improve quality of service at the Puskesmas.
Klasifikasi Penjurusan pada Sekolah Menengah Atas (SMA) dengan Metode Algoritma C4.5 Yofhanda Septi Eirlangga; Aldo Eko Syaputra
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i3.235

Abstract

The Indonesian Minister of Education has stipulated 12 years of compulsory education, but only at high school (SMA) students can only determine the major they are interested in. In every new academic year the PPDB (New Student Admissions) committee has difficulty in determining majors because the determination of majors is still done manually so that there is a mismatch with the interests and talents of students caused by human error. So it is necessary to conduct a study with the aim of assisting the PPDB committee in determining the majors accurately and effectively so that the interests and talents of students can be channeled appropriately. Therefore, the C4.5 algorithm method is used which is one of the data mining algorithms that produces a decision tree that is suitable for classifying large amounts of data. The data used in this study were taken from the grade IX student report cards in 2022 as many as 44 report cards which have 11 subject value variables, namely Science, Social Sciences, Indonesian Language, PKN, Islamic Religious Education, MTK, English, BAM Arts and Culture, ICT and Physical Education. The results of this study obtained a decision tree (decision tree) with 17 rules (knowledge) that has been matched with real data with a very high level of accuracy. So that this research can help and become a benchmark for the PPDB committee in determining the majors of new students every time a new teaching begins at SMA Pertiwi 2 Padang
Model Simulasi untuk Memperkirakan Tingkat Penjualan Garam Menggunakan Metode Monte Carlo Muhammad Thoriq; Aldo Eko Syaputra; Yofhanda Septi Eirlangga
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i4.244

Abstract

The increasing need for salt in the West Sumatra area is inversely proportional to the raw material for making salt. So the stock of salt for consumption becomes less. This causes the purchasing power to be cut off for the needs of regional consumers. Based on these problems, a research was conducted by conducting simulations to predict the amount of salt sales in controlling stock. This study aims to predict sales in maintaining service to consumer demand. The method that can be used in making predictions is the Monte Carlo Method by processing Salt sales data in 2019, 2020, and 2021 at PT. Prosperous Grace. The results of the study are able to predict sales of salt in the form of kilograms (kg) in the future. The average accuracy rate in 2020 is 88% and in 2021 is 91%. So that this research can be a reference in decision making by PT. Kurnia Sejahtera to improve services.
SISTEM PAKAR DALAM MENENTUKAN KENAIKAN PANGKAT ANGGOTA POLRI MENGGUNAKAN METODE FORWARD CHAINING Devi Gusmita; Yofhanda Septi Eirlangga; Sopi Sapriadi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 6, No 1 (2023): February 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v6i1.1194

Abstract

Abstract: This research has been done research on the promotion of the rank of POLRI Members in this process is essentially the examination of the requirements for the proposed promotion of members of POLRI. this research is done design and manufacture of expert systems based rules (Rule Based) to help calculation requirements in the process determination of promotion in the process of appointing the promotion of members of POLRI. The inference method used is forward chaining where the tracking starts from the destination ie the type of the intended rank, then sought the rules of conditions that have tujua it for the conclusion. Tests conducted on this expert system include testing of police data that has prepared the requirements for the promotion process. The results of this study are expected to provide solutions and ease along with accurate information in the process of determining the promotion of members of POLRIKeywords: Expert system; forward chaining; promotion; rule based. Abstrak: Pada penelitian ini berisi tentang kenaikan pangkat Anggota POLRI yang proses intinya adalah pemeriksaan syarat-syarat untuk usulan kenaikan pangkat anggota POLRI. Dalam penelitian ini dilakukan perancangan dan pembuatan sistem pakar berbasiskan aturan(Rule Based) untuk membantu perhitungan syarat-syarat dalam proses penetuan kenaikan pangkat anggota POLRI. Metode inferensi yang digunakan adalah forward chaining dimana pelacakan dimulai dari tujuan yaitu jenis pangkat yang dituju, selanjutnya dicari aturan syarat-syarat yang memiliki tujuan tersebut untuk kesimpulannya. Pengujian yang dilakukan pada sistem pakar ini meliputi pengujian terhadap data polisi yang telah mempersiapkan syarat-syarat untuk proses kenaikan pangkat.Hasil dari penelitian ini diharapkan mampu memberikan solusi dan kemudahan beserta informasi yang akurat dalam proses penentuan kenaikan pangkat anggota POLRI.Kata kunci: Sistem pakar; Forward Chaining; kenaikan pangkat; Rule Based
SISTEM PENUNJANG DALAM PENGAMBILAN KEPUTUSAN PEMBERIAN REWARD DOSEN TERBAIK MENGGUNAKAN METODE TOPSIS Hayati, Nova; Syaputra, Aldo Eko; Eirlangga, Yofhanda Septi
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.12390

Abstract

Lecturers are professional teaching staff who provide all their knowledge and loyalty through teaching students, research and community service. To increase the performance and loyalty of lecturers to tertiary institutions, this is done by giving rewards to the best lecturers. In making the decision to give rewards to lecturers, there are several steps and criteria that must be met, because the large number of lecturers and criteria causes the assessment team to experience difficulties in processing the criteria data and lecturer data who are entitled to the reward, so a method is needed that is implemented into a computerized system that will facilitate the work of the assessment team in data processing and the resulting data to be accurate and reliable. The data applied in this research is data from permanent university lecturers and the conditions set by the university. The purpose of this research is to maximize the performance of the assessment team in processing criteria data and university permanent lecturers to get the best lecturers who are entitled to receive rewards using the TOPSIS method. The decision in determining the alternative to giving rewards to the best lecturers, by selecting 3 lecturers as recipients of the best lecturer rewards as an alternative is the result of this study. From these results, there are influential criteria, namely Research, Teaching, and Attendance.
Prediction of the Number of New Students in the Information Systems Study Program at Adzkia University Using the Monte Carlo Method: Prediksi Jumlah Mahasiswa Baru Program Studi Sistem Informasi Universitas adzkia Menggunakan Metode Monte Carlo Prima, Wahyu; Eko Syaputra, Aldo; Sapriadi, Sopi; Septi Eirlangga , Yofhanda; Hariani Manurung, Kiki; Hayati, Nova
Journal of Vocational Education and Information Technology (JVEIT) Vol. 5 No. 1 (2024): Vol. 5 No. 1 (2024): JVEIT
Publisher : Lembaga Pengembangan dan Inovasi Universitas Dharmas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56667/jveit.v5i1.1458

Abstract

This research aims to predict the number of new students in the Information Systems Study Program at Adzkia University using the Monte Carlo method. The Monte Carlo method was chosen because of its ability to handle variability and uncertainty in historical student enrollment data. The data used in this research is data on students who registered from any pathway during the last 3 years. The simulation process is carried out by creating a probabilistic model from historical data and iterating until a prediction distribution is obtained. The research results show that the Monte Carlo method provides fairly accurate estimates of student predictions for the following year, namely (numbers) which can be used for strategic planning for new student admissions in the future. In conclusion, the use of the Monte Carlo method can be an effective tool in predicting the number of new students and assisting universities in making better decisions regarding student admissions.
Akumulasi dan Prediksi Tingkat Penjualan Minuman dengan Menerapkan Metode Monte Carlo Syaputra, Aldo Eko; Eirlangga, Yofhanda Septi
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v5i1.225

Abstract

25 Coffee has increased sales every day. This situation causes service to consumers to be disrupted because raw materials often run out. Some consumers do not get good service and some even wait too long but do not get the desired item. This situation will cause consumers to be reduced because they move to another seller's place. So this research is carried out to predict sales in maintaining the availability of raw materials so that services are guaranteed and improved. The method used in this study is Monte Carlo by processing sales data in 2019, 2020, and 2021. The results of this study are able to predict the number of beverage sales in the following years with an average accuracy rate of 91%, in 2020 , and 89% in 2021. So this prediction becomes a reference material for 25 COFFE parties to make decisions and improve services.
Sistem Pakar Diagnosa Gaya Belajar Mahasiswa Menggunakan Metode Forward Chaining Sapriadi, Sopi; Eko Syaputra, Aldo; Septi Eirlangga, Yofhanda; Manurung, Kiki Hariani; Hayati, Nova
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.381

Abstract

Sistem pakar merupakan bagian dari pemanfaatan teknologi sehingga menjadi salah satu upaya dalam mendukung berbagai aktivitas manusia. Salah satu cara di mana sistem pakar dimanfaatkan adalah dlam konteks pendidikan. Gaya belajar adalah kecendrungan individu untuk menambil pendekatan khusus dalam proses pembelajarannya, dengan tujuan memastikan bahwa mereka bertanggung jawab dlam menemukan metode belajar yang cocok baik untuk lingkungan perkuliahan maupun materi kuliah yang harus dipelajari. Terdiri dari tia tipe gaya belajar, yakni visual, auditori, dan kinestetik. Walaupun tiap individu dapat mengunakan ketiga modalitas ini tergantung paa situasi, tetap terdapat kecendrungan yang lebih dominan pada salah satu diantaranya. Sehingga dosen harus membuat pembelajaran seefektif mungkin untuk meningkatkan pembelajaran yang seefesien mungkin. Penelitian ini bertujuan untuk melihat kemampuan mahasiswa dalam pemahaman gaya belajar dan pemahaman mahasiswa dalam proses belajar. Oleh karena itu, penelitian ini juga dapat berkontribusi dalam membatu Universitas Adzkia dalam mengambil keputusan yang sesuai untuk meningkatkan mutu pembelajaran di masa mendatang. . Untuk mengatasi sejumlah tantangan yang telah dijelaskan di atas, diperlukan penerapan sistem pakar yang mampu mengambil keputusan sebagaimana yang dilakukan oleh para ahli. Dalam konteks sistem pakar ini yang digunakan adalah metode forward chaining. Metode ini melibatkan pelacakan ke depan, dimulai dari fakta-fakta yang ada hingga mencapai kesimpulan. Dengan pendekatan ini, tujuan akurasi dapat dicapai. Hasil dari hal ini adalah dapat mendeteksi gaya belajar dengan tingkat kesamaan dikategorikan 90%.
SPK PENYELEKSIAN SISWA KELAS UNGGUL DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) eirlangga, Yofhanda Septi; Aldo Eko Syaputra; Muhammad Thoriq
JURNAL FASILKOM Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6348

Abstract

High-achiever classes are specialized groups comprising students who excel in two areas of assessment, possessing intelligence above the average. Teaching in these specialized classes requires specific skills to optimize the potential of the students. Each year, West Pasaman High School conducts screenings for hundreds of students eligible for placement in the high-achiever classes, which are limited to only 50 students. The selection process for these high-achiever classes at West Pasaman High School has traditionally been manual, lacking a systematic method to support the selection process. Consequently, the selection process has been time-consuming, resulting in inefficiencies, compounded by subjective factors like social jealousy over the outcomes of the selection. The proposed solution to address the issue in selecting high-achiever students is by implementing a systematic, computerized method to expedite and improve the accuracy of the selection process. The methodology employed in this study is the Analytical Hierarchy Process (AHP). The school has outlined six criteria for evaluation: normative value, adaptive value, attitude, discipline, creativity, and academic performance. The primary objective of this research conducted at West Pasaman High School is to assist the school administration in swiftly and efficiently identifying high-achiever students. The data processing from this study provides the final scores of students, ranked from highest to lowest, with the highest score obtained by 'Payau' at 0.232 or 23.2%, followed by 'Pada' with a score of 0.229 or 22.9%. It is hoped that this research can serve as a reference for the school administration in refining their selection process and identifying students deserving of a place in the high-achiever classes. Keywords: AHP, high-achiever classes, decision support system, school, selection.
Seminar Edukasi untuk Meningkatkan Motivasi Siswa SMK melanjutkan Pendidikan Tinggi Alima Shofia; Muhammad Thoriq; Ranti Mustika Putri; Kiki Hariani Manurung; Yofhanda Septi Eirlangga
JCSE: Journal of Community Service and Empowerment Vol. 5 No. 1 (2024): JCSE April 2024
Publisher : LP3M Universitas Putra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32639/jcse.v5i1.822

Abstract

Tingkat kesadaran siswa Sekolah Menengah Kejuruan (SMK) akan pentingnya kuliah dapat bervariasi tergantung pada konteks sosial, lingkungan sekolah, dan informasi yang mereka terima. Sebagian siswa SMK mungkin memiliki pemahaman yang terbatas tentang manfaat dan relevansi pendidikan tinggi terhadap kemajuan karir dan kehidupan pribadi mereka. Hal ini bisa disebabkan oleh kurangnya pengetahuan tentang opsi pendidikan lanjutan setelah lulus dari SMK, prioritas keluarga, atau perbedaan budaya di lingkungan mereka. Kegiatan pengabdian kepada masyarakat (PkM) ini bertujuan untuk memberikan motivasi kepada para siswa SMK untuk dapat melanjutkan pendidikan ke jenjang yang lebih tinggi. Hasil penelitian menunjukkan bahwa seminar tersebyt berhasil meningkatkan pemahaman siswa SMK tentang peran dan manfaat pendidikan tinggi dalam mengembangkan karir serta kehidupan pribadi mereka. Selain itu, peserta seminar menunjukkan minat yang tinggi untuk melanjutkan pendidikan ke jenjang yang lebih tinggi setelah lulus dari SMK. Kesimpulannya, seminar ini dapat menjadi instrumen yang efektif dalam meningkatkan akses dan partisipasi siswa SMK dalam pendidikan tinggi serta mempersiapkan mereka untuk masa depan yang lebih cerah.
Co-Authors Aldo Eko Syaputra Alima Shofia Ashim Madani, Muhammad Ayun, Aisyah Qurrata Devi Gusmita Fajar Maulana Hariani Manurung, Kiki Hayati , Nova Hayati, Nova Hendra, Yomei Kiki Hariani Manurung Kiki Hariani Manurung Manurung, Kiki Hariani Maulana, Fajar Mufid, Muhammad Fauzan Muhammad Fauzan Mufid MUHAMMAD THORIQ Muhammad Thoriq Nurul Hasanah Prima, Wahyu Rahmadhani, Firda Ranti Mustika Putri SAKINAH, PUTRI Sapriadi, Sopi Silky Selfira Sopi Sapriadi Thoriq, Muhammad Ulya Mega Wahyuni Yomei Hendra