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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ELECTRANS Proceeding of the Electrical Engineering Computer Science and Informatics Sains Manajemen:Jurnal Manajemen UNSERA Wikrama Parahita : Jurnal Pengabdian Masyarakat Jurnal Pengembangan Riset dan Observasi Teknik Informatika TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Bantenese Jurnal Pengabdian Masyarakat Journal of Machine Learning and Soft Computing Al-Khidmat : Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Keuangan dan Akuntansi Terapan (KUAT)
Sumiati, Sumiati
Jurusan Teknik Informatika Universitas Serang Raya - Banten
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Data Mining Implementation to Predict Sales Using Time Series Method Agung Triayudi; Sumiati Sumiati; Thoha Nurhadiyan; Vidila Rosalina
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 2: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2028

Abstract

Sales transaction data histories can be used to predict the possibility of sales transaction that will occur in the future. These characteristics are in accordance with forecasting using time series method where this method uses previous data as tools to predict transaction value that will appear in the present time. Company X that runs its business by sell their product through distributors has sales data that is not optimally utilized. The average number of sales per year ranges from 5000 transactions which is not use to forecast transactions hereafter. Transaction data is stored in the company database so that data mining technology can be applied to support company X transaction data collection from previous year. The data is processed in applications where the results of forecasting are compared with real data in 2018 to see the accuracy of the forecasting results. The graphic that shown in application has pattern which can use for forecasting. From the forecasting method used, it can be seen that the forecasting results show data that came out did not produce data that matched the real data where the highest level of accuracy was 99.68% and the lowest accuracy was still above 50%.
Pemberdayaan Ibu Rumah Tangga melalui Pembinaan Wirausaha Mandiri Pembuatan Sabun Milan dan Kerupuk Ampas Tahu Sumiati Sumiati; Ratu Dea Mada
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2018)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v2i1.385

Abstract

One of activity occurred in Community Service Program of Unsera is workshop of entrepreneurship which involved the lectures as the supervisor. This workshop is done to established entrepreneurships among housewives in Sukamaju Village, Cikeusal District. We hope that the big numbers of housewives potency at this place can increase the salary for the household and support the needs of the household itself. This workshop produced soap called, Milan Soap and Tofu snacks with variant taste. This workshop also increase the economic level of the people in this place by producing soaps from house oil waste and tofu snacks from tofu waste and develop knowledge about entrepreneurships, accounting and marketing.
Prototype Robot Penyedot Debu Berbasis mikrokontroler atmega328 dan fuzzy logic Dengan Kendali Smarthone Android Di Universitas Serang Raya Ilham Hidayat; sumiati .
ProTekInfo(Pengembangan Riset dan Observasi Teknik Informatika) Vol. 3 (2016)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.484 KB) | DOI: 10.30656/protekinfo.v3i0.56

Abstract

Sistem android yang saat ini banyak digunakan pada Smarphone merupakan OS yang berbasis sistem operasi linux. Aplikasi - aplikasi yang ada didalamnya cukup banyak dan bersifat open source sehingga sangat memungkinkan untuk dikembangkan lebih lanjut dalam berbagai aplikasi, terutama dalam hal pengendalian robot. Aplikasi Android untuk pengendalian robot penyedot  debu menggunakan komunikasi bluetooth merupakan fitur manual untuk mengendalikan robot penyedot debu ini.Alat ini dibuat berdasarkan beberapa bagian antara lain : Mikrokontroler Atmega328, dengan pemrograman C. Sensor Ultrasonic dan sensor debu yang merupakan rangkaian sensor sebagai inputan pada mikrokontroler. Ultrasonic berfungsi untuk mendeteksi adanya halangan pada robot, yang langsung masuk ke mikrokontroler. Sensor debu berfungsi untuk mendeteksi adanya debu di daerah robot.Output mikrokontroler akan menghasilkan logika 1 untuk mengaktifkan driver motor pada pin IC L293D untuk mengaktifkan motor roda kanan dan roda kiri. Motor DC yang digunakan sebagai pengerak robot. Baterai di gunakan sebagai catu daya pada robot. Komponen terpenting yang digunakan pada Robot Penyedot Debu adalah menggunakan salah satu jenis Mikrokontroller yaitu ATmega328. Dengan menggunakan Mikrokontroller ATmega328 tersebut dapat diketahui bahwa dalam merancang sebuah robot dapat ditentukan gerak laju robot tersebut secara otomatis ataupun manual sesuai dengan program yang telah diinputkan ke dalam chip robot
PENGEMBANGAN BIOGAS DARI SAMPAH UNTUK ENERGI LISTRIK DAN BAHAN BAKAR KOMPOR DI TPA CILOWONG, KOTA SERANG, BANTEN Shohifah Annur; Wyke Kusmasari; Retno Wulandari; Sumiati Sumiati
KUAT : Keuangan Umum dan Akuntansi Terapan Vol 2 No 1 (2020): Edisi Maret
Publisher : Polytechnic of State Finance STAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.606 KB) | DOI: 10.31092/kuat.v2i1.823

Abstract

 Kegiatan pengabdian ini bertujuan untuk membuat pembangkit listrik yang berasal dari sampah organik di TPA Cilowong, Kota Serang Banten. TPA Cilowong merupakan tempat pembuangan pusat sampah yang berasal dari seluruh daerah yang ada di wilayah Kota Serang Banten. Setiap harinya TPA ini menerima 5 truk sampah pasar yang dibuang pada landfill dan belum dimanfaatkan secara optimal.  Padahal sampah ini dapat diolah menjadi biogas untuk penerangan listrik TPA dan bahan bakar kompor di dapur umum TPA. Instalasi biogas dibuat dengan satu digester (penampung biogas) berbentuk bulat yang bisa menampung sampah sebesar 6 m3. Untuk pertama kali pemakaian, dibutuhkan starter kotoran sapi yang dicampur dengan sampah organik pasar sebagai starter dengan perbandingan sampah : kotoran sapi = 5: 1. Kegiatan ini bekerja sama dengan 30 orang mahasiswa KKM dan pengurus TPA Cilowong. Biogas dari sampah ini bisa digunakan untuk penerangan listrik di TPA dan sebagai sumber gas di dapur umum TPA.
Diagnosa Kelainan Jantung dengan Pendekatan Fuzzy Logic Mamdani Sumiati Sumiati; Haris Triono Sigit; Agung Triayudi; Melisa Theresia
TELKA - Jurnal Telekomunikasi, Elektronika, Komputasi dan Kontrol Vol 8, No 2 (2022): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v8n2.149-157

Abstract

Penyakit jantung merupakan penyebab utama kematian yang menduduki peringkat satu di Indonesia. Oleh karena itu, dokter perlu mendeteksi sejak dini penyakit jantung pada pasien. Dalam mendiagnosa penyakit jantung diperlukan sebuah alat untuk mengetahui kondisi fisik jantung. Alat yang sering digunakan adalah Elektrokardiogram (EKG). Alat EKG ini dapat memantau aktivitas listrik jantung yang ditampilkan dalam bentuk grafik. Namun, alat EKG ini dinilai belum mampu mendeteksi secara otomatis keadaan jantung pasien. Oleh karena itu, pada penelitian ini dikembangkan sebuah aplikasi untuk mengidentifikasi kelainan jantung secara otomatis berbasis metode Fuzzy Mamdani dengan menggunakan 100 data hasil rekam medis Elektrokardiogram. Sistem yang dikembangkan mampu mengidentifikasi kondisi jantung pasien dalam dua kategori yaitu kondisi jantung yang normal dan kondisi jantung yang abnormal. Adanya sistem ini dapat membantu dokter dalam melakukan pemeriksaan kondisi jantung. Berdasarkan hasil pengujian sistem dengan pendekatan success rate mendapat nilai True positive 0,9%, nilai False Positive 0%, nilai success rate sebesar 95%, dan nilai error rate sebesar 0,05 %.Heart disease is the number one cause of death in Indonesia. Therefore, doctors need to detect early heart disease in patients. In diagnosing heart disease, a tool is needed to determine the physical condition of the heart. The tool often used is the electrocardiogram (EKG). This EKG tool can compile the heart's electrical activity, which is displayed in graphic form. However, this EKG tool cannot detect the patient's heart condition automatically. Therefore, this study developed a system to detect cardiac abnormalities using the Fuzzy Mamdani method using 100 electrocardiogram medical record data. The developed system can identify the patient's heart condition, namely normal heart and abnormal heart conditions. The existence of this system can assist doctors in examining heart conditions. Based on the results of system testing using the success rate approach, a True positive value of 0.9%, a False Positive value of 0%, a success rate of 95%, and an error rate of 0.05%.
Implementasi Klasifikasi Data Mining Untuk Penentuan Kelayakan Pemberian Kredit dengan Menggunakan Algoritma Naïve Bayes Agung Triayudi; Sumiati Sumiati
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4653

Abstract

Credit today is very widely used in the transaction process. At first, lending was only done by banks, but with the development of time and also the increasing needs and purchases from the public, lending is not only done by banks. The granting of credit for financing goods by the company to the buyer is not done haphazardly, but must go through several selection processes. The process of granting credit must be carried out through detailed and strict stages. This causes the process to be lengthy and also lengthens the work of the selection team. Data mining is a data processing technique that is useful for obtaining important patterns from data sets. The Naïve Bayes algorithm is part of the data mining classification process. The process of the Naïve Bayes algorithm is based on the concept of the Bayes theorem. The result of the research is that the new alternative data is ACCEPTABLE for credit applications, it can be seen that the probability value of ACCEPTED is greater than the probability value of REJECTED, which is 0.011108
Implementasi Klasifikasi Data Mining Untuk Penentuan Kelayakan Pemberian Kredit dengan Menggunakan Algoritma Naïve Bayes Agung Triayudi; Sumiati Sumiati
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4653

Abstract

Credit today is very widely used in the transaction process. At first, lending was only done by banks, but with the development of time and also the increasing needs and purchases from the public, lending is not only done by banks. The granting of credit for financing goods by the company to the buyer is not done haphazardly, but must go through several selection processes. The process of granting credit must be carried out through detailed and strict stages. This causes the process to be lengthy and also lengthens the work of the selection team. Data mining is a data processing technique that is useful for obtaining important patterns from data sets. The Naïve Bayes algorithm is part of the data mining classification process. The process of the Naïve Bayes algorithm is based on the concept of the Bayes theorem. The result of the research is that the new alternative data is ACCEPTABLE for credit applications, it can be seen that the probability value of ACCEPTED is greater than the probability value of REJECTED, which is 0.011108
Co-Authors Agung Triayudi Apriliana Dwijayanti Desmira Desmira Dwiyatno, Saleh Febriasari, Arifina Haris Triono Sigit Hoga Saragih Iksal Iksal Ilham Hidayat Karyaningsih, Dentik lia kamelia Mada, Ratu Dea Media Sucahya Melisa Theresia Muhar Dizani Nurhadiyan, Thoha Prakosa Trinorosimo Ratu Erlina Gentari Retno Wulandari Rosalina, Vidila Shodik Nuryadin Shohifah Annur Sigit Sasongko Suherman Suherman Sulasno Sulasno Suryaman Suryaman Susilawati . Tb. Ai Munandar Thoha Nurhadiyan Titik Abdul Rahman Wahyu Oktri Widyarto Wyke Kusmasari, Wyke