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All Journal SITEKIN: Jurnal Sains, Teknologi dan Industri Prosiding Semnastek Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo
Sarjon Defit
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Other

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Evaluasi Mutasai Jabatan Anggota Kepolisian Menggunakan Metode Profile Matching dan Multi Attribute Utility Theory Chairun Nas; Sarjon Defit; Julius Santony
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 16, No 1 (2018): DESEMBER 2018
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v16i1.6734

Abstract

Mutasi jabatan bertujuan untuk menunjang operasional dan meningkatkan efektifitas kerja dari institusi kepolisian. Tujuan dari penelitian ini membantu dalam pengambilan keputusan untuk mutasi jabatan dengan mengevaluasi nilai kriteria setiap anggota kepolisian. Dalam penelitian ini dilakukan pengolahan data kriteria penilaian dan data personel kepolisian yang diperoleh melalui hasil wawancara bersama kepala bagian sumber daya serta pengisian quisioner oleh 15 anggota kepolisian. Dari data tersebut dilakukan pengujian dengan menggunakan metode Profile Matching dan Multi Atribute Utility Theory. Hasil dari pengujian metode-metode tersebut adalah dihasilkan sebuah keputusan pada sebuah alternatif dengan nilai total sebesar 83,3%. Maka metode ini dibutuhkan untuk mengevaluasi penentuan mutasi jabatan sehingga menghasilkan keputusan terbaik.
Pemilihan Supplier Obat yang tepat dengan Metode Simple Additive Weighting Cyntia Trimulia; Sarjon Defit; Gunadi Widi Nurcahyo
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 16, No 1 (2018): DESEMBER 2018
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v16i1.6735

Abstract

Apotek adalah perusahaan yang bergerak di bidang farmasi berupa obat-obatan. Obat-obatan bersumber dari beberapa supplier. Dengan banyaknya supplier menyebabkan sulit dalam menentukan supplier yang bagus. Untuk menentukan supplier yang baik, maka dibutuhkan sebuah sistem pengambilan keputusan. Metode yang digunakan untuk mengambil keputusan dalam penelitian ini adalah Simple Additive Weighting (SAW). Data yang diolah berupa data-data kualitas, harga, petunjuk kegunaan, garansi, pemesanan, pemenuhan pesanan, dan pelayanan. Penilaian dapat dikembangan dengan kriteria yang akan di jadikan acuan untuk perengkingan supplier yang ada. Penilaian dari masing-masing kriteria diperoleh dari penilaian pemilik Apotek Mama Jakarta itu sendiri. Dengan adanya pemilihan supplier nantinya akan memudahan untuk membandingkan hasil kinerja supplier. Hasil yang didapatkan dengan menggunakan metode ini mampu mendapatkan supplier terbaik. Pengambilan keputusan ini membantu pemilik apotek dalam melakukan evaluasi terhadap supplier.
Diagnosis Penyakit Gigi dan Mulut Dengan Metode Forward Chaining Afriosa Syawitri; Sarjon Defit; Gunadi Widi Nurcahyo
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 16, No 1 (2018): DESEMBER 2018
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v16i1.6733

Abstract

Gigi dan mulut adalah organ tubuh yang sering mengalami gangguan penyakit yang disebabkan oleh kurangnya perhatian terhadap kesehatan gigi dan mulut. Untuk mengatasi gangguan penyakit gigi dan mulut, masyarakat membutuhkan konsultasi dengan dokter spesialis guna mendapatkan hasil diagnosis terhadap penyakit yang diderita. Untuk membantu pekerjaan dokter dalam melakukan diagnosis terhadap suatu penyakit maka dibutuhkan sebuah sistem yang memiliki kemampuan dan cara berfikir seperti dokter tersebut, hal ini bisa dilakukan dengan menggunakan sistem pakar (expert system). Didalam sistem pakar membutuhkan sebuah metode salah satunya adalah metode forward chaining. Penelitian ini menghasilkan diagnosis penyakit gigi dan mulut beserta perawatan penyakit tersebut. Dengan adanya penelitian ini dapat memberikan kemudahan kepada spesialis dalam mendiagnosa penyakit gigi dan mulut. Serta dapat memudahkan pasien dalam melakukan konsultasi.
SISTEM PAKAR PENENTUAN BAKAT ANAK DENGAN MENGGUNAKAN METODE FORWARD CHAINING Febi Nur Salisah; Leony Lidya; Sarjon Defit
Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Vol 1, No 1 (2015): Februari
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/rmsi.v1i1.1307

Abstract

Saat ini masih banyak orang tua yang belum mengetahui bakat pada anak mereka. Sedikitnya jumlah pakar untuk berkonsultasi merupakan salah satu penyebab hal ini. Penelitian ini menggunakan sistem pakar untuk mengatasi permasalahan tersebut. Sistem pakar akan memindahkan kemampuan pakar tersebut ke dalam komputer. Bakat-bakat yang digunakan dalam penelitian ini adalah bakat anak menurut standar USOE America. Untuk mesin inferensi penelitian ini menggunakan forward chaining. Anak-anak yang diidentifikasi bakatnya adalah anak TK usia 4-6 tahun.  Hasil analisa menunjukan bahwa sistem pakar ini membutuh 27 indikator, 83 variabel dan 33 rule. Berdasarkan hasil percobaan, sistem pakar ini berhasil mengidentifkasi bakat anak.
IMPLEMENTASI MOVING AVERAGE FILTER PADA MIKROKONTROLER SEBAGAI PEREDAM NOISE SENSOR PIEZO ELEKTRIK UNTUK MENDETEKSI GELOMBANG SEISMIK (GEMPA BUMI) Zulharbi Zulharbi; Firdaus Firdaus; Yul Antonisfia; Sarjon Defit
Prosiding Semnastek PROSIDING SEMNASTEK 2014
Publisher : Universitas Muhammadiyah Jakarta

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

Abstract

Getaran  akibat  gempa  bumi    akan  mengakibatkan  adanya  frekuensi  gelombang  seismik  denganfrekuensi  rendah (0Hz - 20Hz),  untuk  mendeteksi  keberadaan  frekuensi  gelombang  seismiktersebut  dapat  menggunakan  sensor  piezo  elektrik.  Piezo  elektrik  adalah  sebuah  sensor  seismikyang  mempunyai   getaran gempa  beramplitudo rendah  dan sangat mudah terkontaminasi noisesehingga  dibutuhkan  filter  untuk  meredam  sinyal  noise  tersebut.  Moving  Average  (MA)  filteradalah  suatu  metode  yang  sederhana  dan  berguna  untuk  menapis  derau  acak  yang  terdapat  padaderau asli. MA filter bekerja dengan cara meratakan sejumlah titik tertentu dari isyarat masukanuntuk  menghasilkan  tiap  titik  dari  isyarat  luaran. Gelombang  seismic    (getaran buatan) padapenelitian ini adalah dengan memberikan amplitudo sensor piezo PVDF antara  3mm, 5mm, 7mm,9mm dan 12mm pada frekuensi 2 Hz (konstan). Sensor piezo mendeteksi kekuatan getaran buatandengan  menggunakan  Moving  Average  Filter  yang  menghasilkan    nilai SNR  (signal  to  noiseratio)  lebih  kecil  dibandingkan  tidak  menggunakan  MAF  Nilai  PGA  (peak  groundacceleration)  dalam  satuan  grafitasi akan  tinggi pada  saat  sinyal  amplitude  getaran  yangdiberikan  juga  tinggi  (PGA  = 0,01G  pada  saat  amplitude  getaran  3mm  dan  1,43G  pada  saatamplitude getaran 12 mm).
Penerapan Algoritma C4.5 untuk Klasifikasi Data Rekam Medis berdasarkan International Classification Diseases (ICD-10) Yudha Aditya Fiandra; Sarjon Defit; Yuhandri Yuhandri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 1 No 2 (2017): Agustus 2017
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (579.053 KB) | DOI: 10.29207/resti.v1i2.48

Abstract

Abstract The medical record data is the patient's current record of medical records, the medical record data only being data stacked and not traced to generate useful knowledge for the hospital. This study can process the medical record data to classify the disease that occurs in sleeping sickness based on ICD-10. The method used in this research is C4.5 algorithm method by using attribute of international disease code as attribute of destination label as many as 21 international disease group, that is: A00-B99 up to Z00-Z99. This study yields a decision of the value code, C4.5 code can represent as many as 14 attribute values ​​of disease code objectives and data percentage that read more than 66%. The conclusion of this research is C4.5 algorithm help classify international disease code based on ICD-10 and decision tree making which can give information of any disease that often happened at hospital Keywords: data mining, classification, C4.5, medical records, ICD-10
ALGORITMA C4.5 UNTUK PREDIKSI BIMBINGAN SISWA BERDASARKAN TIPOLOGI HIPPOCRATES-GALENUS Boy Sandy Dwi Nugraha.H; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 11 No 1 (2023): TEKNOIF APRIL 2023
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2023.V11.1.1-8

Abstract

The type of personality possessed by a student belived affect their behavior, whether positively or negatively, and if left unattended, it will harm the student. Student guidance is necessary to provide appropriate guidance for the student. This study aims to predict student guidance based on personality by using student data at SMP 1 Negeri Tembilahan. The data collection process was obtained from the BK teacher at SMPN 1 Tembilahan for grade 8 and grade 7. Grade 8 will be used as training data and grade 7 will be used as testing data. 5 parameters were selected for the prediction process and 1 label as the target class. The method used is the C4.5 algorithm to build a decision tree and obtain prediction rules. The results of the study were obtained using Confusion Matrix testing with a prediction accuracy rate of 70%. The ultimate goal of the student guidance prediction process is to have a higher percentage of "Yes" (need guidance) than "No" (don't need guidance) in the prediction results. Therefore, it can be stated that the prediction process model with the C4.5 algorithm is suitable for determining good decision-making results in terms of prediction, and the researcher hopes that after obtaining these results, the BK teacher at SMPN 1 Tembilahan can provide guidance as soon as possible and provide necessary guidance to students who need it.
IMPLEMENTASI SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN ALAT KONTRASEPSI DENGAN METODE AHP DAN TOPSIS (STUDI KASUS DI PUSKESMAS GUNUNG LABU) Pipin Refina Afindania; Sarjon Defit; Sumijan
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 1 (2024): TEKNOIF APRIL 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.1.1-9

Abstract

The problem that is often faced is that many mothers of couples of childbearing age do not understand how to choose a contraceptive method that is suitable for use. To address this problem among couples of reproductive age in choosing the most appropriate contraceptive method, the Analytical Hierarchy Process  (AHP)-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is proposed to be utilized. It is expected to be beneficial in aiding the selection of a suitable contraceptive method for users. The objective of this research is to implement the AHP-TOPSIS method in a decision support system for choosing contraceptive methods for couples of reproductive age at the Gunung Labu Community Health Center. The results of the analysis using the AHP-TOPSIS method indicate that the appropriate contraceptive methods for couples of reproductive age are Implan, IUD, Birth Control Injection, and Birth Control Pills. The combination of AHP-TOPSIS in contraceptive method selection yields the conclusion that the Decision Support System (DSS) built in this research is expected to facilitate midwives in recommending contraceptive methods for couples of reproductive age. AHP method is employed to calculate the weights of each contraceptive method criterion. The results of the priority weight calculations for all criteria used in this study yielded a Consistency Index (CI) of 0.07. The analysis using the AHP-TOPSIS method resulted in Implan, IUD, Birth Control Injection, and Birth Control Pills being identified as the appropriate contraceptive methods for couples of reproductive age.
Implementasi Algoritma K-Means Guna Pengelompokkan Data Penjualan Berdasarkan Pembelian Lubis, Siti Sahara; Sarjon Defit; Sumijan
Jurnal KomtekInfo Vol. 11 No. 4 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i4.557

Abstract

Information technology can help solve problems faced by humans by facilitating performance. Information technology and information systems are difficult to separate in the business world. Data mining is the core of the KDD process, which involves inferring algorithms that explore data, developing models and finding previously unknown patterns. KDD is often referred to as knowledge discovery in databases. The KDD process generally consists of 5 stages, namely data selection, pre-processing/cleaning, transformation, data mining and interpretation/evaluation. K-Means is a clustering algorithm in data mining to be able to produce groups of large amounts of data with a point-based partition method with fast and efficient computing time. Clustering is the process of dividing objects from a data set into several homogeneous clusters. The main purpose of the cluster method is to group a number of data/objects into clusters (groups) so that each cluster will contain data that is as similar as possible. This study aims to provide real solutions to UD. Martua in order to know which items are selling well and which items are not selling well so that the object can know which items need to be added to the stock and which items need to be reduced. The method used in this study is the K-Means method with stages, namely data selection, pre-processing, data transformation, information extraction and evaluation of results. The data consists of 30 item data, there are 8 as members of C1 and are best-selling items and 22 as members of C2 and are not selling items. The conclusion that can be obtained from this study is that the K-Means method can group items at UD. Martua. This study shows that the implementation of the K-Means method with the support of the RapidMiner application is effective in grouping item data at UD. Martua.
Perbandingan Algoritma CART dan C.4 5 Pada Citra Tandan Buah Sawit Untuk Mengetahui Tingkat Kematangan Dalam Penentuan Harga Agustin, Riris; Sarjon Defit; Sumijan
Jurnal KomtekInfo Vol. 11 No. 4 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i4.558

Abstract

Information technology is a means and infrastructure of a system method to organize, send, interpret, use, process, obtain, and store data in a meaningful and useful way. Oil palm is a tropical plant originating from West Africa. The advantage of this plant is that it can also be planted outside its place of origin, including Indonesia. This plant has been widely cultivated in the form of plantations and factories in various regions in Indonesia. Oil palm is an industrial plant that is used as a raw material for vegetable oil, industrial oil, and fuel. Oil palm is important for Indonesia because it creates jobs for local people and is a source of foreign currency for the country. Oil palm plants begin to flower and form fruit after 2-3 years. The fruit will ripen about 5-6 months after pollination. The ripening process of oil palm fruit can be seen from the change in color of the fruit's skin. The fruit will turn orange-red when ripe. When the fruit is ripe, the oil content in the fruit flesh is at its maximum. If it is too ripe, the oil palm fruit will fall from the stalk of the bunch. This study aims to assess the maturity of a bunch of oil palm fruit. The methods used in this study are CART and C.4 5. Each method has several stages that will produce entropy and gain values ​​that will later form a decision tree. The dataset consists of 37 data consisting of 10 criteria originating from Ramp 789 Batang Peranap. Based on the implementation of the C4.5 algorithm and the CART algorithm in determining the level of ripeness of oil palm fruit bunches on RAMP 789 Batang Peranap which produces an accuracy of 98.00%. These results are obtained based on Process data with testing using the RapidMiner application, which produces a Decision tree that is useful as a reference for decisions in determining whether or not oil palm fruit bunches are ripe, which so far have only been predicted.
Co-Authors Abulwafa Muhammad Ade, Ade Puspita Sari Afriosa Syawitri Agustin, Riris Angga Putra Juledi Boy Sandy Dwi Nugraha.H Chairun Nas Cyntia Trimulia Dwiprihatmo, Mohammad Reza Fadillah, Riszki Febi Nur Salisah Firdaus Firdaus Gunadi Widi Nurcahyo Julius Santony Leony Lidya Lubis, Siti Sahara Muhammad, Abulwafa Mukhlis Santoso Pipin Refina Afindania Randy Permana Ruri Hartika Zain Sabil, Muhammad Sumijan Yudha Aditya Fiandra Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yul Antonisfia Zulharbi Zulharbi